cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/0jfk-eb09
title: Dataset for Human Activity Classification with MU-MIMO BFI and CSI

description: This dataset offers both Channel State Information (CSI) and Beamforming Feedback Information (BFI) data for human activity classification, featuring 20 distinct activities performed by three subjects across three environments. Collected in both line-of-sight (LoS) and non-line-of-sight (NLoS) scenarios, this dataset enables researchers to explore the complementary roles of CSI and BFI in activity recognition and environmental characterization.
DOI: 10.15468/dl.f7spvg
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vormela peregusna (Güldenstädt, 1770)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 13 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010051-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ekybra
title: Occurrence Download

description: A dataset containing 3118 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nacellidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3118 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010052-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kgez4y
title: Occurrence Download

description: A dataset containing 220 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Dataset of carabid beetles in the Dolomites mountains"
 ]
}

 The dataset includes 220 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010053-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/pr00010313
title: Effect of liver lipid deposition on the treatment of atezolizumab plus bevacizumab: a retrospective study based on the IMBrave150

description: Chronic hepatitis B is a long-lasting infection of the liver caused by the hepatitis B virus. It can lead to serious liver problems, including liver cancer. Liver cancer is a type of cancer that starts in the cells of the liver and is difficult to treat if not caught early. Another related condition is fatty liver disease, where fat builds up in the liver, making it hard for the organ to function properly. These conditions are important because many people around the world are affected by them, leading to health issues that impact their daily lives and well-being.
This research will look at the effects of two medications called Atezolizumab (commonly known as "T") and Bevacizumab ("a") when given together to treat liver cancer in patients who also have fatty liver disease. Atezolizumab workS by helping the immune system to recognize and kill cancer cells, whereas bevacizumab works by stopping the cancer from growing blood vessels, so it is starved and can't grow.The combination of these two medications is known as "T + a." We want to understand if the presence of fat in the liver changes how well these treatments work.
Understanding how liver fat affects treatment outcomes can help doctors provide better care for patients with liver cancer, especially those with chronic hepatitis B and fatty liver disease. If we learn that fat in the liver impacts treatment effectiveness, we may need to adjust our approach to using these medications for better results. This research could lead to improved treatment options for many people suffering from these liver conditions, potentially saving lives and improving quality of life.
This study aims to help healthcare providers understand the connection between liver fat and treatment success in liver cancer patients. By doing so, we hope to enhance medical knowledge and improve patient care for those affected by chronic hepatitis B, liver cancer, and fatty liver disease.
DOI: 10.15468/dl.kgtats
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Pittosporum phillyraeoides DC."
 ]
}

 The dataset includes 46 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010054-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uz2rce
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Myotis aurascens Kuzyakin, 1935",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 8 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010055-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nsrw4p
title: Occurrence Download

description: A dataset containing 503 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rissoidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 503 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010056-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xjjhyp
title: Occurrence Download

description: A dataset containing 2440372 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Denmark",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than 50000",
 "Year is 2022",
 "DecimalLongitude is greater than or equal to 7.0",
 "DecimalLongitude is less than or equal to 15.5",
 "DecimalLatitude is greater than or equal to 54.5",
 "DecimalLatitude is less than or equal to 58.0"
 ]
}

 The dataset includes 2440372 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010013-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pg2445
title: Occurrence Download

description: A dataset containing 1001 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Galemys pyrenaicus (É.Geoffroy Saint-Hilaire, 1811)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 1001 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010057-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d8p5jy
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anatomidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 90 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010058-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5sj7s
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mustela lutreola (Linnaeus, 1761)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 38 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010060-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bmh4p7
title: Occurrence Download

description: A dataset containing 302 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Margaritidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 302 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010061-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c8qybm
title: Occurrence Download

description: A dataset containing 2912 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Genetta genetta (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 2912 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010063-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.343jse
title: Occurrence Download

description: A dataset containing 1533 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pyramidellidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1533 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010064-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hupu2v
title: Occurrence Download

description: A dataset containing 2274 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capra pyrenaica Schinz, 1838",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 2274 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010065-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jymuga
title: Occurrence Download

description: A dataset containing 314 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anoplophora horsfieldii (Hope, 1843)"
 ]
}

