cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8204326
title: A-Data obs. from the Hanford 300 area

description: A dataset was observed in a semi-arid Hanford area of the Washington State (46°24′32″N, 119°16′30″W) by Gao et al. (2017) which was from https://doi.org/10.1002/2017JD027160. The data includes the ground soil heat flux, temperature and land surface meteorological data. The Sensible heat flux and latent heat flux were quality controlled and gap filling by the author referring to Liu et al. (2014).
description: {"references": ["Gao, Z., E. S., Russell, J. E. C., Missik, M., Huang, X., Chen, C. E., Strickland, R., Clayton, E., Arntzen, Y., Ma, and H. Liu. (2017b). A novel approach to evaluate soil heat flux calculation: An analytical review of nine methods [Dataset]. Journal of Geophysical Research-Atmospheres. https://doi.org/10.1002/2017JD027160.", "Liu, H., Feng, J., Sun, J., Wang, L., & Xu, A.(2014). Eddy covariance measurements of water 911 vapor and CO2 fluxes above the Erhai Lake. Science in China (Earth Sciences), 58(3), 317\u2013328. 912. https://doi.org/10.1007/s11430-014-4828-1"]}
DOI: 10.6084/m9.figshare.3144775.v1
title: ICV and number of years occupied by the colony of CO

description: This file contains data concerning ICV and number of years occupied by the colony of centenarian oaks (CO).
DOI: 10.14768/a2f0891b-763a-49e9-af1b-78ed78b16982
title: CMEMS-LSCE: A global 0.25-degree, monthly reconstruction of the surface ocean carbonate system

description: This dataset, namely CMEMS-LSCE, supports our study focusing on an introduction of a new global 0.25° monthly reconstruction for the period 1985-2021. The CMEMS-LSCE reconstruction derives datasets of six carbonate system variables including surface ocean partial pressure of CO2 (pCO2), total alkalinity (AT), total dissolved inorganic carbon (DIC), surface ocean pH, and saturation states with respect to aragonite (Ωar ) and calcite (Ωca). Reconstructing pCO2 relies on an ensemble of neural network models mapping gridded observation-based data provided by the Surface Ocean CO2 ATlas (SOCAT). Surface ocean AT is estimated with a multiple linear regression approach, and the remaining carbonate variables are resolved by CO2 system speciation given the reconstructed pCO2 and AT. 1σ-uncertainty associated with these estimates is also provided. Here, σ stands for either ensemble standard deviation of pCO2 estimates or total uncertainty for each of the five other variables propagated through the processing chain with input data uncertainty. Reference (article): Chau T.T.T., Gehlen M., Metzl N., Chevallier F. (2023), CMEMS-LSCE: A global 0.25-degree, monthly reconstruction of the surface ocean carbonate system, submitted to the Earth System Science Data journal.
DOI: 10.4227/05/589d45227b2e9
title: Amphibian agricultural woodland data, eastern Australia 2014 - 2015

description: The data set contains count data of amphibians from surveys of grazing properties in the Central and Southern Tablelands of NSW, Australia. Amphibians were surveyed using pitfall and funnel trapping along transects. Twelve properties were surveyed for the data set. Each property was surveyed 5 times for five trap nights each survey between 2014 and 2015.

A total of 2378 amphibians were captured from 11 different species during the surveys. All species captured were from one of three families: Limnodynastidae (three species), Myobatrachidae (four species) and Hylidae (four species)
DOI: 10.5281/zenodo.7806130
title: Historical (1979 - 2020) data for anthropogenic inputs to a catchment and riverine mainstem exports for carbon, nitrogen, and phosphorus

description: We estimated the difference in Net Anthropogenic Nitrogen and Phosphorus Inputs (NANI-NAPI) at the finest scale possible (the municipality) in the <em>Rivière du Nord</em> watershed (Québec, Canada) between 1981 and 2016. The dataset here reports the delta between those two years for each municipality in the watershed. Three sites along the mainstem of <em>Rivière du Nord </em>have been sampled ~bi-monthly from ~1979 - 2020 for dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP), from which we estimated annual riverine export at each site. We also include annual precipitation (as the sum of rain and snow), and NANI-NAPI interpolated for each sub-watershed for 1981, 1986, 1991, 1996, 2001, 2006, 2011, and 2016.
DOI: 10.5521/forestplots.net/2015_2
title: Data from: "Consistent, small effects of tree-fall disturbances on the composition and diversity of four Amazonian forests"

