cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18355477
title: Supporting data for: HGTScanner: Detecting horizontal gene transfer and mitochondrial plastid DNA (MTPT) at the fine scale using whole organelle genomes

description: Appendix S4 for HGTScanner: Detecting horizontal gene transfer and mitochondrial plastid DNA (MTPT) at the fine scale using whole organelle genomes

Input and output files of HGTScanner analyses performed in the current study. This included mitochondrial plastid DNA (MTPT) characterization in Mannagettaea hummelii, Aeginetia indica, Alectra sessiliflora, and Rehmannia glutinosa; MTPT and HGT characterization in Amborella trichopoda; and assessment of moss and algae donors of Amborella HGTs using concatenated sequences of A-D and M genomes in IQ-TREE.
DOI: 10.15468/dl.axgepr
title: Occurrence Download

description: A dataset containing 3483 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gopherus berlandieri",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation)"
 ]
}

 The dataset includes 3483 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008119-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dgx37t
title: Occurrence Download

description: A dataset containing 304 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hansenia weberbaueriana",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 304 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008121-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kzyzvt
title: Occurrence Download

description: A dataset containing 39247 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tichodroma muraria",
 "Country is one of (Albania, Austria, Bosnia and Herzegovina, Belgium, Bulgaria, Belarus, Switzerland, Cyprus, Czechia, Germany, Denmark, Estonia, Spain, Finland, France, United Kingdom of Great Britain and Northern Ireland, Greece, Croatia, Hungary, Ireland, Italy, Lithuania, Luxembourg, Latvia, Moldova, Republic of, Montenegro, North Macedonia, Malta, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Sweden, Slovenia, Slovakia, Türkiye, Ukraine, Kosovo)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 39247 records from 392 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008122-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mmd366
title: Occurrence Download

description: A dataset containing 19238 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Selenophorus Dejean, 1829"
 ]
}

 The dataset includes 19238 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016164-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hstz88
title: Occurrence Download

description: A dataset containing 4035 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Filatima Busck, 1939"
 ]
}

 The dataset includes 4035 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016165-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fu5w5a
title: Occurrence Download

description: A dataset containing 272 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Blepharipappus scaber Hook.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 272 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007294-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15548291
title: GTDB r226 Mash Database (UNOFFICIAL MIRROR)

description: This is an UNOFFICIAL host for the GTDB mash sketch based on GTDB r226

Intended use of this file is to include in the VEBA database for quicker GTDB-Tk analysis. 

Created by running the following command using GTDB-Tk v2.4.1 on the S1 sample from Zenodo:7946802: 

gtdbtk classify_wf --genome_dir veba_output/binning/prokaryotic/S1/output/genomes/  --out_dir test_output -x fa --cpus 1 --mash_db ./gtdb_r226.msh

Source Files: 

gtdbtk_r226_data.tar.gz

RELEASE_NOTES.txt



Release 226.0:
--------------

GTDB release R10-RS226 comprises 732,475 genomes organised into 143,614 species clusters.
Additional statistics for this release are available on the GTDB Statistics page.

Release notes:
--------------

- Post-curation cycle, we identified updated spelling for 1 taxon and a valid name for a placeholder:
	g__Prometheoarchaeum (updated name: Promethearchaeum)
	f__MK-D1 (updated name: Promethearchaeaceae)
  Note that the LPSN linkouts point to the correct updated names. We encourage users to use 
  the updated names as these will appear in the next release.

- QC criteria for GTDB was modified to consider CheckM v1 and v2 completeness
  and contamination estimates. In order to pass QC, a genome must have completeness
  >=50%, contamination <5%, and quality (completeness - 5*contamination)
  >=50% using both the CheckM v1 and v2 estimates. The exception is that a contig
  comprised of <10 contigs passes QC if these criteria are meet be either CheckM v1 or v2.
  
- Mash is no longer used as a prefilter for establishing GTDB species clusters
  as this was found to be unnecessary with the prefiltering provided internally
  by skani (Shaw et al., Nat Methods, 2023).
 
- The 20% most heterogeneous sites were removed from the archaeal MSA using alignment_pruner.pl
  (https://github.com/novigit/broCode/blob/master/alignment_pruner.pl).

- The GTDB taxonomy tree now provides links to Sandpiper (https://sandpiper.qut.edu.au) results
  which provide information about the geographic and environmental distribution of a taxon.
  
- We thank Jan Mares for his assistance in curating the class Cyanobacteriia, 
  Peter Golyshin for bringing Ferroplasma acidiphilum strain Y (GCF_002078355.1) to our attention,
  and Brian Kemish for providing IT support to the project.


