cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6369914
title: SciExpeM - 10.5281/zenodo.6369915

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369917
title: SciExpeM - 10.5281/zenodo.6369917

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369916
title: SciExpeM - 10.5281/zenodo.6369917

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369919
title: SciExpeM - 10.5281/zenodo.6369919

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369918
title: SciExpeM - 10.5281/zenodo.6369919

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369921
title: SciExpeM - 10.5281/zenodo.6369921

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369920
title: SciExpeM - 10.5281/zenodo.6369921

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369924
title: SciExpeM - 10.5281/zenodo.6369924

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369923
title: SciExpeM - 10.5281/zenodo.6369924

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369926
title: SciExpeM - 10.5281/zenodo.6369926

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369928
title: SciExpeM - 10.5281/zenodo.6369928

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369925
title: SciExpeM - 10.5281/zenodo.6369926

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369927
title: SciExpeM - 10.5281/zenodo.6369928

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369938
title: Data for Figures1-4

description: These files are the original data for Figures 1 to 4
DOI: 10.5281/zenodo.6367300
title: Data for Figures1-4

description: These files are the original data for Figures 1 to 4
DOI: 10.6084/m9.figshare.19387106
title: Screening app COVID-19 in Indonesia.pdf

description: The data consists of COVID-19 mHealth apps in Indonesia that we used for systematic review.
DOI: 10.6084/m9.figshare.19387106.v1
title: Screening app COVID-19 in Indonesia.pdf

description: The data consists of COVID-19 mHealth apps in Indonesia that we used for systematic review.
DOI: 10.6084/m9.figshare.19387112
title: Striped Cuckoo raw database

description: Data employed for statistical analyses<br>
DOI: 10.6084/m9.figshare.19387112.v1
title: Striped Cuckoo raw database

description: Data employed for statistical analyses<br>
DOI: 10.34945/f5q597
title: Combined dataset of Rodent Gambling Task in rats after brain injury

description: STUDY PURPOSE: The goal of this analysis set was to compare data collected across four separate studies, all of which evaluated the effects of traumatic brain injury on the Rodent Gambling Task (RGT). This combined data would have sufficient power to analyze both overall and trial-by-trial outcomes. DATA COLLECTED: Data were collected across four studies comprising training and testing on the RGT. Three studies were bilateral frontal controlled cortical impact injuries and one was unilateral, parietal controlled cortical impact. Two trained rats before injury, and two after. A total of 109 rats in TBI or Sham conditions (no other manipulations) can be extracted from these data. Two of these studies are published, one is in review, and one is in preparation for publication. DATA USAGE NOTES:
DOI: 10.12751/g-node.74jj3f
title: CSF Biomarkers in early MS

description: This repository contains the dataset, upon which the article "IL-2, IL-6 and chitinase 3-like 2 might predict early relapse activity in multiple sclerosis" submitted to PLOS ONE in march 2022 was based. The dataset consists of clinical, CSF, serum and MRI findings from 58 patients treated at the MS Centre of the Motol University Hospital between January 2017 and May 2018 and a control group.
description: IsSupplementTo: Petržalka M, Meluzínová E, Libertínová J, Mojžišová H, Hanzalová J, Ročková P, et al. IL-2, IL-6 and chitinase 3-like 2 might predict early relapse activity in multiple sclerosis. PLoS One.
DOI: 10.5281/zenodo.6369955
title: SciExpeM - 10.5281/zenodo.6369955

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369954
title: SciExpeM - 10.5281/zenodo.6369955

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369964
title: SciExpeM - 10.5281/zenodo.6369964

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369963
title: SciExpeM - 10.5281/zenodo.6369964

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369966
title: SciExpeM - 10.5281/zenodo.6369966

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369965
title: SciExpeM - 10.5281/zenodo.6369966

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369968
title: SciExpeM - 10.5281/zenodo.6369968

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369967
title: SciExpeM - 10.5281/zenodo.6369968

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369971
title: SciExpeM - 10.5281/zenodo.6369971

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369970
title: SciExpeM - 10.5281/zenodo.6369971

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369973
title: SciExpeM - 10.5281/zenodo.6369973

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369972
title: SciExpeM - 10.5281/zenodo.6369973

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369975
title: SciExpeM - 10.5281/zenodo.6369975

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369974
title: SciExpeM - 10.5281/zenodo.6369975

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369977
title: SciExpeM - 10.5281/zenodo.6369977

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369976
title: SciExpeM - 10.5281/zenodo.6369977

