cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28816991
title: Supplementary Material for: Intramedullary Glioblastoma as one of multiple radiation-induced neoplasms: Case Report

description: Background
Intramedullary glioblastoma is a rare entity comprising 1,4-9% of spinal gliomas. Spinal cord radiation-induced gliomas are unique, with only thirteen cases reported to date.
Case presentation
A 53-year-old female with a history of mediastinal Hodgkin lymphoma treated with chemotherapy and radiotherapy who subsequently developed thyroid cancer and breast cancer throughout her life, was admitted due to slowly progressing spastic tetraparesis. Cervical MRI revealed an intramedullary lesion at the C4-T1 level, enlarging the spinal cord, with a heterogenous contrast enhancement and a lesion within T1 vertebral body showing contrast enhancement. Whole body 18F-FDG-PET/CT revealed increased radionuclide uptake within the cervical spinal cord at the C2-C7 level and a focus of increased metabolic activity within the T1 vertebral body. The patient underwent a C4-T2 laminectomy with tumor debulking, and a biopsy of the T1 vertebral body was taken. Closure was performed with thecal sac expansion using a fascia lata graft, and laminoplasty was performed using the open-door technique. Postoperatively, the patient experienced progression of lower extremities and left arm paresis. The histomolecular results confirmed the diagnosis of Glioblastoma, IDH-wildtype (CNS WHO G4) in the cervical spinal cord lesion and breast cancer metastasis in the T1 vertebral body. No adjuvant therapy was administered due to neurological deficit progression. The patient died 6 months after surgery.
Conclusion
We report a case of an intramedullary glioblastoma in a patient with a history of radiation and multiple neoplasms located at the irradiation field borders. The full molecular analysis allowed for classification of the tumor as Glioblastoma, IDH-wildtype (CNS WHO G4) and screening for germinal mutations potentially predisposing to spontaneous neoplasm development.
DOI: 10.6103/share.w6.800
title: Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 6
DOI: 10.7289/v5736p36
title: NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2 Cloud and Moisture Imagery Products (CMIP)

description: The Cloud and Moisture Imagery product contains one or more Earth-view images with pixel values identifying brightness values that are scaled to support visual analysis. The product includes data quality information that provides an assessment of the cloud and moisture imagery data values for on-earth pixels. Cloud and Moisture Imagery product files are generated for each of the sixteen Advanced Baseline Imager (ABI) reflective bands (channels 1 - 6 with approximate central wavelengths 0.47, 0.64, 0.865, 1.378, 1.61, 2.25 microns respectively) and emissive bands (channels 7 - 16 with approximate central wavelengths 3.9, 6.185, 6.95, 7.34, 8.5, 9.61, 10.35, 11.2, 12.3, 13.3 microns respectively). In addition, there is a multiband product file where the imagery at all bands is included. The imagery value for the reflective bands, ABI bands 1 through 6, is a dimensionless reflectance factor quantity that is normalized by the solar zenith angle. These bands support the characterization of clouds, vegetation, snow/ice, and aerosols. The imagery value for the emissive bands, ABI bands 7 through 16, is the brightness temperature at the Top-Of-Atmosphere (TOA) in Kelvin. These bands supports the characterization of the surface, clouds, water vapor, ozone, volcanic ash and dust based on emissive properties. The ABI instrument operates on board the NOAA Geostationary Operational Environmental Satellite-R (GOES-R) Series weather satellites providing advanced imagery and atmospheric measurements of Earth’s Western Hemisphere. There are three spatial coverage scenes per satellite (GOES East and GOES West): Full Disk is the full hemispheric view; Contiguous U.S. is the lower 48 states; and Mesoscale 1 and 2 are for weather event views.
DOI: 10.7289/v5d21vhz
title: Global Historical Climatology Network - Daily (GHCN-Daily), Version 3
DOI: 10.15156/bio/sh0892108.09fu
title: SH0892108.09FU

