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

description: A dataset containing 108 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is China",
 "Country is Chinese Taipei"
 ]
 },
 "TaxonKey is Elymus brevipes (Keng & S.L.Chen) S.L.Chen"
 ]
}

 The dataset includes 108 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0247053-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.59sjpt
title: Occurrence Download

description: A dataset listing the 8 species recorded in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Vallea stipularis Mutis ex L.fil."
 ]
}

 The dataset's 8 records were derived from 147 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0389910-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r6tqg5
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Barbacenia conicostigma Goethart & Henrard"
 ]
}

 The dataset includes 37 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0084882-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.krr38r
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Asarcenchelys longimanus McCosker, 1985"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064808-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ftfgat
title: Occurrence Download

description: A dataset containing 190 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Todiramphus leucopygius (J.Verreaux, 1858)"
 ]
}

 The dataset includes 190 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0402347-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17805360
title: Real-Time Road Sign Detection with YOLOv8: Custom Dataset Training and Grounding DINO Benchmarking

description: Road traffic crashes still claim around 1.19 million lives each year worldwide and remain the leading cause of death for children and young adults, according to recent World Health Organization estimates. Robust perception of regulatory road signs is therefore a core requirement for advanced driver assistance and autonomous driving systems. This study develops and rigorously evaluates a real-time road sign detection pipeline based on YOLOv8, trained on a custom dataset containing four safety-critical categories: speed limit, stop, crosswalk, and traffic light. Images are collected from heterogeneous online sources, carefully annotated with CVAT, and enriched through a systematic search over mosaic, mixup, geometric, and photometric data augmentation strategies. Key hyperparameters, including learning rate, optimizer, weight decay, and dropout, are tuned through structured experiments. On a held-out validation set of 88 images and 133 annotated instances, the best YOLOv8 configuration attains an overall mAP50 of 0.935 and mAP50-95 of 0.76, with near-perfect performance on speed limit and crosswalk signs and an average inference time of 17.3 ms per image, which satisfies typical real-time constraints. These results are in line with recent reports on YOLO-based traffic sign detectors. To probe the limits of foundation models, we further conduct a qualitative zero-shot study with Grounding DINO, which localizes sign regions reliably but struggles to distinguish visually similar classes. Overall, the findings indicate that carefully tuned task-specific detectors still provide a clear advantage for safety-critical traffic perception, while zero-shot vision and language models remain promising tools for rapid prototyping and open-set exploration.
DOI: 10.5281/zenodo.17805359
title: Real-Time Road Sign Detection with YOLOv8: Custom Dataset Training and Grounding DINO Benchmarking

description: Road traffic crashes still claim around 1.19 million lives each year worldwide and remain the leading cause of death for children and young adults, according to recent World Health Organization estimates. Robust perception of regulatory road signs is therefore a core requirement for advanced driver assistance and autonomous driving systems. This study develops and rigorously evaluates a real-time road sign detection pipeline based on YOLOv8, trained on a custom dataset containing four safety-critical categories: speed limit, stop, crosswalk, and traffic light. Images are collected from heterogeneous online sources, carefully annotated with CVAT, and enriched through a systematic search over mosaic, mixup, geometric, and photometric data augmentation strategies. Key hyperparameters, including learning rate, optimizer, weight decay, and dropout, are tuned through structured experiments. On a held-out validation set of 88 images and 133 annotated instances, the best YOLOv8 configuration attains an overall mAP50 of 0.935 and mAP50-95 of 0.76, with near-perfect performance on speed limit and crosswalk signs and an average inference time of 17.3 ms per image, which satisfies typical real-time constraints. These results are in line with recent reports on YOLO-based traffic sign detectors. To probe the limits of foundation models, we further conduct a qualitative zero-shot study with Grounding DINO, which localizes sign regions reliably but struggles to distinguish visually similar classes. Overall, the findings indicate that carefully tuned task-specific detectors still provide a clear advantage for safety-critical traffic perception, while zero-shot vision and language models remain promising tools for rapid prototyping and open-set exploration.
DOI: 10.17617/3.xa2yff
title: Advanced-circular-statistics

