cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.mxn3u7
title: Occurrence Download

description: A dataset containing 138 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Gagea fedtschenkoana Pascher"
 ]
}

 The dataset includes 138 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0345875-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n8q8y9
title: Occurrence Download

description: A dataset containing 5862 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vitis flexuosa Thunb."
 ]
}

 The dataset includes 5862 records from 168 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0135850-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2h5wn6
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Commiphora rostrata Engl."
 ]
}

 The dataset includes 29 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009347-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t5achf
title: Occurrence Download

description: A dataset containing 344 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Dendrolagus lumholtzi Collett, 1884",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 344 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013238-190320150433242/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sqb5qc
title: Occurrence Download

description: A dataset containing 5254 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Tigridia Juss."
 ]
}

 The dataset includes 5254 records from 168 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0348541-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h7cvzx
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hypolytrum turgidum C.B.Clarke"
 ]
}

 The dataset includes 14 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026935-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ocltvq
title: Occurrence Download

description: A dataset containing 6789 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Fundulus heteroclitus (Linnaeus, 1766)",
 "TaxonKey is Funtumia elastica (Preuss) Stapf",
 "TaxonKey is Furcifer oustaleti (Mocquard, 1894)",
 "TaxonKey is Furcifer pardalis (Cuvier, 1829)",
 "TaxonKey is Furcraea foetida (L.) Haw.",
 "TaxonKey is Furcraea hexapetala (Jacq.) Urb.",
 "TaxonKey is Fusinus rostratus (Olivi, 1792)",
 "TaxonKey is Fusinus verrucosus (Gmelin, 1791)",
 "TaxonKey is Gabrius nigritulus (Gravenhorst, 1802)",
 "TaxonKey is Gabronthus sulcifrons (Sharp, 1889)",
 "TaxonKey is Gabronthus thermarum (Aubé, 1850)",
 "TaxonKey is Gagea bohemica (Zauschn.) Schult. & Schult.f.",
 "TaxonKey is Gagea granulosa Turcz."
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 6789 records from 215 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013239-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5b995n
title: Occurrence Download

description: A dataset containing 255878 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Apis mellifera Linnaeus, 1758"
 ]
}

 The dataset includes 255878 records from 748 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0140331-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/b5gjmb9byb.1
title: Life sciences-Skeletal Muscle-Derived Exosomes Prevent Osteoporosis by Promoting Osteogenesis

description: raw data
DOI: 10.6084/m9.figshare.26935660
title: Supplementary Material for: Circulating miRNAs as Biomarkers of Subclinical Atherosclerosis associated to Severe Obesity before and after Bariatric Surgery

description: Introduction: severe obesity results in high cardiovascular risk, increasing morbidity and mortality. New and improved methods are needed to detect cardiovascular diseases rapidly in severe obesity. microRNAs (miRNAs) has shown promise as diagnostic tools. This study aimed to identify plasma miRNAs useful as biomarkers of cardiovascular risk (CVR) in people with severe obesity.
Methods: The study included 66 people with severe obesity classified in groups with atheroma (n = 32) and free of plaques (n = 34). Plasma samples were collected 1 month before bariatric surgery and at 6 and 12 months of follow-up. Participants were screened for the levels of 188 miRNAs, and 24 promising candidates were individually validated by quantitative polymerase chain reaction.
Results: After validation, 5 of the 24 miRNAs showed significant differences over time in both groups: miR-375 increased after bariatric surgery, whereas miR-144-5p, miR-20a-3p, miR-145-5p and miR-21-3p exhibited decreased expression after bariatric surgery. The expression of 3 of the 24 miRNAs also differed between patients with and without atheroma: subjects with plaque had lower miR-126 but higher miR-21-3p and miR-133a-3p. Only miR-133a-3p exhibited exceptional discriminatory ability between subjects with and without plaque (area under the curve, 0.90; 95% confidence interval, 0.81–0.99).
Conclusion: A specific signature of c-miRNA comprising miR-375, miR-144-5p, miR-20a-3p, miR-145-5p and miR-21-3p may facilitate CVR monitoring after bariatric surgery. Furthermore, miR-21-3p, miR-126-3p and miR-133a-3p show potential as specific biomarkers for subclinical atherosclerosis, with miR-133a-3p potentially able to diagnose subclinical atherosclerosis early in severe obesity.
DOI: 10.17632/x5mdpxmyr6.1
title: Geological and geographical location of the Neogene facies in the southern Western High Atlas (WHA)

