cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.kk2djw
title: Occurrence Download

description: A dataset containing 623 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Boana pugnax (Schmidt, 1857)"
 ]
}

 The dataset includes 623 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0265897-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cf9dnv
title: Occurrence Download

description: A dataset containing 4097 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Triumfetta rhomboidea Jacq.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4097 records from 220 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022449-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t2vnz2
title: Occurrence Download

description: A dataset containing 258 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Begonia potamophila Gilg"
 ]
}

 The dataset includes 258 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056397-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8vbebm
title: Occurrence Download

description: A dataset containing 3804 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Catálogo de autoridades taxonómicas de Cyanoprocaryota marinos bentónicos de México"
 ]
}

 The dataset includes 3804 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0325280-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vtlh9o
title: Occurrence Download

description: A dataset containing 71 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Observation",
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Material sample",
 "BasisOfRecord is Literature Occurrence",
 "BasisOfRecord is Specimen"
 ]
 },
 "HasCoordinate is true",
 "TaxonKey is Congosorex Heim de Balsac & Lamotte, 1956",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 71 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018308-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ku45nv
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Berberis tianshuiensis T.S.Ying"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056402-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6xjuje
title: Occurrence Download

description: A dataset containing 80 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Berberis tinctoria Lesch."
 ]
}

 The dataset includes 80 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056406-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rrhkgc
title: Occurrence Download

description: A dataset containing 14070161 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Colombia"
 ]
}

 The dataset includes 14070161 records from 3084 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004046-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14272/louprkontzgtke-lhfmaamqsa-n/chmo0001149
title: 1H--15N heteronuclear multiple bond coherence (15N-1H HMBC) ((S)-[(2R,4S,5R)-5-ethenyl-1-azabicyclo[2.2.2]octan-2-yl]-(6-methoxyquinolin-4-yl)methanol)
title: InChI=1S/C20H24N2O2/c1-3-13-12-22-9-7-14(13)10-19(22)20(23)16-6-8-21-18-5-4-15(24-2)11-17(16)18/h3-6,8,11,13-14,19-20,23H,1,7,9-10,12H2,2H3/t13-,14-,19+,20-/m0/s1

description: dataset for 1H--15N heteronuclear multiple bond coherence (15N-1H HMBC)
DOI: 10.5281/zenodo.5118461
title: CLDF dataset derived from de Carvalho's "Comparative reconstruction of Proto-Purus" from 2021

description: Cite the source of the dataset as: de Carvalho, F. O. (2021): A comparative reconstruction of Proto-Purus (Arawakan) segmental phonology. IJAL. 87.1. 49-108
DOI: 10.5281/zenodo.13149291
title: CLDF dataset derived from de Carvalho's "Comparative reconstruction of Proto-Purus" from 2021

description: Cite the source of the dataset as:




de Carvalho, F. O. (2021): A comparative reconstruction of Proto-Purus (Arawakan) segmental phonology. IJAL. 87.1. 49-108
DOI: 10.5281/zenodo.5118460
title: CLDF dataset derived from de Carvalho's "Comparative reconstruction of Proto-Purus" from 2021

description: Cite the source of the dataset as:




de Carvalho, F. O. (2021): A comparative reconstruction of Proto-Purus (Arawakan) segmental phonology. IJAL. 87.1. 49-108
DOI: 10.5281/zenodo.5121195
title: CLDF dataset derived from de Carvalho's "Comparative reconstruction of Proto-Purus" from 2021

description: Cite the source of the dataset as: de Carvalho, F. O. (2021): A comparative reconstruction of Proto-Purus (Arawakan) segmental phonology. IJAL. 87.1. 49-108
DOI: 10.15468/dl.kp5ef9
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.29_1",
 "TaxonKey is Sophora moorcroftiana (Benth.) Benth. ex Baker"
 ]
}

 The dataset includes 68 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044054-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26424307
title: Misperception of the desirability of sexual dimorphism

description: Thin and muscular have been characterised as body shape ideals for women and men, respectively, yet each sex misperceives what the other sex desires; women exaggerate the thinness that men like and men exaggerate the muscularity that women like. Body shape ideals align with stereotypic perceptions of femininity in women and masculinity in men. The present study investigates whether misperception of opposite-sex desires extends to femininity/masculinity in facial morphology. We used interactive 3D head models to represent faces varying in sexual dimorphism. White European heterosexual men and women were asked to choose their own and ideal face shape, the ideal shape of a short- and a long-term partner, and the face shape they thought the opposite sex would most like for a short- and a long-term partner. Women overestimated the facial femininity that men prefer in a partner and men overestimated the facial masculinity that women prefer in a partner. The discrepancy between own and ideal sexual dimorphism (an index of appearance dissatisfaction) was predicted by the misperception of what the opposite sex desires. These results indicate misperception of opposite-sex facial preferences and that mistaken perceptions may contribute to dissatisfaction with own appearance
DOI: 10.15468/dl.65jamb
title: Occurrence Download

description: A dataset containing 20987 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Switzerland",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pieris brassicae (Linnaeus, 1758)"
 ]
}

