cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2g49c9
title: CCDC 2268250: Experimental Crystal Structure Determination

description: Related Article: Bakr F. Abdel-Wahab, Benson M. Kariuki, Hanan A. Mohamed, Mohamed S. Bekheit, Hanem M. Awad, Gamal A. El-Hiti|2023|J.Mol.Struct.|1294|136528|doi:10.1016/j.molstruc.2023.136528
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: 10.25573/data.10046099.v4
title: Bay of Panama Water Quality Monitoring Project, Site 6 of 7

description: Bay of Panama water quality monitoring program. Site #6 (of 7). <br>Location: 8° 47.078'N, 79° 27.968'W<br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde. <br>Parameters measured temperature, salinity, conductivity, pH, turbidity, chlorophyll, Dissolved Oxygen<br><br>
DOI: 10.6084/m9.figshare.24138777
title: protein.txt

description: This is a part of the toy dataset (total of 4 files including labels) provided by the CustOmics authors and available on their GitHub repository: https://github.com/HakimBenkirane/CustOmics/blob/main/toy_data/protein.txtIn this dataset, protein data are provided with one probe per row and one column per subject.
DOI: 10.25573/data.10042721.v4
title: Bay of Panama Water Quality Monitoring Project, Site 2 of 7

description: Bay of Panama water quality monitoring program. Site #6 (of 7). <br>Location: 8° 42.498'N, 78° 57.855'W<br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde. <br>Parameters measured temperature, salinity, conductivity, pH, turbidity, chlorophyll, Dissolved Oxygen
DOI: 10.25573/data.10042724.v4
title: Bay of Panama Water Quality Monitoring Project, Site 4 of 7

description: Bay of Panama water quality monitoring program. Site #4 (of 7). <br>Location: 8° 44.138'N, 79° 15.955'W<br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde. <br>Parameters measured temperature, salinity, conductivity, pH, turbidity, chlorophyll, Dissolved Oxygen
DOI: 10.6084/m9.figshare.24138822
title: Arbuscular mycorrhizal fungi benefit plants in response to major global change factors

description: Land plants play a key role in global carbon cycling, but the potential role of arbuscular mycorrhizal fungi (AMF) in responses of a wide range of plant species to global change factors (GCFs) remains limited. Here, we compiled a dataset regarding the responses of plants inoculated with AMF and their non-inoculated counterparts to four GCFs, drought, warming, nitrogen addition and elevated CO<sub>2</sub> from 181 plant species.
DOI: 10.5281/zenodo.8075978
title: Tetrafluorenofulvalene as a Sterically Frustrated Open-Shell Alkene

description: Cartesian coordinates of calculated structures Source data for Fig. 4 and Supplementary Fig. 12, 16–18, and 21
DOI: 10.5281/zenodo.8075979
title: Tetrafluorenofulvalene as a Sterically Frustrated Open-Shell Alkene

description: Cartesian coordinates of calculated structures Source data for Fig. 4 and Supplementary Fig. 12, 16–18, and 21
DOI: 10.25573/data.10042382.v4
title: Bay of Panama Water Quality Monitoring Project_Temperature, all stations

description: Bay of Panama water quality monitoring program. <br>Initiated July 2017<br><br>Temperature data for all stations<br><br>Depth profiles at 7 locations. Approximately 5m depth intervals<br><br>Sampling Sites<br> 1 8° 38.743'N 79° 2.887'W<br> 2 8° 42.498'N 78° 57.855'W<br> 3 8° 41.894'N 79° 9.648'W<br> 4 8° 44.138'N 79° 15.955'W<br> 5 8° 45.670'N 79° 21.906'W<br> 6 8° 47.078'N 79° 27.968'W<br> 7 8° 51.308'N 79° 28.162'W<br> <br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde.<br>
DOI: 10.25573/data.10042700.v3
title: Bay of Panama Water Quality Monitoring Project_Chlorophyll, all stations