description: A, Geological location based on the geological map of Agadir, 1/50000 scale (1960), and topographic maps of Agadir, 1/50000 scale (1976), and Ghabat Admin, 1/50000 scale (1974). Note that the geological map of Agadir does not cover the N'Toughza valley nor the area east of this valley
DOI: 10.15468/dl.g6mzen
title: Occurrence Download

description: A dataset listing the 3 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Marthamea vitripennis (Burmeister, 1839)"
 ]
}

 The dataset's 3 records were derived from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115841-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/kada-c126-21556
title: Blacksmith outside the East Gate of Seoul

description: Caption: "A blacksmith shop outside the East Gate - Seoul"
DOI: 10.17632/hjfsvfhnzb.1
title: Dataset of Rohingya-related international news published in 2009-2023

description: This repository contains ten datasets of Rohingya-related 8,074 news stories published in ten newspapers from ten countries between 2009 and 2023. Each country has one dataset, with the eleventh dataset containing all news stories in a single file. We used three Python libraries: BeautifulSoup, Selenium, and Newspaper4k, to scrape the data. The newspapers included here are The Daily Star (Bangladesh), China Daily (China), The Times of India (India), The Star (Malaysia), Express Tribune (Pakistan), Al Jazeera (Qatar), Saudi Gazette (Saudi Arabia), Daily Sabah (Turkey), The Guardian (UK), and The New York Times (US). This data was collected as part of a research project that analyzed the framing of Rohingya-related international news.
DOI: 10.17632/hjfsvfhnzb.2
title: Dataset of Rohingya-related international news published in 2009-2023

description: This repository contains ten datasets of Rohingya-related 8,074 news stories published in ten newspapers from ten countries between 2009 and 2023. Each country has one dataset, with the eleventh dataset containing all news stories in a single file. We used three Python libraries: BeautifulSoup, Selenium, and Newspaper4k, to scrape the data. The newspapers included here are The Daily Star (Bangladesh), China Daily (China), The Times of India (India), The Star (Malaysia), Express Tribune (Pakistan), Al Jazeera (Qatar), Saudi Gazette (Saudi Arabia), Daily Sabah (Turkey), The Guardian (UK), and The New York Times (US). This data was collected as part of a research project that analyzed the framing of Rohingya-related international news.
DOI: 10.25549/kada-c126-9837
title: Kungminhoe. Taepyo Taehoe (che 55-cha); 1964. Hoeuirok.

description: Box abstract: Minutes about discussion on the Kungminhoe members, financial issues, the Sinhan Minbo, election, and reports of General Affairs Department's activities, etc.
DOI: 10.17632/hjfsvfhnzb.3
title: Dataset of Rohingya-related international news published in 2009-2023

description: This repository contains ten datasets of Rohingya-related 8,074 news stories published in ten newspapers from ten countries between 2009 and 2023. Each country has one dataset, with the eleventh dataset containing all news stories in a single file. We used three Python libraries: BeautifulSoup, Selenium, and Newspaper4k, to scrape the data. The newspapers included here are The Daily Star (Bangladesh), China Daily (China), The Times of India (India), The Star (Malaysia), Express Tribune (Pakistan), Al Jazeera (Qatar), Saudi Gazette (Saudi Arabia), Daily Sabah (Turkey), The Guardian (UK), and The New York Times (US). This data was collected as part of a research project that analyzed the framing of Rohingya-related international news.
DOI: 10.25549/kada-c126-9340
title: Kungminhoe. Taepyo Taehoe (che 11, 12-cha); Taeuiwonhoe (che 38, 39-hoe), 1946, 1948. Hoeuirok.

