cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.27687447
title: Data set

description: This study investigated the effects of real and virtual environments on volleyball serve performance under different anxiety conditions among nine female athletes from Turkey's 2nd League Women’s Volleyball teams. The research aimed to test assumptions of the ironic process theory, exploring how high-pressure situations might paradoxically increase performance errors despite focused mental control efforts.<b>Methodology and Techniques</b>: Participants, averaging 7.55 years of licensed playing experience, performed serves in both real and virtual reality (VR) setups, each under low and high anxiety conditions. Anxiety was manipulated in both settings: in the real environment, participants faced time constraints, while in the VR environment, rewards were offered alongside time pressure. Serve performance was evaluated for ironic errors, which occur when individuals fail in tasks specifically due to their attempts to avoid failure. The study used heart rate (HR) monitors and heart rate variability (r-MSSD) measurements to capture physiological responses under anxiety, alongside self-assessments of cognitive and somatic anxiety and self-confidence, evaluated through the Mental Readiness Form-3 (MRF-3). These measures provided both objective and subjective data on athletes' psychophysiological and mental states across different conditions.<b>Data Collection and Ethics</b>: All participants volunteered for the study, and data collection adhered to ethical guidelines, with informed consent obtained prior to participation. Confidentiality was maintained by anonymizing data for analysis, ensuring privacy compliance. The research was approved by an ethics committee, confirming adherence to legal and ethical standards for data collection.This detailed approach and methodological transparency provide a reproducible framework for similar studies. The structured data allows other researchers to replicate or build upon these findings, enhancing understanding of anxiety's role in sports performance and the potential benefits of VR training interventions.
DOI: 10.6084/m9.figshare.27687447.v1
title: Data set

description: This study investigated the effects of real and virtual environments on volleyball serve performance under different anxiety conditions among nine female athletes from Turkey's 2nd League Women’s Volleyball teams. The research aimed to test assumptions of the ironic process theory, exploring how high-pressure situations might paradoxically increase performance errors despite focused mental control efforts.<b>Methodology and Techniques</b>: Participants, averaging 7.55 years of licensed playing experience, performed serves in both real and virtual reality (VR) setups, each under low and high anxiety conditions. Anxiety was manipulated in both settings: in the real environment, participants faced time constraints, while in the VR environment, rewards were offered alongside time pressure. Serve performance was evaluated for ironic errors, which occur when individuals fail in tasks specifically due to their attempts to avoid failure. The study used heart rate (HR) monitors and heart rate variability (r-MSSD) measurements to capture physiological responses under anxiety, alongside self-assessments of cognitive and somatic anxiety and self-confidence, evaluated through the Mental Readiness Form-3 (MRF-3). These measures provided both objective and subjective data on athletes' psychophysiological and mental states across different conditions.<b>Data Collection and Ethics</b>: All participants volunteered for the study, and data collection adhered to ethical guidelines, with informed consent obtained prior to participation. Confidentiality was maintained by anonymizing data for analysis, ensuring privacy compliance. The research was approved by an ethics committee, confirming adherence to legal and ethical standards for data collection.This detailed approach and methodological transparency provide a reproducible framework for similar studies. The structured data allows other researchers to replicate or build upon these findings, enhancing understanding of anxiety's role in sports performance and the potential benefits of VR training interventions.
DOI: 10.15468/dl.ywefeb
title: Occurrence Download

description: A dataset containing 1357 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bomarea salsilla (L.) Mirb., Bomarea ovallei (Phil.) Ravenna, Alstroemeria werdermannii Ehr.Bayer, Alstroemeria graminea Phil., Alstroemeria rupestris M.C.Assis, Alstroemeria, Alstroemeria psittacina Lehm., Alstroemeria isabellana Herb., Alstroemeria hookeri subsp. cummingiana (Herb.) Ehr.Bayer)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1357 records from 91 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012015-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14133880
title: Kindlin-3-q595p-mutation-data
DOI: 10.5281/zenodo.14133881
title: Kindlin-3-q595p-mutation-data
DOI: 10.15468/dl.jkfvp8
title: Occurrence Download

description: A dataset containing 53895 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Myctobase, a circumpolar database of mesopelagic fishes for new insights into deep pelagic prey fields - data"
 ]
}

