cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/gsh9-k78
title: Probabilistic cytoarchitectonic map of Area Ig2 (Insula) (v14.0)

description: This dataset contains the distinct architectonic Area Ig2 (Insula) in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to both reference spaces, where each voxel was assigned the probability to belong to Area Ig2 (Insula). The probability map of Area Ig2 (Insula) is provided in the NifTi format for each brain reference space and hemisphere. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Other available data versions of Area Ig2 (Insula): Kurth et al. (2018) [Data set, v11.0] [DOI: 10.25493/N7C7-BHW](https://doi.org/10.25493%2FN7C7-BHW) Kurth et al. (2019) [Data set, v13.1] [DOI: 10.25493/662G-E0W](https://doi.org/10.25493%2F662G-E0W) The most probable delineation of Area Ig2 (Insula) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.13] [DOI: 10.25493/Q3ZS-NV6](https://doi.org/10.25493%2FQ3ZS-NV6) Amunts et al. (2019) [Data set, v1.18] [DOI: 10.25493/8EGG-ZAR](https://doi.org/10.25493%2F8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493%2FTAKY-64D) Amunts et al. (2020) [Data set, v2.4] [DOI: 10.25493/A7Y0-NX9](https://doi.org/10.25493%2FA7Y0-NX9) Amunts et al. (2020) [Data set, v2.5] [DOI: 10.25493/8JKE-M53](https://doi.org/10.25493/8JKE-M53)
DOI: 10.17632/d48d22wdy5.1
title: Review of experimental data on wastewater remediation of Biochemical oxygen demand (BOD) and Chemical oxygen demand (COD) by application of the hydroponic Vetiver system (HVS)

description: The author has reviewed seven studies that evaluate the wastewater remediation potential of Biochemical oxygen demand (BOD) and Chemical oxygen demand (COD) by application of the Vetiver Grass (VG) under hydroponic conditions. The removal efficiency datasets of BOD and COD by this hydroponic Vetiver system (HVS) are separately tabulated in Table-1 and Table-2, respectively.
DOI: 10.17632/gmd86p775b.1
title: Data for: Bipolar resistive switching characteristics of PbZrO3/LaNiO3 heterostructure thin films prepared by a sol-gel process

description: Data for: Bipolar resistive switching characteristics of PbZrO3/LaNiO3 heterostructure thin films prepared by a sol-gel process
DOI: 10.17632/t7ns4yb9mg.1
title: Different Types of Occurrence of Organic Matter in Mudstones, Dongying Sag, Bohai Basin, China

description: The data recorded the pyrolysis characteristics of different occurrence of organic matter in the sequential treatments.
DOI: 10.17632/23gf53n249.1
title: Outer-shelf conduit within growth-fault compartment Pliocene Orinoco Delta

description: The geometrical model of Orinoco Delta system and dynamic competition of rates among accommodation, sediment supply, and accumulation have been discussed in supplements (see details in Figs. X and Y, Table A and B).
DOI: 10.17632/rjf86nv3n6.1
title: Cereal and apple yield data from agroforestry and monoculture systems in the UK, 2018-2020

description: This dataset comprises cereal yield data from agroforestry and paired arable control systems, in addition to apple fruit count, width, and seed count data from agroforestry and orchard systems. The cereal data was collected from three working farms in the UK, each with paired agroforestry and arable fields under the same management. The agroforestry apple data was collected from five agroforestry sites in the UK, while orchard apples were sourced from a UK wholesaler, with the fruits originating from Kent, UK, except for organic Braeburn, which originated from Lower Saxony, Germany. Yield samples were taken shortly prior to harvest of the commercial crop. The agroforestry systems comprised 24 m wide crop alleys separated by rows of apple trees.
The data was collected to compare productivity of apple-cereal intercropping agroforestry systems with comparable monocultures of arable and orchards. Cereal yield data was collected between 2018 and 2020, while all apple data was collected in 2020. All data was collected by Tom Staton (University of Reading).
See the associated publication and Supplementary Material for further details of data collection and results.
DOI: 10.5281/zenodo.5535024
title: kittlein/Landscape v1.1

