cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2n2chm
title: CCDC 2445140: Experimental Crystal Structure Determination

description: Related Article: Mingxia Sun, Jia Chen, Ting Zhang, Jing He, Yunyun Zhang, Huifeng Liu, Wei Xu, Zhao Wang, Hongdeng Qiu|2025|Chem.Eng.Journal|525||doi:10.1016/j.cej.2025.170245
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.cc2n2cjn
title: CCDC 2445141: Experimental Crystal Structure Determination

description: Related Article: Mingxia Sun, Jia Chen, Ting Zhang, Jing He, Yunyun Zhang, Huifeng Liu, Wei Xu, Zhao Wang, Hongdeng Qiu|2025|Chem.Eng.Journal|525||doi:10.1016/j.cej.2025.170245
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.cc2n2d05
title: CCDC 2445156: Experimental Crystal Structure Determination

description: Related Article: Mingxia Sun, Jia Chen, Ting Zhang, Jing He, Yunyun Zhang, Huifeng Liu, Wei Xu, Zhao Wang, Hongdeng Qiu|2025|Chem.Eng.Journal|525||doi:10.1016/j.cej.2025.170245
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.cc2nxyj2
title: CCDC 2470685: Experimental Crystal Structure Determination

description: Related Article: Wei-Chun Lin, Milan Gembicky|2025|CSD Communication|||
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.cc2pmj84
title: CCDC 2491416: Experimental Crystal Structure Determination

description: Related Article: David Rezazgui, Jiří Schulz, Petr Štěpnička|2025|Chem.Commun.|||doi:10.1039/d5cc05762k
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.cc2pmj95
title: CCDC 2491417: Experimental Crystal Structure Determination

description: Related Article: David Rezazgui, Jiří Schulz, Petr Štěpnička|2025|Chem.Commun.|||doi:10.1039/d5cc05762k
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.cc2pmjb6
title: CCDC 2491418: Experimental Crystal Structure Determination

description: Related Article: David Rezazgui, Jiří Schulz, Petr Štěpnička|2025|Chem.Commun.|||doi:10.1039/d5cc05762k
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.cc2pmjc7
title: CCDC 2491419: Experimental Crystal Structure Determination

description: Related Article: David Rezazgui, Jiří Schulz, Petr Štěpnička|2025|Chem.Commun.|||doi:10.1039/d5cc05762k
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.cc2pmjd8
title: CCDC 2491420: Experimental Crystal Structure Determination

description: Related Article: David Rezazgui, Jiří Schulz, Petr Štěpnička|2025|Chem.Commun.|||doi:10.1039/d5cc05762k
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.cc2pmjf9
title: CCDC 2491421: Experimental Crystal Structure Determination

description: Related Article: David Rezazgui, Jiří Schulz, Petr Štěpnička|2025|Chem.Commun.|||doi:10.1039/d5cc05762k
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: 10.15468/dl.f9bvqd
title: Occurrence Download

description: A dataset containing 30791644 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Year 2014-2019"
 ]
}

 The dataset includes 30791644 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002569-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qnarz7
title: Occurrence Download

description: A dataset containing 503 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Psidium guineense"
 ]
}

 The dataset includes 503 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002587-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5cff7t
title: Occurrence Download

description: A dataset containing 71255060 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Year 2021-2024"
 ]
}

 The dataset includes 71255060 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002568-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7trsvv
title: Occurrence Download

description: A dataset containing 16320 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "StateProvince is ESPÍRITO SANTO, ES"
 ]
}

