cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.p7cjhx
title: Occurrence Download

description: A dataset containing 973 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Spectacled bear database for Peru"
 ]
}

 The dataset includes 973 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000169-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5pqzjr
title: Occurrence Download

description: A dataset containing 310 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Taraxacum commixtum G.E.Haglund",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 310 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079702-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xnjwuz
title: Occurrence Download

description: A dataset containing 175 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "HasCoordinate is true",
 "TaxonKey is Scinax sugillatus (Duellman, 1973)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 175 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034782-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f0ezkm
title: Occurrence Download

description: A dataset containing 78126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((3.86719 55.37911,81.21094 55.37911,81.21094 70.84467,3.86719 70.84467,3.86719 55.37911))",
 "HasCoordinate is true",
 "TaxonKey is Cantharellales",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 78126 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015976-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4pzura
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cryptanthus santosii Leme & E.H.Souza"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0154486-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jyy24a
title: Occurrence Download

description: A dataset containing 42552 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "OccurrenceStatus is Present",
 "TaxonKey is Streptopelia turtur (Linnaeus, 1758)"
 ]
}

 The dataset includes 42552 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0230072-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yr296s
title: Occurrence Download

description: A dataset containing 143 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Stilpnia meyerdeschauenseei (Schulenberg & Binford, 1985)"
 ]
}

 The dataset includes 143 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010322-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dno1wd
title: Occurrence Download

description: A dataset containing 128 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "TaxonKey is Centaurea amblensis Graells",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 128 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015988-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.232pau
title: Occurrence Download

description: A dataset containing 5418 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corallorhiza striata Lindl."
 ]
}

 The dataset includes 5418 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0154485-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e9k5kb
title: Occurrence Download

description: A dataset listing the 58320 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fabaceae"
 ]
}

 The dataset's 58320 records were derived from 2678 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015978-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ishfx6
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leucactinia bracteata (S.Watson) Rydb."
 ]
}

 The dataset includes 56 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011092-160311141623029/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2xgnaf
title: Occurrence Download

description: A dataset containing 406752 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is one of (India, China, Bangladesh)",
 "Geometry POLYGON((87.05514 21.28494,90.31713 21.49027,92.94644 20.20584,94.01931 21.85293,95.03933 23.09197,96.30865 24.99595,97.98596 26.49193,98.54507 28.68302,96.94331 29.92211,94.96378 30.85899,91.27671 30.97988,87.63497 31.25851,82.08926 30.92607,81.77193 30.23097,83.63057 29.00698,84.7393 26.36693,84.81971 25.0321,84.98053 23.82593,86.05804 22.37853,87.05514 21.28494))",
 "HasCoordinate is true",
 "IucnRedListCategory is LC",
 "Month is February"
 ]
}

 The dataset includes 406752 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004471-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uu48cu
title: Occurrence Download

description: A dataset containing 297 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ciccaba nigrolineata P.L.Sclater, 1859"
 ]
}

 The dataset includes 297 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012131-240216155721649/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uxdc2s
title: Occurrence Download

description: A dataset containing 9264078 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Turdus merula Linnaeus, 1758"
 ]
}

 The dataset includes 9264078 records from 4968 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004680-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e9qpr3
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dactylorhiza kerryensis (Wilmott) P.F.Hunt & Summerh.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 34 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010764-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/yrjp3bg42y.1
title: Gut microbiota composition positively correlates with sports performance in Competitive non-professional female and male runners

description: Abstract: There is still a pressing need for further investigation to bridge the gap in understanding the differences in gut microbiota composition between female runners and their male counterparts. We aimed to determine the gut microbiota composition in competitive non-professional female and male runners; and to correlate the gut bacteria to performance. Our study included 40 subjects, of which 22 were runners (13 males and nine females) and 18 control subjects (9 males and nine females, representing the general population who perform light physical activity with a weekly running volume of ≤5 km per week). Fecal specimens were collected and analyzed for taxonomic profiling to compare species' relative abundances between males and females based on the results of 16SrRNA analysis. Bacterial alpha and beta diversity were assessed to determine the differences in microbial composition between runners and controls, and between sexes. Each participant underwent a maximal oxygen consumption test and a time-to-exhaustion test at 85% of the measured VO2max. Blood lactate was collected every 5 minutes during the tests. Bacterial alpha diversity showed a significant difference (P=0.04) between runners and controls. Taxonomic analysis of gut microbiota composition showed a lower Enterobacteriaceae abundance and a higher Methanosphaera abundance in runners compared with the control group. Ten different bacteria (Methanosphaera, Mitsuokella, Prevotellaceae, Megamonas, Rothia, Oscillospira, Bacteroides, Odoribacter, Blautia massiliensis, Butyricicoccus_ pullicaecorum) were positively correlated with exercise (Vo2max, lactate blood levels, time to exhaustion, and weekly training volume). We found no significant differences in the gut microbiota composition between male and female runners. Gut microbiota composition positively correlates with sports performance in competitive non-professional female and male runners, and female runners resemble similar gut microbiome diversity to male runners.
DOI: 10.5281/zenodo.14008085
title: Equilibrium Dynamics Shape Diversity Patterns Across Terrestrial Tetrapod Clades

description: This repository contains scripts and documentation organized into folders, each designated for specific analyses conducted in this study. Below is an outline of the folder structure and contents. For setup and usage details, please refer to this README.