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369979
title: SciExpeM - 10.5281/zenodo.6369979

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369978
title: SciExpeM - 10.5281/zenodo.6369979

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369981
title: SciExpeM - 10.5281/zenodo.6369981

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369980
title: SciExpeM - 10.5281/zenodo.6369981

description: Cai, Liming; Jacobs, Sascha; Langer, Raymond; Vom Lehn, Florian; Heufer, Karl Alexander; Pitsch, Heinz - Fuel, 2020, (264), 116711
DOI: 10.5281/zenodo.6369996
title: Evaluation of changes to work patterns in multidisciplinary cancer teams due to the COVID-19 pandemic: a national mixed-method survey study

description: The survey responses evaluating changes to work patterns in multidisciplinary cancer teams due to COVID-19 were compiled into a SPSS dataset, and the qualitative responses into an excel spreadsheet.
DOI: 10.5281/zenodo.6369994
title: Evaluation of changes to work patterns in multidisciplinary cancer teams due to the COVID-19 pandemic: a national mixed-method survey study

description: The survey responses evaluating changes to work patterns in multidisciplinary cancer teams due to COVID-19 were compiled into a SPSS dataset, and the qualitative responses into an excel spreadsheet.
DOI: 10.34740/kaggle/dsv/3324040
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.34740/kaggle/dsv/3324073
title: 2021 World Population (updated daily)
DOI: 10.25345/c5cf9j95w
title: MassIVE MSV000089082 - Integrated multi-omics reveals anaplerotic rewiring in methylmalonyl-CoA mutase deficiency_Metabolomics
title: Multi-layered omics technologies can help define relationships between genetic factors, biochemical processes and phenotypes thus extending research of monogenic diseases beyond identifying their cause. We implemented a multi-layered omics approach for the inherited metabolic disorder methylmalonic aciduria. We performed whole genome sequencing, transcriptomic sequencing, and mass spectrometry-based proteotyping from matched primary fibroblast samples of 230 individuals (210 affected, 20 controls) and related the molecular data to 105 phenotypic features. Integrative analysis identified a molecular diagnosis for 84% (179/210) of affected individuals, the majority (150) of whom had pathogenic variants in methylmalonyl-CoA mutase (MMUT). Untargeted integration of all three omics layers revealed dysregulation of TCA cycle and surrounding metabolic pathways, a finding that was further supported by multi-organ metabolomics of a hemizygous Mmut mouse model. Stratification by phenotypic severity indicated downregulation of oxoglutarate dehydrogenase and upregulation of glutamate dehydrogenase in disease. This was supported by metabolomics and isotope tracing studies which showed increased glutamine-derived anaplerosis. We further identified MMUT to physically interact with both, oxoglutarate dehydrogenase and glutamate dehydrogenase providing a mechanistic link. This study emphasizes the utility of a multi-modal omics approach to investigate metabolic diseases and highlights glutamine anaplerosis as a potential therapeutic intervention point in methylmalonic aciduria.
DOI: 10.5281/zenodo.6370003
title: Reference Datasets for: SHAFTS (v2022.3): a deep-learning-based Python package for Simultaneous extraction of building Height And FootprinT from Sentinel Imagery

description: These are reference building height and footprint datasets which consist of 46 cities worldwide and support the development of SHAFTS (https://github.com/LllC-mmd/3DBuildingInfoMap).
DOI: 10.6084/m9.figshare.17209613.v11
title: Appraising the effect of potential risk factors on thyroid cancer: A Mendelian randomization study

description: Appraising the effect of potential risk factors on thyroid cancer: A Mendelian randomization study
DOI: 10.6084/m9.figshare.19387376
title: Date.xlsx

description: Circulating tumor DNA (ctDNA) has been increasingly proposed as a biomarker for characterizing and monitoring minimal residual disease (MRD) in various solid cancers, e.g., breast cancer and lung cancer. However, such studies for intracranial gliomas remain very few. Cerebrospinal fluid (CSF) is a promising source of ctDNA but still not enough for in-depth application. In this background, here, we reported on glioma cases: 1. Tumor in-situ fluid (TISF) is the local fluid at the tumor site after surgical resection. Through an intraoperatively implanted Ommaya reservoir, we obtained it postoperatively for ctDNA analysis. 2. TISF ctDNA could reflect the existence of MRD in glioma patients although no malignancy was observed by MRI. 3. Sequential follow-up TISF ctDNA could track the molecular evolution of MRD and identify pseudoprogression (PsP) after surgery. To the best of our knowledge, it is the first evidence of TISF-based liquid biopsy for glioma, which would intrigue scholars and start new conversations in this field.
DOI: 10.6084/m9.figshare.19387376.v2
title: Date.xlsx