description: No description provided.
DOI: 10.5281/zenodo.4077438
title: kittlein/Landscape v1.1

description: No description provided.
DOI: 10.6084/m9.figshare.16695736
title: Appendix I. Trump's Tweets from Dec 19th, 2020 to Jan 7th, 2021 (20 days).docx

description: Appendix I for Trump's doublespeak language on Twitter prior to the Capitol insurrection, by Daniel López-Prior.
DOI: 10.6084/m9.figshare.16695904
title: Appendix II. Data Analysis

description: Appendix II. Data Analysis for Trump's doublespeak language on Twitter prior to the Capitol insurrection, by Daniel López-Prior.
DOI: 10.6084/m9.figshare.16695904.v1
title: Appendix II. Data Analysis

description: Appendix II. Data Analysis for Trump's doublespeak language on Twitter prior to the Capitol insurrection, by Daniel López-Prior.
DOI: 10.5281/zenodo.5105545
title: Dataset used in "Machine-learning Kondo physics using variational autoencoders"

description: Spectral functions from the single-impurity Anderson model, generated on a log-linear frequency mesh using the numerical renormalization group algorithm. Used in both https://doi.org/10.1103/PhysRevB.103.245118 (where a detailed description of dataset generation can be found) and https://arxiv.org/abs/2107.08013.
DOI: 10.5281/zenodo.5105544
title: Dataset used in "Machine-learning Kondo physics using variational autoencoders"

description: Spectral functions from the single-impurity Anderson model, generated on a log-linear frequency mesh using the numerical renormalization group algorithm. Used in both https://doi.org/10.1103/PhysRevB.103.245118 (where a detailed description of dataset generation can be found) and https://arxiv.org/abs/2107.08013.
DOI: 10.5517/ccdc.csd.cc27wwxy
title: CCDC 2082391: Experimental Crystal Structure Determination

description: Related Article: William Foley, Hadi Arman, Ghezai T. Musie|2021|J.Inorg.Biochem.|225|111589|doi:10.1016/j.jinorgbio.2021.111589
DOI: 10.5517/ccdc.csd.cc27zc8w
title: CCDC 2084758: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Constantin G. Daniliuc, Klaus Bergander, Gerald Kehr, Gerhard Erker|2021|J.Am.Chem.Soc.|143|14992|doi:10.1021/jacs.1c07465
DOI: 10.5517/ccdc.csd.cc27zc9x
title: CCDC 2084759: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Constantin G. Daniliuc, Klaus Bergander, Gerald Kehr, Gerhard Erker|2021|J.Am.Chem.Soc.|143|14992|doi:10.1021/jacs.1c07465
DOI: 10.5517/ccdc.csd.cc27zcby
title: CCDC 2084760: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Constantin G. Daniliuc, Klaus Bergander, Gerald Kehr, Gerhard Erker|2021|J.Am.Chem.Soc.|143|14992|doi:10.1021/jacs.1c07465
DOI: 10.5517/ccdc.csd.cc27zccz
title: CCDC 2084761: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Constantin G. Daniliuc, Klaus Bergander, Gerald Kehr, Gerhard Erker|2021|J.Am.Chem.Soc.|143|14992|doi:10.1021/jacs.1c07465
DOI: 10.5517/ccdc.csd.cc27zcf1
title: CCDC 2084763: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Constantin G. Daniliuc, Klaus Bergander, Gerald Kehr, Gerhard Erker|2021|J.Am.Chem.Soc.|143|14992|doi:10.1021/jacs.1c07465
DOI: 10.5517/ccdc.csd.cc27zch3
title: CCDC 2084765: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Constantin G. Daniliuc, Klaus Bergander, Gerald Kehr, Gerhard Erker|2021|J.Am.Chem.Soc.|143|14992|doi:10.1021/jacs.1c07465
DOI: 10.5517/ccdc.csd.cc27zcj4
title: CCDC 2084766: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Constantin G. Daniliuc, Klaus Bergander, Gerald Kehr, Gerhard Erker|2021|J.Am.Chem.Soc.|143|14992|doi:10.1021/jacs.1c07465
DOI: 10.5517/ccdc.csd.cc2815vc
title: CCDC 2086512: Experimental Crystal Structure Determination