description: 1. Understanding the resilience of moist tropical forests to tree fall disturbance events is important for understanding the mechanisms that underlie species coexistence and for predicting the future composition of these ecosystems. Here, we test whether variation in the functional composition of Amazonian forests determines their resilience to disturbance.
2. We studied the legacy of natural tree fall disturbance events in four forests across Amazonia that differ substantially in functional composition. We compared the composition and diversity of all free-standing woody stems 2 - 10 cm diameter in previously disturbed and undisturbed 20 x 20 m subplots within 55, one hectare, long-term forest inventory plots. 
3. Overall, stem number increased following disturbance, and species and functional composition shifted to favour light-wooded, small-seeded taxa. Alpha diversity increased, but beta diversity was unaffected by disturbance, in all four forests.
4. Changes in response to disturbance in both functional composition and alpha diversity were, however, small (2 – 4 % depending on the parameter) and similar among forests.
5. Synthesis. This study demonstrates that variation in the functional composition of Amazonian forests does not lead to large differences in the response of these forests to tree fall disturbances and overall, these events have a minor role in maintaining the diversity of these ecosystems.
DOI: 10.34740/kaggle/dsv/1235046
title: A COVID multiclass dataset of CT scans
DOI: 10.5281/zenodo.2559459
title: Southern Hemisphere cyclones tracks 1979-2013

description: This includes the filtered cyclone tracks which combined with ERA-Interim reanalysis data provide the basis for the results published in "Which extra-tropical cyclones contribute most to the transport of moisture in the Southern Hemisphere?" by Sinclair and Dacre in Journal of Geophysical Research - Atmospheres. ERA-Interim reanalysis data can be obtained freely from https://apps.ecmwf.int/datasets/

The cyclone tracks were produced using TRACK. For the method and relevant references please see the paper. For details of the data files, see the README file (README_tracks).
DOI: 10.5281/zenodo.7957903
title: WRF(v4.0)-SUEWS(2018c): input data for the evaluation at two UK sites

description: This archive includes input data for the evaluation at two UK sites (KCL and SWD) in the WRF-SUEWS model development paper. WRF-SUEWS code for the situations can be accessed at https://github.com/Urban-Meteorology-Reading/WRF-SUEWS/releases/tag/paper-WRF4.0-SUEWS2018c
DOI: 10.5281/zenodo.8169158
title: Characterization and Catalytic Datasets for the Multi-Batch Screening Photoreactor

description: Datasets obtained during characterization of the Multi-Batch_Screening_Photoreactor The folder structure is listed below. The documentation, software and all required files for manufacturing are available at GitHub: <br> https://github.com/photonZfeed/modularPhotoreactor<br> https://github.com/photonZfeed/Py4ModPhotoreactor
DOI: 10.5281/zenodo.7629800
title: R10 region mask basd on IPCC AR6 WG3 and ISIMIP

