cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18150/fk3asv
title: Improving hydrogen generation from biomass and solid waste by combining sonophotocatalysis through carbon-based materials: Challenges and future perspectives

description: Environmental pollution is becoming one of the main issues facing human civilisation as a result of the world's growing industrialisation. Using limitless solar energy, photocatalysis may be used to address environmental issues. Whilst, the incorporation of ultrasonic cavitation in the various processes such as fenton-like process, electrochemical process, and specially sono-photocatalysis that offers ideal conditions for increasing biomass fragmentation and conversion into target products. and green hydrogen within a lesser reaction time. The scientific community and industry have taken a serious interest in the intensification of ultrasonic processes for a variety of applications, as well as the resulting synergistic effects based on conventional comparison in literature. In light of this, the purpose of this review is to summarize the current research in the field, provide an overview of the recent studies of ultrasound-assisted different catalysis process for hydrogen production and discuss their limits and validity, compare them as conventional techniques. Finally, a few future perspectives in form of suggestions on the ultrasound-assisted photocatalysis for hydrogen production from a various biomass models and different wastes, and highlighting the role and recent evolution of carbon-based materials in this field are presented together with current issues and challenges and clarify future attitudes in the hopes of exploring this ideal combination for large-scale H2 production.
DOI: 10.18150/3rqvcz
title: Sono-photocatalysis for continuous-flow intensification: A disruptive strategy for lignocellulose valorization

description: The valorization of lignocellulosic biomass represents a significant frontier in scientific research, promising a sustainable source of renewable energy and valuable chemical compounds. Traditional methods for converting lignocellulose often suffer from challenges such as low selectivity, suboptimal yield, and high energy consumption. To address these issues, innovative approaches that blend different catalytic processes are gaining traction. One such approach is the combination of sonication with photocatalysis in continuous-flow systems. This method offers the potential to revolutionize lignocellulose valorization by enhancing process efficiency and selectivity, thus opening new pathways for producing high-value chemicals and energy sources. This paper delves into the potential of integrating sonication and photocatalysis for lignocellulose conversion within continuous-flow systems. It discusses the opportunities that arise from this synergistic approach, as well as the associated challenges, such as the need for precise control of reaction conditions and the integration of scalable technologies. Moreover, a critical review of the current state of the art in this domain is provided to highlight recent advancements and identify avenues for future exploration. This paper is particularly relevant to researchers, engineers, and professionals in chemical engineering, renewable energy, and environmental science who are focused on sustainable technologies and biomass conversion. It is also valuable for academic and industrial stakeholders seeking innovative solutions to enhance the efficiency and sustainability of biomass processing.
DOI: 10.18150/4kfobo
title: Regioselective Hydrocyanation of Internal Alkynes Enabled by a Transition-Metal-Free Dual-Catalytic System

description: Raw data accompanying publication: Regioselective Hydrocyanation of Internal Alkynes Enabled by a Transition-Metal-Free Dual-Catalytic System
DOI: 10.5281/zenodo.14645808
title: Barents Sea irradiance modelling output from HEIMDALL [v1]

description: Dataset used in the manuscript "Increased light availability in the northern Barents Sea driven by sea ice loss" submitted to JGR Oceans. All files contain PAR at 30m and 10m depth at various Barents Sea locations and times. The file "heimdallBarentsSea_1980s.nc", contains PAR data within the area 71-82˚N and 10-60˚E, for the years 1979-1988. The file "heimdallBarentsSea_2010s.nc" contains data for the same area but for the years 2013-2022. The file "heimdallBarentsSea_transect.nc", contains data along the 33˚E transect (71-82˚N) for the years 1979-2022.
DOI: 10.5281/zenodo.14645809
title: Barents Sea irradiance modelling output from HEIMDALL [v1]

