cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2g63f7
title: CCDC 2269988: Experimental Crystal Structure Determination

description: Related Article: Shobhit Mathur, Kalai Selvan Karumban, Arabinda Muley, Nikhil Tuti, Unnikrishnan Paruthiyezhath Shaji, Indrajit Roy, Anushka Verma, Manoj Kumar Kumawat, Anindya Roy, Somnath Maji|2024|Dalton Trans.|53|1163|doi:10.1039/D3DT01864D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h92xt
title: CCDC 2302646: Experimental Crystal Structure Determination

description: Related Article: Mamta Dagar, William W. Brennessel, Ellen M. Matson|2024|J.Mater.Chem.A|12|1517|doi:10.1039/D3TA06432H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10521584
title: MEGANv2.1 1km2 global monthly LAIv for 2003

description: These files contain global monthly estimates of the Leaf Area Index of vegetation covered surfaces (LAIv) at a spatial resolution of 30 sec longitude x 30 sec latitude (about 1 km2). The values are representative of the m2 of one sided leaf area per m2 of vegetation covered area. For example, if the LAI for a specific location is 2 m2/m2 and the vegetation cover fraction is 0.4 (i.e., 40% of the surface is covered by vegetation) then the LAIv = LAI/VCF = 2/0.4 = 5.

There are 12 netcdf format files (one for each month of 2003). The file naming convention is laiv2003MM where MM is month of the year. 

The units are m2 leaf area per 10 m2 surface area (which is the unit expected for the MEGANv2.1 preprocessor)

These files were created in 2005 for use in MEGANv2 as described by Guenther et al. 2006 (doi.org/10.5194/acp-6-3181-2006). They are based on MODIS (MOderate Resolution Imaging Spectroradiometer) satellite LAI estimates described by Zhang et al JGR (2004) doi:10.1029/2004JD004720 and the vegetation cover fraction of Hansen et al.  Earth Interactions 7: 1-15 (2003). Urban and wetland areas and other regions with missing LAI data in this MODIS database were assigned an LAIv based on the average for the surrounding region.
DOI: 10.5281/zenodo.10521585
title: MEGANv2.1 1km2 global monthly LAIv for 2003

description: These files contain global monthly estimates of the Leaf Area Index of vegetation covered surfaces (LAIv) at a spatial resolution of 30 sec longitude x 30 sec latitude (about 1 km2). The values are representative of the m2 of one sided leaf area per m2 of vegetation covered area. For example, if the LAI for a specific location is 2 m2/m2 and the vegetation cover fraction is 0.4 (i.e., 40% of the surface is covered by vegetation) then the LAIv = LAI/VCF = 2/0.4 = 5.

There are 12 netcdf format files (one for each month of 2003). The file naming convention is laiv2003MM where MM is month of the year. 

The units are m2 leaf area per 10 m2 surface area (which is the unit expected for the MEGANv2.1 preprocessor)

These files were created in 2005 for use in MEGANv2 as described by Guenther et al. 2006 (doi.org/10.5194/acp-6-3181-2006). They are based on MODIS (MOderate Resolution Imaging Spectroradiometer) satellite LAI estimates described by Zhang et al JGR (2004) doi:10.1029/2004JD004720 and the vegetation cover fraction of Hansen et al.  Earth Interactions 7: 1-15 (2003). Urban and wetland areas and other regions with missing LAI data in this MODIS database were assigned an LAIv based on the average for the surrounding region.
DOI: 10.5281/zenodo.10518208
title: Dataset PreAlti - baroreflex sensitivity
DOI: 10.5281/zenodo.10518209
title: Dataset PreAlti - baroreflex sensitivity
DOI: 10.5281/zenodo.5242964
title: Food aid in Europe in times of the COVID-19 crisis

description: Description (purpose, methodology, contents, file structure, etc.)