description: 0.5° grid of fractions of grid cell that is part of one of 10 world regions as defined by IPCC Working Group 3. The "region" variable is a dimension (11, 360, 720) variable. The first axis is the fraction (0-1 scale) of the grid cell at latitude and longitude (defined by second and third axis) falling into each world region. Values of first axis correspond to following regions: 0=South-East Asia and developing Pacific 1=Eurasia 2=Asia-Pacific 3=Africa 4=Middle East 5=Latin America and Caribbean 6=North America 7=Eastern Asia 8=Southern Asia 9=Europe 10=World (all land, excluding Antarctica, and the sum of fractions in 0-9). Oceans and inland lakes are not counted within countries/regions. The starting point for this data is the 0.5° country mask from Perrette (2023). Country definitions follow the prescription of IPCC Working Group 3 Annex II (Al Khourdajie et al. 2022) where possible. Some ambiguities exist with regards to post-colonial, geographically detached, and disputed territories which are not explicitly defined in Annex II. These have been grouped by geographic rather than political region (example: French Guiana is classified as Latin America & Caribbean, which it is most definitely geographically part of, rather than Europe, which it is politically part of). A more detailed list of region mappings is available from WG3 authors which is mostly consistent with Annex II and has been followed. Two changes have been made to this list for consistency with Annex II: North Macedonia has been placed in Europe (rather than Eurasia) and Ukraine has been placed in Eurasia (rather than Europe). Perette, 2023: ISI-MIP/isipedia-countries (v2.6). GitHub repository. https://github.com/ISI-MIP/isipedia-countries/releases/tag/v2.6 Al Khourdajie et al., 2022: Annex II: Definitions, Units and Conventions [Al Khourdajie, A., R. van Diemen, W.F. Lamb, M. Pathak, A. Reisinger, S. de la Rue du Can, J. Skea, R. Slade, S. Some, L. Steg (eds)]. In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.021
DOI: 10.5281/zenodo.8362562
title: R10 region mask based on IPCC AR6 WG3 and ISIMIP

description: region_classification.tsv: Tab-separated value file of ISO3 code, country name and the R10 mapping used. r10masks_fractional.nc: 0.5° grid of fractions of grid cell that is part of one of 10 world regions as defined by IPCC Working Group 3. The "region" variable is a dimension (11, 360, 720) variable. The first axis is the fraction (0-1 scale) of the grid cell at latitude and longitude (defined by second and third axis) falling into each world region. Values of first axis correspond to following regions defined in the country mappings file: 0=South-East Asia and developing Pacific 1=Eurasia 2=Asia-Pacific 3=Africa 4=Middle East 5=Latin America and Caribbean 6=North America 7=Eastern Asia 8=Southern Asia 9=Europe 10=World (all land, excluding Antarctica, and the sum of fractions in 0-9). Oceans and inland lakes are not counted within countries/regions. The starting point for this data is the 0.5° country mask from Perrette (2023). Country mappings in the TSV file follow the prescription of IPCC Working Group 3 Annex II (Al Khourdajie et al. 2022) where possible. Some ambiguities exist with regards to post-colonial, geographically detached, and disputed territories which are not explicitly defined in Annex II. These have been grouped by geographic rather than political region (example: French Guiana is classified as Latin America & Caribbean, which it is most definitely geographically part of, rather than Europe, which it is politically part of). Perette, 2023: ISI-MIP/isipedia-countries (v2.6). GitHub repository. https://github.com/ISI-MIP/isipedia-countries/releases/tag/v2.6 Al Khourdajie et al., 2022: Annex II: Definitions, Units and Conventions [Al Khourdajie, A., R. van Diemen, W.F. Lamb, M. Pathak, A. Reisinger, S. de la Rue du Can, J. Skea, R. Slade, S. Some, L. Steg (eds)]. In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.021
DOI: 10.5281/zenodo.7629799
title: R10 region mask based on IPCC AR6 WG3 and ISIMIP

description: region_classification.tsv: Tab-separated value file of ISO3 code, country name and the R10 mapping used. r10masks_fractional.nc: 0.5° grid of fractions of grid cell that is part of one of 10 world regions as defined by IPCC Working Group 3. The "region" variable is a dimension (11, 360, 720) variable. The first axis is the fraction (0-1 scale) of the grid cell at latitude and longitude (defined by second and third axis) falling into each world region. Values of first axis correspond to following regions defined in the country mappings file: 0=South-East Asia and developing Pacific 1=Eurasia 2=Asia-Pacific 3=Africa 4=Middle East 5=Latin America and Caribbean 6=North America 7=Eastern Asia 8=Southern Asia 9=Europe 10=World (all land, excluding Antarctica, and the sum of fractions in 0-9). Oceans and inland lakes are not counted within countries/regions. The starting point for this data is the 0.5° country mask from Perrette (2023). Country mappings in the TSV file follow the prescription of IPCC Working Group 3 Annex II (Al Khourdajie et al. 2022) where possible. Some ambiguities exist with regards to post-colonial, geographically detached, and disputed territories which are not explicitly defined in Annex II. These have been grouped by geographic rather than political region (example: French Guiana is classified as Latin America & Caribbean, which it is most definitely geographically part of, rather than Europe, which it is politically part of). Perette, 2023: ISI-MIP/isipedia-countries (v2.6). GitHub repository. https://github.com/ISI-MIP/isipedia-countries/releases/tag/v2.6 Al Khourdajie et al., 2022: Annex II: Definitions, Units and Conventions [Al Khourdajie, A., R. van Diemen, W.F. Lamb, M. Pathak, A. Reisinger, S. de la Rue du Can, J. Skea, R. Slade, S. Some, L. Steg (eds)]. In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.021
DOI: 10.15454/wq4utv/1zjxkm
title: hs_8_4_oral.fna.gz