description: Related Article: Ildiko Buta, Sergiu Shova, Sorina Ilies, Florica Manea, Marius Andruh, Otilia Costisor|2022|J.Mol.Struct.|1248|131439|doi:10.1016/j.molstruc.2021.131439
DOI: 10.5517/ccdc.csd.cc2815wd
title: CCDC 2086513: Experimental Crystal Structure Determination

description: Related Article: Ildiko Buta, Sergiu Shova, Sorina Ilies, Florica Manea, Marius Andruh, Otilia Costisor|2022|J.Mol.Struct.|1248|131439|doi:10.1016/j.molstruc.2021.131439
DOI: 10.5517/ccdc.csd.cc2815xf
title: CCDC 2086514: Experimental Crystal Structure Determination

description: Related Article: Ildiko Buta, Sergiu Shova, Sorina Ilies, Florica Manea, Marius Andruh, Otilia Costisor|2022|J.Mol.Struct.|1248|131439|doi:10.1016/j.molstruc.2021.131439
DOI: 10.5517/ccdc.csd.cc2815yg
title: CCDC 2086515: Experimental Crystal Structure Determination

description: Related Article: Ildiko Buta, Sergiu Shova, Sorina Ilies, Florica Manea, Marius Andruh, Otilia Costisor|2022|J.Mol.Struct.|1248|131439|doi:10.1016/j.molstruc.2021.131439
DOI: 10.5517/ccdc.csd.cc28162m
title: CCDC 2086519: Experimental Crystal Structure Determination

description: Related Article: Ildiko Buta, Sergiu Shova, Sorina Ilies, Florica Manea, Marius Andruh, Otilia Costisor|2022|J.Mol.Struct.|1248|131439|doi:10.1016/j.molstruc.2021.131439
DOI: 10.5517/ccdc.csd.cc1zmx4n
title: CCDC 1836382: Experimental Crystal Structure Determination

description: Related Article: Mansura Huseynova, Vaqif Farzaliyev, Ajdar Medjidov, Mahizar Aliyeva, Mücahit Özdemir, Parham Taslimi, Yunus Zorlu, Bahattin Yalçın, Şahin Onur|2022|J.Mol.Struct.|1248|131470|doi:10.1016/j.molstruc.2021.131470
DOI: 10.5517/ccdc.csd.cc28lfgs
title: CCDC 2103085: Experimental Crystal Structure Determination

description: Related Article: Takafumi Ide, Kaibo Feng, Charlie F. Dixon, Dawei Teng, Joseph R. Clark, Wei Han, Chloe I. Wendell, Vanessa Koch, M. Christina White|2021|J.Am.Chem.Soc.|143|14969|doi:10.1021/jacs.1c06335
DOI: 10.25493/z7hz-chd
title: Probabilistic cytoarchitectonic map of Area p24c (pACC) (v18.0)

description: This dataset contains the distinct architectonic areas pv24c, pd24cv and pd24cd (combined to a single probability map named Area p24c (pACC)) in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to both reference spaces, where each voxel was assigned the probability to belong to Area p24c (pACC). The probability map of Area p24c (pACC) is provided in the NifTi format for each brain reference space and hemisphere. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Other available data versions of Area p24c (pACC): Palomero-Gallagher et al. (2019) [Data set, v16.0] [DOI: 10.25493/YSP3-WR3](https://doi.org/10.25493%2FYSP3-WR3) Palomero-Gallagher et al. (2019) [Data set, v16.1] [DOI: 10.25493/QA7B-JM9](https://doi.org/10.25493%2FQA7B-JM9) The most probable delineation of Area p24c (pACC) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.18] [DOI: 10.25493/8EGG-ZAR](https://doi.org/10.25493%2F8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493%2FTAKY-64D) Amunts et al. (2020) [Data set, v2.4] [DOI: 10.25493/A7Y0-NX9](https://doi.org/10.25493%2FA7Y0-NX9) Amunts et al. (2020) [Data set, v2.5] [DOI: 10.25493/8JKE-M53](https://doi.org/10.25493/8JKE-M53) Amunts et al. (2021) [Data set, v2.6] [DOI: 10.25493/KJQN-AM0](https://doi.org/10.25493%2FKJQN-AM0)
DOI: 10.25493/q6vj-4bj
title: Probabilistic cytoarchitectonic map of VTM (Amygdala) (v8.0)

