cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.j6qh5x
title: Occurrence Download

description: A dataset containing 5339950 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Molothrus ater (Boddaert, 1783)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5339950 records from 125 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0202146-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.56ewft
title: Occurrence Download

description: A dataset containing 234166 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Geothlypis philadelphia (A.Wilson, 1810)"
 ]
}

 The dataset includes 234166 records from 222 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0408313-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h839v6
title: Occurrence Download

description: A dataset containing 26426 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lobarina scrobiculata (Scop.) Nyl. ex Cromb., Parmotrema arnoldii (Du Rietz) Hale)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 26426 records from 109 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0167920-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sb25sq
title: Occurrence Download

description: A dataset containing 7666 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Romulea ramiflora Ten."
 ]
}

 The dataset includes 7666 records from 137 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0104760-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7pydzp
title: Occurrence Download

description: A dataset containing 3904 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Thesium prostratum A.W.Hill, Noccaea brachypetala (Jord.) F.K.Mey.)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 3904 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0329393-210914110416597/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.24792583
title: Global prevalence of musculoskeletal disorders among sanitary workers: a systematic review and meta-analysis

description: <i>Objectives</i>. Sanitary workers are more likely to experience musculoskeletal disorders (MSDs) due to a lack of ergonomics principles and poor job design. Thus, this systematic review and meta-analysis aimed to quantify MSDs among sanitary workers. <i>Methods</i>. The PRISMA and PICOS protocols were used for flow diagrams and review questions, respectively. Articles published between 2000 and 2022 were eligible. The keywords ‘(Musculoskeletal Disorders) AND (Solid waste collectors *OR Street sweepers *OR Sewage workers *OR health facilities cleaners)’ and MeSH terms were utilized. The data were analyzed using STATA version 17 with a 95% confidence interval (CI). <i>Results</i>. A total of 158 papers were qualified, with 26 studies from 17 countries and a total of 6586 sanitary workers. The global prevalence of MSDs among sanitation workers was 40.52% (95% CI [32.47, 48.67]; <i>p</i> &lt; 0.05). It was 43.32% (95% CI [31.98, 54.68]; <i>p</i> &lt; 0.05) in high-income countries and 38.58% (95% CI [26.94, 50.18]; <i>p</i> &lt; 0.05) in low-income countries. By subgroup analysis, it was 45.12% (95% CI [32.57, 57.67]; <i>p</i> &lt; 0.05) for solid waste collectors, which is the highest prevalence among other workers. <i>Conclusion.</i> Current evidence shows that sanitation workers have a higher prevalence of occupationally associated MSDs, which might be lowered by using ergonomic work design principles.
DOI: 10.6084/m9.figshare.24792583.v2
title: Global prevalence of musculoskeletal disorders among sanitary workers: a systematic review and meta-analysis

description: <i>Objectives</i>. Sanitary workers are more likely to experience musculoskeletal disorders (MSDs) due to a lack of ergonomics principles and poor job design. Thus, this systematic review and meta-analysis aimed to quantify MSDs among sanitary workers. <i>Methods</i>. The PRISMA and PICOS protocols were used for flow diagrams and review questions, respectively. Articles published between 2000 and 2022 were eligible. The keywords ‘(Musculoskeletal Disorders) AND (Solid waste collectors *OR Street sweepers *OR Sewage workers *OR health facilities cleaners)’ and MeSH terms were utilized. The data were analyzed using STATA version 17 with a 95% confidence interval (CI). <i>Results</i>. A total of 158 papers were qualified, with 26 studies from 17 countries and a total of 6586 sanitary workers. The global prevalence of MSDs among sanitation workers was 40.52% (95% CI [32.47, 48.67]; <i>p</i> &lt; 0.05). It was 43.32% (95% CI [31.98, 54.68]; <i>p</i> &lt; 0.05) in high-income countries and 38.58% (95% CI [26.94, 50.18]; <i>p</i> &lt; 0.05) in low-income countries. By subgroup analysis, it was 45.12% (95% CI [32.57, 57.67]; <i>p</i> &lt; 0.05) for solid waste collectors, which is the highest prevalence among other workers. <i>Conclusion.</i> Current evidence shows that sanitation workers have a higher prevalence of occupationally associated MSDs, which might be lowered by using ergonomic work design principles.
DOI: 10.6084/m9.figshare.24792583.v1
title: Global prevalence of musculoskeletal disorders among sanitary workers: A Systematic Review and Meta-Analysis