description: Bay of Panama water quality monitoring program. <br>Initiated July 2017<br><br>Chlorophyll & Blue-green algae measurements for all stations<br><br>Depth profiles at 7 locations. Approximately 5m depth intervals<br><br>Sampling Sites<br> 1 8° 38.743'N 79° 2.887'W<br> 2 8° 42.498'N 78° 57.855'W<br> 3 8° 41.894'N 79° 9.648'W<br> 4 8° 44.138'N 79° 15.955'W<br> 5 8° 45.670'N 79° 21.906'W<br> 6 8° 47.078'N 79° 27.968'W<br> 7 8° 51.308'N 79° 28.162'W<br> <br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde.<br>
DOI: 10.25573/data.10042682.v3
title: Bay of Panama Water Quality Monitoring Project_pH, all stations

description: Bay of Panama water quality monitoring program. <br>Initiated July 2017<br><br>pH data for all stations<br>Depth profiles at 7 locations. Approximately 5m depth intervals<br><br>Sampling Sites<br> 1 8° 38.743'N 79° 2.887'W<br> 2 8° 42.498'N 78° 57.855'W<br> 3 8° 41.894'N 79° 9.648'W<br> 4 8° 44.138'N 79° 15.955'W<br> 5 8° 45.670'N 79° 21.906'W<br> 6 8° 47.078'N 79° 27.968'W<br> 7 8° 51.308'N 79° 28.162'W<br> <br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde.<br>
DOI: 10.34740/kaggle/dsv/6472896
title: COVID Vaccination in World (updated daily)
DOI: 10.25573/data.10042703.v3
title: Bay of Panama Water Quality Monitoring Project, Site 1 of 7

description: Bay of Panama water quality monitoring program. Site #1 (of 7). <br>Location: 8° 38.743'N, 79° 2.887'W<br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde. <br>Parameters measured temperature, salinity, conductivity, pH, turbidity, chlorophyll, Dissolved Oxygen
DOI: 10.25573/data.10042706.v3
title: Bay of Panama Water Quality Monitoring Project, Site 3 of 7

description: Bay of Panama water quality monitoring program. Site #3 (of 7). <br>Location: 8° 41.894'N, 79° 9.648'W<br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde. <br>Parameters measured temperature, salinity, conductivity, pH, turbidity, chlorophyll, Dissolved Oxygen
DOI: 10.25573/data.10042715.v3
title: Bay of Panama Water Quality Monitoring Project, Site 5 of 7

description: Bay of Panama water quality monitoring program. Site #5 (of 7). <br>Location: 8° 45.670'N, 79° 21.906'W<br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde. <br>Parameters measured temperature, salinity, conductivity, pH, turbidity, chlorophyll, Dissolved Oxygen
DOI: 10.25573/data.10042385.v3
title: Bay of Panama Water Quality Monitoring Project, Site 7 of 7

description: Bay of Panama water quality monitoring program. Site #7 (of 7). <br>Location: 8° 51.308'N, 79° 28.162'W<br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde. <br>Parameters measured temperature, salinity, conductivity, pH, turbidity, chlorophyll, Dissolved Oxygen
DOI: 10.5281/zenodo.6510859
title: China-2020

description: Atlite cutout for Pypsa-China
DOI: 10.5281/zenodo.6510858
title: China-2020

description: Atlite cutout for Pypsa-China
DOI: 10.5281/zenodo.8343761
title: China-2020

description: Atlite cutout for Pypsa-China
DOI: 10.25573/data.10042685.v3
title: Bay of Panama Water Quality Monitoring Project_Dissolved Oxygen, all stations

