cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2l96ns
title: CCDC 2392135: Experimental Crystal Structure Determination

description: Related Article: Martina Landrini, Miquel Navarro, Jesús Campos, Luca Rocchigiani|2025|Dalton Trans.|54|898|doi:10.1039/D4DT03150D
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.cc2l96pt
title: CCDC 2392136: Experimental Crystal Structure Determination

description: Related Article: Martina Landrini, Miquel Navarro, Jesús Campos, Luca Rocchigiani|2025|Dalton Trans.|54|898|doi:10.1039/D4DT03150D
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.cc2l96qv
title: CCDC 2392137: Experimental Crystal Structure Determination

description: Related Article: Martina Landrini, Miquel Navarro, Jesús Campos, Luca Rocchigiani|2025|Dalton Trans.|54|898|doi:10.1039/D4DT03150D
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.cc2l96rw
title: CCDC 2392138: Experimental Crystal Structure Determination

description: Related Article: Martina Landrini, Miquel Navarro, Jesús Campos, Luca Rocchigiani|2025|Dalton Trans.|54|898|doi:10.1039/D4DT03150D
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: 10.25438/wes02.28288016.v1
title: CREATIVE: Comparable 2022 General Election Advertising Datasets from Meta and Google

description: We are pleased to provide scholarly access to our digital advertising datasets, which include ads active on Meta and Google platforms from September 1 to Election Day 2022.We are providing these datasets to researchers free of charge. Please complete this form to gain immediate access to the available datasets.
DOI: 10.3886/e158002v1
title: Data and Code for: Using Neural Networks to Predict Micro-Spatial Economic Growth

description: We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2sq-km and 2.4sq-km (where the average US county has dimension of 55.6km), our model predictions achieve R-sq values of 0.85 to 0.91 in levels, which far exceed the accuracy of existing models, and 0.32 to 0.46 in decadal changes, which have no counterpart in the literature and are 3-4 times larger than for commonly used nighttime lights. Our network has wide application for analyzing localized shocks.
description: Weights are not used in our analysis.
description: Response Rates: n/a
description: Presence of Common Scales: No scales were used.
description: All neighborhoods above a population density threshold were included in our analysis.
description: Analysis is conducted on square images of neighborhoods in the contiguous United States. Smallest Geographic Unit: The geographic unit is a neighborhood (image).
description: face-to-face interview; mail questionnaire; remote sensing; Please see our README.md file and our manuscript for details on how each dataset was collected and applied in our study.
DOI: 10.3886/e158002v1-138640
title: Data and Code for: Using Neural Networks to Predict Micro-Spatial Economic Growth

description: We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2sq-km and 2.4sq-km (where the average US county has dimension of 55.6km), our model predictions achieve R-sq values of 0.85 to 0.91 in levels, which far exceed the accuracy of existing models, and 0.32 to 0.46 in decadal changes, which have no counterpart in the literature and are 3-4 times larger than for commonly used nighttime lights. Our network has wide application for analyzing localized shocks.
description: Weights are not used in our analysis.
description: Response Rates: n/a
description: Presence of Common Scales: No scales were used.
description: All neighborhoods above a population density threshold were included in our analysis.
description: Analysis is conducted on square images of neighborhoods in the contiguous United States. Smallest Geographic Unit: The geographic unit is a neighborhood (image).
description: face-to-face interview; mail questionnaire; remote sensing; Please see our README.md file and our manuscript for details on how each dataset was collected and applied in our study.
DOI: 10.3886/e158002
title: Data and Code for: Using Neural Networks to Predict Micro-Spatial Economic Growth

description: We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2sq-km and 2.4sq-km (where the average US county has dimension of 55.6km), our model predictions achieve R-sq values of 0.85 to 0.91 in levels, which far exceed the accuracy of existing models, and 0.32 to 0.46 in decadal changes, which have no counterpart in the literature and are 3-4 times larger than for commonly used nighttime lights. Our network has wide application for analyzing localized shocks.
description: Weights are not used in our analysis.
description: Response Rates: n/a
description: Presence of Common Scales: No scales were used.
description: All neighborhoods above a population density threshold were included in our analysis.
description: Analysis is conducted on square images of neighborhoods in the contiguous United States. Smallest Geographic Unit: The geographic unit is a neighborhood (image).
description: face-to-face interview; mail questionnaire; remote sensing; Please see our README.md file and our manuscript for details on how each dataset was collected and applied in our study.
DOI: 10.3886/e158002v2
title: Data and Code for: Using Neural Networks to Predict Micro-Spatial Economic Growth