description: Sanitary workers are more likely to experience musculoskeletal disorders (MSDs) due to a lack of ergonomics principles and poor job design. Thus, the quantification of this illness among sanitary workers was the goal of this systematic review and meta-analysis. For flow diagrams and review questions the PRISMA and PICOS protocols were used, respectively. The articles published between 2000 to 2022 were eligible. Along with the terms of (Musculoskeletal Disorders) AND (Solid waste collectors *OR Street sweepers *OR Sewage workers *OR health facilities cleaners) and MeSH is utilized. The data was analyzed using STATA 17 software with a 95% confidence interval. A total of 158 papers were qualified, with 26 studies from 17 countries and a total of 6586 sanitary workers were obtained. The global prevalence of MSDs among sanitation workers was 40.52% (95% CI: 32.47-48.67; p &lt; 0.05). It was 43.32% (95%CI:31.98-54.68; p &lt; 0.05) in high-income countries and 38.58% (95%CI:26.94-50.18; p &lt; 0.05) in low-income countries. By sub-group analysis, it was 45.12% (95%CI: 32.57-57.67; p &lt; 0.05) for solid waste collectors, which is the highest prevalence among others. The current evidence shows that sanitation workers have a higher prevalence of occupationally associated MSDs, which might be lowered by using ergonomic work design principles.
DOI: 10.15468/dl.2v87ky
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "TaxonKey is Felis onca Linnaeus, 1758"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0202194-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.khf9u7
title: Occurrence Download

description: A dataset containing 430 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Greece",
 "TaxonKey is Origanum vulgare L."
 ]
}

 The dataset includes 430 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102413-230530130749713/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.24792604
title: Stress influence on real-world driving identified by monitoring heart rate variability and morphologic variability of electrocardiogram signals: the case of intercity roads

description: <i>Objectives.</i> This study examines which of the heart rate variability (HRV) and morphologic variability (MV) metrics may have the highest accuracy in different stress detection during real-world driving. <i>Methods</i>. The cross-sectional study was carried out among 93 intercity mini-bus male drivers aged 22–67 years. The Trillium 5000 Holter Recorder and GARMIN Virb Elite camera were used to determine heart rate and vehicle speed measurements along the path, respectively. We considered the HRV and MV metrics of electrocardiogram (ECG) signals including the mean RR interval (mRR), mean heart rate (mHR), normalized low-frequency spectrum (nLF), normalized high-frequency spectrum (nHF), normalized very low-frequency spectrum (nVLF), difference of normalized low-frequency spectrum and normalized high-frequency spectrum (dLFHF), and sympathovagal balance index (SVI). <i>Results</i>. The analysis showed that the HRV metrics mHR, mRR, nVLF, nLF, nHF, dLFHF and SVI are effective in mental stress detection while driving as compared to rest time. We obtained a high accuracy of stress detection for MV metrics as compared to the traditional HRV analysis, of approximately 92%. <i>Conclusions</i>. Our findings indicate that driver stress could be detected with an accuracy of 92% using MV metrics as an accurate physiological index of the driver’s state.
DOI: 10.6084/m9.figshare.24792604.v2
title: Stress influence on real-world driving identified by monitoring heart rate variability and morphologic variability of electrocardiogram signals: the case of intercity roads

description: <i>Objectives.</i> This study examines which of the heart rate variability (HRV) and morphologic variability (MV) metrics may have the highest accuracy in different stress detection during real-world driving. <i>Methods</i>. The cross-sectional study was carried out among 93 intercity mini-bus male drivers aged 22–67 years. The Trillium 5000 Holter Recorder and GARMIN Virb Elite camera were used to determine heart rate and vehicle speed measurements along the path, respectively. We considered the HRV and MV metrics of electrocardiogram (ECG) signals including the mean RR interval (mRR), mean heart rate (mHR), normalized low-frequency spectrum (nLF), normalized high-frequency spectrum (nHF), normalized very low-frequency spectrum (nVLF), difference of normalized low-frequency spectrum and normalized high-frequency spectrum (dLFHF), and sympathovagal balance index (SVI). <i>Results</i>. The analysis showed that the HRV metrics mHR, mRR, nVLF, nLF, nHF, dLFHF and SVI are effective in mental stress detection while driving as compared to rest time. We obtained a high accuracy of stress detection for MV metrics as compared to the traditional HRV analysis, of approximately 92%. <i>Conclusions</i>. Our findings indicate that driver stress could be detected with an accuracy of 92% using MV metrics as an accurate physiological index of the driver’s state.
DOI: 10.6084/m9.figshare.25242812
title: Modeling alarm detection in noise for normal and hearing-impaired listeners: the effect of elevated thresholds and enlarged auditory filters

description: A model was developed to assess how elevated absolute thresholds and enlarged auditory filters can impede the ability to detect alarms in a noisy background, such alarms being of paramount importance to ensure the safety of workers. Based on previously measured masked thresholds of 80 listeners in five groups (normal hearing to strongly impaired), the model was derived from signal detection theory (SDT) applied to Glasberg and Moore’s excitation pattern model. The model can describe the influence of absolute thresholds and enlarged auditory filters together or separately on the detection ability for normal hearing and hearing-impaired listeners with various hearing profiles. Furthermore, it suggests that enlarged auditory filters alone can explain all of the impairment in this specific alarm detection task. Finally, the possibility of further development of the model into an alarm detection model is discussed.
DOI: 10.6084/m9.figshare.25242812.v1
title: Modeling alarm detection in noise for normal and hearing-impaired listeners: the effect of elevated thresholds and enlarged auditory filters