description: Non-redundant gene catalog of the human oral microbiota
DOI: 10.15454/wq4utv/2e8ygy
title: hs_8_4_oral_vs_cazy.table.gz

description: Functional annotation of the gene catalog with the CAZy database
DOI: 10.15454/wq4utv/cvfyeo
title: hs_8_4_oral.853_MSPs.tsv.gz

description: Gene content of the 853 Metagenomic Species
DOI: 10.15454/wq4utv/gbwyxn
title: hs_8_4_oral.853_MSPs.taxo.tab

description: Taxonomic annotation of MetaGenomic Species
DOI: 10.57745/npigia
title: hs_8_4_oral_853_MSP.20230712.gtdb_r214_annot_long.tab

description: Updated taxonomic annotation of MetaGenomic Species based on GTDB r214
DOI: 10.5281/zenodo.8104491
title: In vivo tracking of functionally tagged Rad51 unveils a robust strategy of homology search.

description: This deposit contains all the raw data presented in the Figures of this manuscript<br>
description: Raw images used for quantification and not shown in the manuscript are available upon reasonable request
DOI: 10.5281/zenodo.8104490
title: In vivo tracking of functionally tagged Rad51 unveils a robust strategy of homology search.

description: This deposit contains all the raw data presented in the Figures of this manuscript<br>
description: Raw images used for quantification and not shown in the manuscript are available upon reasonable request
DOI: 10.6084/m9.figshare.24166656
title: Grounded theory coding of interview transcriptions and observation notes

description: I used the combined observations, notes, and interview transcripts in subsequent grounded theory coding analysis. The grounded theory methodology extracts insights and theories from abstractions and narratives, using codes to flag incidence in the data (Urquhart, 2017). The analysis consists of six steps, producing initial codes, axial codes, selective codes, and emerging themes at each progressive stage of analysis (Braun & Clarke, 2012).Firstly, I familiarized and scrutinized raw data in their unprocessed forms, in this case consist of transcripts, recordings, and notes. This allows generation of initial, posteriori codes (as supposed to priori codes from the literature review) at the semantic and latent level of understanding. While semantic meaning can be revealed through narratives, the latent level of understanding requires additional consideration of non-verbal cues such as tones of speech (Swain, 2018). From the initial codes, I constructed axial codes and subsequently selective codes by categorization. The selective codes underline emerging themes and subthemes that project a synthesized response to the research question (Urquhart, 2017). During this process of categorization and pruning, I constantly reviewed codes and themes to eliminate redundancy.
DOI: 10.18465/fdaf20cc-9feb-4c8a-9131-3c623bd3a20f
title: MNT Guérinière 2021

description: Modèle Numérique de Terrain obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.18465/7c404431-0c17-43a8-a20e-4f4d56d93615
title: MNS Guérinière 2017

description: Modèle Numérique de Surface obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.18465/2ec60933-331d-4035-8790-2a9e156b7fe9
title: MNS Guérinière 2021

description: Modèle Numérique de Surface obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.18465/f44b153d-d770-4581-9cde-10392995fc23
title: MNT Guérinière 2018

description: Modèle Numérique de Terrain obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.57841/casdc.0002460
title: 30kW电堆及系统模块测试数据、报告及产能证明材料数据集
DOI: 10.18465/ffa1dda3-ccaf-4bb9-8a01-ee39491a0a1e
title: MNT Guérinière 2017