 The dataset includes 20987 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044055-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5519/qd.6hu6pm6f
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (3184 records)
DOI: 10.5281/zenodo.5118477
title: CLDF dataset derived from Castro's "Sui Dialect Research" from 2015

description: Cite the source of the dataset as: Castro, Andy and Pan, Xingwen (2015): Sui dialect research. SIL: Guiyang.
DOI: 10.5281/zenodo.13149296
title: CLDF dataset derived from Castro's "Sui Dialect Research" from 2015

description: Cite the source of the dataset as:




Castro, Andy and Pan, Xingwen (2015): Sui dialect research. SIL: Guiyang.
DOI: 10.5281/zenodo.2634730
title: CLDF dataset derived from Castro's "Sui Dialect Research" from 2015

description: Cite the source of the dataset as:




Castro, Andy and Pan, Xingwen (2015): Sui dialect research. SIL: Guiyang.
DOI: 10.5281/zenodo.2634731
title: lexibank/castrosui: Sui dialect research

description: Cite the source dataset as


Castro, Andy and Pan, Xingwen (2015): Sui dialect research. SIL: Guiyang.
DOI: 10.5281/zenodo.3268340
title: lexibank/castrosui: Sui dialect research

description: Cite the source dataset as


Castro, Andy and Pan, Xingwen (2015): Sui dialect research. SIL: Guiyang.
DOI: 10.5281/zenodo.5121213
title: CLDF dataset derived from Castro's "Sui Dialect Research" from 2015

description: Cite the source of the dataset as: Castro, Andy and Pan, Xingwen (2015): Sui dialect research. SIL: Guiyang.
DOI: 10.5519/qd.caqez0ii
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (449 records)
DOI: 10.5281/zenodo.13149289
title: Binary black-hole simulation SXS:BBH:2056

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13149290
title: Binary black-hole simulation SXS:BBH:2056

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5283/epub.45830
title: Data archive of 'Subcycle contact-free nanoscopy of ultrafast interlayer transport in atomically thin heterostructures'
DOI: 10.5283/epub.43815
title: Data archive of "Nanoscale Near-Field Tomography of Surface States on (Bi0.5Sb0.5)2Te3"

description: Three-dimensional topological insulators (TIs) have attracted tremendous interest for their possibility to host massless Dirac Fermions in topologically protected surface states (TSSs), which may enable new kinds of high-speed electronics. However, recent reports have outlined the importance of band bending effects within these materials, which results in an additional two-dimensional electron gas (2DEG) with finite mass at the surface. TI surfaces are also known to be highly inhomogeneous on the nanoscale, which is masked in conventional far-field studies. Here, we use near-field microscopy in the mid infrared spectral range to probe the local surface properties of customtailored (Bi0.5Sb0.5)(2)Te-3 structures with nanometer precision in all three spatial dimensions. Applying nanotomography and nanospectroscopy, we reveal a few-nanometer-thick layer of high surface conductivity and retrieve its local dielectric function without assuming any model for the spectral response. This allows us to directly distinguish between different types of surface states. An intersubband transition within the massive 2DEG formed by quantum confinement in the bent conduction band manifests itself as a sharp, surface-bound, Lorentzian-shaped resonance. An additional broadband background in the imaginary part of the dielectric function may be caused by the TSS. Tracing the intersubband resonance with nanometer spatial precision, we observe changes of its frequency, likely originating from local variations of doping or/and the mixing ratio between Bi and Sb. Our results highlight the importance of studying the surfaces of these novel materials on the nanoscale to directly access the local optical and electronic properties via the dielectric function.
DOI: 10.5281/zenodo.13149301
title: Binary black-hole simulation SXS:BBH:2037

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13149302
title: Binary black-hole simulation SXS:BBH:2037

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.25835/b1do7tfm
title: Analysis of MAS Architectures for Distributed CSPs
DOI: 10.5281/zenodo.5118536
title: CLDF dataset derived from Castro et al.'s "Yi Varieties in Heqing" from 2010

description: Cite the source of the dataset as: Castro, Andy; Crook, Brian; Flaming, Royce (2010): A sociolinguistic survey of Kua-nsi and related Yi varieties in Heqing county, Yunnan province, China. SIL Electronic Survey Reports 2010-001. Dallas: SIL International.
DOI: 10.5281/zenodo.13149313
title: CLDF dataset derived from Castro et al.'s "Yi Varieties in Heqing" from 2010

description: Cite the source of the dataset as:




