cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12553778
title: Taillardat et al. (2020) - Restoration cost database V5.xlsx from Climate change mitigation potential of wetlands and the cost-effectiveness of their restoration

description: The cost-effective mitigation of climate change through nature-based carbon dioxide removal strategies has gained substantial policy attention. Inland and coastal wetlands (specifically boreal, temperate and tropical peatlands; tundra; floodplains; freshwater marshes; saltmarshes and mangroves) are among the most efficient natural long-term carbon sinks, yet they also release methane (CH<sub>4</sub>) that can offset the carbon they sequester. Here, we conducted a meta-analysis on wetland carbon dynamics to (i) determine the role they play on climate and discuss their suitability for inclusion in greenhouse gas emissions (GHG) mitigation policies; (ii) investigate the cost-effectiveness of wetland restoration for climate change mitigation strategies. Depending on metrics, a wetland can simultaneously be a net carbon sink (i.e. boreal and temperate peatlands net ecosystem carbon budget (NECB) = −28.1 ± 19.13 gC m<sup>−2</sup> y<sup>−1</sup>) but have a net warming effect on climate at the 100 years time-scale (i.e. boreal and temperate peatland sustained global warming potential (SGWP) = 298.2 ± 100.6 gCO<sub>2</sub> eq<sup>−1</sup> m<sup>−2</sup> y<sup>−1</sup>). This ambivalence shows that the choice of metric can lead to misinterpretation on the effect of wetlands on global temperature. Moreover, our review report high heterogeneity and a still limited number of studies that document wetland carbon budgets. In this study, we demonstrate that most coastal and inland wetlands have a net cooling effect as of today. This is explained by the limited CH<sub>4</sub> emissions that undisturbed coastal wetlands produce and the short lifetime of CH<sub>4</sub> in the atmosphere, compared with long-term carbon sequestration for older inland wetlands. Analysis of wetland restoration costs relative to the amount of carbon they can sequester revealed that restoration is more cost-effective in coastal wetlands such as mangroves (US$1800 ton C<sup>−1</sup>) compared with inland wetlands (US$ 4200–49 200 ton C<sup>−1</sup>). For inland wetlands, priority should be given to conservation rather than restoration, while for coastal wetlands, both conservation and restoration may be effective techniques for climate change mitigation.
DOI: 10.6084/m9.figshare.12553763
title: Supplementary data from Acoustic allometry and vocal learning in mammals

description: Raw data used for the preliminary analysis carried out in this study
DOI: 10.6084/m9.figshare.12553763.v1
title: Supplementary data from Acoustic allometry and vocal learning in mammals

description: Raw data used for the preliminary analysis carried out in this study
DOI: 10.6084/m9.figshare.12553658
title: Supplementary data from Comparative analysis of metabolic and transcriptomic features of <i>Nothobranchius furzeri</i>

description: An excel le containing the results of the gene enrichment analysis performed as discussed in the Materials and methods section.
DOI: 10.6084/m9.figshare.12553658.v1
title: Supplementary data from Comparative analysis of metabolic and transcriptomic features of <i>Nothobranchius furzeri</i>

description: An excel le containing the results of the gene enrichment analysis performed as discussed in the Materials and methods section.
DOI: 10.6084/m9.figshare.12553625
title: example C++ code used to parse and analyse the vcf files from Signals interpreted as archaic introgression appear to be driven primarily by faster evolution in Africa

description: Annotated C++ code used to calculate conditioned D using individual chromosome vcf files from the 1000 genomes project and equivalent files containing base counts from each site in the Neanderthal and Denisovan genomes.
DOI: 10.6084/m9.figshare.12553622
title: population averaged D-values for all 6 conditioned D measures from Signals interpreted as archaic introgression appear to be driven primarily by faster evolution in Africa

description: Raw data used to generate Figure 1. Each coloured cell contains the value for D(P1, P2, Neanderthal, chimpanzee), where P1 is the 1000 genome population listed for the row and P2 is the 1000 genome population listed for the column. In each block, the conditioning used is given above and to the left. Thus, cell K9 contains the value for D(TSI, JPT, Neanderthal, chimpanzee), conditioned such that only sites that are homozygous in JPT are included. Each value is the average across all pairs of qualifying individuals. Cells are colour-coded according to the value of D, from dark blue (most positive) through to dark pink (most negative).
DOI: 10.6084/m9.figshare.12553625.v2
title: example C++ code used to parse and analyse the vcf files from Signals interpreted as archaic introgression appear to be driven primarily by faster evolution in Africa