description: Code and manuals accompanying the manuscript "Advanced circular statistics in biology: multiple factors, interactions and repeated measures". (Landler et al. 2025, Methods in Ecology and Evolution)
DOI: 10.6073/pasta/6711ef3c35ae2f6f23835f0fdbeb000f
title: Total dissolved nitrogen (TDN), dissolved organic carbon (DOC), radiocarbon (14C-DOC), and stable carbon (13C-DOC) of surface waters from the Canning River watershed, 2019 and 2021

description: Sites along the Canning River mainstem and contributing streams near the Kavik River Camp, Alaska, were visited to track changes in stream and river total dissolved nitrogen (TDN) concentration, dissolved organic carbon (DOC) concentration, and the stable carbon (13C) and radiocarbon (14C) isotopic composition of DOC across transitions between the Brooks Range, Brooks foothills, and Arctic Coastal Plain. The dataset also includes water samples collected from lakes, springs, groundwater, and streams and rivers outside the Canning River watershed. Water samples were collected in late April and early August 2019 and in late July and early August 2021. Data include measurements of individual samples for TDN (milligrams nitrogen per liter), DOC (milligrams carbon per liter), carbon-13 of DOC (reported as delta-13C, per mil), carbon-14 of DOC (reported as fraction modern), and analytical error in the fraction modern values. Additional water chemistry data for these samples can be found in Koch et al. (2024).
 
 
References:
 
 
Koch, J. C., Connolly, C. T., Repasch, M., Best, H. R., Couvillion, C. S., Hunt, A. (2024). [Dataset] Hydrochemistry and age date tracers from springs, streams, and rivers in the Arctic National Wildlife Refuge, 2019-2022, U.S. Geological Survey data release, https://doi.org/10.5066/P95CXJIT.
DOI: 10.17026/ar/sudbsm
title: PAN-00105000 - coin/coin-related, Valens (364- 378), aes III

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00105000&lt;/p&gt;
description: Modified: 2025-05-12T07:44:14+02:00
DOI: 10.6084/m9.figshare.30777173
title: Enhancing machine learning-based crop mapping with high-quality training samples

description: While machine learning (ML) approaches are able to produce crop maps through the classification of remotely sensed imagery, the acquisition of high-quality training samples for ML remains challenging. In this paper, we propose a sample evaluation scheme to address this issue. Firstly, an unsupervised ML is used to generate objective-based clusters, which serve as the basis for stratifications that reduce spatial redundancy in the sampling. Secondly, samples are randomly collected based on the stratification map, producing multiple sets of samples with varying size and spatial distribution. Lastly, the scheme evaluates the representativeness of individual samples by considering multiple features, as expressed by sample representativeness indicator, and introduces a comprehensive representativeness indicator (CRI) for each aggregated sample set. Based on this scheme, we hypothesize that the CRI can serve as a measure of the quality of a sample set. To test this hypothesis, we conducted a series of crop mapping experiments using support vector machine (SVM, a supervised ML) with different sample sets. Results show that: (1) There is an optimal sample size below which mapping accuracies vary significantly when different sample sets are employed. (2) When the sample size falls below the optimal threshold, choosing a sample set with a higher CRI robustly yields higher mapping accuracy. (3) Mapping accuracies and CRIs exhibit a significant correlation. These findings imply that the proposed sample evaluation scheme not only aids in collecting high-quality training samples for ML-based crop mapping but also showcases the capability to predict the accuracy of crop mapping by examining the inherent features of the collected samples.
DOI: 10.6084/m9.figshare.30777173.v1
title: Enhancing machine learning-based crop mapping with high-quality training samples