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: 10.17909/a61h-f081
title: Data from paper: "Dissecting the Mid-Infrared Heart of M83 with JW"

description: MIRI/MRS observations of the nucleus of the spiral galaxy M83.
DOI: 10.18112/openneuro.ds003126.v1.1.0
title: MRI Lab Graz: Reading-related functional activity in children with isolated spelling deficits and dyslexia
DOI: 10.18434/t42s31
title: NIST-JANAF Thermochemical Tables - SRD 13
DOI: 10.21951/hilarri/1960141
title: Hydropower Infrastructure - LAkes, Reservoirs, and RIvers (HILARRI), V2

description: HILARRI Version 2 is a database of links between major datasets of operational hydropower dams and powerplants (National Inventory of Dams (2021), Global Reservoir and Dam Database (GRanD v1.3), Existing Hydropower Assets (EHA 2022), and inland water bodies (NHDPlusV2 river network, NHD water bodies, NHD Watershed Boundary Dataset, HydroLAKES).
DOI: 10.22008/fk2/hmldvh
title: Diamond exploration and prospectivity of Greenland. Gov Greenland Department of Geology Record 1, 228 pp.

description: Greenland is dominated by cratonic blocks that provide conditions for the formation of diamonds. Pre-1.6 Ga rocks are exposed over 43% of ice-free land and many basins in younger areas evidence underlying Archean basement. Studies of mantle xenoliths reveal thick mantle lithosphere to 220 km in the North Atlantic Craton of western Greenland. Kimberlites, ultramafic lamprophyres and lamproites are known to be exposed abundantly, and span 1632 Ma of geological time. With carbonatites, 3029 discrete bedrock diamond-prospective occurrences have been identified. Known diamondiferous bodies are well represented over Greenland’s west coast, most notably the Garnet Lake 4 metre-thick composite aillikite / kimberlite sheet at Sarfartoq, and aillikite sheets at Qeqertaa, Disko Bay. Data from these, and other localities, demonstrate the potential for Greenland to host diamondiferous bodies with large, good quality diamonds in potentially economic concentrations. While preserved pipes may be discovered at higher elevations, the rarity of known pipes and diatremes evidences extensive glacial erosion and raises the potential for offshore and paleoplacer deposits. The Government of Greenland’s Diamond exploration data package is used to conduct a regional diamond prospectivity analysis. Most prior exploration targeted diamond indicator minerals in alluvial and glaciogenic samples averaging 10 kg in weight, and with inspection of recovered indicators concluding that sampling strategies have been adequate. Indicator minerals, including garnet, all reveal mineral chemistries consistent with deep mantle sources, often within the diamond stability field, and ilmenite compositions often support very high diamond preservation. All geographic subdivisions overlap chemistries of indicators from diamond-producing areas of Canada. The North Atlantic Craton of West Greenland and the Ketilidian Orogen of southern Greenland show particularly consistent diamond-prospective chemistries, while the Rae Craton of western Greenland is more variable. Quantitative prospectivity modelling incorporating geophysical data emphasises the importance of these regions but also highlights potential in the under-explored Inglefield Orogen and North Atlantic Craton of eastern Greenland. Historical data, compared with more regional, indirect prospectivity metrics show that further opportunities for diamond exploration exist in Greenland in selected areas of the west coast, as well as within less-explored areas such as eastern and northern regions, and offshore.
DOI: 10.22008/fk2/syal4j
title: Geological map of Greenland 1:2 500 000

description: Geological map onshore and offshore Greenland, 1:2,500,000
DOI: 10.23729/cdfd937c-37d5-46b0-9c16-f6e0c10bc81f
title: ISUH waveform, time and location data products from stimulations of deep geothermal wells in Espoo in 2020