1. Species Presence and Absence per Grid Cell (PAM folder)



Contains geographic data on species presence (1) or absence for each grid cell, separated by tetrapod group: amphibians (PAM_amphibians.rds), birds (PAM_birds.rds), mammals (PAM_mammals.rds), squamates (PAM_squamata.rds), and testudines & crocodiles (PAM_testcroc.rds).

Latitude and longitude coordinates are also provided.


2. Environmental Variables (environmental_data folder)



Includes environmental variables for each grid cell (environmental_data.rds), with data on temperature (°C), precipitation (mm), and net primary productivity (NPP).

Also contains grid cell IDs and latitude/longitude coordinates.


3. Evolutionary Rates Across Species and Grid Cells (evol_rates_merged folder)



Contains evolutionary rate data, including DR, BAMM, and MiSSE speciation estimates for each species and its corresponding grid cells.

Species tip age estimates are also provided.


4. Identified Clades Using Laplacian Spectrum Approach (laplacian_clades folder)



Includes files for 129 tetrapod clades identified via the Laplacian spectrum approach, saved in .json format.

Each file lists the clade ID and the corresponding species within that clade, separated by tetrapod group.


5. Phylogenies



This folder holds phylogenies for each tetrapod group used in the study.


6. Grid Cell Network



Contains equal-area grid cells at 1° x 1° resolution (GriMap100_clean*), used as spatial units in the analyses.


7. Path Analysis Example (path_analysis_example folder)



Contains example R code (path_analysis_clades.R) illustrating path models performed for each tetrapod clade.

Example uses mammalian clades; replace data to apply to other clades.


8. Path Analysis Outputs (path_analysis_output folder)



Provides outputs from path analyses conducted for each clade within each tetrapod group.

The file path_analysis_clades.csv consolidates all path outputs, identifying each clade’s physiology (endotherms or ectotherms), climate origin (warm or cool), and additional data such as clade richness and range size.


9. Comparing Effects by Clade Physiology and Climate Origin (clade_characteristics folder)



Contains R code (clades_characteristics.R) for replicating the analyses shown in Figures 3 and 4 of the main text.
DOI: 10.5281/zenodo.14008141
title: Supplementary Data and Code for 'Comprehensive Evaluation of MACE on Aluminium Alloys'

description: This contains a raw dump of the code and data used in the publication of Comprehensive Evaluation of MACE on Aluminium Alloys. As such it is not yet ready for production use. If you wish to reproduce the results it is highly recommended you contact the author who will be very happy to help get you set up. 

 

In the main code_data directory there are two subdirectories:

data/ 

Which contains the OQMD-dump data used to supply information on basic bulk structures. See the OQMD.LICENSE file for information on the OQMD 

evalpot/ 

Which contains a snapshot of an internal git repository used to produce the results. The installation is not yet ready for a general public and some work may be needed to get it work for your machine. See evalpot/requirements_snapshot.txt for the modules installed via pip at time of code use. (Not all will be needed). 

You may install the code by running; $pip install . 

The main results are run by two jupyter notebooks: 

compute_AllTests.ipynb which runs all the benchmarks

and 

 plot_AllTests.ipynb which plots all the results. 

You will need to adjust some of the file paths in the first few cells to adapt to your machine.
DOI: 10.5281/zenodo.14008142
title: Supplementary Data and Code for 'Comprehensive Evaluation of MACE on Aluminium Alloys'

description: This contains a raw dump of the code and data used in the publication of Comprehensive Evaluation of MACE on Aluminium Alloys. As such it is not yet ready for production use. If you wish to reproduce the results it is highly recommended you contact the author who will be very happy to help get you set up. 

 

In the main code_data directory there are two subdirectories:

data/ 

Which contains the OQMD-dump data used to supply information on basic bulk structures. See the OQMD.LICENSE file for information on the OQMD 

evalpot/ 

Which contains a snapshot of an internal git repository used to produce the results. The installation is not yet ready for a general public and some work may be needed to get it work for your machine. See evalpot/requirements_snapshot.txt for the modules installed via pip at time of code use. (Not all will be needed). 

You may install the code by running; $pip install . 