description: We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2sq-km and 2.4sq-km (where the average US county has dimension of 55.6km), our model predictions achieve R-sq values of 0.85 to 0.91 in levels, which far exceed the accuracy of existing models, and 0.32 to 0.46 in decadal changes, which have no counterpart in the literature and are 3-4 times larger than for commonly used nighttime lights. Our network has wide application for analyzing localized shocks.
description: Weights are not used in our analysis.
description: Response Rates: n/a
description: Presence of Common Scales: No scales were used.
description: All neighborhoods above a population density threshold were included in our analysis.
description: Analysis is conducted on square images of neighborhoods in the contiguous United States. Smallest Geographic Unit: The geographic unit is a neighborhood (image).
description: face-to-face interview; mail questionnaire; remote sensing; Please see our README.md file and our manuscript for details on how each dataset was collected and applied in our study.
DOI: 10.15468/dl.x6kc6d
title: Occurrence Download

description: A dataset containing 115378 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vombatidae"
 ]
}

 The dataset includes 115378 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000561-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.56bv2y
title: Occurrence Download

description: A dataset containing 2261 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Culex coronator Dyar & Knab, 1906"
 ]
}

 The dataset includes 2261 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000599-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7273/000007121
title: DATASET: Intertidal Microcosms of Wave-Swept Rocky Shores: Ecological and Physiological Insights From a Uniquely Stressful Environment

description: Dataset to accompany manuscript of the same name submitted to Phil. Trans. R. Soc. Includes measures of body temperature over the anterior-posterior axis of individual intertidal mussels (Mytilus californianus).
DOI: 10.5281/zenodo.14751060
title: Diamond Mice Prostates
DOI: 10.5281/zenodo.14751061
title: Diamond Mice Prostates
DOI: 10.26025/1912/71331
title: Voltage scans from a prototype hollow core fiber isotope ratio laser spectrometer

description: This dataset consists of 900 one-second-long voltage acquisitions across 2000 detector channels from a prototype hollow core fiber isotope ratio laser spectrometer developed and operated at the Woods Hole Oceanographic Institution’s David Center for Ocean Innovation. Each acquisition covers a spectral range of ~2290.55 to 2299.15 cm-1. The operational conditions are 2.5 torr of pure CO2 in a 1m-long hollow core fiber with an inner diameter of 200 µm at room temperature (~20ºC). The laser was scanned across this spectral range at 50kHz and each one-second acquisition is the average of 50000 individual spectral scans within that one second.
DOI: 10.17863/cam.114388
title: Research Data Supporting "Nuclear Wavefunctions of Dispersion Bound Systems: Endohedral Eigenstates of Endofullerenes"

description: This is the root directory containing data files, bash scripts, and Python scripts to generate the data for the tables and figures in my PhD thesis, titled "Nuclear Wavefunctions of Dispersion Bound Systems: Endohedral Eigenstates of Endofullerenes". This thesis was submitted in September 2024, with corrections (no additional calculations) approved in December 2024. The electronic structure data is provided raw, as outputs from FermiONs++ and FHI-aims. The machine learned PESs are constructed from Python scripts. These are then used to calculate the nuclear eigenstates, which is achieved using a self written library, "EPEE" available on GitLab at https://gitlab.developers.cam.ac.uk/ksp31/epee. Author: Kripa Panchagnula Date: January 2025 To run the machine learning, nuclear diagonalisation, and plotting scripts the "thesis_calcs" branch (commit SHA: 100d79600aae7668d4ceaeafc6274a89f019283c) or "main" branch (commit SHA: 4e4d677f609028710fbc8e4f48dc4895543340db) of EPEE is required alongside NumPy, SciPy, scikit-learn, matplotlib and the "development" branch of QSym2 from https://qsym2.dev/. Any Python script importing from src is referring to the EPEE library. Each Python script must be run from within its containing directory. The data is separated into the following folders: - background/ This folder contains a Python script to generate figures for Chapters 1-3. - He@C60/ This folder contains electronic structure data from FermiONs++ with Python scripts to generate data for Chapter 4. - X@C70/ This folder contains Python scripts to generate data for Chapter 5. - Ne@C70/ This folder contains electronic structure data from FermiONs++ and FHI-aims with Python scripts to generate data for Chapter 6. - H2@C70/ This folder contains Python scripts to generate data for Chapter 7. - peapods/ This folder contains Python scripts to generate data for Chapter 8. Each folder contains its own README, with more details about its structure. File types include text files (.txt, .dat, .cube), scripts (.bash, .py) and NumPy compressed data files (.npz).
DOI: 10.15468/dl.vmpu4z
title: Occurrence Download

description: A dataset containing 10910288 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "Year 1990-2025"
 ]
}