description: In summer 2020 the energy company St1 carried out its second stimulation of deep geothermal wells in Otaniemi, Espoo, in the Helsinki metropolitan area, southern Finland. Institute of Seismology of University of Helsinki (ISUH) monitored the induced seismicity during the stimulation, and also months before and after it. This dataset comprises 85 induced earthquakes that occurred between 8 March 2020 to 8 December, 2020, with local magnitudes between -1.1 and 1.4. Waveform, location and timing data have been produced at ISUH using seismic stations of the Finnish National Seismic Network (doi: 10.14470/UR044600) including the Helsinki local broadband network, the temporary HEL broadband network in Helsinki and Espoo, the temporary borehole network of St1 (doi: 10.1785/0220190253), and a pool of lightweight mobile seismic instruments operated by ISUH (GIPP data cubes, doi: 10.5880/GIPP.201925.1; SmartSolos and Refteks, doi: 10.1785/0220210195). The deployment is described in Rintamäki et al., 2021, A Seismic Network to Monitor the 2020 EGS Stimulation in the Espoo/Helsinki Area, Southern Finland, doi:10.1785/0220210195. Event data, event metadata, and station metadata are provided in distinct directories, and for event data, each event is assigned a subdirectory. Data formats follow generally accepted seismological standards.
DOI: 10.24381/cds.4991cf48
title: ERA5 post-processed daily statistics on single levels from 1940 to present
DOI: 10.24381/cds.f17050d7
title: ERA5 monthly averaged data on single levels from 1940 to present
DOI: 10.24432/c56c76
title: Iris
DOI: 10.24432/c59012
title: Statlog (Australian Credit Approval)
DOI: 10.24432/c5nc77
title: Statlog (German Credit Data)
DOI: 10.26133/nea2
title: Composite Planet Data Table

description: The Composite Planet Data table provides a collection of stellar and planetary parameters for confirmed exoplanets, one row per planet. The table automatically selects the data from other available literature references for the same planet to fill in gaps from the default literature reference. This table has been retired as of 2021 and it has been replaced by the Planetary Systems Composite Parameters table (10.26133/NEA13).

This dataset or service is made available by the NASA Exoplanet Science Institute at IPAC, which is operated by the California Institute of Technology under contract with the National Aeronautics and Space Administration.
DOI: 10.5066/p9wfou5l
title: Survival, growth, behavior and mercury concentrations of mayflies exposed to elevated dietary methylmercury and aqueous selenium

description: Survival and size of mayflies at each life stage, as well as MeHg concentrations in diatoms and mayflies exposed to low and high MeHg concentrations and a range of selenomethione (SeMet) concentrations.
DOI: 10.5067/p8bn9vo9n5c7
title: Global PyGEM-OGGM Glacier Projections with RCP and SSP Scenarios, Version 1
DOI: 10.5067/vjafpli1csiv
title: MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4
DOI: 10.5281/zenodo.11267157
title: Age of stratospheric air: observational data sets

description: This dataset of mean stratospheric age of air is a compilation of data calculated from trace gas observations of CO2 and SF6 on Satellite, Aircraft and Balloon platforms.It provides 1) zonal mean monthly mean values from satellite data, 2) climatological data for different latitude bands from aircraft and balloon data, and 3) the time-series of mean age of air in the northern mid-latitude mid-stratosphere (updating Engel et al, 2009, 2017). Moreover, input data for the calculation of mean age of air from trace gases is provided (reference time series and ratio of moments). 

This data set is a supplement to Garny et al, 2024: "Age of stratospheric air: Progress on processes, observations and long-term trends" (Review of Geophysics, accepted). See Readme for more information.
DOI: 10.5281/zenodo.1257218
title: Priority Fuzzy Database Management System Implementation Based On Gpfcsp Extensions To The Xquery Language

description: Experimental dataset and source code of the FXI - a priority fuzzy database management system including fuzzy extensions to the XQuery Language
DOI: 10.5281/zenodo.12609025
title: Collapse and recovery of livestock systems shape fire regimes on the Eurasian steppe: a review of ecosystem and biodiversity implications

description: This file contains bibliographic data from the literature research; livestock and fire data as well as Google Earth Engine and R-scripts to reproduce all analyses and figures.
DOI: 10.5281/zenodo.13831121
title: MESA inlists for the paper Quantifying systematic uncertainties in white dwarf cooling age determinations

description: This repository contains the work directories for running the MESA models presented in the paper "Quantifying systematic uncertainties in white dwarf cooling age determinations".

1. Contents



MESA model work directories

'wd_builder' work directory for creating initial white dwarf models

'all_compositions_fitted' directory containing Oxygen abundance profiles.