 

If you have found this useful, please cite the original publications: 



Chaumeil PA, et al. 2022. GTDB-Tk v2: memory friendly classification with the Genome Taxonomy Database. Bioinformatics, btac672.

Parks, D.H., et al. (2021). GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. Nucleic Acids Research, 50: D785–D794.
DOI: 10.5281/zenodo.15548292
title: GTDB r226 Mash Database (UNOFFICIAL MIRROR)

description: This is an UNOFFICIAL host for the GTDB mash sketch based on GTDB r226

Intended use of this file is to include in the VEBA database for quicker GTDB-Tk analysis. 

Created by running the following command using GTDB-Tk v2.4.1 on the S1 sample from Zenodo:7946802: 

gtdbtk classify_wf --genome_dir veba_output/binning/prokaryotic/S1/output/genomes/  --out_dir test_output -x fa --cpus 1 --mash_db ./gtdb_r226.msh

Source Files: 

gtdbtk_r226_data.tar.gz

RELEASE_NOTES.txt



Release 226.0:
--------------

GTDB release R10-RS226 comprises 732,475 genomes organised into 143,614 species clusters.
Additional statistics for this release are available on the GTDB Statistics page.

Release notes:
--------------

- Post-curation cycle, we identified updated spelling for 1 taxon and a valid name for a placeholder:
	g__Prometheoarchaeum (updated name: Promethearchaeum)
	f__MK-D1 (updated name: Promethearchaeaceae)
  Note that the LPSN linkouts point to the correct updated names. We encourage users to use 
  the updated names as these will appear in the next release.

- QC criteria for GTDB was modified to consider CheckM v1 and v2 completeness
  and contamination estimates. In order to pass QC, a genome must have completeness
  >=50%, contamination <5%, and quality (completeness - 5*contamination)
  >=50% using both the CheckM v1 and v2 estimates. The exception is that a contig
  comprised of <10 contigs passes QC if these criteria are meet be either CheckM v1 or v2.
  
- Mash is no longer used as a prefilter for establishing GTDB species clusters
  as this was found to be unnecessary with the prefiltering provided internally
  by skani (Shaw et al., Nat Methods, 2023).
 
- The 20% most heterogeneous sites were removed from the archaeal MSA using alignment_pruner.pl
  (https://github.com/novigit/broCode/blob/master/alignment_pruner.pl).

- The GTDB taxonomy tree now provides links to Sandpiper (https://sandpiper.qut.edu.au) results
  which provide information about the geographic and environmental distribution of a taxon.
  
- We thank Jan Mares for his assistance in curating the class Cyanobacteriia, 
  Peter Golyshin for bringing Ferroplasma acidiphilum strain Y (GCF_002078355.1) to our attention,
  and Brian Kemish for providing IT support to the project.


 

If you have found this useful, please cite the original publications: 



Chaumeil PA, et al. 2022. GTDB-Tk v2: memory friendly classification with the Genome Taxonomy Database. Bioinformatics, btac672.

Parks, D.H., et al. (2021). GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. Nucleic Acids Research, 50: D785–D794.
DOI: 10.17028/rd.lboro.29126453
title: Supplementary information files for "The Emperor’s old clothes: a critical review of circular fashion in gray literature"

description: Supplementary files for article "The Emperor’s old clothes: a critical review of circular fashion in gray literature"A consensus across industry, academics, and policy-makers holds that a circular fashion system can reduce pollution and waste while producing continued economic growth. Gray literature, understood here as reports published outside of academic journals, has been foundational to describing and promoting circular economy and circular fashion. Yet, this literature is rarely subjected to critical scrutiny, allowing evidence, claims and methods to go unexamined. This review aims to understand how value and the market are conceptualized in a circular fashion system, and what are the implications of this. The study employs a problematizing review of 20 gray literature documents, including a key text of circular fashion: the Ellen MacArthur Foundation’s 2017 report A New Textiles Economy: Redesigning Fashion’s Future. Textual analysis is used to identify assumptions, inferences and problem framings in the texts. These are evaluated against academic understandings, demonstrating that core concepts of the circular fashion proposal are poorly defined and unconnected to existing theory and knowledge. Existing retail practices and consumer marketing messages are central to circular fashion, while the role of the market in setting prices is ignored. A $460 billion error is revealed, refuting the claim that a circular fashion system provides an opportunity for growth. We offer a critical perspective on the role of gray literature and gray publishers in shaping policy-making and, subsequently, academic research programs. We argue that new proposals for sustainable fashion are needed, based on established knowledge and validated models.<br><br>© 2025 Hussain, Kuzmina and Koria, CC BY 4.0
DOI: 10.17028/rd.lboro.29126453.v1
title: Supplementary information files for "The Emperor’s old clothes: a critical review of circular fashion in gray literature"