description: While machine learning (ML) approaches are able to produce crop maps through the classification of remotely sensed imagery, the acquisition of high-quality training samples for ML remains challenging. In this paper, we propose a sample evaluation scheme to address this issue. Firstly, an unsupervised ML is used to generate objective-based clusters, which serve as the basis for stratifications that reduce spatial redundancy in the sampling. Secondly, samples are randomly collected based on the stratification map, producing multiple sets of samples with varying size and spatial distribution. Lastly, the scheme evaluates the representativeness of individual samples by considering multiple features, as expressed by sample representativeness indicator, and introduces a comprehensive representativeness indicator (CRI) for each aggregated sample set. Based on this scheme, we hypothesize that the CRI can serve as a measure of the quality of a sample set. To test this hypothesis, we conducted a series of crop mapping experiments using support vector machine (SVM, a supervised ML) with different sample sets. Results show that: (1) There is an optimal sample size below which mapping accuracies vary significantly when different sample sets are employed. (2) When the sample size falls below the optimal threshold, choosing a sample set with a higher CRI robustly yields higher mapping accuracy. (3) Mapping accuracies and CRIs exhibit a significant correlation. These findings imply that the proposed sample evaluation scheme not only aids in collecting high-quality training samples for ML-based crop mapping but also showcases the capability to predict the accuracy of crop mapping by examining the inherent features of the collected samples.
DOI: 10.15468/dl.xyn7dt
title: Occurrence Download

description: A dataset containing 3922 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((29.05615 49.34451,33.27634 49.34451,33.27634 51.03187,29.05615 51.03187,29.05615 49.34451))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Amphibia"
 ]
}

 The dataset includes 3922 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025685-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60707/dycw-cw41
title: NANO SCALE THERMAL CONDUCTIVITY CONTRAST MEASUREMENTS OF BENNU SAMPLE OREX-800055-9 USING AN ATOMIC FORCE MICROSCOPE
DOI: 10.60707/zgq5-ev70
title: NANO SCALE THERMAL CONDUCTIVITY CONTRAST MEASUREMENTS OF BENNU SAMPLE OREX-800055-9 USING AN ATOMIC FORCE MICROSCOPE
DOI: 10.60707/c280-h777
title: NANO SCALE THERMAL CONDUCTIVITY CONTRAST MEASUREMENTS OF BENNU SAMPLE OREX-800055-9 USING AN ATOMIC FORCE MICROSCOPE
DOI: 10.60707/5shd-ap83
title: NANO SCALE THERMAL CONDUCTIVITY CONTRAST MEASUREMENTS OF BENNU SAMPLE OREX-800055-9 USING AN ATOMIC FORCE MICROSCOPE
DOI: 10.60707/rp0f-bx56
title: NANO SCALE THERMAL CONDUCTIVITY CONTRAST MEASUREMENTS OF BENNU SAMPLE OREX-800055-9 USING AN ATOMIC FORCE MICROSCOPE
DOI: 10.60707/dn95-zf42
title: NANO SCALE THERMAL CONDUCTIVITY CONTRAST MEASUREMENTS OF BENNU SAMPLE OREX-800055-9 USING AN ATOMIC FORCE MICROSCOPE
DOI: 10.60707/pfb2-1716
title: NANO SCALE THERMAL CONDUCTIVITY CONTRAST MEASUREMENTS OF BENNU SAMPLE OREX-800055-9 USING AN ATOMIC FORCE MICROSCOPE
DOI: 10.5066/p13sytqc
title: qPCR data from eDNA autosampler surveys for salmon migrating through the Lake Washington Ship Canal, June - September 2022

description: The content contains metadata from an eDNA survey that assessed the efficacy of an autonomous eDNA sampler for tracking Chinook, sockeye, and coho salmon migrating through the Lake Washington Ship Canal between June and September 2022.
DOI: 10.24381/ba504f7a
title: Comprehensive Upper-air Observation Network from 1901 to present
DOI: 10.17632/jkp8pkmmyk
title: Implementación de Realidad Aumentada en la Plaza Principal Alfonso Ávila Quintero: Revitalizando el Turismo y la Cultura en Agustín Codazzi, Cesar