 The dataset includes 10910288 records from 1080 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000567-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25438/wes02.28288016.v2
title: CREATIVE: Comparable 2022 General Election Advertising Datasets from Meta and Google

description: We are pleased to provide scholarly access to our digital advertising datasets, which include ads active on Meta and Google platforms from September 1 to Election Day 2022.We are providing these datasets to researchers free of charge. Please complete this form to gain immediate access to the available datasets.
DOI: 10.6084/m9.figshare.28288505
title: Crustivorous macro-arthropods regulate the microtopography and carbon dynamics of biological soil crusts

description: Data and code for the article titled:Crustivorous macro-arthropods regulate the microtopography and carbon dynamics of biological soil crusts(Sagi, Sagy, Felde & Hawlena 2025, <i>Geoderma</i>)The methodology, including field collection, lab experiments and measurements, and statistical analysis, is detailed in the above-mentioned reference.<br>Abstract:Biological soil crusts (biocrusts) play key roles in dryland ecosystem processes by mediating soil surface conditions. How consumption by macro-arthropods affects biocrust surface roughness and carbon cycling remains largely unknown. In two separate experiments, we addressed this knowledge gap by exposing biocrusts to varying levels of desert isopod crustivory (i.e. grazing intensity), and quantifying the consequences for microtopography, CO<sub>2</sub> efflux and carbon fixation. Biocrust surface roughness peaked under intermediate crustivory pressure, implying that varying levels of crustivory may have opposing consequences for ecosystem processes such as carbon cycling, water infiltration, runoff generation and soil erosion. However, crustivory had a monotonic negative effect on biocrust carbon cycling. Biocrust CO<sub>2</sub> efflux decreased with increasing crustivory, but recovered after several wetting events. Crustivory had a negative effect on biocrust C fixation, but only after the CO<sub>2</sub> efflux recovered to pre-crustivory levels. Our findings suggest that macro-crustivores may play a pivotal role in regulating biocrust functioning, introducing a whole new line of trophic research that may transform our understanding of ecosystems dynamics in drylands.<br>
DOI: 10.6084/m9.figshare.28288505.v1
title: Crustivorous macro-arthropods regulate the microtopography and carbon dynamics of biological soil crusts

description: Data and code for the article titled:Crustivorous macro-arthropods regulate the microtopography and carbon dynamics of biological soil crusts(Sagi, Sagy, Felde & Hawlena 2025, <i>Geoderma</i>)The methodology, including field collection, lab experiments and measurements, and statistical analysis, is detailed in the above-mentioned reference.<br>Abstract:Biological soil crusts (biocrusts) play key roles in dryland ecosystem processes by mediating soil surface conditions. How consumption by macro-arthropods affects biocrust surface roughness and carbon cycling remains largely unknown. In two separate experiments, we addressed this knowledge gap by exposing biocrusts to varying levels of desert isopod crustivory (i.e. grazing intensity), and quantifying the consequences for microtopography, CO<sub>2</sub> efflux and carbon fixation. Biocrust surface roughness peaked under intermediate crustivory pressure, implying that varying levels of crustivory may have opposing consequences for ecosystem processes such as carbon cycling, water infiltration, runoff generation and soil erosion. However, crustivory had a monotonic negative effect on biocrust carbon cycling. Biocrust CO<sub>2</sub> efflux decreased with increasing crustivory, but recovered after several wetting events. Crustivory had a negative effect on biocrust C fixation, but only after the CO<sub>2</sub> efflux recovered to pre-crustivory levels. Our findings suggest that macro-crustivores may play a pivotal role in regulating biocrust functioning, introducing a whole new line of trophic research that may transform our understanding of ecosystems dynamics in drylands.<br>
DOI: 10.6084/m9.figshare.28291820
title: MetS and coffee consumption

description: There is minimal information in the Saudi population about the relationship between coffee consumption and metabolic syndrome (MetS) components. Furthermore, in Saudi Arabia, studies are being undertaken on coffee consumption and MetS risk factors, but not on MetS components. Hence, this study aimed to assess the relationship between coffee consumption and MetS components among Saudi adults at King Abdulaziz University hospital.
DOI: 10.15468/dl.huc6dr
title: Occurrence Download

description: A dataset containing 2693 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anolis gundlachi Peters, 1877"
 ]
}