 The dataset includes 16320 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002589-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13735337
title: Bangla Natural Language Inference Dataset
DOI: 10.15468/dl.9zrsfm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-116.1813 35.852, -116.1834 35.85354, -116.1865 35.85224, -116.1853 35.85011, -116.1813 35.852))",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002590-251120083545085/datasets/export for details.
DOI: 10.15468/dl.4h4jcd
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((-86.70699 18.42923,-84.61715 19.9103,-85.79084 22.96874,-84.38241 23.50797,-81.10851 23.89318,-80.78405 24.98606,-80.8165 25.4264,-81.21528 26.60591,-82.08896 29.0341,-82.96264 30.76518,-84.71 31.93761,-90.32652 32.57092,-99.31294 29.68678,-100.68587 22.28976,-98.56407 18.66588,-95.94303 17.36028,-92.94756 17.59838,-89.45284 18.66588,-86.70699 18.42923))",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (b3bf3a83-1f68-4541-a03f-330d30d567f5, 2b8e48b0-812d-11de-86fe-b8a03c50a862, 493fe050-055d-11d8-b84f-b8a03c50a862, 045f6b80-812c-11de-86fd-b8a03c50a862, 8483a1f0-1032-11db-ae00-b8a03c50a862, bc092ff0-02e4-11dc-991f-b8a03c50a862, 1e9400fa-ce73-4737-9eaa-f25df148945c, c3ad790a-d426-4ac1-8e32-da61f81f0117, ff90b050-c256-11db-b71b-b8a03c50a862)",
 "TaxonKey is Nudibranchia"
 ]
}

 The dataset includes 38 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002591-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e155161v91-191750
title: Advance Layoff Notice Data from the WARN Act

description: We collect novel and timely data from advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. The act requires larger employers to notify affected workers at least 60 days before a potential mass layoff. We assemble WARN data from across the United States, and for many large states our data begin in the 1990s. We aggregate these data into an unbalanced, monthly panel of the state-level number of workers affected by WARN notices, and we update this panel twice a month. We also aggregate this panel to a national-level indicator of job loss (the "WARN factor") using a dynamic factor model.<br>

<b><br>Data Collection</b><br>We update the data twice a month by collecting WARN
notices from state websites. For many states, we have extended our historical
data by using digital archives of the internet and contacting state
officials.<br> <br><b>Citation</b><br>To learn more about
the data and the dynamic factor model, see:<br>Krolikowski, Pawel M. and Kurt G. Lunsford. 2022. “Advance Layoff Notices and Aggregate Job Loss.” Federal Reserve Bank of Cleveland, Working Paper no. 20-03R. https://doi.org/10.26509/frbc-wp-202003R.<br>Krolikowski, Pawel M., and Kurt G. Lunsford. 2024 “Advance Layoff Notices and Aggregate Job Loss.” Journal of Applied Econometrics. https://doi.org/10.1002/jae.3032.<b><br><br></b><b>File Description</b><br>The file labelled WARNFiles_YYYYMMDD.zip in the
main directory contains our most recent data. All data included in this zip
file were collected as of the date listed in the file name. Previous
vintages of our data appear in the `Archived_Vintages’ folder, with the same
naming convention.<br>
<br>The zip files contain three files:<br>
<br>


1. 
README.txt

<br>2. 
WARNData_NSA_YYYYMMDD.csv


 
 This .csv contains the number of workers affected by
 WARN notices by state and month. These data are not seasonally adjusted.
 These data are the input into the dynamic factor model.
 


3. 
WARNFactors_YYYYMMDD.csv


 
 This .csv contains the output of the dynamic factor
 model. The output is labeled as follows:
 
 WARN Factor: the estimates of the factor from the
 dynamic factor model.
 MSE: the estimated mean squared errors
 of the WARN factor.
 WARN_hat: the number of workers affected by
 WARN notices as implied by the WARN factor.
 WARN_sum: the sum of the number of
 workers affected by WARN notices from several states that form a
 balanced panel beginning in January 2006. These states can change every
 update.<b>Disclaimer</b><br>These data are
updated by the authors and are not an official product of the Federal Reserve Bank of Cleveland.<br>
description: Smallest Geographic Unit: State
DOI: 10.18112/openneuro.ds006949.v1.0.0
title: Safety MRIs for Focused Ultrasound for the Complex Patient
DOI: 10.15468/dl.4qep86
title: Occurrence Download

description: A dataset containing 1075 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Russian Federation",
 "OccurrenceStatus is Present",
 "TaxonKey is Capreolus capreolus"
 ]
}

