cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.rcc7dy
title: Occurrence Download

description: A dataset containing 127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tubifex blanchardi Vejdovsky, 1891)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 127 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041771-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p937p08q
title: Surface water chemistry from the San Juan River watershed, 2021-2022, Four Corners USA

description: This study was done because elevated concentrations of metals including aluminum, arsenic, and lead were identified by Navajo Nation EPA staff in the San Juan River from below the Navajo Dam, through the Navajo Nation to Mexican Hat, Utah in the Four Corners Region of the United States (Colorado, Arizona, New Mexico, Utah). An interdisciplinary team applied approaches and principles of geology, geochemistry, geomorphology, hydrology, and statistics to gain a better understanding of the tributaries supplying the source(s) of metals to the San Juan River. Water samples were collected in single-siphon samples and by grab sample at 59 ephemeral and perennial tributaries to the San Juan River in 2021 and 2022. Eighteen surface water sites along the San Juan River were sampled as grab samples in 2021 and 2022 and fifteen sites along the San Juan River were sampled by equal width increment and composited in a churn during a baseflow synoptic sampling campaign in February 2021. A total of 765 unfiltered and 282 filtered samples were analyzed for major and trace cations. All samples were analyzed through the USGS Analytical Chemistry Laboratory in Denver, Colorado (Taggart, 2022; USGS, 2023 Method 37).
DOI: 10.15468/dl.pte67j
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tucumania tapiacola Dyar, 1925)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041772-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3rxxrw
title: Occurrence Download

description: A dataset containing 462 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Magnolia Plum. ex L."
 ]
}

 The dataset includes 462 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041773-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.635qcm
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tulostoma subfuscum V.S.White)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041775-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9jfe75
title: Occurrence Download

description: A dataset containing 328024 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gymnocephalus cernua (Linnaeus, 1758)"
 ]
}

 The dataset includes 328024 records from 291 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041762-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z2appy
title: Occurrence Download

description: A dataset containing 22296 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "StateProvince is ALberta",
 "TaxonKey is Araneae"
 ]
}

 The dataset includes 22296 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041776-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zym6t9
title: Occurrence Download

description: A dataset containing 993 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tupinambis cryptus Murphy, Jowers, Lehtinen, Charles, Colli, Peres Jr, Hendry & Pyron, 2016)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 993 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041777-240626123714530/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.26400520
title: Supplementary material_Chapter 4.pdf

description: Supplementary material_Chapter 4.pdf
DOI: 10.6084/m9.figshare.26400520.v1
title: Supplementary material_Chapter 4.pdf

description: Supplementary material_Chapter 4.pdf
DOI: 10.15468/dl.hqjyh6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tuponia elegans (Jakovlev, 1867))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041779-240626123714530/datasets/export for details.
DOI: 10.15468/dl.bys2pd
title: Occurrence Download

description: A dataset containing 1295 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Leuresthes tenuis (Ayres, 1860))"
 ]
}

 The dataset includes 1295 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041778-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jwtd2t
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Turbonilla edgarii (Melvill, 1896))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041780-240626123714530/datasets/export for details.
DOI: 10.26300/0ahz-qw21
title: Data documentation for "Do Medicare Beneficiaries Under Accountable Care or Medicare Advantage Use lower Quality Nursing Homes?"
DOI: 10.25390/caryinstitute.11367455
title: Non-native species have multiple abundance-impact curves (model results)

description: Data files containing the results of simple simulation models of the effects of ecosystem characteristics on the impacts and abundance-impact curves of non-native (invasive) species. These models were used in the paper: Strayer, D.L. 2020. Non-native species have multiple abundance-impact curves. Ecology and Evolution.<br>
DOI: 10.25390/caryinstitute.11367455.v1
title: Non-native species have multiple abundance-impact curves (model results)

description: Data files containing the results of simple simulation models of the effects of ecosystem characteristics on the impacts and abundance-impact curves of non-native (invasive) species. These models were used in the paper: Strayer, D.L. 2020. Non-native species have multiple abundance-impact curves. Ecology and Evolution.<br>
DOI: 10.6084/m9.figshare.26400148
title: RPM SQ tumor associated mIF files. Transplanted into castrated host.