 The dataset includes 2693 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000604-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t3jxca
title: Occurrence Download

description: A dataset containing 8428 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-92.0161 17.3785,-91.96829 17.37348,-91.95395 17.45141,-91.95339 17.49146,-91.98742 17.49731,-92.00822 17.47886,-92.01108 17.44759,-92.01347 17.40551,-92.0161 17.3785))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8428 records from 133 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000605-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14727852
title: Data supporting "The Role of Seasonal Precipitation Sequences in Shaping the Climate of the US Southwest"

description: Data presented in this entry are seasonal total precipitation and average temperature for five different regions across the southwest United States. The seasonal values are derived from monthly values of the PRISM gridded climate dataset. The regions were developed using a clustering technique detailed in the corresponding manuscript. 

Region values are presented in columns with the following labels:

"Colorado Plateau (CP)","Great Plains (GP)","Lower Gila/Colorado (LGC)","Upper Gila (UG)","Rio Grande (RG)"
DOI: 10.5281/zenodo.14727853
title: Data supporting "The Role of Seasonal Precipitation Sequences in Shaping the Climate of the US Southwest"

description: Data presented in this entry are seasonal total precipitation and average temperature for five different regions across the southwest United States. The seasonal values are derived from monthly values of the PRISM gridded climate dataset. The regions were developed using a clustering technique detailed in the corresponding manuscript. 

Region values are presented in columns with the following labels:

"Colorado Plateau (CP)","Great Plains (GP)","Lower Gila/Colorado (LGC)","Upper Gila (UG)","Rio Grande (RG)"
DOI: 10.15468/dl.r8wrk3
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "HasCoordinate is false",
 "TaxonKey is Ulex europaeus L."
 ]
}

 The dataset includes 39 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000607-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.647na8
title: Occurrence Download

description: A dataset containing 1301 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Indonesia",
 "OccurrenceStatus is Present",
 "TaxonKey is Pometia pinnata J.R.Forst. & G.Forst."
 ]
}

 The dataset includes 1301 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000608-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14751157
title: Catabolome

description: final metabolite concentrations at fermented drinks
DOI: 10.15468/dl.9vbd98
title: Occurrence Download

description: A dataset containing 3998 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "GadmGid is POL",
 "TaxonKey is Castor fiber Linnaeus, 1758"
 ]
}

 The dataset includes 3998 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000611-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14751166
title: Desarrollo de la empleabilidad de personas refugiadas en España: Programa de Intervención
DOI: 10.5281/zenodo.14751167
title: Desarrollo de la empleabilidad de personas refugiadas en España: Programa de Intervención
DOI: 10.6084/m9.figshare.26026741
title: Datasets of delta-containing GABA<sub>A</sub> receptor knockout in PV interneurons

description: We explored cellular, synaptic, and local-circuit activity in PV interneurons and pyramidal neurons in mouse mPFC after selectively deleting δ subunits in PV interneurons (cKO mice). In current-clamp recordings, cKO PV interneurons exhibited a higher frequency of action potentials and higher input resistance than wild type (WT) PV interneurons. Picrotoxin increased firing and GABA decreased firing in WT PV interneurons but not in cKO PV interneurons. The δ-preferring agonist THIP reduced spontaneous inhibitory postsynaptic currents in WT pyramidal neurons but not in cKO pyramidal neurons. In WT slices, depolarizing the network with 400 nM kainate increased firing of pyramidal neurons but had little effect on PV interneuron firing. By contrast, in cKO slices kainate recruited PV interneurons at the expense of pyramidal neurons. At the population level, kainate induced broadband increases in local field potentials in WT but not cKO slices. These results on cells and the network can be understood through increased excitability of cKO PV interneurons. In summary, our study demonstrates that δ-containing GABA<sub>A</sub> receptors in mPFC PV interneurons play a crucial role in regulating their excitability and the phasic inhibition of pyramidal neurons, elucidating intricate mechanisms governing cortical circuitry.