description: Bay of Panama water quality monitoring program. <br>Initiated July 2017<br><br>Dissolved Oxygen for all stations<br>Depth profiles at 7 locations. Approximately 5m depth intervals<br><br>Sampling Sites<br> 1 8° 38.743'N 79° 2.887'W<br> 2 8° 42.498'N 78° 57.855'W<br> 3 8° 41.894'N 79° 9.648'W<br> 4 8° 44.138'N 79° 15.955'W<br> 5 8° 45.670'N 79° 21.906'W<br> 6 8° 47.078'N 79° 27.968'W<br> 7 8° 51.308'N 79° 28.162'W<br> <br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde.<br>
DOI: 10.5281/zenodo.8345025
title: NuCLR AME2020 Dataset

description: Copy of AME2020 dataset used to train NuCLR: https://openreview.net/pdf?id=DICZxsnvYD
DOI: 10.5281/zenodo.8345024
title: NuCLR AME2020 Dataset

description: Copy of AME2020 dataset used to train NuCLR: https://openreview.net/pdf?id=DICZxsnvYD
DOI: 10.25573/data.10042712.v3
title: Bay of Panama Water Quality Monitoring Project_Salinity, all stations

description: Bay of Panama water quality monitoring program. <br>Initiated July 2017<br><br>Salinity and conductivity for all stations<br><br>Depth profiles at 7 locations. Approximately 5m depth intervals<br><br>Sampling Sites<br> 1 8° 38.743'N 79° 2.887'W<br> 2 8° 42.498'N 78° 57.855'W<br> 3 8° 41.894'N 79° 9.648'W<br> 4 8° 44.138'N 79° 15.955'W<br> 5 8° 45.670'N 79° 21.906'W<br> 6 8° 47.078'N 79° 27.968'W<br> 7 8° 51.308'N 79° 28.162'W<br> <br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde.<br>
DOI: 10.25573/data.10042709.v3
title: Bay of Panama Water Quality Monitoring Project_Dissolved Organic matter, all stations

description: Bay of Panama water quality monitoring program. <br>Initiated July 2017<br><br>Dissolved Oxygen measurements for all stations<br>Depth profiles at 7 locations. Approximately 5m depth intervals<br><br>Sampling Sites<br> 1 8° 38.743'N 79° 2.887'W<br> 2 8° 42.498'N 78° 57.855'W<br> 3 8° 41.894'N 79° 9.648'W<br> 4 8° 44.138'N 79° 15.955'W<br> 5 8° 45.670'N 79° 21.906'W<br> 6 8° 47.078'N 79° 27.968'W<br> 7 8° 51.308'N 79° 28.162'W<br> <br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde.<br>
DOI: 10.48339/9k8m-ae74
title: Barnlösa män och icke-föräldralediga fäder
DOI: 10.25573/data.10042388.v3
title: Bay of Panama Water Quality Monitoring Project_Turbidity, all stations

description: Bay of Panama water quality monitoring program. <br>Initiated July 2017<br><br>Turbidity data for all stations<br>Depth profiles at 7 locations. Approximately 5m depth intervals<br><br>Sampling Sites<br> 1 8° 38.743'N 79° 2.887'W<br> 2 8° 42.498'N 78° 57.855'W<br> 3 8° 41.894'N 79° 9.648'W<br> 4 8° 44.138'N 79° 15.955'W<br> 5 8° 45.670'N 79° 21.906'W<br> 6 8° 47.078'N 79° 27.968'W<br> 7 8° 51.308'N 79° 28.162'W<br> <br>Weekly depth profile (approximately 5m intervals) using YSI EXO 2 sonde.<br>
DOI: 10.48339/te0j-ze82
title: Employer learning about worker productivity in the Swedish labor market
DOI: 10.5281/zenodo.8340311
title: Charge Transport Across Au–P3HT–Graphene van der Waals Vertical Heterostructures (Dataset)

