cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.974117
title: Satellite Color Images, Vegetation Indices, and Metabolism Indices from Oldenburg (Oldenburg), Germany from 1984 – 2023

description: The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document.The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications.In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description).Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
DOI: 10.15468/dl.eqehxf
title: Occurrence Download

description: A dataset containing 26097 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calocitta colliei (Vigors, 1829)"
 ]
}

 The dataset includes 26097 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024343-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9zu2an
title: Occurrence Download

description: A dataset containing 163749 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Month is December",
 "StateProvince is Illinois",
 "TaxonKey is one of (Quiscalus quiscula (Linnaeus, 1758), Cardinalis cardinalis (Linnaeus, 1758), Turdus migratorius Linnaeus, 1766, Passer domesticus (Linnaeus, 1758), Poecile atricapillus (Linnaeus, 1766))"
 ]
}

 The dataset includes 163749 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024328-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.972178
title: Satellite Color Images, Vegetation Indices, and Metabolism Indices from Aalen, Germany from 1984 – 2023

description: The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document.The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications.In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description).Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
DOI: 10.15468/dl.gautdw
title: Occurrence Download

description: A dataset containing 16994 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Anaxyrus punctatus (Baird & Girard, 1852))"
 ]
}

 The dataset includes 16994 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024345-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.umam97
title: Occurrence Download

description: A dataset containing 598 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((124.73112 6.92539,126.47363 6.92539,127.07415 6.87485,125.37356 7.52076,125.23613 7.53122,124.73112 7.62302,124.73112 6.92539))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pithecophaga jefferyi Ogilvie-Grant, 1896"
 ]
}

 The dataset includes 598 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024346-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xu4gj5
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phyllosticta cavendishii M.H.Wong & Crous"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024347-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t3vwae
title: Occurrence Download

description: A dataset containing 3731 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Anaxyrus quercicus (Holbrook, 1840))"
 ]
}

 The dataset includes 3731 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024348-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7yemjj
title: Occurrence Download

description: A dataset containing 161 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Trichechus inunguis (Natterer, 1883)"
 ]
}

 The dataset includes 161 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024349-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ytkrt
title: Occurrence Download

description: A dataset containing 902 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Anaxyrus retiformis (Sanders & Smith, 1951))"
 ]
}

 The dataset includes 902 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024350-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10969443
title: BAM Generalized National Models Documentation, Version 4.0

description: Reliable information on species' population sizes, trends, habitat associations, and distributions is important for conservation and land-use planning, as well as status assessment and recovery planning for species at risk. However, the development of such estimates at a national scale is challenged by a variety of factors, including sparse data coverage in remote regions, differential habitat selection across large geographies, and variation in survey protocols.


With these factors in mind, we developed a generalized analytical approach to model species density in relation to environmental covariates, using the Boreal Avian Modelling Project database of point-count surveys (through 2018) and widely available spatial predictors. We developed separate models for each geographic region (bird conservation regions intersected by jurisdiction boundaries) based on covariates such as tree species biomass (local and landscape scale), forest age, topography, land use, and climate. We used machine learning to allow for variable interactions and non-linear responses while avoiding time-consuming species-by-species parameterization. We applied cross-validation to avoid overfitting and bootstrap resampling to estimate uncertainty associated with our density estimates.


Results available at https://borealbirds.github.io/
DOI: 10.5281/zenodo.4018336
title: BAM Generalized National Models Documentation, Version 4.0