The dataset is linked to a cross-sectional study on the organisation of food aid in different European countries before and during the COVID-19 crisis. The survey was conducted with local organisations providing food aid in Belgium, Germany, Hungary, Lithuania, the Netherlands, Poland, Portugal and Spain. We set the target population as the total number of local food aid organisations affiliated with the largest national food aid umbrella organisation(s) in each country. The English source questionnaire was developed based on many feedback loops with all project partners (see below) as well as a pilot study. For reasons of consistency, the translation process from the source questionnaire to the target languages followed the translation recommendations of the ‘Cross Cultural Survey Guidelines’ as much as feasible within the context of this project. The final questionnaire included multiple choice questions, dichotomous questions, matrix questions and open-ended questions. Survey participants were recruited by means of a self-administered questionnaire and the technique of computer-assisted web-interviewing as well as via email (in Belgium and partly in Lithuania and Portugal). 

Project website: https://food-aid-in-europe.eu/



Personal data yes/no
no


Type(s) of data and data format
Survey data, Excel file (1.8 MB)


Temporal and special coverage
Data was collected from 22 March to 4 August 2021 in Belgium, Germany, Hungary, Lithuania, the Netherlands, Poland, Portugal and Spain.


Language of files
English


Subject
Food aid in Europe, COVID-19 crisis, survey data


Audience
Social Sciences


Rightsholder
 University of Antwerp, Johanna Greiss, phd student, ORCID 0000-0001-6985-1792


Access Rights
Open access
DOI: 10.5281/zenodo.5242965
title: Food aid in Europe in times of the COVID-19 crisis

description: Description (purpose, methodology, contents, file structure, etc.)


The dataset is linked to a cross-sectional study on the organisation of food aid in different European countries before and during the COVID-19 crisis. The survey was conducted with local organisations providing food aid in Belgium, Germany, Hungary, Lithuania, the Netherlands, Poland, Portugal and Spain. We set the target population as the total number of local food aid organisations affiliated with the largest national food aid umbrella organisation(s) in each country. The English source questionnaire was developed based on many feedback loops with all project partners (see below) as well as a pilot study. For reasons of consistency, the translation process from the source questionnaire to the target languages followed the translation recommendations of the ‘Cross Cultural Survey Guidelines’ as much as feasible within the context of this project. The final questionnaire included multiple choice questions, dichotomous questions, matrix questions and open-ended questions. Survey participants were recruited by means of a self-administered questionnaire and the technique of computer-assisted web-interviewing as well as via email (in Belgium and partly in Lithuania and Portugal). 

Project website: https://food-aid-in-europe.eu/



Personal data yes/no
no


Type(s) of data and data format
Survey data, Excel file (1.8 MB)


Temporal and special coverage
Data was collected from 22 March to 4 August 2021 in Belgium, Germany, Hungary, Lithuania, the Netherlands, Poland, Portugal and Spain.


Language of files
English


Subject
Food aid in Europe, COVID-19 crisis, survey data


Audience
Social Sciences


Rightsholder
 University of Antwerp, Johanna Greiss, phd student, ORCID 0000-0001-6985-1792


Access Rights
Open access
DOI: 10.5281/zenodo.10507228
title: Fatigue Dataset
DOI: 10.5281/zenodo.10507229
title: Fatigue Dataset
DOI: 10.5281/zenodo.10519228
title: Water chemistry of LTER-Europe research site Lake Paione Inferiore LTER_EU_IT_088 (1984-2013)

description: This dataset provides information about water chemical parameters for Lake Paione Inferiore LTER_EU_IT_088: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 1984-2013.

Lake Paione Inferiore (LPI) is a high altitude Alpine lake, located at 2002 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.86 ha and a maximum depth of 13.5 m. The Lake, together with Lake Paione Superiore (LPS), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.

This dataset includes the following files: Metadata LTER_EU_IT_088.xls and per each parameter one xls file with data records. Dataset for water chemistry of LPI for the  period 2014-2020 is available at https://doi.org/10.5281/zenodo.10519349

Detailed description of the site LPI is available at https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f
description: The data collection was partly supported by the Italian Ministry for the Environment through the ICP Waters Programme.
To whom is interested in data of Lake Paione Superiore LTER_EU_IT_089, we have published data of chemical parameters under DOI: 10.5281/zenodo.7642703
DOI: 10.5281/zenodo.7642498
title: Water chemistry of LTER-Europe research site Lake Paione Inferiore LTER_EU_IT_088 (1984-2013)

description: This dataset provides information about water chemical parameters for Lake Paione Inferiore LTER_EU_IT_088: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 1984-2013.