description: Dataset of the vertical Au-P3HT-Gr stacks measurements related to the publication: "Charge Transport Across Au–P3HT–Graphene van der Waals Vertical Heterostructures", ACS, Appl. Mater. Interfaces, 2022. The dataset includes: AFM raw data Raman spectroscopy raw data Room temperature measurements Impedance analysis measurements Temperature dependent measurements
DOI: 10.5281/zenodo.8340310
title: Charge Transport Across Au–P3HT–Graphene van der Waals Vertical Heterostructures (Dataset)

description: Dataset of the vertical Au-P3HT-Gr stacks measurements related to the publication: "Charge Transport Across Au–P3HT–Graphene van der Waals Vertical Heterostructures", ACS, Appl. Mater. Interfaces, 2022. The dataset includes: AFM raw data Raman spectroscopy raw data Room temperature measurements Impedance analysis measurements Temperature dependent measurements
DOI: 10.48339/5xy4-nj60
title: UGU-data till projektet: Elevers motivation, välbefinnande och prestationer från mellanstadiet till gymnasiet
DOI: 10.48339/pjsn-xe72
title: UGU data till projektet: Växelvis boende i Sverige
DOI: 10.5281/zenodo.8028483
title: TBD

description: TBD
DOI: 10.5281/zenodo.8028484
title: TBD

description: TBD
DOI: 10.6096/3003
title: Clustering and inundation maps based on CYGNSS reflectivity

description: 
March 16, 2023

Contact: pierre.zeiger@outlook.fr (Pierre Zeiger)

These files present statistical parameters based on CYGNSS reflectivity derived 
from the CYGNSS Level 1 Science Data Records, v3.0, which were further used to 
produce a clustering map and an estimation of the fractional inundation. 
The spatial resolution is 0.1° and the temporal resolution is 7 days. The
estimations cover the inter-tropical band from -37.5° to 37.5° latitude during a
1-year study period, from August 1, 2018 to July 31, 2019.

Here are the reference papers for this work:
1) Pierre Zeiger, Frédéric Frappart, José Darrozes, Catherine Prigent and Carlos 
	   Jiménez. Analysis of CYGNSS coherent reflectivity over land for the 
	   characterization of pan-tropical inundation dynamics. Remote Sensing of 
	   Environment, 2022, https://doi.org/10.1016/j.rse.2022.113278

2) Pierre Zeiger, Frédéric Frappart, José Darrozes, Catherine Prigent, Carlos 
	   Jiménez and Luc Bourrel. Weekly mapping of surface water extent in the 
	   pan-tropical wetlands using spaceborne GNSS Reflectometry (submitted).

Two files are distributed:

	a) LEGOS_ReflectivityCYGNSS_0.1deg_7D_2018-2019_v1.0.nc contains the statistical 
	   parameters (weighted mean and standard deviation, median and median absolute 
	   deviation, maximum, 75th and 90th percentile, number of observations) based
	   on CYGNSS reflectivity, gridded at 0.1° spatial resolution and 7-day temporal 
	   resolution for the entire spatiotemporal coverage of the study. It should be 
	   useful as a basis to understand the reflectivity signal in regions with varying 
	   geophysical properties.
	   
	   Dimensions: lon, lat, time
	   Variables: means (mean reflectivity), stds (std reflectivity), counts (number of 
	   observations), maxs (maximum of reflectivity), medians (median reflectivity), mad 
	   (median absolute deviation of reflectivity), per75 (75th percentile of reflectivity), 
	   per90 (90th percentile of reflectivity)
	   
	b) LEGOS_WaterFractionCYGNSS_0.1deg_7D_2018-2019_v1.0.nc contains the more advanced 
	   results, i.e. the clustering map permitting to delineate flooded regions and the 
	   dynamic estimation of the fraction of water in 0.1° pixels. It should be useful to 
	   compare with other flooding products and to support hydrological researches.
	   
