cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.23728/b2share.965055f4f2cc498ab1298f467e3a0d38
title: Nature Reserve Rode Forest and Laan Valley - Regional climate model data from EURO-CORDEX for the eLTER project

description: The dataset provides climate scenario data as time series based on an ensemble of EURO-CORDEX regional climate model (RCM) simulations for each LTER site location throughout Europe. The EURO-CORDEX ensemble used here consists of dynamically downscaled CMIP5 global climate models (GCMs) for different greenhouse gas concentration trajectories, the representative concentration pathways (RCPs: RCP2.6 (6), RCP4.5 (14) and RCP8.5 (14)). The datasets cover the following, non-bias adjusted variables: tas = near-surface air temperature [degC], tasmin = daily minimum near-surface air temperature [degC], tasmax = daily minimum near-surface air temperature [degC], pr = precipitation sum [mm day-1], psl = mean sea level pressure [Pa], huss = near-surface specific humidity [kg kg-1], rsds = surface downwelling shortwave radiation [W m-2], and sfcWind = near-surface wind speed [m s-1] in txt and netCDF data format at daily, monthly and yearly temporal resolution. Each ZIP-file data package contains the data file as well as an extensive disclaimer with additional information.
DOI: 10.23728/b2share.97952e5883144940a9d43812b7bbce21
title: Baelen - Regional climate model data from EURO-CORDEX for the eLTER project

description: The dataset provides climate scenario data as time series based on an ensemble of EURO-CORDEX regional climate model (RCM) simulations for each LTER site location throughout Europe. The EURO-CORDEX ensemble used here consists of dynamically downscaled CMIP5 global climate models (GCMs) for different greenhouse gas concentration trajectories, the representative concentration pathways (RCPs: RCP2.6 (6), RCP4.5 (14) and RCP8.5 (14)). The datasets cover the following, non-bias adjusted variables: tas = near-surface air temperature [degC], tasmin = daily minimum near-surface air temperature [degC], tasmax = daily minimum near-surface air temperature [degC], pr = precipitation sum [mm day-1], psl = mean sea level pressure [Pa], huss = near-surface specific humidity [kg kg-1], rsds = surface downwelling shortwave radiation [W m-2], and sfcWind = near-surface wind speed [m s-1] in txt and netCDF data format at daily, monthly and yearly temporal resolution. Each ZIP-file data package contains the data file as well as an extensive disclaimer with additional information.
DOI: 10.23728/b2share.404481e89d1c45329798d79177d0b6d3
title: Tellin - Regional climate model data from EURO-CORDEX for the eLTER project

description: The dataset provides climate scenario data as time series based on an ensemble of EURO-CORDEX regional climate model (RCM) simulations for each LTER site location throughout Europe. The EURO-CORDEX ensemble used here consists of dynamically downscaled CMIP5 global climate models (GCMs) for different greenhouse gas concentration trajectories, the representative concentration pathways (RCPs: RCP2.6 (6), RCP4.5 (14) and RCP8.5 (14)). The datasets cover the following, non-bias adjusted variables: tas = near-surface air temperature [degC], tasmin = daily minimum near-surface air temperature [degC], tasmax = daily minimum near-surface air temperature [degC], pr = precipitation sum [mm day-1], psl = mean sea level pressure [Pa], huss = near-surface specific humidity [kg kg-1], rsds = surface downwelling shortwave radiation [W m-2], and sfcWind = near-surface wind speed [m s-1] in txt and netCDF data format at daily, monthly and yearly temporal resolution. Each ZIP-file data package contains the data file as well as an extensive disclaimer with additional information.
DOI: 10.23728/b2share.44998059ad144ee68bb68223625164a6
title: LTSER Zone Atelier Territoires Uranifères - Regional climate model data from EURO-CORDEX for the eLTER project

description: The dataset provides climate scenario data as time series based on an ensemble of EURO-CORDEX regional climate model (RCM) simulations for each LTER site location throughout Europe. The EURO-CORDEX ensemble used here consists of dynamically downscaled CMIP5 global climate models (GCMs) for different greenhouse gas concentration trajectories, the representative concentration pathways (RCPs: RCP2.6 (6), RCP4.5 (14) and RCP8.5 (14)). The datasets cover the following, non-bias adjusted variables: tas = near-surface air temperature [degC], tasmin = daily minimum near-surface air temperature [degC], tasmax = daily minimum near-surface air temperature [degC], pr = precipitation sum [mm day-1], psl = mean sea level pressure [Pa], huss = near-surface specific humidity [kg kg-1], rsds = surface downwelling shortwave radiation [W m-2], and sfcWind = near-surface wind speed [m s-1] in txt and netCDF data format at daily, monthly and yearly temporal resolution. Each ZIP-file data package contains the data file as well as an extensive disclaimer with additional information.
DOI: 10.23728/b2share.07e679383b8142d5bbde12687515b4ba
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: NO2 in 2016 (18h CET) (shapefile)