description: Circulating tumor DNA (ctDNA) has been increasingly proposed as a biomarker for characterizing and monitoring minimal residual disease (MRD) in various solid cancers, e.g., breast cancer and lung cancer. However, such studies for intracranial gliomas remain very few. Cerebrospinal fluid (CSF) is a promising source of ctDNA but still not enough for in-depth application. In this background, here, we reported on glioma cases: 1. Tumor in-situ fluid (TISF) is the local fluid at the tumor site after surgical resection. Through an intraoperatively implanted Ommaya reservoir, we obtained it postoperatively for ctDNA analysis. 2. TISF ctDNA could reflect the existence of MRD in glioma patients although no malignancy was observed by MRI. 3. Sequential follow-up TISF ctDNA could track the molecular evolution of MRD and identify pseudoprogression (PsP) after surgery. To the best of our knowledge, it is the first evidence of TISF-based liquid biopsy for glioma, which would intrigue scholars and start new conversations in this field.
DOI: 10.6084/m9.figshare.19387376.v1
title: Date.xlsx

description: Circulating tumor DNA (ctDNA) has been increasingly proposed as a biomarker for characterizing and monitoring minimal residual disease (MRD) in various solid cancers, e.g., breast cancer and lung cancer. However, such studies for intracranial gliomas remain very few. Cerebrospinal fluid (CSF) is a promising source of ctDNA but still not enough for in-depth application. In this background, here, we reported on glioma cases: 1. Tumor in-situ fluid (TISF) is the local fluid at the tumor site after surgical resection. Through an intraoperatively implanted Ommaya reservoir, we obtained it postoperatively for ctDNA analysis. 2. TISF ctDNA could reflect the existence of MRD in glioma patients although no malignancy was observed by MRI. 3. Sequential follow-up TISF ctDNA could track the molecular evolution of MRD and identify pseudoprogression (PsP) after surgery. To the best of our knowledge, it is the first evidence of TISF-based liquid biopsy for glioma, which would intrigue scholars and start new conversations in this field.
DOI: 10.5519/qd.ntjgp2ap
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (6149 records)
DOI: 10.5281/zenodo.4314249
title: F.A.I.R. open dataset of brushed DC motor faults for testing of AI algorithms

description: Practical research in AI often lacks of available and reliable datasets so the practitioners can try different algorithms. The field of predictive maintenance is particularly challenging in this aspect as many researchers don't have access to full-size industrial equipment or there is not available datasets representing a rich information content in different evolutions of faults. This dataset presents the evolution of typical faults (commutator, winding and brush wear) in inexpensive DC motors under extensive monitoring (vibration, temperature, voltage, current and noise). These motors exhibit a particularly short useful life when operating out of nominal conditions (from 30 minutes to 6 hours) which make them very interesting to test different signal processing algorithms and introduce students and researchers into signal processing, fault detection and predictive maintenance. The data-set comprises two main elements: A spreadsheet with the processing of each raw data file 4 folders with raw data files in HDF5 format The spread sheet contains the following columns filename of the raw data file timestamp of the raw data file speed of the motor in rpm speed of the motor in Hz Current of the moter (A) Voltage supply (V) surface motor temperature (ºC) ambient temperature (ºC) For each measured signal (Vibration, current, voltage) the vibration of the main harmonic (at the speed of the motor) and it's first 10 multiple. For each measured signal (Vibration, current, voltage) the vibration in 4 bands: 0-4kHz, 4kHz-8kHz, 8kHz-16kHz, 16kHz-26kHz The raw data files in HDF5 format contains the instantaneous measured vibration (g), current (A) and voltage (volts) of the DC motor at 51.200 Hz.
DOI: 10.5281/zenodo.4314248
title: F.A.I.R. open dataset of brushed DC motor faults for testing of AI algorithms