Castro, Andy; Crook, Brian; Flaming, Royce (2010): A sociolinguistic survey of Kua-nsi and related Yi varieties in Heqing county, Yunnan province, China. SIL Electronic Survey Reports 2010-001. Dallas: SIL International.
DOI: 10.5281/zenodo.5118535
title: CLDF dataset derived from Castro et al.'s "Yi Varieties in Heqing" from 2010

description: Cite the source of the dataset as:




Castro, Andy; Crook, Brian; Flaming, Royce (2010): A sociolinguistic survey of Kua-nsi and related Yi varieties in Heqing county, Yunnan province, China. SIL Electronic Survey Reports 2010-001. Dallas: SIL International.
DOI: 10.5281/zenodo.5121214
title: CLDF dataset derived from Castro et al.'s "Yi Varieties in Heqing" from 2010

description: Cite the source of the dataset as: Castro, Andy; Crook, Brian; Flaming, Royce (2010): A sociolinguistic survey of Kua-nsi and related Yi varieties in Heqing county, Yunnan province, China. SIL Electronic Survey Reports 2010-001. Dallas: SIL International.
DOI: 10.15468/dl.n58qhs
title: Occurrence Download

description: A dataset containing 392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((13.70714 46.49939,13.70714 44.90629,18.45136 42.62257,21.38084 42.20148,22.703 43.39978,22.54745 44.70396,20.31793 46.21312,17.41437 45.99742,16.14406 46.80192,13.70714 46.49939))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ursus arctos Linnaeus, 1758"
 ]
}

 The dataset includes 392 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044056-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5285/1d4a3bf0-feab-465c-e063-7086abc0ef74
title: Ocean Bottom Seismograph data deployed along the Congo Submarine Canyon and Channel (Atlantic Ocean) on cruise JC187, September 2019-September 2020.

description: Passive seismic measurements of turbidity currents by Ocean-Bottom seismographs (OBS) in the Congo Canyon-Channel, offshore West Africa. Instruments were deployed in September 2019 (cruise JC187) and recovered in September 2020 (cruise JC209). The OBS's stopped recording between May 16th and June 28th, 2020 when the instrument batteries ran out. Five OBS's were deployed in the Upper Congo Canyon in Angolan waters (all of which were recovered), and seven OBS moorings were deployed in the deep-water channel in international waters (of which five were recovered). The OBS's were deployed 700-2900 metres away from the centre of the canyon-channel, on flat canyon terraces or on overbank areas outside the channel. The location of each OBS is based on the ship’s position when the instrument was deployed, and OBS drift while sinking is expected to be small. The nine OBS's deployed by OBIC (Ocean Bottom Instrument Consortium) consisted of three-channel Sercel L28-LB geophones and a Hi-Tech HTI-90U hydrophone. All geophone output was sampled at a frequency of 1 kHz, apart from OBS4 (250 Hz). The data are stored as raw counts from the analogue-to-digital converter (ADC) in netCDF formatted raw (continuous) data. The OBS were supplied and deployed by OBIC (Ocean Bottom Instrument Consortium). These data were generated under the NERC grant NE/R001952/1.
DOI: 10.5281/zenodo.13149318
title: CLDF dataset derived from Castro and Hansen's "Zhuang Dialects in Hongshui He" from 2010

description: Cite the source of the dataset as:




Castro, Andy; Hansen, Bruce (2010): Hongshui He Zhuang dialect intelligibility survey. Dallas: SIL International.
DOI: 10.5281/zenodo.5118683
title: CLDF dataset derived from Castro and Hansen's "Zhuang Dialects in Hongshui He" from 2010

description: Cite the source of the dataset as:




Castro, Andy; Hansen, Bruce (2010): Hongshui He Zhuang dialect intelligibility survey. Dallas: SIL International.
DOI: 10.5281/zenodo.5118684
title: CLDF dataset derived from Castro and Hansen's "Zhuang Dialects in Hongshui He" from 2010

description: Cite the source of the dataset as: Castro, Andy; Hansen, Bruce (2010): Hongshui He Zhuang dialect intelligibility survey. Dallas: SIL International.
DOI: 10.5281/zenodo.5121215
title: CLDF dataset derived from Castro and Hansen's "Zhuang Dialects in Hongshui He" from 2010

description: Cite the source of the dataset as: Castro, Andy; Hansen, Bruce (2010): Hongshui He Zhuang dialect intelligibility survey. Dallas: SIL International.
DOI: 10.5281/zenodo.11615205
title: Power Quality State Estimation for Distribution Grids based on Physics-Aware Neural Networks - Harmonic State Estimation

description: Data set for the paper "Power Quality State Estimation for Distribution Grids based on Physics-Aware Neural Networks - Harmonic State Estimation"

This upload contains



Training set

Validation set

Test set

Admittance matrices per frequency


used for the paper as pickle files and weights of trained models as zip files.

