cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17032/shu-0000000274
title: Technical performance variations in elite Olympic recurve archers

description: This study analysed the shot cycle of elite Olympic recurve archers in major tournaments to understand how they exploit movement variability to achieve the same performance outcomes. Participants were 30 top World-ranked archers (15 men and 15 women) who competed in different World Cup series in 2023. A video notational analysis system was designed, based on the shot cycle (stance, bow raise, loading, full draw, anchor, release and follow-through), to assess technical variability in the elite archers. For each archer, 18 shots were selected from analysis of performance in individual or team competitions. Results showed that the elite archers used different forms in each phase of the shot cycle. Findings also revealed that there were two styles of Olympic recurve archery in the sample of elite performers; some displayed a common style and some a more complex style. The two styles were mainly different in movement complexity when raising the bow, loading and bow arm follow-through. In conclusion, the designed notational analysis system in recurve archery can be used by coaches and performance analysts for the skill adaptation of young archers in their development pathway. The existing technical variability in the elite archers can justify our definition of the ideal/optimal performance in this sport and direct towards skill adaptations based on individual, environmental and task constraints.
DOI: 10.15468/dl.vrs76z
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acapoeta tanganicae (Boulenger, 1900)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((14.0551 -24.7971,14.1824 -24.9401,19.1382 -24.9401,19.1382 -15.9401,11.232 -15.9401,11.1685 -16.5532,11.3443 -18.2026,12.161 -19.3946,13.5014 -21.9972,13.9613 -22.5582,13.9546 -24.0815,14.0551 -24.7971))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057195-250525065834625/datasets/export for details.
DOI: 10.15468/dl.rujett
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cocconeis C.G.Ehrenberg, 1837",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.5808 -24.13,35.5909 -24.0715,30.5701 -24.0715,30.5701 -28.5786,32.4847 -28.5786,32.55 -28.5222,33.0346 -26.8668,32.9741 -26.7838,33.0415 -26.059,32.9304 -26.0011,32.7994 -26.1281,32.6834 -26.0015,32.813 -25.8728,32.8513 -25.7166,33.3048 -25.3731,35.1489 -24.6699,35.5808 -24.13))"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057196-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u5m4uv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acapoeta tanganicae (Boulenger, 1900)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((11.254 -15.728,11.232 -15.9401,19.1382 -15.9401,19.1382 -6.9401,12.1951 -6.9401,12.344 -7.1754,12.8488 -8.4495,12.5495 -8.8082,12.5162 -9.2401,13.3445 -11.0815,13.2057 -11.9763,12.5854 -12.4817,12.0545 -13.266,11.8142 -14.5077,11.254 -15.728))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057197-250525065834625/datasets/export for details.
DOI: 10.15468/dl.vst264
title: Occurrence Download

description: A dataset containing 368641 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Valeriana officinalis L., Pinus contorta Douglas ex Loudon, Picea glauca (Moench) Voss, Salix myrsinifolia Salisb., Salix gmelinii Pall.)",
 "Geometry POLYGON ((-180 45.53015, 180 45.53015, 180 83.62313, -180 83.62313, -180 45.53015))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "CoordinateUncertaintyInMeters is less than or equal to 50000"
 ]
}

 The dataset includes 368641 records from 895 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057180-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gp8pnw
title: Occurrence Download

description: A dataset containing 5623 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Burhinus oedicnemus (Linnaeus, 1758)",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 5623 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057198-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17028/rd.lboro.29366081
title: Supplementary information files for "A comparison of two rotational traction test devices for artificial turf"

description: Supplementary files for article "A comparison of two rotational traction test devices for artificial turf"<br><br>The Rotational Traction Tester and Lightweight Rotational Traction Tester are the two devices specified in sports pitch certification test standards. They are thought to provide comparable results, when used to characterise the rotational resistance properties of artificial turf pitches. While both devices have been used on polymeric-infilled surfaces for many years, a recently introduced restriction on the use of microplastic infills within the European Union has caused a focus on organic-based materials such as Cork, wood, and Olive pits for use as the performance infill in newly built systems. These infills have different properties to traditional polymeric infills, with many comprised of what is considered to be more rigid particles and thus may respond differently to traction testing. In this study, rotational traction testing was conducted on a Styrene-Butadiene Rubber, Cork, Olive pit, Birch, and Pine pitch with the two standard mechanical devices. Testing included the normal operation of both devices and also the Rotational Traction Tester used without a drop. In addition, two stud designs were included to investigate the response to an alternate geometry—standard cylindrical Fédération Internationale de Football Association studs and a narrower tip conical design of the same length. Overall, peak torque values were found to be significantly affected by the testing configuration across all the pitches. The Rotational Traction Tester used without a drop showed poor agreement with the Rotational Traction Tester used with a drop and Lightweight Rotational Traction Tester peak torque values for every pitch tested. Peak torque values were comparable between the Lightweight Rotational Traction Tester and Rotational Traction Tester when using standard Fédération Internationale de Football Association studs across all pitches. The conical studs were found to significantly increase peak torque on pitches with more rigid infill particles i.e. the Birch, Pine and Olive pitches. In contrast, a decrease in peak torque values on the Styrene-Butadiene Rubber pitch was observed for the conical studs, attributed to the slightly smaller cross-sectional area. The results highlight a need for further investigations into the methods/devices used for sport pitch traction characterisation.<br><br>© The Author(s), CC BY 4.0
DOI: 10.17028/rd.lboro.29366081.v1
title: Supplementary information files for "A comparison of two rotational traction test devices for artificial turf"

