cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1053481.10fu
title: SH1053481.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1053484.10fu
title: SH1053484.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1053487.10fu
title: SH1053487.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1053489.10fu
title: SH1053489.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.b9w8z3
title: Occurrence Download

description: A dataset containing 77418887 species occurrences available in GBIF matching the query:
{
 "Continent" : [
 "is Africa"
 ]
}

 The dataset includes 77418887 records from 5969 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011036-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vk6qey
title: Occurrence Download

description: A dataset containing 33591 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Numenius madagascariensis (Linnaeus, 1766)",
 "Year 2020-2025"
 ]
}

 The dataset includes 33591 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020543-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5285/44adfc4f92834bd9950341dd24d6d2e0
title: Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.23 (v20211001)

description: Data for Figure 3.23 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.23 shows multi-model-mean bias of (a) sea surface temperature and (b) near-surface salinity, defined as the difference between the CMIP6 multi-model mean and the climatology from the World Ocean Atlas 2018. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has two panels, with data provided for all panels in subdirectories named panel_a and panel_b. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Global bias of modelled annual-mean sea surface temperature (°C) of CMIP6 for the period 1995–2014 to WOA 2018 - Global bias of modelled annual-mean sea surface salinity (PSS-76) of CMIP6 for the period 1995–2014 to WOA 2018 CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. WOA 2018 is the World Ocean Atlas 2018. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/fig_3_23_a.nc (sst, CMIP6 Sea Surface Temperature Bias) - panel_b/fig_3_23_b.nc (sss, CMIP6 Sea Surface Salinity Bias) --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo.
DOI: 10.5281/zenodo.14986362
title: CMIP6 input data usage information for IPCC WGI AR6 figure 3.23

description: The record contains information on input dataset usage and citation information from the WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) for the generation of figure 3.23 of the Sixth Assessment Report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC AR6 WGI). CMIP6 data that were used as input to this figure follow the Data Reference Syntax. Persistent Identifiers (PIDs) for data identification (provenance) are available for individual datasets as Handle IDs. DOIs for data citation are available on the following dataset collections: CMIP6 DOIs contain all datasets provided by an Earth System model to a CMIP6 experiment. The data subsets of CMIP6 dataset collections used in the IPCC AR6 WGI have DOIs at this granularity of a model contribution to an experiment. The AR6 subset DOIs are included because they reside in a long-term preservation archive hosted by the IPCC Data Distribution Centre (DDC).

The uploaded human-readable csv file provides a list of datasets/Handle IDs used for the generation of this figure grouped by the corresponding dataset collections they belong to. The machine-actionable json-ld file describes the record as Complex Citation Object (see Agarwal et al., 2024, https://doi.org/10.5281/zenodo.14106602) in a preliminary standard, using the following vocabulary to specify the different functions of the contained Linked Digital Objects: Credit (input dataset collection to be cited/to which credit is to be assigned), Provenance (dataset contributing information to the generation of the DataProduct), archivedAt (dataset collection with long-term preservation), DigitalDocument (referenced papers containing further information), DataProduct (generated final dataset), ImageObject (visualization of the DataProduct), SoftwareSourceCode (software applied to generate the DataProduct), Chapter (IPCC AR6 WGI chapter in which the DataProduct is used/referenced).

Use and cite this record when referring to the generation of IPCC WGI AR6 figure 3.23.
DOI: 10.15151/esrf-es-2011355240
title: Macromolecular crystallography at the Philipps University Marburg (MarBAG)

description: The MarBAG, based at Philipps-University Marburg and the Max-Planck-Institute for Terrestrial Microbiology in Marburg, Germany, employs X-ray crystallography to elucidate the fundamental mechanisms underlying the synthesis, assembly, and function of macromolecular machines and cellular structures. This research encompasses critical biological processes, including CO2 fixation pathways, flagellar biosynthesis, CRISPR-Cas systems, and phage-bacteria interactions. Additionally, our investigations extend to plant-pathogen interactions and the role of nucleotide-derived signaling molecules in cellular stress physiology and organization of bacteria and higher organisms.
To enhance our structural characterization of macromolecular complexes that are challenging to crystallize, we have recently installed a 200 keV cryo-electron microscope at UMR. This advanced instrumentation enables routine screening and quality assessment of samples for cryoelectron microscopy.
DOI: 10.15151/esrf-es-2101374289
title: Bridging the gap between cellular and whole body imaging using Hierarchical Phase-Contrast Tomography: HiP-CT