description: Practical research in AI often lacks of available and reliable datasets so the practitioners can try different algorithms. The field of predictive maintenance is particularly challenging in this aspect as many researchers don't have access to full-size industrial equipment or there is not available datasets representing a rich information content in different evolutions of faults. This dataset presents the evolution of typical faults (commutator, winding and brush wear) in inexpensive DC motors under extensive monitoring (vibration, temperature, voltage, current and noise). These motors exhibit a particularly short useful life when operating out of nominal conditions (from 30 minutes to 6 hours) which make them very interesting to test different signal processing algorithms and introduce students and researchers into signal processing, fault detection and predictive maintenance. The data-set comprises two main elements: A spreadsheet with the processing of each raw data file 4 folders with raw data files in HDF5 format The spread sheet contains the following columns filename of the raw data file timestamp of the raw data file speed of the motor in rpm speed of the motor in Hz Current of the moter (A) Voltage supply (V) surface motor temperature (ºC) ambient temperature (ºC) For each measured signal (Vibration, current, voltage) the vibration of the main harmonic (at the speed of the motor) and it's first 10 multiple. For each measured signal (Vibration, current, voltage) the vibration in 4 bands: 0-4kHz, 4kHz-8kHz, 8kHz-16kHz, 16kHz-26kHz The raw data files in HDF5 format contains the instantaneous measured vibration (g), current (A) and voltage (volts) of the DC motor at 51.200 Hz.
DOI: 10.6084/m9.figshare.12939854
title: Phylogenetic dependence of plant-soil feedback promotes rare species in a subtropical forest

description: seedlings growth data in the shade-house and field experiments
DOI: 10.6084/m9.figshare.12939854.v1
title: Phylogenetic dependence of plant-soil feedback promotes rare species in a subtropical forest

description: seedlings growth data in the shade-house and field experiments
DOI: 10.34740/kaggle/dsv/3324280
title: COVID Vaccination in World (updated daily)
DOI: 10.5281/zenodo.4925828
title: Simultaneous airglow imaging and two dimensional horizontally resolved wind-field observations over northern Germany

description: All-sky imager data at 630.0 nm airglow emission line from Kühlungsborn, Germany MMARIA wind data
DOI: 10.5281/zenodo.4308322
title: Simultaneous airglow imaging and two dimensional horizontally resolved wind-field observations over northern Germany

description: All-sky imager data at 630.0 nm airglow emission line from Kühlungsborn, Germany MMARIA wind data
DOI: 10.6084/m9.figshare.19386536.v1
title: source_data_and_codes

description: This repo contains the per-figure source data and codes to reproduce all plots represented in our manuscript. Each Figure panel was produced from individual plots using Adobe Illustrator (AI).
DOI: 10.25345/c57p8th27
title: MassIVE MSV000089083 - GNPS - Computational metabolomics tools reveal metabolic reconfig-urations underlying the effects of biostimulant seaweed extracts on maize plants under drought stress conditions_Positive Ionisation
title: Leave extracts, from maize plants with seaweed extract based biostimulant treatment under drought and normal conditions, analysed in positive ionisation.
DOI: 10.6084/m9.figshare.19386536.v3
title: source_data_and_codes

description: This repo contains the per-figure source data and codes to reproduce all plots represented in our manuscript. Each Figure panel was produced from individual plots using Adobe Illustrator (AI).
DOI: 10.6084/m9.figshare.19386536.v2
title: source_data_and_codes

description: This repo contains the per-figure source data and codes to reproduce all plots represented in our manuscript. Each Figure panel was produced from individual plots using Adobe Illustrator (AI).
DOI: 10.5281/zenodo.6370062
title: The dataset of the paper titled "Investigating End-Users' Values in Agriculture Mobile Applications Development: An Empirical Study on Bangladeshi Female Farmers"

description: This package includes a survey questionnaire, demographic questions, and 10 main values with corresponding attributes and the referred names used in this paper submitted to JSS.
DOI: 10.5281/zenodo.6370061
title: The dataset of the paper titled "Investigating End-Users' Values in Agriculture Mobile Applications Development: An Empirical Study on Bangladeshi Female Farmers"

description: This package includes a survey questionnaire, demographic questions, and 10 main values with corresponding attributes and the referred names used in this paper submitted to JSS.
DOI: 10.5281/zenodo.6370064
title: Coupled lithospheric deformation in the Qinling Orogen, central China: Insights from seismic reflection and surface-wave tomography

description: <strong>Data of geochronology of intrusive plutons and selected zircon Hf values shown in Figure S1 and the references cited</strong>
DOI: 10.5281/zenodo.6370063
title: Coupled lithospheric deformation in the Qinling Orogen, central China: Insights from seismic reflection and surface-wave tomography

description: <strong>Data of geochronology of intrusive plutons and selected zircon Hf values shown in Figure S1 and the references cited</strong>