description: Reliable information on species' population sizes, trends, habitat associations, and distributions is important for conservation and land-use planning, as well as status assessment and recovery planning for species at risk. However, the development of such estimates at a national scale is challenged by a variety of factors, including sparse data coverage in remote regions, differential habitat selection across large geographies, and variation in survey protocols. With these factors in mind, we developed a generalized analytical approach to model species density in relation to environmental covariates, using the Boreal Avian Modelling Project database of point-count surveys (through 2018) and widely available spatial predictors. We developed separate models for each geographic region (bird conservation regions intersected by jurisdiction boundaries) based on covariates such as tree species biomass (local and landscape scale), forest age, topography, land use, and climate. We used machine learning to allow for variable interactions and non-linear responses while avoiding time-consuming species-by-species parameterization. We applied cross-validation to avoid overfitting and bootstrap resampling to estimate uncertainty associated with our density estimates. Results available at https://borealbirds.github.io/
DOI: 10.15468/dl.9m5qzw
title: Occurrence Download

description: A dataset containing 5681 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Anaxyrus speciosus (Girard, 1854))"
 ]
}

 The dataset includes 5681 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024352-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n9v6tb
title: Occurrence Download

description: A dataset containing 9562 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Plantago virginica L."
 ]
}

 The dataset includes 9562 records from 280 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024351-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3a2y5k
title: Occurrence Download

description: A dataset containing 127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-96.81589 17.516,-96.57089 15.68619,-94.98225 16.18,-93.72282 16.07665,-94.03289 17.76865,-94.79468 17.09874,-96.81589 17.516))",
 "TaxonKey is Leopardus wiedii (Schinz, 1821)"
 ]
}

 The dataset includes 127 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024353-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kvrau4
title: Occurrence Download

description: A dataset containing 21781 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Anaxyrus terrestris (Bonnaterre, 1789))"
 ]
}

 The dataset includes 21781 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024354-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4rd7hs
title: Occurrence Download

description: A dataset containing 1134 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "DatasetKey is EOD – eBird Observation Dataset",
 "TaxonKey is Loxia scotica Hartert, 1904",
 "Year 1960-2024"
 ]
}

 The dataset includes 1134 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020018-241107131044228/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.27255626
title: Analysis of oral and inhalation toxicity of per- and polyfluoroalkylated organic compounds in rats and mice using multivariate QSAR

description: Per- and polyfluoroalkylated organic compounds (PFAs) are versatile compounds extensively used in global industries. However, they are also persistent organic pollutants (POPs). This study aimed to develop new models for assessing oral and inhalation toxicity in rat and mice models. A set of 407 PFAs from the literature was divided into four groups based on the endpoints of interest. The models were constructed using only 2D structure descriptors derived from SMILES strings. The resulting models showed a strong statistical quality for all endpoints. They present an applicability domain (AD) that ensures good reliability, and provided meaningful interpretation, which are partially supported by existing literature. Consequently, these models are valuable for understanding how PFAs exert their toxic effect on mammals and for predicting the risk associated with these significant industrial chemical agents.
DOI: 10.6084/m9.figshare.27255626.v1
title: Analysis of oral and inhalation toxicity of per- and polyfluoroalkylated organic compounds in rats and mice using multivariate QSAR

description: Per- and polyfluoroalkylated organic compounds (PFAs) are versatile compounds extensively used in global industries. However, they are also persistent organic pollutants (POPs). This study aimed to develop new models for assessing oral and inhalation toxicity in rat and mice models. A set of 407 PFAs from the literature was divided into four groups based on the endpoints of interest. The models were constructed using only 2D structure descriptors derived from SMILES strings. The resulting models showed a strong statistical quality for all endpoints. They present an applicability domain (AD) that ensures good reliability, and provided meaningful interpretation, which are partially supported by existing literature. Consequently, these models are valuable for understanding how PFAs exert their toxic effect on mammals and for predicting the risk associated with these significant industrial chemical agents.
DOI: 10.6084/m9.figshare.27620787
title: Computational investigations of flavonoids as ALDH isoform inhibitors for treatment of cancer