description: Dataset used in the manuscript "Increased light availability in the northern Barents Sea driven by sea ice loss" submitted to JGR Oceans. All files contain PAR at 30m and 10m depth at various Barents Sea locations and times. The file "heimdallBarentsSea_1980s.nc", contains PAR data within the area 71-82˚N and 10-60˚E, for the years 1979-1988. The file "heimdallBarentsSea_2010s.nc" contains data for the same area but for the years 2013-2022. The file "heimdallBarentsSea_transect.nc", contains data along the 33˚E transect (71-82˚N) for the years 1979-2022.
DOI: 10.5281/zenodo.15392186
title: Pr2Graph KG for Top-100 Websites, and Formal Policies
DOI: 10.5281/zenodo.15392187
title: Pr2Graph KG for Top-100 Websites
DOI: 10.5281/zenodo.15408913
title: Pr2Graph KG for Top-100 Websites, and Formal Policies
DOI: 10.7910/dvn/epeugo
title: SeasonBench-EA

description: The datasets for SeasonBench-EA Benchmark, which contains the monthly reanalysis data (1940-2024) and ensemble forecasts for CMCC. All data are downloaded from the Copernicus Climate Data Store (https://cds.climate.copernicus.eu/) and reorganized for benchmark construction. Please ensure compliance with the CDS Licence when using or redistributing the data.
DOI: 10.5281/zenodo.15423001
title: ICD-11 KG

description: This project presents a semantically rich knowledge graph (ICD-KG) focused on mental and behavioral disorders, based on the ICD classification. Using a multi-stage pipeline, the data was transformed into RDF/OWL format, ensuring ontological consistency and machine interpretability. The pipeline constructs a hierarchical structure of diseases and related medical entities, modeled using RDFS and OWL constructs. Core concepts include diseases, diagnostic criteria, symptoms, and drug classes, connected via semantic relations such as rdfs:subClassOf, icd-kg:hasDiagnosticRequirements, schema:drug, and schema:signOrSymptom. This ontology-driven approach enhances interoperability, supporting advanced applications in medical knowledge representation and reasoning.
DOI: 10.5281/zenodo.15423002
title: ICD-11 KG

description: This project presents a semantically rich knowledge graph (ICD-KG) focused on mental and behavioral disorders, based on the ICD classification. Using a multi-stage pipeline, the data was transformed into RDF/OWL format, ensuring ontological consistency and machine interpretability. The pipeline constructs a hierarchical structure of diseases and related medical entities, modeled using RDFS and OWL constructs. Core concepts include diseases, diagnostic criteria, symptoms, and drug classes, connected via semantic relations such as rdfs:subClassOf, icd-kg:hasDiagnosticRequirements, schema:drug, and schema:signOrSymptom. This ontology-driven approach enhances interoperability, supporting advanced applications in medical knowledge representation and reasoning.
DOI: 10.5281/zenodo.15423954
title: ICD-11 KG

description: This project presents a semantically rich knowledge graph (ICD-KG) focused on mental and behavioral disorders, based on the ICD classification. Using a multi-stage pipeline, the data was transformed into RDF/OWL format, ensuring ontological consistency and machine interpretability. The pipeline constructs a hierarchical structure of diseases and related medical entities, modeled using RDFS and OWL constructs. Core concepts include diseases, diagnostic criteria, symptoms, and drug classes, connected via semantic relations such as rdfs:subClassOf, icd-kg:hasDiagnosticRequirements, schema:drug, and schema:signOrSymptom. This ontology-driven approach enhances interoperability, supporting advanced applications in medical knowledge representation and reasoning.
DOI: 10.5281/zenodo.15423909
title: Data 10 bestseller novels

description: The data consist of OCR /scan of the first chapters of ten best-seller novels that can be further used for digital text analysis using Voyant Tools.
DOI: 10.5281/zenodo.15423910
title: Data 10 bestseller novels

description: The data consist of OCR /scan of the first chapters of ten best-seller novels that can be further used for digital text analysis using Voyant Tools.
DOI: 10.34740/kaggle/dsv/11822542
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.15319259
title: AstraZeneca metabolite identification (MetID) schemes for 120 compounds

description: This file contains metabolite identification schemes for 120 compounds, derived from incubations in human hepatocytes (Gender: Pooled, Hepatocyte Concentration: 1 million cells/mL, Compound Concentration: 4 µM, Incubation Time: 120 min).