Lake Paione Inferiore (LPI) is a high altitude Alpine lake, located at 2002 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.86 ha and a maximum depth of 13.5 m. The Lake, together with Lake Paione Superiore (LPS), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.

This dataset includes the following files: Metadata LTER_EU_IT_088.xls and per each parameter one xls file with data records. Dataset for water chemistry of LPI for the  period 2014-2020 is available at https://doi.org/10.5281/zenodo.10519349

Detailed description of the site LPI is available at https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f
description: The data collection was partly supported by the Italian Ministry for the Environment through the ICP Waters Programme.
To whom is interested in data of Lake Paione Superiore LTER_EU_IT_089, we have published data of chemical parameters under DOI: 10.5281/zenodo.7642703
DOI: 10.5281/zenodo.7642499
title: Water chemistry of LTER-Europe research site Lake Paione Inferiore LTER_EU_IT_088 (1984-2013)

description: This dataset provides information about water chemical parameters for Lake Paione Inferiore LTER_EU_IT_088: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 1984-2013.


Lake Paione Inferiore (LPI) is a high altitude Alpine lake, located at 2002 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.86 ha and a maximum depth of 13.5 m. The Lake, together with Lake Paione Superiore (LPS), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.


This dataset includes the following files: Metadata LTER_EU_IT_088.xls and per each parameter one xls file with data records.


Detailed description of the site LPI is available at https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f
description: The data collection was partly supported by the Italian Ministry for the Environment through the ICP Waters Programme.
To whom is interested in data of Lake Paione Superiore LTER_EU_IT_089, we have published data of chemical parameters under DOI: 10.5281/zenodo.7642703
DOI: 10.6084/m9.figshare.25011701
title: <b>Molecular Study of Extended Spectrum Beta lactamase Resistance in </b><b><i>Sheigella</i></b><b> species Isolated from Pediatric Patients, One Egyptian Center Study</b>

description: <b>Molecular Study of Extended Spectrum Beta lactamase Resistance in </b><b><i>Sheigella</i></b><b> species Isolated from Pediatric Patients, One Egyptian Center Study</b>
DOI: 10.6084/m9.figshare.25011701.v1
title: <b>Molecular Study of Extended Spectrum Beta lactamase Resistance in </b><b><i>Sheigella</i></b><b> species Isolated from Pediatric Patients, One Egyptian Center Study</b>

description: <b>Molecular Study of Extended Spectrum Beta lactamase Resistance in </b><b><i>Sheigella</i></b><b> species Isolated from Pediatric Patients, One Egyptian Center Study</b>
DOI: 10.5281/zenodo.10519348
title: Water chemistry of LTER-Europe research site Lake Paione Inferiore LTER_EU_IT_088 (2014-2020)

description: This dataset provides information about water chemical parameters for Lake Paione Inferiore LTER_EU_IT_088: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 2014-2020.

Lake Paione Inferiore (LPI) is a high altitude Alpine lake, located at 2002 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.86 ha and a maximum depth of 13.5 m. The Lake, together with Lake Paione Superiore (LPS), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.

This dataset includes the following files: Metadata LTER_EU_IT_088.xls and per each parameter one xls file with data records.  Dataset for the period 1984-2013 is available at https://doi.org/10.5281/zenodo.7642499.

Detailed description of the site LPI is available at https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f
description: The data collection was partly supported by the Italian Ministry for the Environment through the ICP Waters Programme. To whom is interested in data of Lake Paione Superiore LTER_EU_IT_089, we have published data of chemical parameters under DOI: https://doi.org/10.5281/zenodo.10519126.

The lake surveys and the data collection were funded by a 2-year cooperation agreement between the Italian Ministry for Ecological Transition (MiTE) and Carabinieri - CUFA (Command of Forestry, environmental and Agri-food Units; formerly National Forest Service) for the development of the Italian monitoring network under the NEC Directive (NEC Italy).
DOI: 10.5281/zenodo.10519349
title: Water chemistry of LTER-Europe research site Lake Paione Inferiore LTER_EU_IT_088 (2014-2020)

description: This dataset provides information about water chemical parameters for Lake Paione Inferiore LTER_EU_IT_088: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 2014-2020.