description: This dataset contains the distinct architectonic VTM (Amygdala) in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to both reference spaces, where each voxel was assigned the probability to belong to VTM (Amygdala). The probability map of VTM (Amygdala) are provided in the NifTi format for each brain reference space and hemisphere. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Other available data versions of VTM (Amygdala): Kedo et al. (2019) [Data set, v6.4] [DOI: 10.25493/99HN-XRE](https://doi.org/10.25493%2F99HN-XRE) The most probable delineation of VTM (Amygdala) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.18] [DOI: 10.25493/8EGG-ZAR](https://doi.org/10.25493%2F8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493%2FTAKY-64D) Amunts et al. (2020) [Data set, v2.4] [DOI: 10.25493/A7Y0-NX9](https://doi.org/10.25493%2FA7Y0-NX9) Amunts et al. (2020) [Data set, v2.5] [DOI: 10.25493/8JKE-M53](https://doi.org/10.25493/8JKE-M53) Amunts et al. (2021) [Data set, v2.6] [DOI: 10.25493/KJQN-AM0](https://doi.org/10.25493%2FKJQN-AM0)
DOI: 10.25493/bmnk-b8f
title: Probabilistic cytoarchitectonic map of Area Ia2 (Insula) (v4.0)

description: This dataset contains cytoarchitectonic probability maps of the Area Ia2 (Insula) in the single subject template of the MNI (“Colin 27”) and the MNI ICBM 152 reference space, as part of the Julich-Brain atlas. The area was identified using cytoarchitectonic analysis on cell-body-stained histological sections in both hemispheres of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The maps show the probability to belong to the Area Ia2 (Insula) for each voxel of the reference spaces. Data is provided in the NifTi format. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create probabilistic brain maps. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Delineations of the Area Ia2 (Insula) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2021) [Data set, v2.9] [DOI: 10.25493/VSMK-H94](https://doi.org/10.25493/VSMK-H94)
DOI: 10.25493/b2wy-6k4
title: Probabilistic cytoarchitectonic map of Area Fp2 (FPole) (v4.0)

description: This dataset contains the distinct architectonic Area Fp2 (FPole) in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to both reference spaces, where each voxel was assigned the probability to belong to Area Fp2 (FPole). The probability map of Area Fp2 (FPole) are provided in the NifTi format for each brain reference space and hemisphere. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Other available data versions of Area Fp2 (FPole): Bludau et al. (2018) [Data set, v2.2] [DOI: 10.25493/26WT-E3P](https://doi.org/10.25493%2F26WT-E3P) Bludau et al. (2019) [Data set, v2.4 [DOI: 10.25493/GZW1-7R3](https://doi.org/10.25493%2FGZW1-7R3) The most probable delineation of Area Fp2 (FPole) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.13] [DOI: 10.25493/Q3ZS-NV6](https://doi.org/10.25493%2FQ3ZS-NV6) Amunts et al. (2019) [Data set, v1.18] [DOI: 10.25493/8EGG-ZAR](https://doi.org/10.25493%2F8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493%2FTAKY-64D) Amunts et al. (2020) [Data set, v2.4] [DOI: 10.25493/A7Y0-NX9](https://doi.org/10.25493%2FA7Y0-NX9) Amunts et al. (2020) [Data set, v2.5] [DOI: 10.25493/8JKE-M53](https://doi.org/10.25493/8JKE-M53) Amunts et al. (2021) [Data set, v2.6] [DOI: 10.25493/KJQN-AM0](https://doi.org/10.25493%2FKJQN-AM0)
DOI: 10.5281/zenodo.5533881
title: Wikidata Dump

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.5533880
title: Wikidata Dump

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.5534122
title: Wikidata Dump occupation-music

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.5534121
title: Wikidata Dump occupation-music