Weights represent the model with the best validation loss recorded within the first 3000 Epochs of training.

Code for reading in the data sets, preprocessing and state estimation is available in the linked repository.

To replicate the results of the paper follow these steps:



clone the linked repository

save the provided pickle files in the data folder of the linked repository

optional: unzip weights and save them in the data folder, otherwise train a model yourself instead


Version 1.1:

Added data and model weights for the IEEE33 grid to improve comparability.

For the IEEE33 grid, all data (train, test, validation) is saved in one pickle file; see the release tag 1.1.0 in the accompanying GitHub repository for details on the data format. Moreover, the training set size of the new grid was increased from 35040 to 131400 samples to incorporate simulation results that capture a broader range of system states. 

The code was slightly updated to account for inclusion of the IEEE33 grid. Therefore, model weights and input data are now expected in either `cigrelv` or `ieee33` subfolder.

Added Transformer and CNN model weights for IEEE33 and CNN weights for the CIGRE grid. The Transformer model is trained with a smaller batch size since the model did not fit into GPU memory using the same batch size as in other models. This change results in more gradient updates and significantly longer training times, thus the amount of epochs was reduced to achieve a fairer comparison (batch sized reduced from 16384 to 1024, epochs reduced from 3000 to 375, total amount of gradient updates increased from 27000 to 48375). The training of the PANN model over 3000 Epochs is significantly faster than that of the Transformer model trained over 375 epochs (approximately 2.5 hours vs 12.5 hours).
DOI: 10.5281/zenodo.11615206
title: Power Quality State Estimation for Distribution Grids based on Physics-Aware Neural Networks - Harmonic State Estimation

description: Data set for the paper "Power Quality State Estimation for Distribution Grids based on Physics-Aware Neural Networks - Harmonic State Estimation"

This upload contains



Training set

Validation set

Test set

Admittance matrices per frequency


used for the paper as pickle files and weights of trained models as zip files.

Weights represent the model with the best validation loss recorded within the first 3000 Epochs of training.

Code for reading in the data sets, preprocessing and state estimation is available in the linked repository.

To replicate the results of the paper follow these steps:



clone the linked repository

save the provided pickle files in the data folder under 'CigreLVDist' of the linked repository

optional: unzip weights and save them in the data folder, otherwise train a model yourself instead
DOI: 10.5281/zenodo.13122171
title: Power Quality State Estimation for Distribution Grids based on Physics-Aware Neural Networks - Harmonic State Estimation

description: Data set for the paper "Power Quality State Estimation for Distribution Grids based on Physics-Aware Neural Networks - Harmonic State Estimation"

This upload contains



Training set

Validation set

Test set

Admittance matrices per frequency


used for the paper as pickle files and weights of trained models as zip files.

Weights represent the model with the best validation loss recorded within the first 3000 Epochs of training.

Code for reading in the data sets, preprocessing and state estimation is available in the linked repository.

To replicate the results of the paper follow these steps:



clone the linked repository

save the provided pickle files in the data folder of the linked repository

optional: unzip weights and save them in the data folder, otherwise train a model yourself instead


Version 1.1:

Added data and model weights for the IEEE33 grid to improve comparability.

For the IEEE33 grid, all data (train, test, validation) is saved in one pickle file; see the release tag 1.1.0 in the accompanying GitHub repository for details on the data format. Moreover, the training set size of the new grid was increased from 35040 to 131400 samples to incorporate simulation results that capture a broader range of system states. 

The code was slightly updated to account for inclusion of the IEEE33 grid. Therefore, model weights and input data are now expected in either `cigrelv` or `ieee33` subfolder.

Added Transformer and CNN model weights for IEEE33 and CNN weights for the CIGRE grid. The Transformer model is trained with a smaller batch size since the model did not fit into GPU memory using the same batch size as in other models. This change results in more gradient updates and significantly longer training times, thus the amount of epochs was reduced to achieve a fairer comparison (batch sized reduced from 16384 to 1024, epochs reduced from 3000 to 375, total amount of gradient updates increased from 27000 to 48375). The training of the PANN model over 3000 Epochs is significantly faster than that of the Transformer model trained over 375 epochs (approximately 2.5 hours vs 12.5 hours).
DOI: 10.5281/zenodo.13149305
title: Binary black-hole simulation SXS:BBH:1986

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13149306
title: Binary black-hole simulation SXS:BBH:1986

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.15468/dl.85vc28
title: Occurrence Download

description: A dataset containing 118 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.29_1",
 "TaxonKey is Pennisetum flaccidum Griseb."
 ]
}

 The dataset includes 118 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044057-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.