 The dataset includes 1075 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002592-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yhrrcn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-118.5997 34.87462, -118.5999 34.8774, -118.6017 34.87761, -118.6049 34.878, -118.6046 34.87435, -118.6021 34.87394, -118.5997 34.87462))",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002593-251120083545085/datasets/export for details.
DOI: 10.15468/dl.hh9n47
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Colección de arañas de Facultad de Ciencias UdelaR"
 ]
}

 The dataset includes 9 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002594-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2923mk
title: Occurrence Download

description: A dataset containing 71 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Phylloscopus makirensis"
 ]
}

 The dataset includes 71 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002595-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17674671
title: Solar wind prediction for Uranus near opposition in 2024

description: 1. Model

 

We use a 3-D magnetohydrodynamic model that predicts solar wind conditions between 1 and 40 AU using time-dependent boundary conditions implemented in the adaptive mesh refinement framework of Multi-scale Fluid-kinetic Simulation Suite (MS-FLUKSS), which is a numerical toolkit designed primarily for modeling flows of partially ionized plasma. See Kim et al. (2016) and Lamy et al. (2017) for details.

 

Simulation domain: 1-40 AUSimulation grid: 4,320 x 720 x 36 (r, phi, theta)Grid size: dr = 0.009 AU, dphi = 0.5 deg, dtheta = 5 deg

 

At 1 AU, the solar wind boundary conditions are derived from OMNI data at low latitudes and fit to Ulysses data at middle to high latitudes (e.g., Kim et al. 2016, 2017; Zirnstein et al. 2022, 2024).

 

At 40 AU, the interstellar neutral hydrogen atom parameters are:

Number density = 0.115 cm^3 (Swaczyna et al. 2020; Swaczyna et al. 2025)Flow speed = 22 km/s (Lallement et al. 2005)Temperature = 10,000 K.

 

2. Data

 

The simulation data file ("uranus2024_ms-flukss.dat") consists of a header and 22 columns of numerical values in the following order:

 

(1) time (fractional year)

(2) distance (AU)

(3) MS-FLUKSS longitude (rotated by ~180 degrees from HGI longitude in degrees)

(4) MS-FLUKSS latitude (same as heliographic latitude in degrees)

(5) solar wind proton number density (cm^-3)

(6) solar wind Vr (km/s)

(7) solar wind Vphi (km/s)

(8) solar wind Vtheta (km/s)

(9) thermal pressure of solar wind and interstellar pickup ion mixture (picodyne/cm^2)

(10) Br (microgauss)

(11) Bphi (microgauss)

(12) Btheta (microgauss)

(13) interstellar hydrogen atom number density (cm^-3)

(14) interstellar hydrogen Vr (km/s)

(15) interstellar hydrogen Vphi (km/s)

(16) interstellar hydrogen Vtheta (km/s)

(17) interstellar hydrogen atom thermal pressure (picodyne/cm^2)

(18) tracking parameter for the heliospheric current sheet 

(19) solar wind and interstellar pickup proton temperature (K)

(20) fractional day of year 2024

(21) interplanetary magnetic field strength (nT)

(22) solar wind dynamic pressure (nPa)

 

3. Figure

 

The figure shows the model predictions of interplanetary magnetic field, solar wind dynamic pressure, radial velocity, and proton number density at Uranus from 2024-09-01 to 2024-11-30.
DOI: 10.5281/zenodo.17674672
title: Solar wind prediction for Uranus near opposition in 2024

description: 1. Model

 

We use a 3-D magnetohydrodynamic model that predicts solar wind conditions between 1 and 40 AU using time-dependent boundary conditions implemented in the adaptive mesh refinement framework of Multi-scale Fluid-kinetic Simulation Suite (MS-FLUKSS), which is a numerical toolkit designed primarily for modeling flows of partially ionized plasma. See Kim et al. (2016) and Lamy et al. (2017) for details.

 

Simulation domain: 1-40 AUSimulation grid: 4,320 x 720 x 36 (r, phi, theta)Grid size: dr = 0.009 AU, dphi = 0.5 deg, dtheta = 5 deg

 

At 1 AU, the solar wind boundary conditions are derived from OMNI data at low latitudes and fit to Ulysses data at middle to high latitudes (e.g., Kim et al. 2016, 2017; Zirnstein et al. 2022, 2024).