description: Annotated C++ code used to calculate conditioned D using individual chromosome vcf files from the 1000 genomes project and equivalent files containing base counts from each site in the Neanderthal and Denisovan genomes.
DOI: 10.6084/m9.figshare.12553625.v1
title: example C++ code used to parse and analyse the vcf files from Signals interpreted as archaic introgression appear to be driven primarily by accelerated evolution in Africa

description: Annotated C++ code used to calculate conditioned D using individual chromosome vcf files from the 1000 genomes project and equivalent files containing base counts from each site in the Neanderthal and Denisovan genomes.
DOI: 10.6084/m9.figshare.12553622.v2
title: population averaged D-values for all 6 conditioned D measures from Signals interpreted as archaic introgression appear to be driven primarily by faster evolution in Africa

description: Raw data used to generate Figure 1. Each coloured cell contains the value for D(P1, P2, Neanderthal, chimpanzee), where P1 is the 1000 genome population listed for the row and P2 is the 1000 genome population listed for the column. In each block, the conditioning used is given above and to the left. Thus, cell K9 contains the value for D(TSI, JPT, Neanderthal, chimpanzee), conditioned such that only sites that are homozygous in JPT are included. Each value is the average across all pairs of qualifying individuals. Cells are colour-coded according to the value of D, from dark blue (most positive) through to dark pink (most negative).
DOI: 10.6084/m9.figshare.12553622.v1
title: population averaged D-values for all 6 conditioned D measures from Signals interpreted as archaic introgression appear to be driven primarily by accelerated evolution in Africa

description: Raw data used to generate Figure 1. Each coloured cell contains the value for D(P1, P2, Neanderthal, chimpanzee), where P1 is the 1000 genome population listed for the row and P2 is the 1000 genome population listed for the column. In each block, the conditioning used is given above and to the left. Thus, cell K9 contains the value for D(TSI, JPT, Neanderthal, chimpanzee), conditioned such that only sites that are homozygous in JPT are included. Each value is the average across all pairs of qualifying individuals. Cells are colour-coded according to the value of D, from dark blue (most positive) through to dark pink (most negative).
DOI: 10.6084/m9.figshare.12553286
title: Bourgeois_procb_ESM6.xlsx from Weed diversity is driven by complex interplay between multi-scale dispersal and local filtering

description: Arable weeds are key organisms for biodiversity maintenance and ecosystem service provision in agroecosystems. Disentangling the drivers of weed diversity is critical to counteract the global decline of farmland biodiversity. Even if distinct scale-dependent processes were alternatively proposed, no general framework unifying the multi-scale drivers of weed dynamics has yet emerged. Here, we investigate the joint effects of field- and landscape-scale processes on weed assemblages in 444 arable fields. First, field margins sheltered greater weed diversity than field core evidencing their role of biodiversity refugia. Second, community similarity between field core and margin decreased with the distance to margin, highlighting a major role of local dispersal. Third, weed diversity at field margin increased with organic field cover in the landscape, pointing out massive regional dispersal. Fourth, while both local and landscape dispersal explained up to 41% of field core weed diversity, crop type strongly modulated their strength, depicting intense filtering effect by agricultural management. This study sheds a new light on the complex multi-scale interactions shaping weed diversity, field margins playing a key role by strengthening regional dispersal and sustaining local dispersal. Land-sharing strategies improving habitat heterogeneity both locally and regionally should largely promote agroecosystem multifunctionality and sustainability.
DOI: 10.6084/m9.figshare.12553286.v1
title: Bourgeois_procb_ESM6.xlsx from Weed diversity is driven by complex interplay between multi-scale dispersal and local filtering

description: Arable weeds are key organisms for biodiversity maintenance and ecosystem service provision in agroecosystems. Disentangling the drivers of weed diversity is critical to counteract the global decline of farmland biodiversity. Even if distinct scale-dependent processes were alternatively proposed, no general framework unifying the multi-scale drivers of weed dynamics has yet emerged. Here, we investigate the joint effects of field- and landscape-scale processes on weed assemblages in 444 arable fields. First, field margins sheltered greater weed diversity than field core evidencing their role of biodiversity refugia. Second, community similarity between field core and margin decreased with the distance to margin, highlighting a major role of local dispersal. Third, weed diversity at field margin increased with organic field cover in the landscape, pointing out massive regional dispersal. Fourth, while both local and landscape dispersal explained up to 41% of field core weed diversity, crop type strongly modulated their strength, depicting intense filtering effect by agricultural management. This study sheds a new light on the complex multi-scale interactions shaping weed diversity, field margins playing a key role by strengthening regional dispersal and sustaining local dispersal. Land-sharing strategies improving habitat heterogeneity both locally and regionally should largely promote agroecosystem multifunctionality and sustainability.
DOI: 10.6084/m9.figshare.12552983
title: Additional file 2 of Minor surgery in general practice in Ireland- a report of workload and safety