Preprint: 10.26434/chemrxiv-2025-pd36x
DOI: 10.6084/m9.figshare.29070131
title: Density-dependent effects of simultaneous root and floral herbivory on plant fitness and defense

description: Plants are attacked by multiple herbivores, and depend on a precise regulation of responses to cope with a wide range of antagonists. Simultaneous herbivory can occur in different plant compartments, which may pose a serious threat to plant growth and reproduction. In particular, plants often face co-occurring root and floral herbivory, but few studies have focused on such interactions. Here, we investigated in the field the combined density-dependent effects of root-chewing cebrionid beetle larvae and flower-chewing pierid caterpillars on the fitness and defense of a semiarid Brassicaceae herb. We found that the fitness impact of both herbivore groups was independent and density-dependent. Increasing root herbivore density non-significantly reduced plant fitness, while the relationship between increasing floral herbivore density and the reduction they caused in both seed number and seedling emergence was non-linear. The plant defensive response was non-additive with regard to the different densities of root and floral herbivores; high floral herbivore density provoked compensatory investment in reproduction, and this tolerance response was combined with aboveground chemical defense induction when also root herbivore density was high. Plants may thus prioritize specific trait combinations in response to varying combined below- and aboveground herbivore densities to minimize negative impacts on fitness.
DOI: 10.6084/m9.figshare.29070131.v1
title: Density-dependent effects of simultaneous root and floral herbivory on plant fitness and defense

description: Plants are attacked by multiple herbivores, and depend on a precise regulation of responses to cope with a wide range of antagonists. Simultaneous herbivory can occur in different plant compartments, which may pose a serious threat to plant growth and reproduction. In particular, plants often face co-occurring root and floral herbivory, but few studies have focused on such interactions. Here, we investigated in the field the combined density-dependent effects of root-chewing cebrionid beetle larvae and flower-chewing pierid caterpillars on the fitness and defense of a semiarid Brassicaceae herb. We found that the fitness impact of both herbivore groups was independent and density-dependent. Increasing root herbivore density non-significantly reduced plant fitness, while the relationship between increasing floral herbivore density and the reduction they caused in both seed number and seedling emergence was non-linear. The plant defensive response was non-additive with regard to the different densities of root and floral herbivores; high floral herbivore density provoked compensatory investment in reproduction, and this tolerance response was combined with aboveground chemical defense induction when also root herbivore density was high. Plants may thus prioritize specific trait combinations in response to varying combined below- and aboveground herbivore densities to minimize negative impacts on fitness.
DOI: 10.48597/ha6c-uwqg
title: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory

description: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory
DOI: 10.48597/2za6-9qe8
title: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory

description: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory
DOI: 10.48597/3zqq-2zj4
title: Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory

description: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory
DOI: 10.48597/vvsd-jxcr
title: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory

description: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory
DOI: 10.48597/yvb4-me6u
title: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory

description: Measurement of Aerosol_absorption_coefficient at SIRTA Atmospheric Research Observatory
DOI: 10.6084/m9.figshare.29070403
title: S4: Synchronous Cretaceous magmatism and migmatization in the Lohit and Dibang Valley, Easternmost Himalaya

description: Table S2
DOI: 10.6084/m9.figshare.29070403.v1
title: S4: Synchronous Cretaceous magmatism and migmatization in the Lohit and Dibang Valley, Easternmost Himalaya

description: Table S2
DOI: 10.6084/m9.figshare.29070424.v1
title: S3: Intense weathering attending the emergence of the southeast Amazonian Craton during the Neoarchean

description: Appendix C
DOI: 10.6084/m9.figshare.29070424
title: S3: Intense weathering attending the emergence of the southeast Amazonian Craton during the Neoarchean

description: Appendix C
DOI: 10.6084/m9.figshare.29070427
title: S1: Intense weathering attending the emergence of the southeast Amazonian Craton during the Neoarchean

description: Appendix A
DOI: 10.6084/m9.figshare.29070427.v1
title: S1: Intense weathering attending the emergence of the southeast Amazonian Craton during the Neoarchean

description: Appendix A
DOI: 10.5281/zenodo.15423967
title: trigonectes_rubromarginatus_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.15423968
title: trigonectes_rubromarginatus_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.15424002
title: PM-Sampo Dataset