description: Box abstract: Minutes about discussion on the Kungminhoe members, financial issues, the Sinhan Minbo, election, and reports of General Affairs Department's activities, etc.
DOI: 10.15468/dl.xqk35c
title: Occurrence Download

description: A dataset listing the 2 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Perla burmeisteriana Claassen, 1936"
 ]
}

 The dataset's 2 records were derived from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115840-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/kada-c126-10839
title: Kungminhoe. Member tracking.

description: [contents] Unit_ID: page001.; Unit_ID: page002.; Unit_ID: page003.; Unit_ID: page004.; Unit_ID: page005.; Unit_ID: page006.; Unit_ID: page007.; Unit_ID: page008.; Unit_ID: page009.; Unit_ID: page010.; Unit_ID: page011.; Unit_ID: page012.; Unit_ID: page013.; Unit_ID: page014.; Unit_ID: page015.; Unit_ID: page016.; Unit_ID: page017.; Unit_ID: page018.; Unit_ID: page019.; Unit_ID: page020.; Unit_ID: page021.; Unit_ID: page022.; Unit_ID: page023.; Unit_ID: page024.; Unit_ID: page025.; Unit_ID: page026.; Unit_ID: page027.; Unit_ID: page028.; Unit_ID: page029.; Unit_ID: page030.; Unit_ID: page031.; Unit_ID: page032.; Unit_ID: page033.; Unit_ID: page034.; Unit_ID: page035.; Unit_ID: page036.; Unit_ID: page037.; Unit_ID: page038.; Unit_ID: page039.; Unit_ID: page040.; Unit_ID: page041.; Unit_ID: page042.; Unit_ID: page043.; Unit_ID: page044.; Unit_ID: page045.; Unit_ID: page046.; Unit_ID: page047.; Unit_ID: page048.; Unit_ID: page049.; Unit_ID: page050.
DOI: 10.15468/dl.56dwpk
title: Occurrence Download

description: A dataset listing the 1383 species recorded in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "PublishingCountry is India"
 ]
}

 The dataset's 1383 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115843-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s7rdg8
title: Occurrence Download

description: A dataset containing 55691 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aedes aegypti (Linnaeus, 1762)"
 ]
}

 The dataset includes 55691 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115856-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7aek3a
title: Occurrence Download

description: A dataset containing 55691 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aedes aegypti (Linnaeus, 1762)"
 ]
}

 The dataset includes 55691 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115857-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bexsm8
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is cdef28b1-db4e-4c58-aa71-3c5238c2d0b5",
 "TaxonKey is Nematoda"
 ]
}

 The dataset includes 23 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115858-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.88v48q
title: Occurrence Download

description: A dataset containing 388 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Taxus wallichiana var. mairei (Lemée & Lév.) L.K.Fu & Nan Li"
 ]
}

 The dataset includes 388 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115860-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.7265582
title: MobMeter: a global human mobility data set based on smartphone trajectories