description: Objetivo: Evaluar el impacto de la implementación de tecnología de Realidad Aumentada (AR) en la Plaza Principal Alfonso Ávila Quintero, con la hipótesis de que la AR puede revitalizar el turismo y la cultura en Agustín Codazzi, Cesar.
Metodología o método: Para la implementación, se diseñaron experiencias de AR específicas para la plaza, integrando aspectos históricos y culturales locales. Se recopilaron datos que permitieron identificar cuáles serían las características de los desarrollos a realizar, para que contaran con la articulación del componente autóctono de la región.
Resultados: Los resultados mostraron un aumento significativo en la mejora en la percepción y el interés cultural de los visitantes hacia Agustín Codazzi. Estos resultados son novedosos en el contexto del uso de AR en espacios públicos para fines turísticos y culturales.
Conclusiones: Se concluye que la implementación de AR en la Plaza Alfonso Ávila Quintero ha tenido un impacto positivo en el turismo y la cultura local. Se sugiere que futuras investigaciones exploren la sostenibilidad a largo plazo de estas tecnologías en entornos similares y su posible aplicación en otras regiones
DOI: 10.15468/dl.2yv6vw
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Limonium malacitanum"
 ]
}

 The dataset includes 75 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025688-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tztedp
title: Occurrence Download

description: A dataset containing 124916 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Barbastella barbastellus",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 124916 records from 2018 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025658-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n4c8pv
title: Occurrence Download

description: A dataset containing 186 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Habenaria davidii Franch."
 ]
}

 The dataset includes 186 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012794-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4bkvmt
title: Occurrence Download

description: A dataset containing 716 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Austrobrickellia R.M.King & H.Rob."
 ]
}

 The dataset includes 716 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0214417-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hyfhh1
title: Occurrence Download

description: A dataset containing 141 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chirostoma consocium Jordan & Hubbs, 1919"
 ]
}

 The dataset includes 141 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001856-181003121212138/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xqjqe6
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Occurrence evidence)",
 "Continent is South America",
 "OccurrenceStatus is Present",
 "TaxonKey is Capparicordis crotonoides (Kunth) Iltis & Cornejo",
 "Year 1960-2023"
 ]
}

 The dataset includes 41 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0134354-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6k6nwj
title: Occurrence Download

description: A dataset containing 6705 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Archibaccharis Heering"
 ]
}

 The dataset includes 6705 records from 205 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0214393-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n732f8
title: Occurrence Download

description: A dataset containing 45589 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lessonia Swainson, 1832"
 ]
}

 The dataset includes 45589 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069080-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4zduu8
title: Occurrence Download

description: A dataset containing 859642 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Calluna vulgaris (L.) Hull)",
 "HasCoordinate is true",
 "Geometry POLYGON ((25.280527 74.385866, 34 74.516506, 34 35.773364,\n 32.861584 35.588421, 26.375071 34.609982, 22.816449 34.504241, 13.627633 36.690862,\n 10.001544 38.719154, -0.356862 36.404548, -9.323257 35.627079, -12.292937 57.408982,\n 25.280527 74.385866))"
 ]
}

 The dataset includes 859642 records from 1148 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0134375-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8xqwyr
title: Occurrence Download

description: A dataset containing 5433 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oedera L."
 ]
}

 The dataset includes 5433 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0214389-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tde24g
title: Occurrence Download

description: A dataset containing 413 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "TaxonKey is Orycteropus G.Cuvier, 1798"
 ]
}

 The dataset includes 413 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069096-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dvwya5
title: Occurrence Download

description: A dataset containing 1996 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Asteriscus maritimus (L.) Less."
 ]
}

 The dataset includes 1996 records from 103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0134371-230224095556074/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.cc2nf3z6
title: CCDC 2455478: Experimental Crystal Structure Determination

description: Related Article: J. T. Mague, M. S. Balakrishna|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.cc2nf4mw
title: CCDC 2455498: Experimental Crystal Structure Determination

description: Related Article: J. T. Mague, M. S. Balakrishna|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.cc2nf62d
title: CCDC 2455543: Experimental Crystal Structure Determination

description: Related Article: J. T. Mague, M. S. Balakrishna|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.