description: Human aldehyde dehydrogenases (ALDHs) are a group of 19 isoforms often overexpressed in cancer stem cells (CSCs). These enzymes play critical roles in CSC protection, maintenance, cancer progression, therapeutic resistance, and poor prognosis. Thus, targeting ALDH isoforms offers potential for innovative cancer treatments. Flavonoids, known for their ability to affect multiple cancer-related pathways, have shown anticancer activity by downregulating specific ALDH isoforms. This study aimed to evaluate 830 flavonoids from the PubChem database against five ALDH isoforms (ALDH1A1, ALDH1A2, ALDH1A3, ALDH2, ALDH3A1) using computational methods to identify potent inhibitors. Extra precision (XP) Glide docking and MM-GBSA free binding energy calculations identified several flavonoids with high binding affinities. MD simulation highlighted flavonoids 1, 2, 18, 27, and 42 as potential specific inhibitors for each isoform, respectively. Flavonoid 10 showed high binding affinities for ALDH1A2, ALDH1A3, and ALDH3A1, emerging as a potential multi-ALDH inhibitor. ADMET property evaluation indicated that the promising hits have acceptable drug-like profiles, but further optimization is needed to enhance their therapeutic efficacy and reduce toxicity, making them more effective ALDH inhibitors for future cancer treatment.
DOI: 10.6084/m9.figshare.27620787.v1
title: Computational investigations of flavonoids as ALDH isoform inhibitors for treatment of cancer

description: Human aldehyde dehydrogenases (ALDHs) are a group of 19 isoforms often overexpressed in cancer stem cells (CSCs). These enzymes play critical roles in CSC protection, maintenance, cancer progression, therapeutic resistance, and poor prognosis. Thus, targeting ALDH isoforms offers potential for innovative cancer treatments. Flavonoids, known for their ability to affect multiple cancer-related pathways, have shown anticancer activity by downregulating specific ALDH isoforms. This study aimed to evaluate 830 flavonoids from the PubChem database against five ALDH isoforms (ALDH1A1, ALDH1A2, ALDH1A3, ALDH2, ALDH3A1) using computational methods to identify potent inhibitors. Extra precision (XP) Glide docking and MM-GBSA free binding energy calculations identified several flavonoids with high binding affinities. MD simulation highlighted flavonoids 1, 2, 18, 27, and 42 as potential specific inhibitors for each isoform, respectively. Flavonoid 10 showed high binding affinities for ALDH1A2, ALDH1A3, and ALDH3A1, emerging as a potential multi-ALDH inhibitor. ADMET property evaluation indicated that the promising hits have acceptable drug-like profiles, but further optimization is needed to enhance their therapeutic efficacy and reduce toxicity, making them more effective ALDH inhibitors for future cancer treatment.
DOI: 10.15468/dl.ns9ahb
title: Occurrence Download

description: A dataset containing 2695 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Raphia P.Beauv.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2695 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020021-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8cww3x
title: Occurrence Download

description: A dataset containing 20897 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Vitis laeta Wall., Vicia lutea L., Vicia lanata Vis., 1852, Vicia lutea Pall., Vicia lutea Pall. ex M.Bieb., Virbia laeta Guérin-Méneville, 1844, Vicia serinica R.Uechtr. & Huter, Vicia serenica Uechtr. & Huter, Vincetoxicum nigrum (L.) Moench, Ziziphora graveolens (M.Bieb.) Melnikov, Ziziphora suaveolens (Sm.) Melnikov, Ziziphora suaveolens (Sm.) Melnikov, Ziziphora graveolens (M.Bieb.) Melnikov)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 20897 records from 647 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020028-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14180747
title: OF DIFFERENCE IN LENGTH OF YARN YARN IN POORLY HEATED YARN ON YARN QUALITY
DOI: 10.5281/zenodo.14180748
title: OF DIFFERENCE IN LENGTH OF YARN YARN IN POORLY HEATED YARN ON YARN QUALITY
DOI: 10.15468/dl.689hgm
title: Occurrence Download

description: A dataset containing 1862 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Thailand",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pavo muticus Linnaeus, 1766"
 ]
}

 The dataset includes 1862 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020035-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.