description: The data set provides estimates of country-level daily mobility metrics (uncertainty included) for 17 countries from March 11, 2020 to present. Estimates are based on more than 3.8 million smartphone trajectories. Metrics: Estimated daily average travelled distance by people. Estimated percentage of people who did not move during the 24 hours of the day. Countries: Argentina (ARG), Chile (CHL), Colombia (COL), Costa Rica (CRI), Ecuador (ECU), Greece (GRC), Guatemala (GTM), Italy (ITA), Mexico (MEX), Nicaragua (NIC), Panama (PAN), Peru (PER), Philippines (PHL), Slovenia (SVN), Turkey (TUR), United States (USA) and Venezuela (VEN). Covered period: from March 11, 2020 to present. Temporal resolution: daily. Temporal smoothing: No smoothing. 7-day moving average. 14-day moving average. 21-day moving average. 28-day moving average. Uncertainty: 95% bootstrap confidence interval. <strong>Data ownership</strong> Anonymized data on smartphone trajectories are collected, owned and managed by Futura Innovation SRL. Smartphone trajectories are stored and analyzed on servers owned by Futura Innovation SRL and not shared with third parties, including the author of this repository and his organization (University of Bergamo). <strong>Contribution</strong> Ilaria Cremonesi of Futura Innovation SRL is the data owner and data manager. Francesco Finazzi of University of Bergamo developed the statistical methodology for the data analysis and the algorithms implemented on Futura Innovation SRL servers.
description: {"references": ["Finazzi, F. (2022) Replacing discontinued Big Tech mobility reports: a penetration-based analysis, arXiv:2210.09714"]}
DOI: 10.5281/zenodo.7387068
title: MobMeter: a global human mobility data set based on smartphone trajectories

description: The data set provides estimates of country-level daily mobility metrics (uncertainty included) for 17 countries from March 11, 2020 to present. Estimates are based on more than 3.8 million smartphone trajectories. Metrics: Estimated daily average travelled distance by people. Estimated percentage of people who did not move during the 24 hours of the day. Countries: Argentina (ARG), Chile (CHL), Colombia (COL), Costa Rica (CRI), Ecuador (ECU), Greece (GRC), Guatemala (GTM), Italy (ITA), Mexico (MEX), Nicaragua (NIC), Panama (PAN), Peru (PER), Philippines (PHL), Slovenia (SVN), Turkey (TUR), United States (USA) and Venezuela (VEN). Covered period: from March 11, 2020 to present. Temporal resolution: daily. Temporal smoothing: No smoothing. 7-day moving average. 14-day moving average. 21-day moving average. 28-day moving average. Uncertainty: 95% bootstrap confidence interval. <strong>Data ownership</strong> Anonymized data on smartphone trajectories are collected, owned and managed by Futura Innovation SRL. Smartphone trajectories are stored and analyzed on servers owned by Futura Innovation SRL and not shared with third parties, including the author of this repository and his organization (University of Bergamo). <strong>Contribution</strong> Ilaria Cremonesi of Futura Innovation SRL is the data owner and data manager. Francesco Finazzi of University of Bergamo developed the statistical methodology for the data analysis and the algorithms implemented on Futura Innovation SRL servers.
description: {"references": ["Finazzi, F. (2022) Replacing discontinued Big Tech mobility reports: a penetration-based analysis, arXiv:2210.09714"]}
DOI: 10.5281/zenodo.7500820
title: MobMeter: a global human mobility data set based on smartphone trajectories

description: The data set provides estimates of country-level daily mobility metrics (uncertainty included) for 17 countries from March 11, 2020 to present. Estimates are based on more than 3.8 million smartphone trajectories. Metrics: Estimated daily average travelled distance by people. Estimated percentage of people who did not move during the 24 hours of the day. Countries: Argentina (ARG), Chile (CHL), Colombia (COL), Costa Rica (CRI), Ecuador (ECU), Greece (GRC), Guatemala (GTM), Italy (ITA), Mexico (MEX), Nicaragua (NIC), Panama (PAN), Peru (PER), Philippines (PHL), Slovenia (SVN), Turkey (TUR), United States (USA) and Venezuela (VEN). Covered period: from March 11, 2020 to present. Temporal resolution: daily. Temporal smoothing: No smoothing. 7-day moving average. 14-day moving average. 21-day moving average. 28-day moving average. Uncertainty: 95% bootstrap confidence interval. <strong>Data ownership</strong> Anonymized data on smartphone trajectories are collected, owned and managed by Futura Innovation SRL. Smartphone trajectories are stored and analyzed on servers owned by Futura Innovation SRL and not shared with third parties, including the author of this repository and his organization (University of Bergamo). <strong>Contribution</strong> Ilaria Cremonesi of Futura Innovation SRL is the data owner and data manager. Francesco Finazzi of University of Bergamo developed the statistical methodology for the data analysis and the algorithms implemented on Futura Innovation SRL servers.
description: {"references": ["Finazzi, F. (2022) Replacing discontinued Big Tech mobility reports: a penetration-based analysis, arXiv:2210.09714"]}
DOI: 10.5281/zenodo.7251940
title: MobMeter: a global mobility data set based on smartphone trajectories