description: Supplementary files for article "A comparison of two rotational traction test devices for artificial turf"<br><br>The Rotational Traction Tester and Lightweight Rotational Traction Tester are the two devices specified in sports pitch certification test standards. They are thought to provide comparable results, when used to characterise the rotational resistance properties of artificial turf pitches. While both devices have been used on polymeric-infilled surfaces for many years, a recently introduced restriction on the use of microplastic infills within the European Union has caused a focus on organic-based materials such as Cork, wood, and Olive pits for use as the performance infill in newly built systems. These infills have different properties to traditional polymeric infills, with many comprised of what is considered to be more rigid particles and thus may respond differently to traction testing. In this study, rotational traction testing was conducted on a Styrene-Butadiene Rubber, Cork, Olive pit, Birch, and Pine pitch with the two standard mechanical devices. Testing included the normal operation of both devices and also the Rotational Traction Tester used without a drop. In addition, two stud designs were included to investigate the response to an alternate geometry—standard cylindrical Fédération Internationale de Football Association studs and a narrower tip conical design of the same length. Overall, peak torque values were found to be significantly affected by the testing configuration across all the pitches. The Rotational Traction Tester used without a drop showed poor agreement with the Rotational Traction Tester used with a drop and Lightweight Rotational Traction Tester peak torque values for every pitch tested. Peak torque values were comparable between the Lightweight Rotational Traction Tester and Rotational Traction Tester when using standard Fédération Internationale de Football Association studs across all pitches. The conical studs were found to significantly increase peak torque on pitches with more rigid infill particles i.e. the Birch, Pine and Olive pitches. In contrast, a decrease in peak torque values on the Styrene-Butadiene Rubber pitch was observed for the conical studs, attributed to the slightly smaller cross-sectional area. The results highlight a need for further investigations into the methods/devices used for sport pitch traction characterisation.<br><br>© The Author(s), CC BY 4.0
DOI: 10.15468/dl.waexuk
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cocconeis C.G.Ehrenberg, 1837",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((31.8862 -21.3285,30.5701 -20.3186,30.5701 -24.0715,35.5909 -24.0715,35.6007 -24.0157,35.6007 -23.8125,35.4969 -23.7035,35.6007 -23.165,35.6007 -22.9702,35.227 -22.2482,34.6862 -21.6944,34.013 -21.3095,33.5 -21.1593,32.9675 -21.1092,32.4352 -21.1612,31.8862 -21.3285))"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057199-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fy75py
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acapoeta tanganicae (Boulenger, 1900)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((10.1382 20.0599,1.1382 20.0599,1.1382 11.0599,10.1382 11.0599,10.1382 20.0599))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057201-250525065834625/datasets/export for details.
DOI: 10.15468/dl.sx93jr
title: Occurrence Download

description: A dataset containing 88490 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Japan",
 "License is CC-BY 4.0",
 "OccurrenceStatus is Present",
 "TaxonKey is Odonata"
 ]
}

 The dataset includes 88490 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057187-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4sncdy
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "OccurrenceStatus is Present",
 "TaxonKey is Liolaemus pantherinus Pellegrin, 1909"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057204-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q6nsfg
title: Occurrence Download

description: A dataset containing 16378 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Burhinus senegalensis (Swainson, 1837)",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 16378 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057203-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2ngyfj
title: CCDC 2457228: Experimental Crystal Structure Determination

description: Related Article: F. Sueyoshi, K. Sakai|2025|IUCrData|10|x250517|doi:10.1107/S2414314625005176
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.sfq6uq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acapoeta tanganicae (Boulenger, 1900)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((10.1382 29.0599,1.1382 29.0599,1.1382 20.0599,10.1382 20.0599,10.1382 29.0599))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057206-250525065834625/datasets/export for details.
DOI: 10.15468/dl.bach5b
title: Occurrence Download

description: A dataset containing 9596 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Formica sanguinea Latreille, 1798"
 ]
}

 The dataset includes 9596 records from 214 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057205-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b38q5e
title: Occurrence Download

description: A dataset containing 685438 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Daucus carota L."
 ]
}