description: Shapefile including air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of nitrogen dioxide during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.3f1deb95dd664ed5b3c0d336734c3da8
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: NO2 in 2016 (18h CET) (interpolated PNG)

description: PNG image representing interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of nitrogen dioxide during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.77c2ba3d931643fd91aa5ce125c83f14
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: NO2 in 2016 (18h CET) (clipped GeoTIFF)

description: Clipped GeoTIFF file including interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of nitrogen dioxide during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.b34e6a7808ee416aba653389f5dee590
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: NO in 2016 at 18h CET (dataset)

description: csv file including air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of nitrogen monoxide during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.b53a3d0b61984998b24c5cb0c5975806
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: NO in 2016 (18h CET) (interpolated PNG)

description: PNG image representing interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of nitrogen monoxide during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.9ab8ebc66ca64d349062b372ffb8d2a5
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: NO in 2016 (18h CET) (interpolated GeoTIFF)

description: GeoTIFF file including interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of nitrogen monoxide during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.7aff3972a0a64b50a71d03849fe575a2
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: temperature and humidity in 2016 at 19h CET (dataset)

description: csv file including air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of temperature and humidity during 2016, aggregated by hour (19h CET).
DOI: 10.15468/dl.gyapwp
title: Occurrence Download

description: A dataset containing 333 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Loxogramme scolopendrioides (Gaudich.) C.V.Morton"
 ]
}

 The dataset includes 333 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047656-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23728/b2share.696630bb3e754809ad49ac2342f99e7f
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: NO in 2016 (18h CET) (clipped GeoTIFF)

description: Clipped GeoTIFF file including interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of nitrogen monoxide during 2016, aggregated by hour (18h CET).
DOI: 10.15468/dl.38chya
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phyllanthus vespertilio Baill."
 ]
}

 The dataset includes 21 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047657-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23728/b2share.01bfa389222b4672a1588c01cb6eb42e
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: O3 in 2016 at 18h CET (dataset)

description: csv file including air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of ozone during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.34843fade05c4756bdb301c8248db2ff
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: O3 in 2016 (18h CET) (shapefile)

description: Shapefile including air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of ozone during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.894589e64e9d4b3db3b5d5cd18fa44f1
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: O3 in 2016 (18h CET) (interpolated GeoTIFF)

description: GeoTIFF file including interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of ozone during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.a77924479fe54fc1aeb8d59806f0ba56
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: O3 in 2016 (18h CET) (interpolated PNG)

description: PNG image representing interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of ozone during 2016, aggregated by hour (18h CET).
DOI: 10.15468/dl.nutsq7
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lithocarpus acuminatus (Roxb.) Rehder"
 ]
}

 The dataset includes 16 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047658-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23728/b2share.e9b7d18bff854b5bb54c936f501788f3
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: O3 in 2016 (18h CET) (clipped GeoTIFF)

description: Clipped GeoTIFF file including interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of ozone during 2016, aggregated by hour (18h CET).
DOI: 10.23728/b2share.b5352d565b124403972e4446f20ccac2
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: O3 in 2016 (18h CET) (clipped PNG)

description: PNG image representing clipped interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of ozone during 2016, aggregated by hour (18h CET).
DOI: 10.34816/efa.archives.795531
title: Délos-PV_3280-Chapiteau.

description: Référence : PV_3280<br />Publication(s) : EAD II, fig. 95<br />Domaine : Architecture<br />
DOI: 10.23728/b2share.e04a3c2905f543e48bc7a45a1a046a05
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: PM1, PM2.5 and PM10 in 2016 at 18h CET (dataset)

description: csv file including air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of PM1, PM2.5 and PM10 particles during 2016, aggregated by hour (18h CET).
DOI: 10.34816/efa.archives.795530
title: Délos-PV_3276-Entablement.