description: Supplementary files for article "The Emperor’s old clothes: a critical review of circular fashion in gray literature"A consensus across industry, academics, and policy-makers holds that a circular fashion system can reduce pollution and waste while producing continued economic growth. Gray literature, understood here as reports published outside of academic journals, has been foundational to describing and promoting circular economy and circular fashion. Yet, this literature is rarely subjected to critical scrutiny, allowing evidence, claims and methods to go unexamined. This review aims to understand how value and the market are conceptualized in a circular fashion system, and what are the implications of this. The study employs a problematizing review of 20 gray literature documents, including a key text of circular fashion: the Ellen MacArthur Foundation’s 2017 report A New Textiles Economy: Redesigning Fashion’s Future. Textual analysis is used to identify assumptions, inferences and problem framings in the texts. These are evaluated against academic understandings, demonstrating that core concepts of the circular fashion proposal are poorly defined and unconnected to existing theory and knowledge. Existing retail practices and consumer marketing messages are central to circular fashion, while the role of the market in setting prices is ignored. A $460 billion error is revealed, refuting the claim that a circular fashion system provides an opportunity for growth. We offer a critical perspective on the role of gray literature and gray publishers in shaping policy-making and, subsequently, academic research programs. We argue that new proposals for sustainable fashion are needed, based on established knowledge and validated models.<br><br>© 2025 Hussain, Kuzmina and Koria, CC BY 4.0
DOI: 10.25326/2rac-2604
title: biomass burning plume + NO2 - Aerosol study - physical properties - 2019-01-22

description: Publication of the dataset
DOI: 10.25326/tts1-3p38
title: Biomass burning plume + O3 - Aerosol study - physical properties - 2019-01-25

description: Publication of the dataset
DOI: 10.25326/r5nv-ne92
title: BiomassBurning + O3 - Aerosol study - physical properties - 2019-02-01

description: Publication of the dataset
DOI: 10.25326/xpjq-eq74
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-02-11

description: Publication of the dataset
DOI: 10.25326/ft1e-gm81
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-02-25

description: Publication of the dataset
DOI: 10.25326/e0wq-hz26
title: Biomass Burning + None - Aerosol study - physical properties - 2019-03-22

description: Publication of the dataset
DOI: 10.25326/v80e-vs31
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-03-25

description: Publication of the dataset
DOI: 10.25326/xqn8-3d48
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-04-22

description: Publication of the dataset
DOI: 10.25326/mj2b-qt08
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-04-24

description: Publication of the dataset
DOI: 10.25326/1eqe-1767
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-04-01

description: Publication of the dataset
DOI: 10.25326/vvf1-mp85
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-04-05

description: Publication of the dataset
DOI: 10.25326/hz71-4a26
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-04-11

description: Publication of the dataset
DOI: 10.25326/a5s1-dh54
title: Biomass Burning + O3 - Aerosol study - physical properties - 2019-04-13

description: Publication of the dataset
DOI: 10.5061/dryad.zw3r2286w
title: Susceptibility of fire-bellied toad (B. bombina and B. variegata) tadpoles to predation

description: B. bombina and B. variegata are ecologically distinct taxa that
 nevertheless hybridise in nature wherever their distribution ranges
 adjoin. These data were collected to test the hypothesis that B. variegata
 tadpoles are more susceptible to predation than those of B. bombina. The
 former develop in ephemeral aquatic sites that can be predator-free,
 whereas the latter are found in predator-rich semi-permanent ponds.
 Tadpoles of both taxa were raised under under uniform laboratory
 conditions and their relative predation risk was assessed over a four-week
 period using dragonfly larvae as predators. The tadpoles were reared in
 the presence of chemical predation cues so that they could develop a
 predator-induced phenotype. The data confirm our hypothesis. These results
 suggest that B. variegata traits associated with higher predation risk
 produce barriers to gene flow across the hybrid zone.
description: Data associated with each predation trial includes the trial
 composition (full-sib families of <em>B. bombina</em> and
 <em>B. variegata</em> that were represented), morphological
 measurements of each tadpole, the identity of the first consumed tadpole
 (out of 4, trial ended after the first predation event). Behavioural data
 (time spent by a focal tadpole swimming, feeding or resting) were
 collected from a subset of trials. The archive contains a Perl script
 (plus input and output files) that was used to generate lists of
 pseudo-random trial compositions according to the experimental design (see
 README.txt for details).
description: The structure of each data file is documented in the README.txt
 file.
DOI: 10.5061/dryad.j9kd51c9t
title: Digital coaching strategies to facilitate behavioral change in type 2 diabetes: a systematic review