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.5534737
title: Dados da Febrace

description: Informações referentes aos projetos aprovados para a Feira de Ciências e Engenharia, no ano de 20xx. Inclui dados demográficos da escola dos estudantes proponentes, assim como título, resumo e palavras-chave dos projetos.
DOI: 10.5281/zenodo.5534736
title: Dados da Febrace

description: Informações referentes aos projetos aprovados para a Feira de Ciências e Engenharia, no ano de 20xx. Inclui dados demográficos da escola dos estudantes proponentes, assim como título, resumo e palavras-chave dos projetos.
DOI: 10.5281/zenodo.5535058
title: sample_test_caio

description: A small sample of data of atm sensors.
DOI: 10.5281/zenodo.5535057
title: sample_test_caio

description: A small sample of data of atm sensors.
DOI: 10.6084/m9.figshare.16695940
title: Article_Data

description: This is raw data for a research project related to employer branding and employee advocacy via social media(specifically LinkedIn)
DOI: 10.5281/zenodo.5535033
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.6084/m9.figshare.16695964
title: Comprehensive library of ribosomal proteins of different microbial species

description: Ribosomal proteins are building blocks of ribosome, and are thus essential proteins of any cell. Work reported in the literature has eluded to the important roles ribosomal proteins in ensuring cell viability, as well as encoding phylogeny of a species in addition to 16S or 18S rRNA. It is such phylogenetic significance that lends ribosomal protein use in different microbial identification protocols such as matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) or other soft ionization mass spectrometry proteomics approaches. To support this role of ribosomal proteins, this work collated the ribosomal protein complement of different microbial species to help build a comprehensive library of ribosomal proteins useful to help annotate ribosomal protein mass peaks. Concatenating protein name, amino acid sequence, nucleotide sequence, number of residues and molecular weight, the library should find use in various methodologies that require annotation of the protein mass peaks.
DOI: 10.6084/m9.figshare.16695964.v1
title: Comprehensive library of ribosomal proteins of different microbial species

description: Ribosomal proteins are building blocks of ribosome, and are thus essential proteins of any cell. Work reported in the literature has eluded to the important roles ribosomal proteins in ensuring cell viability, as well as encoding phylogeny of a species in addition to 16S or 18S rRNA. It is such phylogenetic significance that lends ribosomal protein use in different microbial identification protocols such as matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) or other soft ionization mass spectrometry proteomics approaches. To support this role of ribosomal proteins, this work collated the ribosomal protein complement of different microbial species to help build a comprehensive library of ribosomal proteins useful to help annotate ribosomal protein mass peaks. Concatenating protein name, amino acid sequence, nucleotide sequence, number of residues and molecular weight, the library should find use in various methodologies that require annotation of the protein mass peaks.
DOI: 10.25451/flinders.16675507
title: Transience of Riparian Freshwater Lenses

description: The transience of riparian lens movement is investigated for the first time, considering a fully penetrating, gaining river and rapid variations in hydraulic boundary conditions. Controlled laboratory experiments and numerical modeling are used to determine the timescales associated with lens movements. The insights into riparian lenses transience attained from the current study build on the understanding of transience obtained for other mixed-convective hydrogeological processes, such as seawater intrusion and retreat.
DOI: 10.25451/flinders.16675507.v1
title: Transience of Riparian Freshwater Lenses

description: The transience of riparian lens movement is investigated for the first time, considering a fully penetrating, gaining river and rapid variations in hydraulic boundary conditions. Controlled laboratory experiments and numerical modeling are used to determine the timescales associated with lens movements. The insights into riparian lenses transience attained from the current study build on the understanding of transience obtained for other mixed-convective hydrogeological processes, such as seawater intrusion and retreat.
DOI: 10.5281/zenodo.5535083
title: Thermophilic methane oxidation is widespread in New Zealand geothermal fields

description: This is processed data used for analysis in a manuscipt currently being prepared for publication.<br> Samples of soil or sediment were taken from geothermal fields in the Taupo Volcanic Zone, New Zealand;<br> methane oxidation was quantified; DNA was extracted from each sample for 16S rRNA gene sequencing.