 The dataset includes 53895 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012014-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10892039
title: Chemical analysis dataset for contaminants of emerging concern and bioanalytical data for samples from a low mountain stream in Central Germany

description: In 2022, river-water samples were collected at six sampling sites along the Holtemme River in Central Germany using large-volume solid phase extraction. The extracts were analysed by target chemical analysis for contaminants of emerging concern. In addition, the extracts were analysed in a bioanalytical test battery using effect-based tools. The battery included assays for cytotoxicity (neutral red retention assay), oxidative stress (Nrf2-CALUX®), endocrine disruption (ER-, AR-, anti-ER-, anti-AR-, GR- and PR-CALUX®) and the fish embryotoxicity test with zebrafish (Danio rerio). The data obtained are included in the .csv files in this repository.
DOI: 10.5281/zenodo.10930780
title: Chemical analysis dataset for contaminants of emerging concern and bioanalytical data for samples from a low mountain stream in Central Germany

description: In 2022, river-water samples were collected at six sampling sites along the Holtemme River in Central Germany using large-volume solid phase extraction. The extracts were analysed by target chemical analysis for contaminants of emerging concern. In addition, the extracts were analysed in a bioanalytical test battery using effect-based tools. The battery included assays for cytotoxicity (neutral red retention assay), oxidative stress (Nrf2-CALUX®), endocrine disruption (ER-, AR-, anti-ER-, anti-AR-, GR- and PR-CALUX®) and the fish embryotoxicity test with zebrafish (Danio rerio). The data obtained are included in the .csv files in this repository.
DOI: 10.5281/zenodo.11114083
title: Chemical analysis dataset for contaminants of emerging concern and bioanalytical data for samples from a low mountain stream in Central Germany

description: In 2022, river-water samples were collected at six sampling sites along the Holtemme River in Central Germany using large-volume solid phase extraction. The extracts were analysed by target chemical analysis for contaminants of emerging concern. In addition, the extracts were analysed in a bioanalytical test battery using effect-based tools. The battery included assays for cytotoxicity (neutral red retention assay), oxidative stress (Nrf2-CALUX®), endocrine disruption (ER-, AR-, anti-ER-, anti-AR-, GR- and PR-CALUX®) and the fish embryotoxicity test with zebrafish (Danio rerio). The data obtained are included in the .csv files in this repository.
DOI: 10.5281/zenodo.10892038
title: Chemical analysis dataset for contaminants of emerging concern and bioanalytical data for samples from a low mountain stream in Central Germany

description: In 2022, river-water samples were collected at six sampling sites along the Holtemme River in Central Germany using large-volume solid phase extraction. The extracts were analysed by target chemical analysis for contaminants of emerging concern. In addition, the extracts were analysed in a bioanalytical test battery using effect-based tools. The battery included assays for cytotoxicity (neutral red retention assay), oxidative stress (Nrf2-CALUX®), endocrine disruption (ER-, AR-, anti-ER-, anti-AR-, GR- and PR-CALUX®) and the fish embryotoxicity test with zebrafish (Danio rerio). The data obtained are included in the .csv files in this repository.
DOI: 10.5281/zenodo.14133949
title: Chemical analysis dataset for contaminants of emerging concern and bioanalytical data for samples from a low mountain stream in Central Germany

description: In 2022, river-water samples were collected at six sampling sites along the Holtemme River in Central Germany using large-volume solid phase extraction. The extracts were analysed by target chemical analysis for contaminants of emerging concern. In addition, the extracts were analysed in a bioanalytical test battery using effect-based tools. The battery included assays for cytotoxicity (neutral red retention assay), oxidative stress (Nrf2-CALUX®), endocrine disruption (ER-, AR-, anti-ER-, anti-AR-, GR- and PR-CALUX®) and the fish embryotoxicity test with zebrafish (Danio rerio). The data obtained are included in the .csv files in this repository.
DOI: 10.57754/fdat.333b8-n1m86
title: On the acceptability of imperfective or perfective verbs in combination with iterative quantifiers (Iter Decision)

description: One of the most frequently discussed occurrences of aspectual competition within the Slavic languages is the competition between perfective and imperfective aspects in iterative contexts. This experiment was used to investigate the acceptability of imperfective or perfective verbs in combination with iterative quantifiers dwa razy, kilka razy and często with respect to their verb preceding or verb postpositive position.
description: Research carried out in work package C02 of the SFB 833.
DOI: 10.15468/dl.xetqvs
title: Occurrence Download

description: A dataset containing 34244 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Gadus morhua Linnaeus, 1758"
 ]
}

 The dataset includes 34244 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012016-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2bgbzd
title: Occurrence Download

description: A dataset containing 162 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ethiopia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Swertia lugardae Bullock"
 ]
}