	   Dimensions: lon, lat, time
	   Variables: water_fraction (fractional inundation in the pixel), clustering_map
	   (output of the DTW clustering), pixel_size (size of 0.1° pxiels in km²)

This dataset is referenced, please use the dedicated citations.
DOI: 10.5281/zenodo.8345048
title: Databases social representation of nutrition

description: Data from an investigation of the social representation of nutrition in palliative care cancer patients and their caregivers.
DOI: 10.5281/zenodo.8345047
title: Databases social representation of nutrition

description: Data from an investigation of the social representation of nutrition in palliative care cancer patients and their caregivers.
DOI: 10.18462/iir.icr.2023.0539
title: Sustainability within food cold chain sectors in Norway.
DOI: 10.5519/qd.s7ldx2os
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (42 records)
DOI: 10.6084/m9.figshare.24138975
title: CEOF amplitude maps

description: Decomposition into Complex Empirical Orthogonal Functions (CEOF) of the intraseasonal sea level anomalies from the CR-long simulation. Spatial patterns of the amplitude of the first (CEOF1) and second (CEOF2) mode. Rt: Reconstructed SLA from CEOF1 and averaged in the region (2°S–2°N, 150°W–130°W).
DOI: 10.6084/m9.figshare.24138975.v1
title: CEOF amplitude maps

description: Decomposition into Complex Empirical Orthogonal Functions (CEOF) of the intraseasonal sea level anomalies from the CR-long simulation. Spatial patterns of the amplitude of the first (CEOF1) and second (CEOF2) mode. Rt: Reconstructed SLA from CEOF1 and averaged in the region (2°S–2°N, 150°W–130°W).
DOI: 10.6084/m9.figshare.23750538
title: TNBC-Tregs

description: Source data-TNBC-Tregs
DOI: 10.6084/m9.figshare.23750538.v4
title: TNBC-Tregs

description: Source data-TNBC-Tregs
DOI: 10.6084/m9.figshare.23750538.v3
title: TNBC-Tregs

description: Source data-TNBC-Tregs
DOI: 10.6084/m9.figshare.24001356
title: Spatial transcriptomic_TNBC_Tregs

description: TNBC_Tregs
DOI: 10.6084/m9.figshare.24001356.v2
title: Spatial transcriptomic_TNBC_Tregs

description: TNBC_Tregs
DOI: 10.6084/m9.figshare.24001356.v1
title: Spatial transcriptomic_TNBC_Tregs

description: TNBC_Tregs
DOI: 10.7924/r4h133m7w
title: Data from: Nasal immunization with small molecule mast cell activators enhance immunity to co-administered subunit immunogens

description: Mast cell activators are a novel class of mucosal vaccine adjuvants. The polymeric compound, Compound 48/80 (C48/80), and cationic peptide, Mastoparan 7 (M7) are mast cell activators that provide adjuvant activity when administered by the nasal route. However, small molecule mast cell activators may be a more cost-efficient adjuvant alternative that is easily synthesized with high purity compared to M7 or C48/80. To identify novel mast cell activating compounds that could be evaluated for mucosal vaccine adjuvant activity, we employed high-throughput screening to assess over 55,000 small molecules for mast cell degranulation activity. Fifteen mast cell activating compounds were down-selected to five compounds based on in vitro immune activation activities including cytokine production and cellular cytotoxicity, synthesis feasibility, and selection for functional diversity.  These small molecule mast cell activators were evaluated for in vivo adjuvant activity and induction of protective immunity against West Nile Virus infection in BALB/c mice when combined with West Nile Virus envelope domain III (EDIII) protein in a nasal vaccine.  We found that three of the five mast cell activators, ST101036, ST048871, and R529877, evoked high levels of EDIII-specific antibody and conferred comparable levels of protection against WNV challenge. The level of protection provided by these small molecule mast cell activators was comparable to the protection evoked by M7 (67%), but markedly higher than the levels seen with mice immunized with EDIII alone (no adjuvant 33%). Thus, novel small molecule mast cell activators identified by high throughput screening are as efficacious as previously described mast cell activators   when used as nasal vaccine adjuvants and represent next generation mast cell activators for evaluation in mucosal vaccine studies
DOI: 10.25403/upresearchdata.24115440
title: Risk disclosure readability