description: Référence : PV_3276<br />Publication(s) : EAD V, p. 21, fig. 24<br />Domaine : Architecture<br />
DOI: 10.23728/b2share.22fe331480c64f558235eaa170ebfdee
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: PM1, PM2.5 and PM10 in 2016 (18h CET) (shapefile)

description: Shapefile including air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of PM1, PM2.5 and PM10 particles during 2016, aggregated by hour (18h CET).
DOI: 10.15468/dl.3vrg5p
title: Occurrence Download

description: A dataset containing 11412698 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Betula L., Ulmus L., Pyrus L., Prunus L., Populus L., Platanus orientalis L., Platanus occidentalis L., Platanus L., Malus Mill., Lagerstroemia indica L., Lagerstroemia L., Fagus L., Cotoneaster Medik., Corylus avellana L., Citrus ×limon (L.) Osbeck, Citrus ×aurantium var. sinensis L., Citrus reticulata Blanco, Citrus L., Carpinus L., Alnus Mill., Aesculus hippocastanum L., Acer saccharinum L., Acer palmatum Thunb., Acer negundo L., Acer L.)",
 "Year 1970-2024"
 ]
}

 The dataset includes 11412698 records from 5196 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047620-240321170329656/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.13636918.v1
title: Additional file 11 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 11: Supplementary Table S10. Prevalence of outlier tiles at flow cell level.
DOI: 10.6084/m9.figshare.13636921
title: Additional file 12 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 12: Supplementary Table S11. Outlier tiles.
DOI: 10.6084/m9.figshare.13636921.v1
title: Additional file 12 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 12: Supplementary Table S11. Outlier tiles.
DOI: 10.6084/m9.figshare.13636918
title: Additional file 11 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 11: Supplementary Table S10. Prevalence of outlier tiles at flow cell level.
DOI: 10.6084/m9.figshare.13636924.v1
title: Additional file 13 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 13: Supplementary Table S12. Tile-level sequencer error rate estimated using a common reference DNA library.
DOI: 10.6084/m9.figshare.13636924
title: Additional file 13 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 13: Supplementary Table S12. Tile-level sequencer error rate estimated using a common reference DNA library.
DOI: 10.6084/m9.figshare.13636927
title: Additional file 14 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 14: Supplementary Table S13. Sequencer effect and outlier tile effect on overall error rate of a common reference DNA library.
DOI: 10.6084/m9.figshare.13636927.v1
title: Additional file 14 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 14: Supplementary Table S13. Sequencer effect and outlier tile effect on overall error rate of a common reference DNA library.
DOI: 10.6084/m9.figshare.13636930
title: Additional file 15 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 15: Supplementary Table S14. Sample names of a dataset generated in different sequencing centers by using a common reference DNA library.
DOI: 10.6084/m9.figshare.13636930.v1
title: Additional file 15 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 15: Supplementary Table S14. Sample names of a dataset generated in different sequencing centers by using a common reference DNA library.
DOI: 10.6084/m9.figshare.13636915
title: Additional file 10 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 10: Supplementary Table S9. Extent of outlier tiles.
DOI: 10.6084/m9.figshare.13636939
title: Additional file 2 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 2: Supplementary Table S1. List of NCBI SRA ( https://www.ncbi.nlm.nih.gov/sra ) studies and associated platform, research institute and country.
DOI: 10.6084/m9.figshare.16782671
title: Risk factors for mortality in hemodialysis patients with COVID-19: a systematic review and meta-analysis

description: New evidence from studies on risk factors for mortality in hemodialysis (HD) patients with COVID-19 became available. We aimed to review the clinical risk factors for fatal outcomes in these patients. We performed meta-analysis using the PubMed, EMBASE, and Cochrane databases. A fixed- or random-effects model was used for calculating heterogeneity. We used contour-enhanced funnel plot and Egger’s tests to assess potential publication bias. Twenty-one studies were included. The proportion of males was lower in the survivor group than in the non-survivor group (OR = 0.75, 95% CI [0.61, 0.94]). The proportion of respiratory diseases was significantly lower in the survivor group than in the non-survivor group (OR = 0.42, 95% CI [0.29, 0.60]). The proportion of patients with fever, cough, and dyspnea was significantly lower in the survivor group (fever: OR = 0.53, 95% CI [0.31, 0.92]; cough: OR = 0.50, 95% CI [0.38, 0.65]; dyspnea: OR = 0.25, 95% CI [0.14, 0.47]) than in the non-survivor group. Compared with the non-survivor group, the survivor group had higher albumin and platelet levels and lower leucocyte counts. Male patients might have a higher risk of developing severe COVID-19. Comorbidities, such as respiratory diseases could also greatly influence the clinical prognosis of COVID-19. Clinical features, such as fever, dyspnea, cough, and abnormal platelet, leucocyte, and albumin levels, could imply eventual death. Our findings will help clinicians identify markers for the detection of high mortality risk in HD patients at an early stage of COVID-19.
DOI: 10.6084/m9.figshare.16782671.v1
title: Risk factors for mortality in hemodialysis patients with COVID-19: a systematic review and meta-analysis