description: RPM SQ tumor associated mIF files. Transplanted into castrated host.
DOI: 10.6084/m9.figshare.26400148.v1
title: RPM SQ tumor associated mIF files. Transplanted into castrated host.

description: RPM SQ tumor associated mIF files. Transplanted into castrated host.
DOI: 10.6084/m9.figshare.26400157
title: RPM Ascl1 KO SQ tumor associated mIF files. Transplanted into intact host.

description: RPM SQ tumor associated mIF files. Transplanted into intact host.
DOI: 10.6084/m9.figshare.26400079
title: RPM SQ tumor associated mIF files. Transplanted into intact host.

description: RPM SQ tumor transplanted into intact host.
DOI: 10.6084/m9.figshare.26400079.v1
title: RPM SQ tumor associated mIF files. Transplanted into intact host.

description: RPM SQ tumor transplanted into intact host.
DOI: 10.48597/e6gx-54ck
title: VOC (aromatics) at Dübendorf

description: Measurement of VOC (aromatics) at Dübendorf
DOI: 10.48597/vgv5-8nmy
title: Measurement of VOC (aromatics) at Dübendorf

description: Measurement of VOC (aromatics) at Dübendorf
DOI: 10.48597/rux6-7pbu
title: Measurement of VOC (aromatics) at Dübendorf

description: Measurement of VOC (aromatics) at Dübendorf
DOI: 10.5281/zenodo.13127821
title: Data Supplement for: "Gradient dynamics model for drops of volatile liquid on a porous substrate"

description: This dataset contains supplementary data for the following preprint:

Hartmann, S. & Thiele, U.Gradient dynamics model for drops of volatile liquid on a porous substrate.(submitted 2024)

We provide the data and sources necessary to generate all figures in the paper.

The figures are built either with LaTeX/TikZ (Figure 1) or Python/Matplotlib (all other figures).Each subfolder contains the full source code and data for one figure each.
DOI: 10.5281/zenodo.13127822
title: Data Supplement for: "Gradient dynamics model for drops of volatile liquid on a porous substrate"

description: This dataset contains supplementary data for the following preprint:

Hartmann, S. & Thiele, U.Gradient dynamics model for drops of volatile liquid on a porous substrate.(submitted 2024)

We provide the data and sources necessary to generate all figures in the paper.

The figures are built either with LaTeX/TikZ (Figure 1) or Python/Matplotlib (all other figures).Each subfolder contains the full source code and data for one figure each.
DOI: 10.5281/zenodo.13127738
title: Annealing rate as a crucial parameter controlling the photoelectrochemical properties of AuCu mosaic core-shell  nanoparticles

description: The following dataset contains research data that is the basis of the research article:

"Annealing rate as a crucial parameter controlling the photoelectrochemical properties of AuCu mosaic core-shell  nanoparticles"

Contents of the package are the following:

a) Linear voltammetry carried out in 0.1 M NaOH for 1F-AuCuTiND, 1F-TiND, 1S-AuCuTiND, 1S-TiND, 4F-AuCuTiND, 4S-AuCuTiND

b) Electrochemical impedance spectroscopy measurement for 1F-AuCuTiND, 1F-TiND, 1S-AuCuTiND, 1S-TiND

c) Experimental results of UV-vis absorbance for 1F-AuCuTiND, 1S-AuCuTiND, 4F-AuCuTiND, 4S-AuCuTiND
DOI: 10.5281/zenodo.13127739
title: Annealing rate as a crucial parameter controlling the photoelectrochemical properties of AuCu mosaic core-shell  nanoparticles

description: The following dataset contains research data that is the basis of the research article:

"Annealing rate as a crucial parameter controlling the photoelectrochemical properties of AuCu mosaic core-shell  nanoparticles"