description: The dataset used to implement PM-Sampo, along with the source code to create the data.
DOI: 10.5281/zenodo.15424003
title: PM-Sampo Dataset

description: The dataset used to implement PM-Sampo, along with the source code to create the data.
DOI: 10.5281/zenodo.15401852
title: Energy for Future: Engaging young people in modelling for a more inclusive energy transition at the country scale

description: This is a dataset and instantiation of the highRES-Norway modelling framework, which allows a user to run the Norway-specific version of the highRES-European version (https://github.com/highRES-model/highRES-Europe-WF). Additional information on how the model and workflow is structured can be found in the repository: (https://github.com/JavedMS/highRES-Norway). Parts of this dataset are acquired and updated from the highRES-European version dataset available at (https://zenodo.org/records/14223618) 

This particular version of the data is set to run a model based on the weather conditions of 2010, which may impact the performance and availability of variable renewable energy sources (wind, solar, and hydro) and demand.

Demand data

The underlying demand data is acquired from the interannual demand calculator (https://zenodo.org/records/10820928), which is further processed to envision future projections, as documented here: https://github.com/tobiasvh15/highRES-Norway/tree/demand. The data available in the interannual demand calculator ranges from between 1941-2023. 

Weather data

Weather data used in highRES-Europe is based on ERA5 reanalysis data from ECMWF (https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5), which is available from 1940 to the present. ERA5 reanalysis data is used to generate hourly capacity factor time series for onshore and offshore wind power, solar power, and run-of-river hydropower, as well as to estimate hourly inflow to hydropower reservoirs. Moreover, the wind power capacity factors are bias-corrected using historical wind power production data from the Norwegian Water Resources and Energy Directorate (NVE). The hydropower time series are further normalised based on historic electricity generation data from the U.S. Energy Information Administration (https://www.eia.gov/international/data/world/electricity/electricity-generation). 

Techno-economic data

Cost and technical data is taken from UKTM (<https://www.ucl.ac.uk/energy-models/models/uk-times>) with data from the JRC report "Cost development of low carbon energy technologies: Scenario-based cost trajectories to 2050" (<https://publications.jrc.ec.europa.eu/repository/handle/JRC109894>) used to update some areas. Energy storage capacities for reservoir and pumped storage are taken from Schlachtberger et al. (2017) and Geth et al. (2015) respectively (https://doi.org/10.1016/j.energy.2017.06.004 and https://doi.org/10.1016/j.rser.2015.07.145). 

Land availability restrictions and shapefiles

Part of the workflow includes excluding areas from VRE deployment. 

Shapefiles are acquired from Eurostat (https://ec.europa.eu/eurostat/web/gisco/geodata/statistical-units/territorial-units-statistics). The main exclusions are based on Corine land cover (https://doi.org/10.2909/960998c1-1870-4e82-8051-6485205ebbac),  Norway landscape data (https://www.geonorge.no/en/about/) and WDPA (https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA).
DOI: 10.5281/zenodo.15401853
title: Energy for Future: Engaging young people in modelling for a more inclusive energy transition at the country scale

description: This is a dataset and instantiation of the highRES-Norway modelling framework, which allows a user to run the Norway-specific version of the highRES-European version (https://github.com/highRES-model/highRES-Europe-WF). Additional information on how the model and workflow is structured can be found in the repository: (https://github.com/JavedMS/highRES-Norway). Parts of this dataset are acquired and updated from the highRES-European version dataset available at (https://zenodo.org/records/14223618) 

This particular version of the data is set to run a model based on the weather conditions of 2010, which may impact the performance and availability of variable renewable energy sources (wind, solar, and hydro) and demand.

Demand data

The underlying demand data is acquired from the interannual demand calculator (https://zenodo.org/records/10820928), which is further processed to envision future projections, as documented here: https://github.com/tobiasvh15/highRES-Norway/tree/demand. The data available in the interannual demand calculator ranges from between 1941-2023. 