description: Modèle Numérique de Terrain obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.57841/casdc.0002461
title: 双极板测试数据、报告及生产线证明材料数据集
DOI: 10.57841/casdc.0002462
title: 非氟离子传导膜测试数据、报告及生产线证明材料数据集
DOI: 10.18465/6f0c8104-1899-4d36-9244-b73aad2f834a
title: MNT Guérinière 2020

description: Modèle Numérique de Terrain obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.5281/zenodo.8093234
title: IL-27 increases energy storage in white adipocytes by enhancing glucose uptake and fatty acid esterification

description: Data set associated with a submitted paper.
DOI: 10.5281/zenodo.8093235
title: IL-27 increases energy storage in white adipocytes by enhancing glucose uptake and fatty acid esterification

description: Data set associated with a submitted paper.
DOI: 10.5281/zenodo.8362620
title: IL-27 increases energy storage in white adipocytes by enhancing glucose uptake and fatty acid esterification

description: Data set associated with a submitted paper.
DOI: 10.5281/zenodo.8362627
title: IL-27 increases energy storage in white adipocytes by enhancing glucose uptake and fatty acid esterification

description: Data set associated with a submitted paper.
DOI: 10.57841/casdc.0002463
title: 气化粗渣化学活化铝硅分质利用技术中试数据集
DOI: 10.18465/80669856-b32d-43cf-bd96-484754fa1016
title: MNS Guérinière 2020

description: Modèle Numérique de Surface obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.57841/casdc.0002464
title: 2000t/天气流床气化炉气化渣铝硅 分质利用工程应用解决方案
DOI: 10.18465/776b4ebd-f1da-46e7-bfdb-619d1dbef79c
title: MNT Guérinière 2019

description: Modèle Numérique de Terrain obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.18465/79aa7da8-092c-4cd0-80bb-278ae1a19ab7
title: MNS Guérinière 2019

description: Modèle Numérique de Surface obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.5281/zenodo.8362606
title: Mechanical design BLAZE pilot plant components

description: Mechanical design BLAZE pilot plant components related to WP5, D5.3
DOI: 10.5281/zenodo.8362607
title: Mechanical design BLAZE pilot plant components

description: Mechanical design BLAZE pilot plant components related to WP5, D5.3
DOI: 10.5281/zenodo.8362619
title: Mechanical design BLAZE pilot plant components

description: Mechanical design BLAZE pilot plant components related to WP5, D5.3
DOI: 10.18465/d47db41d-31c1-4b17-ac41-e133e9462051
title: MNS Guérinière 2018

description: Modèle Numérique de Surface obtenu par LiDAR sur la côte vendéenne au niveau de la Guérinière
DOI: 10.6084/m9.figshare.23925291.v4
title: Dataset Artificial warming decreases heterotroph densities and trophic transfer efficiency

description: This file holds the data and scripts used in the article "Artificial warming decreases heterotroph densities and trophic transfer efficiency".Data are available in files whose name begins with the prefix "df". The variables names "date" and "date_c" represent the sampling date in discrete or continue value, respectively. "mesocosm_ID" is the identity of the mesocosm. "fish" represent the fish treatment (NF for no fish, CF for cold fish and WF for warm fish). "warming" is the temperature treatment (NW for no warming, W for warming). "tmean15" is the mean temperature of the 15 days prior to the sampling date. "compartment", "class", "order" and "taxa" represent the taxonomy of the organisms. "N_l" is the density per liter. "C_mug_l" is the carbon biomass in microgram per liter. "C_mug" is the individual carbon biomass. "S" and "H" are the species richness and the Shannon diversity index, respectively. "ZP" is the zooplankton:phytoplankton biomass ratio. The variables in df_bss.csv file are described in the main text of the article.Files with a numeric prefix are the scripts used for the statistical analyzes (multivariate analyzes, ecological index, community density and biomass, individual biomass, Predator Prey Biomass Ratio and Biomass Size Spectra).
DOI: 10.21942/uva.19506658
title: Aggregated dataset and readme file

description: Dataset for the paper: Willful ignorance: a Meta-analysis
DOI: 10.21942/uva.19506658.v1
title: Aggregated dataset and readme file

description: Dataset for the paper: Willful ignorance: a Meta-analysis