Lake Paione Inferiore (LPI) is a high altitude Alpine lake, located at 2002 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.86 ha and a maximum depth of 13.5 m. The Lake, together with Lake Paione Superiore (LPS), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.

This dataset includes the following files: Metadata LTER_EU_IT_088.xls and per each parameter one xls file with data records.  Dataset for the period 1984-2013 is available at https://doi.org/10.5281/zenodo.7642499.

Detailed description of the site LPI is available at https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f
description: The data collection was partly supported by the Italian Ministry for the Environment through the ICP Waters Programme. To whom is interested in data of Lake Paione Superiore LTER_EU_IT_089, we have published data of chemical parameters under DOI: https://doi.org/10.5281/zenodo.10519126.

The lake surveys and the data collection were funded by a 2-year cooperation agreement between the Italian Ministry for Ecological Transition (MiTE) and Carabinieri - CUFA (Command of Forestry, environmental and Agri-food Units; formerly National Forest Service) for the development of the Italian monitoring network under the NEC Directive (NEC Italy).
DOI: 10.5281/zenodo.7974306
title: Data HTC-NN

description: This repository contains all data of the HTC-NN and its submodels as well as results of the paper "Highresolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on a machine learning approach". However, data from the sensor network must be requested directly from the University of Freiburg.
DOI: 10.5281/zenodo.7974307
title: Data HTC-NN

description: This repository contains all data of the HTC-NN and its submodels as well as results of the paper "Highresolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on a machine learning approach". However, data from the sensor network must be requested directly from the University of Freiburg.
DOI: 10.5519/qd.blnjeoh0
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1411 records)
DOI: 10.5281/zenodo.10521798
title: COVID-19 International Wellbeing Study: Italian data
DOI: 10.5281/zenodo.10521799
title: COVID-19 International Wellbeing Study: Italian data
DOI: 10.5281/zenodo.10159692
title: LU4M4TGT: An AI-Powered Global Database of impact craters >=0.5 km on the Moon.

description: Release of a new global craters catalog (LU4M4TGT) with more than 4.4 million craters (>=0.5 km in diameter)

File source csv
Header: Longitude, Latitude, Diameter_w, Diameter_h, Confidence, WindowMinLon, WindowMaxLon, WindowMinLat, WindowMaxLat.
The coordinates are absolute in the range of [-180, +180] of Longitude and [-90, +90] of Latitude. All coordinates are expressed in cylindrical projection system.
Diameters (km)
description: main reference of this upload:

@article{la2023yololens,
  title={YOLOLens: A Deep Learning Model Based on Super-Resolution to Enhance the Crater Detection of the Planetary Surfaces},
  author={La Grassa, Riccardo and Cremonese, Gabriele and Gallo, Ignazio and Re, Cristina and Martellato, Elena},
  journal={Remote Sensing},
  volume={15},
  number={5},
  pages={1171},
  year={2023},
  publisher={MDPI}
}
DOI: 10.5281/zenodo.10521779
title: LU3M7TGT: An AI-Powered Global Database of impact craters >=0.5 km on the Moon.

description: Release of a new global craters catalog (LU3M7TGT) with more than 3.7 million craters (>=0.5 km in diameter)



File source csv

Header: Longitude, Latitude, Diameter_w, Diameter_h, Confidence, WindowMinLon, WindowMaxLon, WindowMinLat, WindowMaxLat.

The coordinates are absolute in the range of [-180, +180] of Longitude and [-90, +90] of Latitude. All coordinates are expressed in cylindrical projection system.