 The dataset includes 314 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010066-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.65wfu7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capra pyrenaica pyrenaica",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010067-241107131044228/datasets/export for details.
DOI: 10.5281/zenodo.5643035
title: Global Landside Clustering of Aquaculture Ponds Distribution Acquired from Dense Time-Series Sentinel-2 Images by Google Earth Engine

description: This dataset reveals the global distribution pattern of landside clustering aquaculture ponds (LCAP) from a spatial perspective for the first time. It was derived from 4,015,054 tiles of the 10-m Sentinel-2 time-series images collected throughout 2020. The total area of global LCAP was estimated at 55,337.03 km2. Accuracy verification revealed that the Omission Error and Commission Error of the data is 7.51% and 16.69% respectively. We provide this dataset in ESRI shapefile format (.zip), which can be opened by ArcGIS. We invite you to download and utilize this dataset and recommend citing the following two references.
DOI: 10.5281/zenodo.5643036
title: Global Landside Clustering of Aquaculture Ponds Distribution Acquired from Dense Time-Series Sentinel-2 Images by Google Earth Engine

description: This dataset reveals the global distribution pattern of landside clustering aquaculture ponds (LCAP) from a spatial perspective for the first time. It was derived from 4,015,054 tiles of the 10-m Sentinel-2 time-series images collected throughout 2020. The total area of global LCAP was estimated at 55,337.03 km2. Accuracy verification revealed that the Omission Error and Commission Error of the data is 7.51% and 16.69% respectively. We provide this dataset in ESRI shapefile format (.zip), which can be opened by ArcGIS. We invite you to download and utilize this dataset and recommend citing the following two references.
DOI: 10.5281/zenodo.10402760
title: IT-SNOW: a snow reanalysis for Italy blending modeling, in-situ data, and satellite observations

description: IT-SNOW is a serially complete and multi-year snow reanalysis for Italy. The dataset includes daily maps of Snow Water Equivalent (SWE), snow depth (HS), bulk-snow density (RhoS), and liquid water content (Theta_W). 

Data are organized in monthly netCDF files, each providing time and lat/lon information for georeference. Units are as follows: HS is in cm, SWE is in mm w.e., RhoS is in kg/m3, and Theta_W is in %. Note that maps are instantaneous snapshots at 11AM UTC, here assumed as representative values for the day. 

As the output of an operational chain employed in real-world civil-protection applications (S3M Italy), IT-SNOW ingests input data from thousands of automatic weather stations, snow-covered-area maps from Sentinel 2, MODIS, and H-SAF products, and maps of snow depth from the spazialization of 350+ on-the-ground snow-depth sensors. Additional information are available in the following paper submitted to Earth System Science Data: 

"IT-SNOW: a snow reanalysis for Italy blending modeling, in-situ data, and satellite observations (2009-2021)", Francesco Avanzi et al., 2022. 

The initial time span of data is September 1, 2010 to August 31, 2021, with future updates envisaged on an annual basis (see updates below).

UPDATES



December 20, 2022: released v2 with the complete 2022 water year (September 2021 - August 2022).


LICENSE INFORMATION

IT-SNOW is distributed under a CC BY-NC 4.0 license. you are free to: 

1. Share — copy and redistribute the material in any medium or format; 2. Adapt — remix, transform, and build upon the material;

under the following terms: 

a. Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.b. NonCommercial — You may not use the material for commercial purposes.

DATA ARE PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THESE DATA, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

For details about the CC BY-NC 4.0 license, see: https://creativecommons.org/licenses/by-nc/4.0/deed.en
DOI: 10.5281/zenodo.13626816
title: IT-SNOW: a snow reanalysis for Italy blending modeling, in-situ data, and satellite observations

description: IT-SNOW is a serially complete and multi-year snow reanalysis for Italy. The dataset includes daily maps of Snow Water Equivalent (SWE), snow depth (HS), bulk-snow density (RhoS), and liquid water content (Theta_W). 