description: Diction analyses text in terms of five main categories, namely: activity, certainty, commonality, optimism, and realism. Risk disclosures and risk management disclosures from the integrated reports of companies listed on the Johannesburg Stock Exchange were analysed according to these categories. A detailed table containing information for all the sub-categories is presented here.
DOI: 10.25403/upresearchdata.24115440.v1
title: Risk disclosure readability

description: Diction analyses text in terms of five main categories, namely: activity, certainty, commonality, optimism, and realism. Risk disclosures and risk management disclosures from the integrated reports of companies listed on the Johannesburg Stock Exchange were analysed according to these categories. A detailed table containing information for all the sub-categories is presented here.
DOI: 10.23645/epacomptox.6062623.v10
title: ToxCast Database: invitrodb version 3.5

description: ToxCast high-throughput assay information including assay annotation user guide, assay target information, study design information and quality statistics on the assays.
DOI: 10.6084/m9.figshare.24117117
title: Files needed for the plot_gubbins.R example.

description: Files needed for the plot_gubbins.R example, generated from the analysis described in https://doi.org/10.1186/s13073-022-01147-2.
DOI: 10.5281/zenodo.8345018
title: RESISTIRÉ Dataset: Narratives on inequalities caused by policy and societal responses to Covid-19 in Europe – second cycle

description: This dataset contains 295 narratives, including keywords and specifically telling quotes. It is the second of three sets of narratives collected and analysed in RESISTIRÉ. The narrative interviews were conducted in national languages by the consortium partners and a network of national researchers covering the EU27 (except Malta), and Iceland, Serbia, and the UK in December 2021-February 2022. Narrative interviewing is a qualitative research method that involves inviting participants to tell their own stories and experiences in their own words. The technique is used to collect and share a person’s story which entails both a research methodology and a mechanism for storytelling i.e. both a way of telling a story, and a way of knowing. Narratives as a technique can make visible how multiple sources of inequalities intersect, as well as the situational and contextual nature of inequalities from a single person’s perspective.
DOI: 10.5281/zenodo.8345017
title: RESISTIRÉ Dataset: Narratives on inequalities caused by policy and societal responses to Covid-19 in Europe – second cycle

description: This dataset contains 295 narratives, including keywords and specifically telling quotes. It is the second of three sets of narratives collected and analysed in RESISTIRÉ. The narrative interviews were conducted in national languages by the consortium partners and a network of national researchers covering the EU27 (except Malta), and Iceland, Serbia, and the UK in December 2021-February 2022. Narrative interviewing is a qualitative research method that involves inviting participants to tell their own stories and experiences in their own words. The technique is used to collect and share a person’s story which entails both a research methodology and a mechanism for storytelling i.e. both a way of telling a story, and a way of knowing. Narratives as a technique can make visible how multiple sources of inequalities intersect, as well as the situational and contextual nature of inequalities from a single person’s perspective.
DOI: 10.25405/data.ncl.21066037
title: Quantum Droplets in Imbalanced Mixtures

description: The figure generating scripts and data files (all in .csv format) are contained in the 'imbal_drops_figs_data.tar.gz' file, with further details of the data given in the 'README.md' file.The techniques behind generating and extracting the attached data, all appear in the original manuscript.I generated all of the data using Rocket, Newcastle University's High Performance Computing service.
DOI: 10.25405/data.ncl.21066037.v1
title: Quantum Droplets in Imbalanced Mixtures

description: The figure generating scripts and data files (all in .csv format) are contained in the 'imbal_drops_figs_data.tar.gz' file, with further details of the data given in the 'README.md' file.The techniques behind generating and extracting the attached data, all appear in the original manuscript.I generated all of the data using Rocket, Newcastle University's High Performance Computing service.