description: Humans and other large organisms are three-dimensional multiscale biological systems where large scale function and structure are dependent on the macrostructure’s interconnectivity down to the cellular and subcellular level. Using the exceptional coherence provided by the ESRF-EBS, we have demonstrated that propagation-based phase-contrast can effectively decouple resolution from specimen size in soft tissue, obtaining 1.4 micron voxel resolution in 150 mm diameter human organs. Through this Long Term Proposal (LTP) we will develop the techniques required to image whole human and animal bodies ex vivo at 25 micron resolution, zooming to sub-micron voxels (0.7micron) locally, resolving sub-cellular structures through hard- and soft-tissue. Resolving how the micro (sub-cellular) interacts with the macro (whole organism) across length scales will provide all new insights into biological and biomedical function. This is true for both healthy and pathological system level behaviour.
DOI: 10.15151/esrf-es-2090459607
title: Structural Investigation of Fibrillar Collagen Maturation Using Cryo Electron Microscopy

description: The biosynthesis of fibrillar collagens (I-III, V, XI) is crucial for development, bone remodeling, and wound healing, while its disruption causes inherited disorders like Osteogenesis Imperfecta and acquired conditions such as fibrosis. The C-terminal proteolytic maturation of procollagens, mediated by a 570 kDa complex of BMP 1 protease, procollagen, and PCPE proteins, is essential for collagen fibrillogenesis and represents a key therapeutic target. Building on preliminary results, including a medium-resolution map of a (mini )procollagen I, this project focuses on improving conditions for assembling and analyzing the maturation complex. This includes testing new crosslinking strategies, increasing the proportion of complexed forms, and optimizing cryo EM grid preparation. These efforts aim to resolve the structure, enhancing understanding of collagen biosynthesis and guiding future drug development.
DOI: 10.6084/m9.figshare.25122034
title: Exploring Heterogeneous Effects of Victimization on Changes in Fear of Crime: The Moderating Role of Neighborhood Conditions

description: A growing research body shows that victimization increases victims’ fear of crime. Typically, this research estimates average effects, which may conceal that people respond differently to victimization or that ecological contexts shape the experience of crime. The current study is among the few that attempt to uncover potential heterogeneities in victimization effects by ecological contexts. It explores whether the victims’ neighborhood conditions (levels of crime, disorder, and concentrated disadvantage) moderate the impact of violent victimization close to home on fear of crime. For this purpose, longitudinal multilevel models were estimated using data from a two-wave panel survey of about 3300 adult respondents nested in 140 neighborhoods in two large German cities. The results suggest that individuals from more disadvantaged neighborhoods tend to increase their fear of crime more strongly after victimization than those from more advantaged areas. For the other neighborhood conditions, victimization effects were estimated to be more homogenous.
DOI: 10.15151/esrf-es-1965825584
title: Structural analysis of historical materials

description: This proposal is a continuation of the HG-213 and HG-172 BAG pexperiments, a new access route to the ESRF structural analysis capacities for the Heritage Science community. The upgrade to the ESRF-EBS was the triggering element to propose a single block allocation group (BAG). Two complementary analytical configurations are used in the BAG: High angular resolution XRD (ID22) and High lateral resolution XRD (ID13). The combination of these two beamlines generates precious clues on the origin, processing and degradation of historical materials. By relying on the new analytical capacities of the EBS combined with optimized access route, sample preparation procedures and processing pipelines, the Heritage BAG has proven to be a very efficient way to increase the output of the Cultural Heritage community, to reinforce a scientific network of expert users structured around the ESRF, and to initiate new European collaborations in Heritage Science.
DOI: 10.15151/esrf-es-2009731967
title: Multi-scale Multi-techniques investigations of Li-ion batteries: towards a European Battery Hub