description: Context: In this systematic review, we focus on the clinical impact of
 digital tools for providing health coaching, education, and facilitating
 behavior in patients with prediabetes or type 2 diabetes. Our approach was
 designed to provide insights for clinicians and health care systems that
 are considering adopting such digital tools. This dataset provides summary
 information related to the systematic review.  Evidence
 Acquisition: We searched the CINAHL, Scopus, and Ovid/MEDLINE databases
 using PRISMA guidelines for studies that reported digital coaching
 strategies for management and prevention of type 2 diabetes published from
 January 2014 to June 2019. Articles were reviewed by 2 independent blinded
 reviewers. Twenty-one articles met inclusion criteria. Evidence
 Synthesis: We found that 20 of 21 studies in our analysis showed
 statistically significant improvements in at least one measure of diabetes
 control including HbA1c, weight loss, fasting blood glucose, and BMI.
 Studies that reported weight loss percentage from baseline at 1 year
 reported values ranging from −3.04% to −8.98%, similar to outcomes with
 traditional coaching in the Diabetes Prevention Program (N = 4).
 Additionally, all studies that included a comparison group of in-person or
 telephone-based coaching showed statistically better or similar outcomes
 in the digital coaching group (N = 5). Conclusions: The evidence reported
 in this systematic review suggests that digital health coaching offers a
 promising strategy for long-term management and prevention of type 2
 diabetes in diverse populations with similar benefits to in-person or
 telephone-based health coaching. We argue that, with the potential to
 treat large numbers of individuals in diverse geographic locations,
 digital coaching offers a promising solution to the rapid increase in
 diabetes prevalence.
description: We searched the CINAHL, Scopus, and Ovid/MEDLINE databases using
 PRISMA guidelines for studies that reported digital coaching strategies
 for management and prevention of type 2 diabetes published from January
 2014 to June 2019. Articles were reviewed by 2 independent blinded
 reviewers. Twenty-one articles met inclusion criteria. We combined results
 and summarized them in an evidence table to clarify the differences
 between coaching components, outcomes, and populations.
DOI: 10.5061/dryad.rjdfn2z8m
title: Potential distribution of seagrass meadows based on MaxEnt model in Chinese coastal waters

description: Seagrass meadows are generally diverse in China and have the same
 essential ecosystem services as elsewhere. However, an evaluation of
 seagrass distribution across China is still lacking, and the magnitude and
 direction of changes in seagrass meadows remains unclear. Our primary
 objective was to provide a nationwide seagrass distribution map, and to
 explore the dynamic changes of seagrass population under global climate
 change. We use simulation studies within the modelling software MaxEnt
 with 58961 occurrence records and 27 marine environmental variables, to
 simulate the potential distribution of seagrasses and calculate the area.
 7 environmental variables were deleted before the modelling processes
 based on a correlation analysis to ensure predicted suitability. The
 predicted area was 790.09 km2, which is much larger than the known
 seagrass distribution in China, and would be increased to 923.62 km2 by
 the year 2100. However, the suitable habitat of almost all seagrass will
 shift northwest in the future. The sum of individual family will
 under-predict the national distribution of seagrass, showed a downward
 trend consistently in the future. Out of all environmental variables, the
 physical ones (e.g. depth, land distance and sea surface temperature) had
 the greatest contribution in predicting seagrass distributions, and
 nutrients (e.g. nitrate, phosphate) ranked among the key influential
 predictors for habitat suitability in our focal area. As this is a ﬁrst
 effort to ﬁll a gap in our understanding of the distribution of seagrass
 in China, further studies are necessary using both modeling and
 biological/ecological approaches.
description: This dataset contains input data for the maxent model, including
 seagrass occurrence data and marine environment data. There are 4
 families, Cymodoceaceae, Hydrocharitaceae, Ruppiaceae, and Zosteraceae,
 with a total of 22 species of seagrasses distributed in Chinese coastal
 waters. Hence, this study focused on the species belonging to these
 families. Seagrass occurrence data were extracted from the Global
 Biodiversity Information Facility (GBIF, 2017) and Ocean Biogeographic
 Information System (OBIS, 2017). 27 abiotic variables related to the
 distribution of seagrasses were chosen as modelling parameters from the
 Global Marine Environment Datasets (GMED), which are the publicly
 available climatic, biological, and geophysical environmental layers
 featuring present, past, and future environmental conditions.