description: New evidence from studies on risk factors for mortality in hemodialysis (HD) patients with COVID-19 became available. We aimed to review the clinical risk factors for fatal outcomes in these patients. We performed meta-analysis using the PubMed, EMBASE, and Cochrane databases. A fixed- or random-effects model was used for calculating heterogeneity. We used contour-enhanced funnel plot and Egger’s tests to assess potential publication bias. Twenty-one studies were included. The proportion of males was lower in the survivor group than in the non-survivor group (OR = 0.75, 95% CI [0.61, 0.94]). The proportion of respiratory diseases was significantly lower in the survivor group than in the non-survivor group (OR = 0.42, 95% CI [0.29, 0.60]). The proportion of patients with fever, cough, and dyspnea was significantly lower in the survivor group (fever: OR = 0.53, 95% CI [0.31, 0.92]; cough: OR = 0.50, 95% CI [0.38, 0.65]; dyspnea: OR = 0.25, 95% CI [0.14, 0.47]) than in the non-survivor group. Compared with the non-survivor group, the survivor group had higher albumin and platelet levels and lower leucocyte counts. Male patients might have a higher risk of developing severe COVID-19. Comorbidities, such as respiratory diseases could also greatly influence the clinical prognosis of COVID-19. Clinical features, such as fever, dyspnea, cough, and abnormal platelet, leucocyte, and albumin levels, could imply eventual death. Our findings will help clinicians identify markers for the detection of high mortality risk in HD patients at an early stage of COVID-19.
DOI: 10.6084/m9.figshare.13636939.v1
title: Additional file 2 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 2: Supplementary Table S1. List of NCBI SRA ( https://www.ncbi.nlm.nih.gov/sra ) studies and associated platform, research institute and country.
DOI: 10.6084/m9.figshare.13636942
title: Additional file 3 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 3: Supplementary Table S2. HiSeq datasets. Publicly accessible studies deposited in NCBI SRA ( https://www.ncbi.nlm.nih.gov/sra ) were reviewed to account for lost read names.
DOI: 10.6084/m9.figshare.13636942.v1
title: Additional file 3 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 3: Supplementary Table S2. HiSeq datasets. Publicly accessible studies deposited in NCBI SRA ( https://www.ncbi.nlm.nih.gov/sra ) were reviewed to account for lost read names.
DOI: 10.6084/m9.figshare.13636945
title: Additional file 4 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 4: Supplementary Table S3. NextSeq datasets. Publicly accessible studies deposited in NCBI SRA ( https://www.ncbi.nlm.nih.gov/sra ) were reviewed to account for lost read names.
DOI: 10.6084/m9.figshare.13636945.v1
title: Additional file 4 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 4: Supplementary Table S3. NextSeq datasets. Publicly accessible studies deposited in NCBI SRA ( https://www.ncbi.nlm.nih.gov/sra ) were reviewed to account for lost read names.
DOI: 10.6084/m9.figshare.13636948
title: Additional file 5 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 5: Supplementary Table S4. NovaSeq datasets. Publicly accessible studies deposited in NCBI SRA ( https://www.ncbi.nlm.nih.gov/sra ) were reviewed to account for lost read names.
DOI: 10.6084/m9.figshare.13636948.v1
title: Additional file 5 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 5: Supplementary Table S4. NovaSeq datasets. Publicly accessible studies deposited in NCBI SRA ( https://www.ncbi.nlm.nih.gov/sra ) were reviewed to account for lost read names.
DOI: 10.6084/m9.figshare.13636951
title: Additional file 6 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 6: Supplementary Table S5. Sample effect is minimal on flow cell-level analysis.
DOI: 10.6084/m9.figshare.13636951.v1
title: Additional file 6 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 6: Supplementary Table S5. Sample effect is minimal on flow cell-level analysis.
DOI: 10.6084/m9.figshare.13636954
title: Additional file 7 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 7: Supplementary Table S6. Flow cell-level sequencer error rate.
DOI: 10.6084/m9.figshare.13636954.v1
title: Additional file 7 of SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

description: Additional file 7: Supplementary Table S6. Flow cell-level sequencer error rate.