Diameters (km)
description: main reference of this upload:

@article{la2023yololens,
  title={YOLOLens: A Deep Learning Model Based on Super-Resolution to Enhance the Crater Detection of the Planetary Surfaces},
  author={La Grassa, Riccardo and Cremonese, Gabriele and Gallo, Ignazio and Re, Cristina and Martellato, Elena},
  journal={Remote Sensing},
  volume={15},
  number={5},
  pages={1171},
  year={2023},
  publisher={MDPI}
}
DOI: 10.5281/zenodo.8005858
title: LU3M7TGT: An AI-Powered Global Database of impact craters >=0.5 km on the Moon.

description: Release of a new global craters catalog (LU3M7TGT) with more than 3.7 million craters (>=0.5 km in diameter)



File source csv

Header: Longitude, Latitude, Diameter_w, Diameter_h, Confidence, WindowMinLon, WindowMaxLon, WindowMinLat, WindowMaxLat.

The coordinates are absolute in the range of [-180, +180] of Longitude and [-90, +90] of Latitude. All coordinates are expressed in cylindrical projection system.

Diameters (km)
description: main reference of this upload:

@article{la2023yololens,
  title={YOLOLens: A Deep Learning Model Based on Super-Resolution to Enhance the Crater Detection of the Planetary Surfaces},
  author={La Grassa, Riccardo and Cremonese, Gabriele and Gallo, Ignazio and Re, Cristina and Martellato, Elena},
  journal={Remote Sensing},
  volume={15},
  number={5},
  pages={1171},
  year={2023},
  publisher={MDPI}
}
DOI: 10.5281/zenodo.8005859
title: LU3M6TGT: An AI-Powered Global Database of impact craters &gt;=0.5 km on the Moon.

description: Release of a new global craters catalog (<strong>LU3M6TGT</strong>) with more than 3.6 million craters (&gt;=0.5 km in diameter) <em>File source csv</em> <em>Header: Longitude, Latitude, Diameter_w, Diameter_h, Confidence, WindowMinLon, WindowMaxLon, WindowMinLat, WindowMaxLat.</em> <em>The coordinates are absolute in the range of [-180, +180] of Longitude and [-90, +90] of Latitude. All coordinates are expressed in <strong>cylindrical projection system</strong>.</em> <em>Diameters (km)</em> <em>Confidence value in a range [0, 1] where 0 indicate low crater confidence and 1 high crater confidence.</em>
description: main reference of this upload: @article{la2023yololens, title={YOLOLens: A Deep Learning Model Based on Super-Resolution to Enhance the Crater Detection of the Planetary Surfaces}, author={La Grassa, Riccardo and Cremonese, Gabriele and Gallo, Ignazio and Re, Cristina and Martellato, Elena}, journal={Remote Sensing}, volume={15}, number={5}, pages={1171}, year={2023}, publisher={MDPI} }
DOI: 10.58154/2r9f-p278
title: Transboundary Water Cooperation Under SDG indicator 6.5.2:  Disaggregating Data to Provide Additional Insights at the Aquifer Level

description: Based on data extracted from national country reports of SDG indicator 6.5.2 on transboundary water cooperation, the dataset shows the level of cooperation at the transboundary aquifer (TBA) level, to compliment the national approach currently followed by the official SDG framework.
DOI: 10.6084/m9.figshare.24121098
title: <b>Spirulina Plantesis Kefir Probiotics as Anti Diabetes Functional Food</b>

description: Chronic elevation of blood sugar levels has detrimental effects on the functioning and structure of pancreatic β cells. This is primarily attributed to lipid peroxidation and changes in pro-inflammatory cytokines. Therefore, the aim of this study was to evaluate the efficacy of Spirulina platensis kefir, a probiotic, in managing diabetes and its impact on glycemic status, GLUT 4 post-receptors, and C-peptide in rats with hyperglycemia. The research involved Sprague Dawley rats with high blood sugar levels, which were randomly divided into two groups: a control group of normal rats and a group of rats with hyperglycemia. The hyperglycemic rats were further divided into three subgroups: (1) receiving standard oral hypoglycemic drugs, (2) receiving oral hypoglycemic drugs along with a standard diet, and (3) receiving 200 ml of kefir spirulina along with a standard diet for a period of 30 days. Glucose levels were measured enzymatically, while levels of GLUT-4 and C-peptide were assessed using ELISA. The collected data was analyzed using statistical tests such as Analysis of Covariance (ANCOVA), Duncan, and Mann Whitney, with a significance level set at p&lt;0.05.<br>