description: The data set provides estimates of country-level daily mobility metrics (uncertainty included) for 17 countries from March 11, 2020 to present. Estimates are based on more than 3.8 million smartphone trajectories. Metrics: Estimated daily average travelled distance by people. Estimated percentage of people who did not move during the 24 hours of the day. Countries: Argentina (ARG), Chile (CHL), Colombia (COL), Costa Rica (CRI), Ecuador (ECU), Greece (GRC), Guatemala (GTM), Italy (ITA), Mexico (MEX), Nicaragua (NIC), Panama (PAN), Peru (PER), Philippines (PHL), Slovenia (SVN), Turkey (TUR), United States (USA) and Venezuela (VEN). Covered period: from March 11, 2020 to present. Temporal resolution: daily. Temporal smoothing: No smoothing. 7-day moving average. 14-day moving average. 21-day moving average. 28-day moving average. Uncertainty: 95% bootstrap confidence interval. <strong>Data ownership</strong> Anonymized data on smartphone trajectories are collected, owned and managed by Futura Innovation SRL. Smartphone trajectories are stored and analyzed on servers owned by Futura Innovation SRL and not shared with third parties, including the author of this repository and his organization (University of Bergamo). <strong>Contribution</strong> Ilaria Cremonesi of Futura Innovation SRL is the data owner and data manager. Francesco Finazzi of University of Bergamo developed the statistical methodology for the data analysis and the algorithms implemented on Futura Innovation SRL servers.
description: {"references": ["Finazzi, F. (2022) Replacing discontinued Big Tech mobility reports: a penetration-based analysis, arXiv:2210.09714"]}
DOI: 10.5281/zenodo.7439307
title: MobMeter: a global human mobility data set based on smartphone trajectories

description: The data set provides estimates of country-level daily mobility metrics (uncertainty included) for 17 countries from March 11, 2020 to present. Estimates are based on more than 3.8 million smartphone trajectories. Metrics: Estimated daily average travelled distance by people. Estimated percentage of people who did not move during the 24 hours of the day. Countries: Argentina (ARG), Chile (CHL), Colombia (COL), Costa Rica (CRI), Ecuador (ECU), Greece (GRC), Guatemala (GTM), Italy (ITA), Mexico (MEX), Nicaragua (NIC), Panama (PAN), Peru (PER), Philippines (PHL), Slovenia (SVN), Turkey (TUR), United States (USA) and Venezuela (VEN). Covered period: from March 11, 2020 to present. Temporal resolution: daily. Temporal smoothing: No smoothing. 7-day moving average. 14-day moving average. 21-day moving average. 28-day moving average. Uncertainty: 95% bootstrap confidence interval. <strong>Data ownership</strong> Anonymized data on smartphone trajectories are collected, owned and managed by Futura Innovation SRL. Smartphone trajectories are stored and analyzed on servers owned by Futura Innovation SRL and not shared with third parties, including the author of this repository and his organization (University of Bergamo). <strong>Contribution</strong> Ilaria Cremonesi of Futura Innovation SRL is the data owner and data manager. Francesco Finazzi of University of Bergamo developed the statistical methodology for the data analysis and the algorithms implemented on Futura Innovation SRL servers.
description: {"references": ["Finazzi, F. (2022) Replacing discontinued Big Tech mobility reports: a penetration-based analysis, arXiv:2210.09714"]}