Data are organized in monthly netCDF files, each providing time and lat/lon information for georeference. Units are as follows: HS is in cm, SWE is in mm w.e., RhoS is in kg/m3, and Theta_W is in %. Note that maps are instantaneous snapshots at 11AM UTC, here assumed as representative values for the day. 

As the output of an operational chain employed in real-world civil-protection applications (S3M Italy), IT-SNOW ingests input data from thousands of automatic weather stations, snow-covered-area maps from Sentinel 2, MODIS, and H-SAF products, and maps of snow depth from the spazialization of 350+ on-the-ground snow-depth sensors. Additional information are available in the following paper submitted to Earth System Science Data: 

"IT-SNOW: a snow reanalysis for Italy blending modeling, in-situ data, and satellite observations (2009-2021)", Francesco Avanzi et al., 2022. 

The initial time span of data is September 1, 2010 to August 31, 2021, with future updates envisaged on an annual basis (see updates below).

UPDATES



September 02, 2024: released v3 with the complete 2023 water year (September 2022 - August 2023).

December 20, 2023: released v2 with the complete 2022 water year (September 2021 - August 2022).


LICENSE INFORMATION

IT-SNOW is distributed under a CC BY-NC 4.0 license. you are free to: 

1. Share — copy and redistribute the material in any medium or format; 2. Adapt — remix, transform, and build upon the material;

under the following terms: 

a. Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.b. NonCommercial — You may not use the material for commercial purposes.

DATA ARE PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THESE DATA, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

For details about the CC BY-NC 4.0 license, see: https://creativecommons.org/licenses/by-nc/4.0/deed.en
DOI: 10.5281/zenodo.13627506
title: IT-SNOW: a snow reanalysis for Italy blending modeling, in-situ data, and satellite observations

description: IT-SNOW is a serially complete and multi-year snow reanalysis for Italy. The dataset includes daily maps of Snow Water Equivalent (SWE), snow depth (HS), bulk-snow density (RhoS), and liquid water content (Theta_W). 

Data are organized in monthly netCDF files, each providing time and lat/lon information for georeference. Units are as follows: HS is in cm, SWE is in mm w.e., RhoS is in kg/m3, and Theta_W is in %. Note that maps are instantaneous snapshots at 11AM UTC, here assumed as representative values for the day. 

As the output of an operational chain employed in real-world civil-protection applications (S3M Italy), IT-SNOW ingests input data from thousands of automatic weather stations, snow-covered-area maps from Sentinel 2, MODIS, and H-SAF products, and maps of snow depth from the spazialization of 350+ on-the-ground snow-depth sensors. Additional information are available in the following paper submitted to Earth System Science Data: 

"IT-SNOW: a snow reanalysis for Italy blending modeling, in-situ data, and satellite observations (2009-2021)", Francesco Avanzi et al., 2022. 

The initial time span of data is September 1, 2010 to August 31, 2021, with future updates envisaged on an annual basis (see updates below).

UPDATES



September 02, 2024: released v3.1 with the complete 2023 water year (September 2022 - August 2023) AND all previous water years (which were inadvertently NOT carried over while creating v3).

September 02, 2024: released v3 with the complete 2023 water year (September 2022 - August 2023).

December 20, 2023: released v2 with the complete 2022 water year (September 2021 - August 2022).


LICENSE INFORMATION

IT-SNOW is distributed under a CC BY-NC 4.0 license. you are free to: 

1. Share — copy and redistribute the material in any medium or format; 2. Adapt — remix, transform, and build upon the material;

under the following terms: 

a. Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.b. NonCommercial — You may not use the material for commercial purposes.

DATA ARE PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THESE DATA, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

For details about the CC BY-NC 4.0 license, see: https://creativecommons.org/licenses/by-nc/4.0/deed.en