2.  Requirements



MESA version: r23.05.1

MESASDK version x86_64-linux-22.6.1.

Proper environment variables must be set up before running MESA (see MESA documentation)


3.  Directory Structure



 'all_compositions_fitted'


This directory contains Oxygen abundance profiles for 0.6 Msun white dwarf from various evolutionary models and asteroseismological studies. These profiles were used to inform the parameter space sampled in this work.



'wd_builder'


This directory contains inlists for the MESA tool 'wd_builder'. It uses an initial composition file 'composition.dat' to create an initial white dwarf model called 'saved.mod'.



 'phase_sep'


This directory contains the inlists for white dwarf evolution, modified from the inlists of Bauer 2023. It uses the initial white dwarf model 'saved.mod' and creates an evolved, cooled white dwarf model at 3000K called 'final.mod'.

4.  Usage



 Set up the MESA environment variables as per the MESA documentation.

 Use the 'wd_builder' directory to create an initial white dwarf model:



Ensure 'composition.dat' is present in the directory.

Run the MESA 'wd_builder' tool to generate 'saved.mod'



Use the 'phase_sep' directory to evolve the white dwarf model:



Copy or move 'saved.mod' to this directory.

Run the MESA evolution script to generate 'final.mod'.




5.  References



 Bauer, E. B. (2023). MESA inlists for white dwarf evolution. Zenodo. https://zenodo.org/records/7846751


For more details on the research methodology and results, please refer to the full paper: "Quantifying systematic uncertainties in white dwarf cooling age determinations".
DOI: 10.5281/zenodo.13899448
title: Data repository for Uniaxial compression of 3D printed samples with voids: laboratory measurements compared with Effective Medium Theory
DOI: 10.5281/zenodo.14191280
title: A global expert elicitation on present-day human-fire interactions: data & analysis code

description: These files support "A global expert elicitation on present-day human-fire interactions", accepted for publication in the Philosophical Transactions of the Royal Society B. doi: 10.1098/rstb.2023-0463

The files contain data from a survey of experts on human-fire interactions as well as code used to process and analyse it.

An overview of the files is given below. 

1) Data

Raw survey data are provided by geographic region ("GFUS_region"). Data processed to produce analyses in the associated paper are provided as "GFUS_Processed".

Columns in data files are named by the question of the survey that generated them (Q1b through Q90). The contents of the associated questions that were asked are given in the data_dictionary.xlsx file.

- GFUS_spatial provides the data merged with a shapefile of the survey regions. 

- "Gov_compare" and "LIFE_SH_fire" provide files to compare survey data with the DAFI and LIFE literature meta-analyses (see Supplementary 3 to the main text).

- Question meta-data and question-summary provides an overview of the questions, as well as a topline overview of the numbers of responses and internal coherence (entropy) of survey responses. 

2) Code

4 scripts are provided. 

- Firstly the script that was used to summarise survey responses by geographic region (Summarise_by_region)- Secondly the code used to conduct statistical tests presented in the paper- Thirdly the code used to produce plots in the paper- Fourthly the code used to produce topline descriptive statistics presented in the paper
DOI: 10.5281/zenodo.14227217
title: Post-fire spectral recovery and driving factors across the boreal and temperate forests
DOI: 10.5281/zenodo.3114194
title: High-spatial-resolution monthly precipitation dataset over China during 1901–2017

description: The dataset with 0.5 arcminute (~1 km) was spatially downscaled from CRU TS v4.02 based on Delta downscaling method, including monthly precipitation from 1901.1 to 2017.12. The dataset covers the main land area of China. The dataset was evaluated by 496 national weather stations across China, and the evaluation indicated that the downscaled dataset is reliable for the investigations related to climate change across China. Another data download site is Loess plateau Scientific Data Center (http://loess.geodata.cn/). This is a Chinese website. This website publishes the updated histrorical dataset and future downscaled monthly precipitation under multiple SSP Scenarios and GCMs, with 1 km spatial resolution. /*************/ The dataset is updated yearly. Now, the period of the dataset is from 1901.1 to 2020.12. /*************/ The future 1km dataset from 2021-2100 is published. <br> The data provider recommended the below publication as the reference.<br> Peng Shouzhang, Ding Yongxia, Liu Wenzhao, Li Zhi. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Earth System Science Data, 2019, 11, 1931–1946, https://doi.org/10.5194/essd-11-1931-2019.
description: {"references": ["Peng Shouzhang, Ding Yongxia, Liu Wenzhao, Li Zhi. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Earth System Science Data, 11, 1931\u20131946, https://doi.org/10.5194/essd-11-1931-2019, 2019."]}
DOI: 10.5281/zenodo.3996814
title: Global vegetation productivity from 1981 to 2018 estimated from remote sensing data