 

At 40 AU, the interstellar neutral hydrogen atom parameters are:

Number density = 0.115 cm^3 (Swaczyna et al. 2020; Swaczyna et al. 2025)Flow speed = 22 km/s (Lallement et al. 2005)Temperature = 10,000 K.

 

2. Data

 

The simulation data file ("uranus2024_ms-flukss.dat") consists of a header and 22 columns of numerical values in the following order:

 

(1) time (fractional year)

(2) distance (AU)

(3) MS-FLUKSS longitude (rotated by ~180 degrees from HGI longitude in degrees)

(4) MS-FLUKSS latitude (same as heliographic latitude in degrees)

(5) solar wind proton number density (cm^-3)

(6) solar wind Vr (km/s)

(7) solar wind Vphi (km/s)

(8) solar wind Vtheta (km/s)

(9) thermal pressure of solar wind and interstellar pickup ion mixture (picodyne/cm^2)

(10) Br (microgauss)

(11) Bphi (microgauss)

(12) Btheta (microgauss)

(13) interstellar hydrogen atom number density (cm^-3)

(14) interstellar hydrogen Vr (km/s)

(15) interstellar hydrogen Vphi (km/s)

(16) interstellar hydrogen Vtheta (km/s)

(17) interstellar hydrogen atom thermal pressure (picodyne/cm^2)

(18) tracking parameter for the heliospheric current sheet 

(19) solar wind and interstellar pickup proton temperature (K)

(20) fractional day of year 2024

(21) interplanetary magnetic field strength (nT)

(22) solar wind dynamic pressure (nPa)

 

3. Figure

 

The figure shows the model predictions of interplanetary magnetic field, solar wind dynamic pressure, radial velocity, and proton number density at Uranus from 2024-09-01 to 2024-11-30.
DOI: 10.82250/3003645
title: Genome assembly ASM1285115v1
DOI: 10.15468/dl.knrdk5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-115.8012 35.40948, -115.799 35.40924, -115.7986 35.41052, -115.8011 35.41078, -115.8012 35.40948))",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002596-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.17674471
title: Supplementary Dataset for "Hydrostatic Water Displacement Sensing for Continuous Biogas Monitoring"

description: This dataset contains all supplementary design, schematic, firmware and analytical materials associated with the prototype described in the article “Hydrostatic Water Displacement Sensing for Continuous Biogas Monitoring.”It provides the complete mechanical assembly in SolidWorks Pack & Go format, a CAD-generated non-final bill of materials, the supplementary pricing table (Table S1), and the full electronic design in the form of the native EasyEDA project together with PDF and PNG schematic exports. The package further includes the Arduino/ESP32 firmware exported from Arduino Cloud, as well as all measurement datasets used for the 24-hour and 90-hour stability tests. To ensure full reproducibility of the figures published in the manuscript, Vega plotting scripts are also provided.

The files are intended to support reproduction, verification and further development of the hydrostatic biogas monitoring system in other laboratories or research environments.For additional information, alternative file formats (such as STEP exports), or further support, please contact marekhabara@gmail.com.
DOI: 10.5281/zenodo.17674470
title: Supplementary Dataset for "Hydrostatic Water Displacement Sensing for Continuous Biogas Monitoring"

description: This dataset contains all supplementary design, schematic, firmware and analytical materials associated with the prototype described in the article “Hydrostatic Water Displacement Sensing for Continuous Biogas Monitoring.”It provides the complete mechanical assembly in SolidWorks Pack & Go format, a CAD-generated non-final bill of materials, the supplementary pricing table (Table S1), and the full electronic design in the form of the native EasyEDA project together with PDF and PNG schematic exports. The package further includes the Arduino/ESP32 firmware exported from Arduino Cloud, as well as all measurement datasets used for the 24-hour and 90-hour stability tests. To ensure full reproducibility of the figures published in the manuscript, Vega plotting scripts are also provided.

The files are intended to support reproduction, verification and further development of the hydrostatic biogas monitoring system in other laboratories or research environments.For additional information, alternative file formats (such as STEP exports), or further support, please contact marekhabara@gmail.com.