 The dataset includes 162 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012017-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14134007
title: dem files for Antarctic maps and data analysis

description: We use BedMachine Antarctica v2, 1km resolution [https://nsidc.org/data/nsidc-0756/versions/2](https://nsidc.org/data/nsidc-0756/versions/2) (to be updated one day to v3, see below) to:  * estimate the surface elevation of observation when not available: [BedMachineAntarctica_v02.nc](./data/dem/BedMachineAntarctica_v02.nc)  * generate lower resolution maps of Antarctica for plots: e.g. at 10km, [ANT10km_BedMachineAntarctica_v02.nc](./data/dem/ANT10km_BedMachineAntarctica_v02.nc)You can load this data in the [./data/dem](./data/dem) from the> [!IMPORTANT]> Do not forget to cite the following articles when using this script>> #### Data Citation and Acknowledgment> As a condition of using these data, you must cite the use of this data set. Such a practice gives credit to data set producers and advances principles of transparency and reproducibility.>> * Morlighem, M. (2020). MEaSUREs BedMachine Antarctica. (NSIDC-0756, Version 2). [Data Set]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/E1QL9HFQ7A8M. [describe subset used if applicable]. Date Accessed 11-13-2024.>> When using this data product in a publication, please include the following citations in addition to the data product citation provided above:>> * Morlighem, M., Rignot, E., Binder, T., Blankenship, D. D., Drews, R., Eagles, G., Eisen, O., Ferraccioli, F., Forsberg, R., Fretwell, P., Goel, V., Greenbaum, J. S., Gudmundsson, H., Guo, J., Helm, V., Hofstede, C., Howat, I., Humbert, A., Jokat, W., Karlsson, N. B., Lee, W., Matsuoka, K., Millan, R., Mouginot, J., Paden, J., Pattyn, F., Roberts, J. L., Rosier, S., Ruppel, A., Seroussi, H., Smith, E. C., Steinhage, D., Sun, B., van den Broeke, M. R., van Ommen, T., van Wessem, M. & Young, D. A.. 2020. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet. Nature Geoscience. 13. DOI: 10.1038/s41561-019-0510-8.>> To promote open science principles and reproducibility, we encourage you to make your data citation specific to the subset used in your research. Common examples of information include spatial and temporal range and file types if relevant.You can load your favorite dem for Antarctica in [./data/dem](./data/dem):* The dem should be in the Spatial Reference System "Antarctic Polar Stereographic EPSG:3031"* E.g. the last version of BedMachine Antarctica: https://nsidc.org/data/nsidc-0756/
DOI: 10.5281/zenodo.14134008
title: dem files for Antarctic maps and data analysis

description: We use BedMachine Antarctica v2, 1km resolution [https://nsidc.org/data/nsidc-0756/versions/2](https://nsidc.org/data/nsidc-0756/versions/2) (to be updated one day to v3, see below) to:  * estimate the surface elevation of observation when not available: [BedMachineAntarctica_v02.nc](./data/dem/BedMachineAntarctica_v02.nc)  * generate lower resolution maps of Antarctica for plots: e.g. at 10km, [ANT10km_BedMachineAntarctica_v02.nc](./data/dem/ANT10km_BedMachineAntarctica_v02.nc)You can load this data in the [./data/dem](./data/dem) from the> [!IMPORTANT]> Do not forget to cite the following articles when using this script>> #### Data Citation and Acknowledgment> As a condition of using these data, you must cite the use of this data set. Such a practice gives credit to data set producers and advances principles of transparency and reproducibility.>> * Morlighem, M. (2020). MEaSUREs BedMachine Antarctica. (NSIDC-0756, Version 2). [Data Set]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/E1QL9HFQ7A8M. [describe subset used if applicable]. Date Accessed 11-13-2024.>> When using this data product in a publication, please include the following citations in addition to the data product citation provided above:>> * Morlighem, M., Rignot, E., Binder, T., Blankenship, D. D., Drews, R., Eagles, G., Eisen, O., Ferraccioli, F., Forsberg, R., Fretwell, P., Goel, V., Greenbaum, J. S., Gudmundsson, H., Guo, J., Helm, V., Hofstede, C., Howat, I., Humbert, A., Jokat, W., Karlsson, N. B., Lee, W., Matsuoka, K., Millan, R., Mouginot, J., Paden, J., Pattyn, F., Roberts, J. L., Rosier, S., Ruppel, A., Seroussi, H., Smith, E. C., Steinhage, D., Sun, B., van den Broeke, M. R., van Ommen, T., van Wessem, M. & Young, D. A.. 2020. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet. Nature Geoscience. 13. DOI: 10.1038/s41561-019-0510-8.>> To promote open science principles and reproducibility, we encourage you to make your data citation specific to the subset used in your research. Common examples of information include spatial and temporal range and file types if relevant.You can load your favorite dem for Antarctica in [./data/dem](./data/dem):* The dem should be in the Spatial Reference System "Antarctic Polar Stereographic EPSG:3031"* E.g. the last version of BedMachine Antarctica: https://nsidc.org/data/nsidc-0756/
DOI: 10.57754/fdat.xk59n-4ey34
title: On the acceptability of imperfective or perfective verbs in combination with iterative quantifiers (Iter judgement)