description: A model was developed to assess how elevated absolute thresholds and enlarged auditory filters can impede the ability to detect alarms in a noisy background, such alarms being of paramount importance to ensure the safety of workers. Based on previously measured masked thresholds of 80 listeners in five groups (normal hearing to strongly impaired), the model was derived from signal detection theory (SDT) applied to Glasberg and Moore’s excitation pattern model. The model can describe the influence of absolute thresholds and enlarged auditory filters together or separately on the detection ability for normal hearing and hearing-impaired listeners with various hearing profiles. Furthermore, it suggests that enlarged auditory filters alone can explain all of the impairment in this specific alarm detection task. Finally, the possibility of further development of the model into an alarm detection model is discussed.
DOI: 10.15468/dl.m3as8m
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation)",
 "Country is Sweden",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Agriotes lineatus (Linnaeus, 1767)",
 "Year 2000-2011"
 ]
}

 The dataset includes 62 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0167646-220831081235567/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.24792604.v1
title: Stress influence on real-world driving identified by monitoring heart rate variability and morphologic variability of ECG signals: The case of intercity roads

description: This study examines which one of the heart rate variability (HRV) and morphologic variability (MV) metrics may have the highest accuracy in different stress detection during real-world driving. This cross-sectional study was carried out among 93 intercity mini-bus male drivers aged 22-67 years. Trillium 5000 Holter Recorder and GARMIN Virb Elite camera were used to determine heart rate and vehicle speed measurements along the path, respectively. We have considered the HRV and MV metrics of ECG signals including mean RR interval (mRR), mean heart rate (mHR), normalized low-frequency spectrum (nLF), normalized high-frequency spectrum (nHF), normalized very low-frequency spectrum (nVLF), a difference of normalized low-frequency spectrum and normalized high-frequency spectrum (dLFHF), and sympathovagal balance index (SVI). The analysis showed that HRV metrics named mHR, mRR, nVLF, nLF, nHF, dLFHF, and SVI are effective in mental stress detection while driving as compared to rest time. We obtained a high accuracy of stress detection for MV metrics as compared to the traditional HRV analysis, approximately 92%. Our findings indicate that driver stress could be detected with an accuracy of 92% using MV metrics as an accurate physiological index of the driver's state.
DOI: 10.15468/dl.xdmv9h
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Magnoliopsida, Liliopsida)",
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000",
 "Geometry MULTIPOLYGON (((-86.44409 23.87683, -86.583 23.685, -86.583 23.218, -86.87491 23.10333, -86.97291 22.37433, -86.59305 22.361, -86.55887 22.8273, -86.39009 23.04352, -86.27 23.62171, -86.011 23.60995, -86.01879 23.997, -86.44409 23.87683)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0178350-210914110416597/datasets/export for details.
DOI: 10.15468/dl.daabv2
title: Occurrence Download

description: A dataset containing 96902 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Glycine max (L.) Merr."
 ]
}

 The dataset includes 96902 records from 377 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0172604-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wbs8sg
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aecidium sambucinum Arthur & Cummins",
 {
 "not" : {
 "Country" : [
 "is United States of America"
 ]
 }
 },
 {
 "not" : {
 "Country" : [
 "is Canada"
 ]
 }
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 }
 ]
}

 The dataset includes 19 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102345-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tfpmgy
title: Occurrence Download

description: A dataset containing 229 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Sceloporus bulleri Boulenger, 1895",
 "Year 1950-2022"
 ]
}

 The dataset includes 229 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009944-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kh95m9
title: Occurrence Download

description: A dataset containing 10851 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Guadua angustifolia Kunth"
 ]
}

 The dataset includes 10851 records from 144 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0281655-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2caggr
title: Occurrence Download

description: A dataset containing 2592699 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Pl@ntNet observations"
 ]
}

 The dataset includes 2592699 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059136-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6t28sr
title: Occurrence Download

description: A dataset containing 867346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cirsium vulgare",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 867346 records from 3401 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059108-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10704879
title: Linked collectors and determiners for: The genus Sicoderus Vanin 1986 (Coleoptera: Curculionidae: Curculioninae: Erodiscini) in the West Indies.

description: Natural history specimen data linked to collectors and determiners held within, "The genus Sicoderus Vanin 1986 (Coleoptera: Curculionidae: Curculioninae: Erodiscini) in the West Indies". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/55770274-cac7-4dde-871a-6c4cf42522c5 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/55770274-cac7-4dde-871a-6c4cf42522c5. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10872634
title: Linked collectors and determiners for: The genus Sicoderus Vanin 1986 (Coleoptera: Curculionidae: Curculioninae: Erodiscini) in the West Indies.

description: Natural history specimen data linked to collectors and determiners held within, "The genus Sicoderus Vanin 1986 (Coleoptera: Curculionidae: Curculioninae: Erodiscini) in the West Indies". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/55770274-cac7-4dde-871a-6c4cf42522c5 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/55770274-cac7-4dde-871a-6c4cf42522c5. Formatted as a Frictionless Data package.