description: Additional file 2.
DOI: 10.6084/m9.figshare.12552983.v1
title: Additional file 2 of Minor surgery in general practice in Ireland- a report of workload and safety

description: Additional file 2.
DOI: 10.6084/m9.figshare.12552953
title: Additional file 3 of Identification of pathogens from native urine samples by MALDI-TOF/TOF tandem mass spectrometry

description: Additional file 3: Excel tables.
DOI: 10.6084/m9.figshare.12552953.v1
title: Additional file 3 of Identification of pathogens from native urine samples by MALDI-TOF/TOF tandem mass spectrometry

description: Additional file 3: Excel tables.
DOI: 10.6084/m9.figshare.12552932
title: Additional file 2 of Pre-stroke adherence to a Mediterranean diet pattern is associated with lower acute ischemic stroke severity: a cross-sectional analysis of a prospective hospital-register study

description: Additional file 2:. Excel spread sheet 1997–2003 (.xls). RECCA2015_DATA_LABELS_2019-07-17_1307 MeDi y NIHSS Febrero 2017 Julio 2019. Dataset supporting the conclusions.
DOI: 10.6084/m9.figshare.12860132
title: bd_BurntEngagment_Maroco et al_PlosOne.rds

description: In this study we modelled possible causes and consequences of student burnout and engagement on academic efficacy and dropout intention in university students. Further we asked, can student engagement protect against the effects of burnout? In total 4,061 university students from Portugal, Brazil, Mozambique, the United Kingdom, the United States of America, Finland, Serbia, and Macao SAR, Taiwan participated in this study. With the data collected we analyzed the influence of Social Support, Coping Strategies, and school/course related variables on student engagement and burnout using structural equation modeling. We also analyzed the effect of student engagement, student burnout, and their interaction, on Academic Performance and Dropout Intention. We found that both student engagement and burnout are good predictors of subjective academic performance and dropout intention. However, student burnout suppresses the effect of student engagement on these variables. This result has strong implications for practitioners and administrators. To prevent student dropout, it is not enough to promote student engagement—additionally, and importantly, levels of student burnout must be kept low. Other variables such as social support and coping strategies are also relevant predictors of student engagement and burnout and should be considered when implementing preventive actions, self-help and guided intervention programs for college students.
DOI: 10.6084/m9.figshare.12552932.v1
title: Additional file 2 of Pre-stroke adherence to a Mediterranean diet pattern is associated with lower acute ischemic stroke severity: a cross-sectional analysis of a prospective hospital-register study

description: Additional file 2:. Excel spread sheet 1997–2003 (.xls). RECCA2015_DATA_LABELS_2019-07-17_1307 MeDi y NIHSS Febrero 2017 Julio 2019. Dataset supporting the conclusions.
DOI: 10.6084/m9.figshare.12552920
title: Additional file 2 of Randomized comparative study of child and caregiver responses to three software functions added to the Japanese version of the electronic Pediatric Quality of Life Inventory (ePedsQL) questionnaire

description: Additional file 2.
DOI: 10.6084/m9.figshare.12552920.v1
title: Additional file 2 of Randomized comparative study of child and caregiver responses to three software functions added to the Japanese version of the electronic Pediatric Quality of Life Inventory (ePedsQL) questionnaire

description: Additional file 2.
DOI: 10.6084/m9.figshare.12552911
title: Additional file 1 of Randomized comparative study of child and caregiver responses to three software functions added to the Japanese version of the electronic Pediatric Quality of Life Inventory (ePedsQL) questionnaire

description: Additional file 1.
DOI: 10.6084/m9.figshare.12552911.v1
title: Additional file 1 of Randomized comparative study of child and caregiver responses to three software functions added to the Japanese version of the electronic Pediatric Quality of Life Inventory (ePedsQL) questionnaire