The main results are run by two jupyter notebooks: 

compute_AllTests.ipynb which runs all the benchmarks

and 

 plot_AllTests.ipynb which plots all the results. 

You will need to adjust some of the file paths in the first few cells to adapt to your machine.
DOI: 10.15468/dl.dvnu93
title: Occurrence Download

description: A dataset containing 147 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dactylorhiza occidentalis (Pugsley) P.Delforge",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 147 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010765-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/p95yykt4mv.1
title: Burie horizons

description: The data refer to a soil profile with buried horizon of the metropolitan region of Porto Alegre, Rio Grande do Sul, Brazil.
DOI: 10.17632/nx6whv5dvr.1
title: Financial Inclusion of the Informal Sector of Marginalized Counties in Kenya

description: The informal sector in marginalized counties of Kenya faces significant barriers to accessing financial services, despite the critical role of financial inclusion in economic growth and advancements in financial technology. This research aims to investigate the extent of financial inclusion in these regions, focusing specifically on the informal sector. Based on the FinAcess Survey Report (2021), a purposive sampling method was used to select nine counties (Turkana, Mandera, Wajir, Marsabit, Garissa, Samburu, Tana River, Isiolo, and West Pokot) where financial inclusion rates are below 70%. A stratified random sampling technique was then applied to gather a sample of 320 respondents. Data were collected using structured questionnaires and analyzed with a probit model. The target population for this study comprised various small businesses operating within the informal sector, commonly referred to as the Jua Kali sector, in the counties of Samburu, Narok, Turkana, Garissa, and West Pokot. The businesses included in this population were primarily engaged in activities such as selling secondhand clothing, operating food canteens, managing grocery stores, and running small kiosks. Participants were selected based on specific inclusion criteria: they had to be available and willing to participate in the study, have an annual turnover between KShs 500,000 and KShs 2 million, and operate as sole proprietors or employ fewer than two workers on a weekly basis, depending on sales. Additionally, participants did not receive a formal salary. Respondents were required to be at least 18 years of age, ensuring that they held national identity cards, which are necessary for opening bank accounts and conducting transactions via mobile services. This age criterion also aligns with the parameters of financial inclusion, which encompass access to banking and mobile services. To gather qualitative data, semi-structured interviews were conducted with key stakeholders, including informal sector entrepreneurs, local financial service providers, and government officials. These interviews aimed to explore participants' experiences, challenges, and perceptions related to financial inclusion. Throughout the research process, the confidentiality and anonymity of all respondents were strictly maintained to uphold ethical standards.
DOI: 10.5281/zenodo.1205138
title: Satellite Sensor Relative Spectral Response Data

description: Satellite Spectral Response functions for a number of imaging sensors. Currently supports:


	Himawari-8 AHI
	GOES-16 ABI
	NOAA AVHRR/1, AVHRR/2, AVHRR/3
	Metop AVHRR/3
	TIROS-N AVHRR/1
	Envisat AATSR
	Sentinel-3A SLSTR
	Sentinel-3A OLCI
	Meteosat SEVIRI
	Terra/Aqua MODIS
	Suomi-NPP VIIRS
	JPSS-1 (NOAA-20) VIIRS
	Sentinel-2A MSI
	Sentinel-2B MSI
	Landsat-8 OLI
description: The data are derived with Pyspectral from the original Agency specific Spectral response data using Pyspectral
DOI: 10.5281/zenodo.1409621
title: Satellite Sensor Relative Spectral Response Data

description: Satellite Spectral Response functions for a number of imaging sensors. Currently supports:


	Himawari-8 AHI
	GOES-16 ABI
	GOES-17 ABI
	NOAA AVHRR/1, AVHRR/2, AVHRR/3
	Metop AVHRR/3
	TIROS-N AVHRR/1
	Envisat AATSR
	Sentinel-3A SLSTR
	Sentinel-3A OLCI
	Meteosat SEVIRI
	Terra/Aqua MODIS
	Suomi-NPP VIIRS
	JPSS-1 (NOAA-20) VIIRS
	Sentinel-2A MSI
	Sentinel-2B MSI
	Landsat-8 OLI
description: The data are derived with Pyspectral from the original Agency specific Spectral response data using Pyspectral
DOI: 10.5281/zenodo.3786824
title: Satellite Sensor Relative Spectral Response data