Contents of the package are the following:

a) Linear voltammetry carried out in 0.1 M NaOH for 1F-AuCuTiND, 1F-TiND, 1S-AuCuTiND, 1S-TiND, 4F-AuCuTiND, 4S-AuCuTiND

b) Electrochemical impedance spectroscopy measurement for 1F-AuCuTiND, 1F-TiND, 1S-AuCuTiND, 1S-TiND

c) Experimental results of UV-vis absorbance for 1F-AuCuTiND, 1S-AuCuTiND, 4F-AuCuTiND, 4S-AuCuTiND
DOI: 10.26300/2vre-m903
title: Data documentation for "Dual Disparity in Accountable Care Organization Attribution among Medicare Beneficiaries: A Cross-sectional Study"
DOI: 10.6084/m9.figshare.26400172
title: RPM Ascl1 KO SQ tumor associated mIF files. Transplanted into castrated host.

description: RPM Ascl1 KO subQ tumors in castrated hosts (n = 2 biologically independent tumors).
DOI: 10.3886/e180482v1-128561
title: The U.S. COVID-19 County Policy Database

description: It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. Yet there has been limited work to systematically evaluate the substantial variation in local COVID-19-related policies in the U.S. The objective of the U.S. COVID-19 County Policy (UCCP) Database is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. The current data upload represents the first wave of data collection, which includes data on over 20 policies gathered across 171 counties in 7 states during January-March 2021. These include county-level COVID-19-related policies within 3 policy domains that are likely to affect a variety of health outcomes: (1) containment/closure, (2) economic support, and (3) public health. In ongoing work, we are conducting retrospective longitudinal weekly data collection for the period 2020-2021 from a larger swath of 300+ U.S. counties in all 50 states and Washington D.C., and the current database will be updated with new data as it becomes available. <br>
description: N/A
description: Response Rates: N/A
description: Presence of Common Scales: N/A
description: N/A
description: 171 counties in 7 states (see above geographic coverage)<br>. Smallest Geographic Unit: Counties
description: other; record abstracts; In January-March 2021, we collected cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health.
DOI: 10.3886/e180482v1-131064
title: The U.S. COVID-19 County Policy Database

description: It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. Yet there has been limited work to systematically evaluate the substantial variation in local COVID-19-related policies in the U.S. The objective of the U.S. COVID-19 County Policy (UCCP) Database is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. The current data upload represents the first wave of data collection, which includes data on over 20 policies gathered across 171 counties in 7 states during January-March 2021. These include county-level COVID-19-related policies within 3 policy domains that are likely to affect a variety of health outcomes: (1) containment/closure, (2) economic support, and (3) public health. In ongoing work, we are conducting retrospective longitudinal weekly data collection for the period 2020-2021 from a larger swath of 300+ U.S. counties in all 50 states and Washington D.C., and the current database will be updated with new data as it becomes available. <br>
description: N/A
description: Response Rates: N/A
description: Presence of Common Scales: N/A
description: N/A
description: 171 counties in 7 states (see above geographic coverage)<br>. Smallest Geographic Unit: Counties
description: other; record abstracts; In January-March 2021, we collected cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health.
DOI: 10.3886/e180482v2
title: The U.S. COVID-19 County Policy Database

description: It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. Yet there has been limited work to systematically evaluate the substantial variation in local COVID-19-related policies in the U.S. The objective of the U.S. COVID-19 County Policy (UCCP) Database is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. The current data upload represents the first wave of data collection, which includes data on over 20 policies gathered across 171 counties in 7 states during January-March 2021. These include county-level COVID-19-related policies within 3 policy domains that are likely to affect a variety of health outcomes: (1) containment/closure, (2) economic support, and (3) public health. In ongoing work, we are conducting retrospective longitudinal weekly data collection for the period 2020-2021 from a larger swath of 300+ U.S. counties in all 50 states and Washington D.C. The current database will be updated with new data as it becomes available, in late 2023 or early 2024.<br><br>Researchers who use this database for their studies should acknowledge the funders below in all publications.
description: N/A
description: Response Rates: N/A
description: Presence of Common Scales: N/A
description: N/A
description: 171 counties in 7 states (see above geographic coverage)<br>. Smallest Geographic Unit: Counties
description: other; record abstracts; In January-March 2021, we collected cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health.
DOI: 10.3886/e180482v1
title: The U.S. COVID-19 County Policy Database