description: The  MUltiscale Satellite remotE Sensing (MUSES) global vegetation productivity dataset includes gross primary productivity (GPP) and net primary productivity (NPP) data from 1981 to 2018. GPP and NPP were estimated with a light use efficiency (LUE) model and  MUSES leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR) products.

The MUSES product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/).

The detail information of the MUSES 5-km global GPP and NPP products are as below:

Name: MUSES 5-km global GPP and NPP products

Period: 1981-2018

Spatial resolution: 0.05°

Temporal resolution: 8 days

Projection: geographic latitude/longitude

Data format: Tiff

Data type: integer (16bit)

Upper left coordinates: -180°E, 90°N

Scale factor: 100

Unit: gCm-2d-1

 

Citation (Please cite these papers  when these data are used)

1. Wang, J.M., Sun, R., Zhang, H.L., Xiao, Z.Q., Zhu A.R., Wang, M.J., Yu, T., Xiang, K.L., New global MuSyQ GPP/NPP remote sensing products from 1981 to 2018. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14, 5596-5612.

2. Wang, M.J.; Sun, R.; Zhu, A.R.; Xiao, Z. Q. Evaluation and Comparison of Light Use Efficiency and Gross Primary Productivity Using Three Different Approaches. Remote Sensing. 2020, 12, 1003.

3. Yu, T.; Sun, R.; Xiao, Z.Q. ;Zhang , Q.; Liu, G.; Cui, T.X.; Wang, J.M. Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data. Remote sensing. 2018, 10, 327.
description: This dataset was supported by the National Key R&D Program of China (2017YFA0603002, 2016YFB0501502).
DOI: 10.5281/zenodo.4587955
title: Silva 138.1 prokaryotic SSU taxonomic training data formatted for DADA2

description: These training fasta files are derived from the Silva Project's version 138.1 release and formatted for use with DADA2. These files are intended for use in classifying prokaryotic 16S sequencing data and are not appropriate for classifying eukaryotic ASVs. See https://benjjneb.github.io/dada2/training.html for information about DADA2 reference databases and https://www.arb-silva.de/documentation/release-138.1/ for database and citation information for Silva 138.1. The Silva 138.1 database is licensed under Creative Commons Attribution 4.0 (CC-BY 4.0); see file "SILVA_LICENSE.txt". These fasta database files were generated and checked for consistency using the R markdown documents in the silva-138.1 folder in https://zenodo.org/record/4587946. If you use these files, please cite one or both of the Silva references below (or at the above link) and the DADA2 paper (reference below). I also recommend citing or linking to the Zenodo record for this specific version in your Methods or published source code to record the specific taxonomic database files used in your analysis. <strong>NOTE:</strong> These database files have a known problem in 3/895 families and 59/3936 genera. See https://github.com/mikemc/dada2-reference-databases/blob/main/silva-138.1/v1/bad-taxa.csv for a list of affected taxa and https://github.com/benjjneb/dada2/issues/1293 for more information.
description: {"references": ["Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Gl\u00f6ckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl. Acids Res. 41 (D1): D590-D596.", "Yilmaz P, Parfrey LW, Yarza P, Gerken J, Pruesse E, Quast C, Schweer T, Peplies J, Ludwig W, Gl\u00f6ckner FO (2014) The SILVA and \"All-species Living Tree Project (LTP)\" taxonomic frameworks. Nucl. Acids Res. 42:D643-D648", "Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. 2016. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 13:581\u2013583. doi:10.1038/nmeth.3869"]}