description: Satellite Spectral Response functions for a number of imaging sensors. Currently supports: Himawari-8 AHI GOES-16 ABI GOES-17 ABI NOAA AVHRR/1, AVHRR/2, AVHRR/3 Metop AVHRR/3 TIROS-N AVHRR/1 Envisat AATSR Sentinel-3A SLSTR Sentinel-3A OLCI - mean rsr Meteosat SEVIRI Terra/Aqua MODIS Suomi-NPP VIIRS JPSS-1 (NOAA-20) VIIRS Sentinel-2A MSI Sentinel-2B MSI Landsat-8 OLI HY-1C COCTS Metop-SG-A1 MetImage - multiple detectors Sentinel-3B OLCI - mean rsr FY-3D MERSI-2 FY-4A AGRI FY-3B VIRR FY-3C VIRR GEO-KOMPSAT-2A AMI Sentinel-3B SLSTR Meteosat-12 FCI
description: The data are derived with Pyspectral from the original Agency specific Spectral response data using Pyspectral
DOI: 10.5281/zenodo.889206
title: Satellite Sensor Relative Spectral Response Data

description: Satellite Spectral Response functions for a number of imaging sensors. Currently supports:


	Himawari AHI
	GOES-R ABI
	NOAA AVHRR/1, AVHRR/2, AVHRR/3
	Metop AVHRR/3
	TIROS-N AVHRR/1
	Envisat AATSR
	Sentinel-3A SLSTR
	Sentinel-3A OLCI
	Meteosat SEVIRI
	Terra/Aqua MODIS
	Suomi-NPP VIIRS
description: The data are derived with Pyspectral from the original Agency specific Spectral response data using Pyspectral
DOI: 10.5281/zenodo.1146757
title: Satellite Sensor Relative Spectral Response Data

description: Satellite Spectral Response functions for a number of imaging sensors. Currently supports:


	Himawari-8 AHI
	GOES-16 ABI
	NOAA AVHRR/1, AVHRR/2, AVHRR/3
	Metop AVHRR/3
	TIROS-N AVHRR/1
	Envisat AATSR
	Sentinel-3A SLSTR
	Sentinel-3A OLCI
	Meteosat SEVIRI
	Terra/Aqua MODIS
	Suomi-NPP VIIRS
	JPSS-1 (NOAA-20) VIIRS
	Sentinel-2A MSI
	Sentinel-2B MSI
	Landsat-8 OLI
description: The data are derived with Pyspectral from the original Agency specific Spectral response data using Pyspectral
DOI: 10.5281/zenodo.2545299
title: Satellite Sensor Relative Spectral Response data

description: Satellite Spectral Response functions for a number of imaging sensors. Currently supports: Himawari-8 AHI GOES-16 ABI GOES-17 ABI NOAA AVHRR/1, AVHRR/2, AVHRR/3 Metop AVHRR/3 TIROS-N AVHRR/1 Envisat AATSR Sentinel-3A SLSTR Sentinel-3A OLCI Meteosat SEVIRI Terra/Aqua MODIS Suomi-NPP VIIRS JPSS-1 (NOAA-20) VIIRS Sentinel-2A MSI Sentinel-2B MSI Landsat-8 OLI HY-1C COCTS FY-3D MERSI-2
description: The data are derived with Pyspectral from the original Agency specific Spectral response data using Pyspectral
DOI: 10.5281/zenodo.3667766
title: Satellite Sensor Relative Spectral Response data

description: Satellite Spectral Response functions for a number of imaging sensors. Currently supports: Himawari-8 AHI GOES-16 ABI GOES-17 ABI NOAA AVHRR/1, AVHRR/2, AVHRR/3 Metop AVHRR/3 TIROS-N AVHRR/1 Envisat AATSR Sentinel-3A SLSTR Sentinel-3A OLCI - mean rsr Meteosat SEVIRI Terra/Aqua MODIS Suomi-NPP VIIRS JPSS-1 (NOAA-20) VIIRS Sentinel-2A MSI Sentinel-2B MSI Landsat-8 OLI HY-1C COCTS Metop-SG-A1 MetImage - multiple detectors Sentinel-3B OLCI - mean rsr FY-3D MERSI-2 FY-4A AGRI FY-3B VIRR FY-3C VIRR GEO-KOMPSAT-2A AMI Sentinel-3B SLSTR
description: The data are derived with Pyspectral from the original Agency specific Spectral response data using Pyspectral
DOI: 10.5281/zenodo.1012412
title: Satellite Sensor Relative Spectral Response Data

description: Satellite Spectral Response functions for a number of imaging sensors. Currently supports:


	Himawari-8 AHI
	GOES-16 ABI
	NOAA AVHRR/1, AVHRR/2, AVHRR/3
	Metop AVHRR/3
	TIROS-N AVHRR/1
	Envisat AATSR
	Sentinel-3A SLSTR
	Sentinel-3A OLCI
	Meteosat SEVIRI
	Terra/Aqua MODIS
	Suomi-NPP VIIRS
	JPSS-1 (NOAA-20) VIIRS
description: The data are derived with Pyspectral from the original Agency specific Spectral response data using Pyspectral