description: Additional file 1.
DOI: 10.6084/m9.figshare.12552884
title: Additional file 6 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 6.
DOI: 10.6084/m9.figshare.12552887
title: Additional file 7 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 7.
DOI: 10.6084/m9.figshare.12552884.v1
title: Additional file 6 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 6.
DOI: 10.6084/m9.figshare.12552887.v1
title: Additional file 7 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 7.
DOI: 10.6084/m9.figshare.12552869
title: Additional file 4 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 4: Supplementary Table 3. Differentially methylated regions (DMRs) between the PCa T cell DNA and healthy control T cell DNA. The data was obtained using DMR function in the ChAMP pipeline and input into the IGV browser to identify nearby genes and location of each DMR manually. Reference genome H19 was used for alignment. TSS, Transcription start site.
DOI: 10.6084/m9.figshare.12552875
title: Additional file 5 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 5.
DOI: 10.6084/m9.figshare.12552869.v1
title: Additional file 4 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 4: Supplementary Table 3. Differentially methylated regions (DMRs) between the PCa T cell DNA and healthy control T cell DNA. The data was obtained using DMR function in the ChAMP pipeline and input into the IGV browser to identify nearby genes and location of each DMR manually. Reference genome H19 was used for alignment. TSS, Transcription start site.
DOI: 10.6084/m9.figshare.12552863
title: Additional file 3 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 3: Supplementary Table 2. List of the primers used for pyrosequencing and amplicon sequencing (Illumina MiSeq system).
DOI: 10.6084/m9.figshare.12552875.v1
title: Additional file 5 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 5.
DOI: 10.6084/m9.figshare.12552860
title: Additional file 2 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 2: Supplementary Table 1. List of negative-biopsy healthy controls and positive-biopsy PCa patient sample ids with their respective Gleason score.
DOI: 10.6084/m9.figshare.12552863.v1
title: Additional file 3 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 3: Supplementary Table 2. List of the primers used for pyrosequencing and amplicon sequencing (Illumina MiSeq system).
DOI: 10.6084/m9.figshare.12552860.v1
title: Additional file 2 of DNA methylation signatures of Prostate Cancer in peripheral T-cells

description: Additional file 2: Supplementary Table 1. List of negative-biopsy healthy controls and positive-biopsy PCa patient sample ids with their respective Gleason score.
DOI: 10.6084/m9.figshare.12552833
title: Additional file 1 of Asymptomatic carriage of Plasmodium falciparum by individuals with variant blood groups and haemoglobin genotypes in southern Ghana

description: Additional file 1. Statistical analysis. Tables containing the exact counts of different variables determined at each site (Greater Accra and Central Region) as well as details of the Chi-Squared tests and Binary Logistic Regression analysis performed on the data.
DOI: 10.6084/m9.figshare.12552824
title: Additional file 9 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 9. Opticin. FASTA format file (.fasta) containing the complete multiple sequence alignment of the opticin dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552818
title: Additional file 8 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 8. Epiphycan. FASTA format file (.fasta) containing the complete multiple sequence alignment of the epiphycan dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552824.v1
title: Additional file 9 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 9. Opticin. FASTA format file (.fasta) containing the complete multiple sequence alignment of the opticin dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552812
title: Additional file 7 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 7. Mimecan. FASTA format file (.fasta) containing the complete multiple sequence alignment of the mimecan dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552818.v1
title: Additional file 8 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 8. Epiphycan. FASTA format file (.fasta) containing the complete multiple sequence alignment of the epiphycan dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552803
title: Additional file 6 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 6. PRELP. FASTA format file (.fasta) containing the complete multiple sequence alignment of the PRELP dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552812.v1
title: Additional file 7 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 7. Mimecan. FASTA format file (.fasta) containing the complete multiple sequence alignment of the mimecan dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552794
title: Additional file 4 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 4. Osteoadherin. FASTA format file (.fasta) containing the complete multiple sequence alignment of the osteoadherin dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552797
title: Additional file 5 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 5. Keratocan. FASTA format file (.fasta) containing the complete multiple sequence alignment of the keratocan dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.
DOI: 10.6084/m9.figshare.12552803.v1
title: Additional file 6 of The origins and developments of sulfation-prone tyrosine-rich and acidic N- and C-terminal extensions of class ll and lll small leucine-rich repeat proteins shed light on connective tissue evolution in vertebrates

description: Additional file 6. PRELP. FASTA format file (.fasta) containing the complete multiple sequence alignment of the PRELP dataset with signal peptides removed. May be accessed using common multiple sequence alignment workbenches such as Jalview.