description: One of the most frequently discussed occurrences of aspectual competition within the Slavic languages is the competition between perfective and imperfective aspects in iterative contexts. This experiment was used to investigate the acceptability of imperfective or perfective verbs in combination with iterative quantifiers dwa razy, kilka razy and często with respect to their verb preceding or verb postpositive position.
description: Research carried out in work package C02 of the SFB 833.
DOI: 10.5281/zenodo.13222171
title: Processed data from SnoHATS and METCRAX II:  anisotropic turbulence and geometry of the Reynolds stress tensor in a streamline coordinate system

description: Datasets used for the paper 'Interpreting turbulence anisotropy in a streamline coordinate system'. Data from SnoHATS and METCRAX II field campaigns. Datasets include turbulent quantities calculated on 30- and 1-min averaging windows for unstable and stable conditions, with prior linear detrending. Planar fit was used in METCRAX II and double rotation in SnoHATS to rotate the flow into the mean wind direction. Datasets include quantities to characterize the anisotropy of the Reynolds stress tensor, such as eigenvalues, eigenvectors, and the angles between the eigenvectors and the streamline coordinate system, defined in the direction of the mean wind vector.

1c: one-component Reynolds stress tensor

2c: two-component axisymmetric Reynolds stress tensor

3c: isotropic Reynolds stress tensor
DOI: 10.5281/zenodo.13222170
title: Processed data from SnoHATS and METCRAX II:  anisotropic turbulence and geometry of the Reynolds stress tensor in a streamline coordinate system

description: Datasets used for the paper 'Interpreting turbulence anisotropy in a streamline coordinate system'. Data from SnoHATS and METCRAX II field campaigns. Datasets include turbulent quantities calculated on 30- and 1-min averaging windows for unstable and stable conditions, with prior linear detrending. Planar fit was used in METCRAX II and double rotation in SnoHATS to rotate the flow into the mean wind direction. Datasets include quantities to characterize the anisotropy of the Reynolds stress tensor, such as eigenvalues, eigenvectors, and the angles between the eigenvectors and the streamline coordinate system, defined in the direction of the mean wind vector.

1c: one-component Reynolds stress tensor

2c: two-component axisymmetric Reynolds stress tensor

3c: isotropic Reynolds stress tensor
DOI: 10.15468/dl.6nhvvb
title: Occurrence Download

description: A dataset containing 1991 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Quillaja saponaria Molina"
 ]
}

 The dataset includes 1991 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012020-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.87pdub
title: Occurrence Download

description: A dataset listing the 13997 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Tanzania, United Republic of",
 "Geometry POLYGON((34.47878 -7.15557,34.25312 -7.39378,33.80805 -8.05824,33.73283 -8.7039,33.77044 -9.17404,34.06506 -9.46239,34.59162 -9.62537,34.96773 -9.6003,35.54443 -9.41224,36.29038 -9.1427,36.79187 -9.09255,37.33096 -8.20242,37.53782 -7.52542,37.43126 -6.96125,36.87336 -6.78573,36.10233 -6.81081,35.40025 -6.84215,34.78594 -6.94871,34.47878 -7.15557))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset's 13997 records were derived from 308 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008201-250402121839773/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.30030205
title: My Test Dataset

description: Uploaded via Python API
DOI: 10.6084/m9.figshare.30030205.v4
title: My Test Dataset

description: Uploaded via Python API
DOI: 10.6084/m9.figshare.30030205.v3
title: My Test Dataset

description: Uploaded via Python API
DOI: 10.15468/dl.97fkcf
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Clibadium surinamense",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 42 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022410-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w6g2yf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Clibadium surinamense",
 "Country is Madagascar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022411-250920141307145/datasets/export for details.
DOI: 10.15468/dl.h4knqe
title: Occurrence Download

description: A dataset containing 297 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Crossostephium chinense",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 297 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022409-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wuhegx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Jacobaea vulgaris",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022414-250920141307145/datasets/export for details.
DOI: 10.15468/dl.z5kbre
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dendranthema indicum",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022415-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17212286
title: Predicting algal bloom dynamics from turbidity front movements along tide–dominated coasts