Weather data

Weather data used in highRES-Europe is based on ERA5 reanalysis data from ECMWF (https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5), which is available from 1940 to the present. ERA5 reanalysis data is used to generate hourly capacity factor time series for onshore and offshore wind power, solar power, and run-of-river hydropower, as well as to estimate hourly inflow to hydropower reservoirs. Moreover, the wind power capacity factors are bias-corrected using historical wind power production data from the Norwegian Water Resources and Energy Directorate (NVE). The hydropower time series are further normalised based on historic electricity generation data from the U.S. Energy Information Administration (https://www.eia.gov/international/data/world/electricity/electricity-generation). 

Techno-economic data

Cost and technical data is taken from UKTM (<https://www.ucl.ac.uk/energy-models/models/uk-times>) with data from the JRC report "Cost development of low carbon energy technologies: Scenario-based cost trajectories to 2050" (<https://publications.jrc.ec.europa.eu/repository/handle/JRC109894>) used to update some areas. Energy storage capacities for reservoir and pumped storage are taken from Schlachtberger et al. (2017) and Geth et al. (2015) respectively (https://doi.org/10.1016/j.energy.2017.06.004 and https://doi.org/10.1016/j.rser.2015.07.145). 

Land availability restrictions and shapefiles

Part of the workflow includes excluding areas from VRE deployment. 

Shapefiles are acquired from Eurostat (https://ec.europa.eu/eurostat/web/gisco/geodata/statistical-units/territorial-units-statistics). The main exclusions are based on Corine land cover (https://doi.org/10.2909/960998c1-1870-4e82-8051-6485205ebbac),  Norway landscape data (https://www.geonorge.no/en/about/) and WDPA (https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA).
DOI: 10.5285/800d6734-2dd5-4ed0-a698-972594800042
title: Heat flow United Kingdom version 1

description: The dataset portrays heat flow as a continuous modelled surface, interpolated between observation points. Onshore coverage is provided for England, Wales, Scotland and Northern Ireland. 
The British Geological Survey (BGS) Heat flow dataset version 1 (United Kingdom) is derived from a catalogue of legacy heat flow observations and ground-heat modelling. Heat flow data is typically used to determine temperatures beneath the ground surface, and model how much thermal energy may be stored in or recovered from the ground. 
The dataset is presented as a raster model, but is also available as cellular, vector grids.  The raster and square-cellular grid defines each cell by an area of c. 4km2 (2km per side). The hexagonal-cellular defines each cell by an area of c. 2.56km2 (1km per side). Heat flow values are milli-Watts per square metre (mWm-2).
The data are available under BGS data licence.
DOI: 10.6084/m9.figshare.29070395
title: failure_qual.data_figshare

description: 30 medical students from the University of Basel participated in a 16-hour workshop entitled ‘How Physicians Deal with Failure in Medicine’. Two senior surgeons and a life and leadership coach facilitated the workshop between August 2021 and February 2022, aiming to enable medical learners to reflect on failure and develop useful coping strategies. The authors used a directed qualitative content analysis to analyze pre- and post-workshop reflective essays from the workshop participants.
DOI: 10.17909/385q-xc98
title: Creating test DOI in DOI Form

description: Creating test DOI in DOI Form
DOI: 10.5285/def961e0-3432-4af8-a09a-a489c845af54
title: Thermal properties Great Britain version 1

description: Data identifying landscape areas (shown as polygons) attributed with geological descriptions and thermal properties of geological materials. The scale of the data is 1:250 000 scale for the Thermal Properties V1 dataset. Onshore coverage is for Great Britain and the Isle of Man. This dataset shows thermal properties relating to bedrock beneath our feet. The information can be used to assess the potential for closed and open loop ground source heat pumps across, or deeper geothermal assessments, across the United Kingdom. The attribution and spatial data underpinning the model are that which is described and shown by Rollin (1987) and Gale (2004, 2005). The information is presented vector-based, irregular polygon coverage at 1:250 000 scale Each polygon is attributed with a range of geological properties including modelled values for Thermal conductivity, thermal diffusivity, specific heat capacity and density. The data are available in vector format (containing the geometry of each feature linked to a database record describing their attributes) as ESRI shapefiles and are available under BGS data licence.
DOI: 10.6084/m9.figshare.29070398
title: CSR Data

description: Plant leaf traits of 2,503 individuals from 160 woody species were measured, and the components of CSR were quantified at both individual and community levels.