description: It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. Yet there has been limited work to systematically evaluate the substantial variation in local COVID-19-related policies in the U.S. The objective of the U.S. COVID-19 County Policy (UCCP) Database is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. The current data upload represents the first wave of data collection, which includes data on over 20 policies gathered across 171 counties in 7 states during January-March 2021. These include county-level COVID-19-related policies within 3 policy domains that are likely to affect a variety of health outcomes: (1) containment/closure, (2) economic support, and (3) public health. In ongoing work, we are conducting retrospective longitudinal weekly data collection for the period 2020-2021 from a larger swath of 300+ U.S. counties in all 50 states and Washington D.C., and the current database will be updated with new data as it becomes available. <br>
description: N/A
description: Response Rates: N/A
description: Presence of Common Scales: N/A
description: N/A
description: 171 counties in 7 states (see above geographic coverage)<br>. Smallest Geographic Unit: Counties
description: other; record abstracts; In January-March 2021, we collected cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health.
DOI: 10.3886/e180482v3
title: The U.S. COVID-19 County Policy Database (Preliminary)

description: Please note that an updated version of this data set with additional waves of policy data for a larger set of counties has now been released and is available at ICPSR 39109: https://doi.org/10.3886/ICPSR39109.v1. The description of this preliminary data set follows:<br><br>It is increasingly recognized that policies have
played a role in both alleviating and exacerbating the health and economic
consequences of the COVID-19 pandemic. Yet there has been limited work to
systematically evaluate the substantial variation in local COVID-19-related
policies in the U.S. The
objective of the U.S. COVID-19 County Policy (UCCP) Database is to systematically
gather, characterize, and assess variation in U.S. county-level
COVID-19-related policies. The current data upload represents the first wave of data collection, which includes data on over 20 policies gathered across 171 counties in 7 states during January-March 2021. These include county-level
COVID-19-related policies within 3 policy domains that are likely to affect a
variety of health outcomes: (1) containment/closure, (2) economic support, and
(3) public health. In ongoing work, we are
conducting retrospective longitudinal weekly data collection for the period
2020-2021 from a larger swath of 300+ U.S. counties in all 50 states and Washington
D.C. The current database will be updated with new data
as it becomes available, in late 2023 or early 2024.<br><br>Researchers who use this database for their studies should acknowledge the funders below in all publications.
description: N/A
description: Response Rates: N/A
description: Presence of Common Scales: N/A
description: N/A
description: 171 counties in 7 states (see above geographic coverage)<br>. Smallest Geographic Unit: Counties
description: other; record abstracts;  In January-March 2021, we collected cross-sectional data from government and
media websites for 171 counties in
7 states on 22 county-level COVID-19-related policies within 3 policy domains
that are likely to affect health: (1) containment/closure, (2) economic
support, and (3) public health.
DOI: 10.6084/m9.figshare.26398525
title: RPM_intact_OT_measurements.csv

description: RPM Ascl1 WT orthotopic tumors in intact (sham) hosts.
DOI: 10.6084/m9.figshare.26398525.v1
title: RPM_intact_OT_measurements.csv

description: RPM Ascl1 WT orthotopic tumors in intact (sham) hosts.
DOI: 10.6084/m9.figshare.26398549
title: RPMAKO_castrate_OT_measurements.csv

description: RPM Ascl1 KO orthotopic tumors in castrated hosts.
DOI: 10.6084/m9.figshare.26398552.v1
title: RPMAKO_intact_OT_measurements.csv

description: RPM Ascl1 KO orthotopic tumors in intact (sham) hosts.
DOI: 10.6084/m9.figshare.26398510
title: RPM_castrate_OT_measurements.csv

description: RPM Ascl1 WT orthotopic tumors in castrated hosts.
DOI: 10.6084/m9.figshare.26398549.v1
title: RPMAKO_castrate_OT_measurements.csv

description: RPM Ascl1 KO orthotopic tumors in castrated hosts.
DOI: 10.6084/m9.figshare.26398552
title: RPMAKO_intact_OT_measurements.csv

description: RPM Ascl1 KO orthotopic tumors in intact (sham) hosts.