 The dataset includes 685438 records from 3231 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057190-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18029054
title: LOKAL VA GLOBAL KOMPYUTER TARMOQLARI, AXBOROTLARINI QAYTA ISHLASH TARMOQ TEXNOLOGIYALARI
DOI: 10.5281/zenodo.18029055
title: LOKAL VA GLOBAL KOMPYUTER TARMOQLARI, AXBOROTLARINI QAYTA ISHLASH TARMOQ TEXNOLOGIYALARI
DOI: 10.5281/zenodo.18028841
title: How AI and Social Media Shape Student Achievement Through Smart Learning

description: Abstract— In the JABODETABEK area, this research examines the effect of the use of AI tools and social media on higher education student’s academic performance, with mediating moderation of smart learning. Findings Based on cross-sectional survey data collected from a sample of 431 students and the development of the structural equation model metrics using PLS-SEM, it is found that AI tool use significantly and positively predicts academic performance, with social media use also having a positive direct impact. Smart learning appears to partially mediate the influence of both AI and social media on academic performance. These results imply that AI and social media may serve to improve learning performance directly or indirectly (through smart learning activities), and therefore, the higher education should propose policies and training sessions that encourage using these tools in an organized manner. Longitudinal or intervention follow-ups along with exploration of moderators, such as digital literacy and institutional support, are suggested in this study.

Keywords— Artificial Intelligence, Social Media, Smart Learning, Academic Performance, Higher Education, Digital Learning, Mediation Model, Indonesia
DOI: 10.5281/zenodo.18028840
title: How AI and Social Media Shape Student Achievement Through Smart Learning

description: Abstract— In the JABODETABEK area, this research examines the effect of the use of AI tools and social media on higher education student’s academic performance, with mediating moderation of smart learning. Findings Based on cross-sectional survey data collected from a sample of 431 students and the development of the structural equation model metrics using PLS-SEM, it is found that AI tool use significantly and positively predicts academic performance, with social media use also having a positive direct impact. Smart learning appears to partially mediate the influence of both AI and social media on academic performance. These results imply that AI and social media may serve to improve learning performance directly or indirectly (through smart learning activities), and therefore, the higher education should propose policies and training sessions that encourage using these tools in an organized manner. Longitudinal or intervention follow-ups along with exploration of moderators, such as digital literacy and institutional support, are suggested in this study.

Keywords— Artificial Intelligence, Social Media, Smart Learning, Academic Performance, Higher Education, Digital Learning, Mediation Model, Indonesia
DOI: 10.15468/dl.qb9wwe
title: Occurrence Download

description: A dataset containing 764 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Kalidium foliatum"
 ]
}

 The dataset includes 764 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063615-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25976/h483-jc56
title: New Brunswick Surface Water Monitoring Network

description: The New Brunswick Department of Environment and Local Government’s Surface Water Monitoring Network (SWMN) provides information on the quality of the New Brunswick’s major river systems. The SWMN program was fully established in 2003 and is currently composed of 55 monitoring stations that are sampled several times throughout the year. Station locations were selected to provide proper geographical coverage of the province’s major river systems. The goals of the SWMN program include:
•	to monitor, assess and report on the ambient water quality of major rivers and tributaries in the Province of New Brunswick, 
•	to ensure that high quality data is available to support DELG’s programs for planning and approvals; contribute to cumulative effects assessments; aid in public reporting and meet requirements of our partners.
•	to conduct assessments and reporting on our surface waters and to raise awareness of the state of the environment in New Brunswick.
description: A multimeter is used to collect data on physio-chemical parameters at all sampling locations (n= 55). To assess additional chemical parameters, river water is collected in a 500 ml bottle, a 50ml vial and 250ml bacteria bottle at each river monitoring station. Water samples are placed in a cooler with ice packs and arrive at the laboratory within 24 hours of collection. Water samples are analyzed for nutrients, major ions, and trace metals.
description: New Brunswick Department of Environment and Local Government uses a unique identifier for each surface water sample to ensure that the analytical results that come from the laboratory match up with the sample information that is stored in DELG’s data base.
DOI: 10.6084/m9.figshare.30853586
title: DIPY_synthseg_data

description: This contains data and weights for the synthseg model implemented in DIPY.
DOI: 10.6084/m9.figshare.30853586.v1
title: DIPY_synthseg_data

description: This contains data and weights for the synthseg model implemented in DIPY.
DOI: 10.6084/m9.figshare.30853586.v2
title: DIPY_synthseg_data

description: This contains data and weights for the synthseg model implemented in DIPY.
DOI: 10.15468/dl.mzbv7y
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Japan",
 "DatasetKey is Data on coral species occurrences in Japan since 1929",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Danafungia scruposa"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063616-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18028409
title: Decoding Coral Resistance to Eutrophication: Association of Hyper-Efficient Denitrifiers as Key Microbial Allies

description: This dataset includes the raw data used to plot the Fig. 3 in the manuscript entitled "Decoding Coral Resistance to Eutrophication: Association of Hyper-Efficient Denitrifiers as Key Microbial Allies".