description: In this science-driven Long-Term proposal, we propose a 3-years multi-beamline program tackling grand challenges for actual, emerging and future battery technologies. We will deploy advanced methodologies for accelerating research by setting new cooperation modes for multi-techniques multi-scale studies. Three chemistry-neutral scientific cases have been identified to fulfil this LTP: bulk-to-surface mechanisms, high energy system and smart sensing. Multiple, time-coordinated, interoperable spectroscopic, imaging & scattering techniques will be implemented. This proposal is the Pilot Phase towards a European Battery Hub aiming at accelerating workflows in battery research by optimizing the exceptional diversity of means available at ESRF. We expect to demonstrate the added value of a new “proposal” mechanism, e.g. science-driven beamtime allocation group, serving the fast growing, highly competitive and rapidly evolving European battery community.
DOI: 10.15151/esrf-es-2020258722
title: Operando XAS studies of nickel-iron phosphosulfide nanotube for direct seawater electrolysis

description: Nickel iron phosphosulfide (NiFeSP) nanotube has been reported to be a promising electrocatalyst for overall direct seawater electrolysis, active for several reactions including the hydrogen/oxygen evolution reactions (HER/OER) and the urea oxidation reaction (UOR) in seawater. Operando XAS collected as a function of applied potentials will provide characterisation of the working state of the novel NiFeSP as well as two reference nickel-iron phosphide (NiFeP) and nickel-iron sulfide (NiFeS) catalysts. Spectra collected at the Ni and Fe edges will allow for identification of structural transformation and the actual active structure and species under HER, OER and UOR conditions, shedding light on the structure-activity relationship of NiFeSP and the promotion mechanism of P and S incorporation.
DOI: 10.15151/esrf-es-2029272398
title: Molecular bases of regulation of cardiac muscle contractility

description: Regulation of heart contractility is operated by both thin, actin containing filaments, and thick, myosin containing filaments. Ca2+-induced structural changes in the regulatory proteins of the thin filament release the actin sites for interaction with myosin motors. Thick filament mechanosensing adapts to the load the number of motors recruited from the OFF state in which they lie tilted back on their tails unable to interact with actin. In the heartbeat both thin and thick filament activations are under the control of modulatory mechanisms by accessory proteins. Mutations in these proteins cause dysregulation and cardiomyopathy. We use sarcomere-level mechanics and X-ray diffraction on intact and demembranated myocytes of the ventricle of wild type, mutant and transgenic animal models to investigate the mechanisms that control thick filament regulation/dysregulation and test small molecules candidate as therapeutic tools.
DOI: 10.15468/dl.u8gpww
title: Occurrence Download

description: A dataset containing 6741 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Erythrina crista-galli L.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 6741 records from 173 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007708-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14986367
title: CMIP6 input data usage information for IPCC WGI AR6 figure 3.26

description: The record contains information on input dataset usage and citation information from the WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) for the generation of figure 3.26 of the Sixth Assessment Report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC AR6 WGI). CMIP6 data that were used as input to this figure follow the Data Reference Syntax. Persistent Identifiers (PIDs) for data identification (provenance) are available for individual datasets as Handle IDs. DOIs for data citation are available on the following dataset collections: CMIP6 DOIs contain all datasets provided by an Earth System model to a CMIP6 experiment. The data subsets of CMIP6 dataset collections used in the IPCC AR6 WGI have DOIs at this granularity of a model contribution to an experiment. The AR6 subset DOIs are included because they reside in a long-term preservation archive hosted by the IPCC Data Distribution Centre (DDC).

The uploaded human-readable csv file provides a list of datasets/Handle IDs used for the generation of this figure grouped by the corresponding dataset collections they belong to. The machine-actionable json-ld file describes the record as Complex Citation Object (see Agarwal et al., 2024, https://doi.org/10.5281/zenodo.14106602) in a preliminary standard, using the following vocabulary to specify the different functions of the contained Linked Digital Objects: Credit (input dataset collection to be cited/to which credit is to be assigned), Provenance (dataset contributing information to the generation of the DataProduct), archivedAt (dataset collection with long-term preservation), DigitalDocument (referenced papers containing further information), DataProduct (generated final dataset), ImageObject (visualization of the DataProduct), SoftwareSourceCode (software applied to generate the DataProduct), Chapter (IPCC AR6 WGI chapter in which the DataProduct is used/referenced).

Use and cite this record when referring to the generation of IPCC WGI AR6 figure 3.26.