cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ax6tjc
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Memecylon ultramaficum R.D.Stone"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057105-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10895026
title: Health AI Risk Taxonomy (HART)
DOI: 10.5281/zenodo.10895027
title: Health AI Risk Taxonomy (HART)
DOI: 10.15468/dl.a6mksa
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mitrephora cagayanensis Merr."
 ]
}

 The dataset includes 13 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057106-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ce6s24
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Megatritheca devredii (Germ.) Cristóbal"
 ]
}

 The dataset includes 10 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057107-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x4esbu
title: Occurrence Download

description: A dataset containing 7607245 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 7607245 records from 1808 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057086-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.5091865
title: The adipokine tartrate-resistant acid phosphatase 5a in serum correlates to adipose tissue expansion in obesity

description: <b>Purpose:</b> Tartrate-resistant acid phosphatase (TRAP) exists as two isoforms, 5a and 5b. TRAP 5a is elevated in adipose tissue of obese women, interacts with pre-adipocytes and is linked to insulin-sensitive hyperplastic obesity when overexpressed in mice. The aim of this study was to investigate the relation between serum TRAP 5a, adiposity indices and metabolic syndrome risk markers in lean and obese women, using a newly developed TRAP 5a-specific ELISA. <b>Materials and methods:</b> A TRAP 5a sandwich ELISA was optimized using TRAP 5a-specific monoclonal antibodies and tested in sera of healthy males. TRAP 5a levels were quantitated in sera from healthy males and lean and obese women. <b>Results:</b> Serum TRAP 5a protein levels were lower in obese women in comparison with lean. In obese, but not in lean women, serum TRAP 5a correlated positively to % fat mass, BMI, waist- and hip circumference, waist-to-hip ratio and PAI, while no correlations to serum leptin, HOMA, glucose, insulin, FFA, HDL, TG, APO-A1 and APO-B were observed. <b>Conclusions:</b> TRAP 5a serum levels correlated positively to anthropometric obesity parameters but not to metabolic syndrome risk factors, indicating that serum TRAP 5a is associated with pathological adipose tissue expansion.
DOI: 10.5517/ccdc.csd.cc24hgw0
title: CCDC 1981082: Experimental Crystal Structure Determination

description: Related Article: Alexei N. Izmest'ev, Galina A. Gazieva, Valentina A. Karnoukhova, Angelina N. Kravchenko|2020|Org.Biomol.Chem.|18|6905|doi:10.1039/D0OB01628D
DOI: 10.5517/ccdc.csd.cc24hgx1
title: CCDC 1981083: Experimental Crystal Structure Determination

description: Related Article: Alexei N. Izmest'ev, Galina A. Gazieva, Valentina A. Karnoukhova, Angelina N. Kravchenko|2020|Org.Biomol.Chem.|18|6905|doi:10.1039/D0OB01628D
DOI: 10.5517/ccdc.csd.cc24hgy2
title: CCDC 1981084: Experimental Crystal Structure Determination

description: Related Article: Alexei N. Izmest'ev, Galina A. Gazieva, Valentina A. Karnoukhova, Angelina N. Kravchenko|2020|Org.Biomol.Chem.|18|6905|doi:10.1039/D0OB01628D
DOI: 10.5517/ccdc.csd.cc24hgz3
title: CCDC 1981085: Experimental Crystal Structure Determination

description: Related Article: Alexei N. Izmest'ev, Galina A. Gazieva, Valentina A. Karnoukhova, Angelina N. Kravchenko|2020|Org.Biomol.Chem.|18|6905|doi:10.1039/D0OB01628D
DOI: 10.5517/ccdc.csd.cc24k5nk
title: CCDC 1982718: Experimental Crystal Structure Determination

description: Related Article: Fazhou Yang, Ziyan Liu, Hao Liu, Yu Shangguan, Hao Deng, Jiaxing Huang, Yumei Xiao, Hongchao Guo, Cheng Zhang|2020|Org.Biomol.Chem.|18|6724|doi:10.1039/D0OB00291G
DOI: 10.5517/ccdc.csd.cc24kfcj
title: CCDC 1982957: Experimental Crystal Structure Determination

description: Related Article: Dong Zhang, Zhishan Su, Qianwen He, Zhikun Wu, Yuqiao Zhou, Chenjing Pan, Xiaohua Liu, Xiaoming Feng|2020|J.Am.Chem.Soc.|142|15975|doi:10.1021/jacs.0c07066
DOI: 10.5517/ccdc.csd.cc24kztj
title: CCDC 1983498: Experimental Crystal Structure Determination

description: Related Article: Xiu Xin,  Haiwen Shan,  Tian Tian,  Yaorong Wang,  Dan Yuan,  Hongpeng You,  Yingming Yao|2020|ACS Sustain.Chem.Eng.|8|13185|doi:10.1021/acssuschemeng.0c01736
DOI: 10.5517/ccdc.csd.cc24kzxm
title: CCDC 1983501: Experimental Crystal Structure Determination

description: Related Article: Xiu Xin,  Haiwen Shan,  Tian Tian,  Yaorong Wang,  Dan Yuan,  Hongpeng You,  Yingming Yao|2020|ACS Sustain.Chem.Eng.|8|13185|doi:10.1021/acssuschemeng.0c01736
DOI: 10.5517/ccdc.csd.cc24kzyn
title: CCDC 1983502: Experimental Crystal Structure Determination

description: Related Article: Xiu Xin,  Haiwen Shan,  Tian Tian,  Yaorong Wang,  Dan Yuan,  Hongpeng You,  Yingming Yao|2020|ACS Sustain.Chem.Eng.|8|13185|doi:10.1021/acssuschemeng.0c01736
DOI: 10.5517/ccdc.csd.cc24l03w
title: CCDC 1983507: Experimental Crystal Structure Determination

description: Related Article: Xiu Xin,  Haiwen Shan,  Tian Tian,  Yaorong Wang,  Dan Yuan,  Hongpeng You,  Yingming Yao|2020|ACS Sustain.Chem.Eng.|8|13185|doi:10.1021/acssuschemeng.0c01736
DOI: 10.5517/ccdc.csd.cc24l1b4
title: CCDC 1983545: Experimental Crystal Structure Determination

description: Related Article: Xiu Xin,  Haiwen Shan,  Tian Tian,  Yaorong Wang,  Dan Yuan,  Hongpeng You,  Yingming Yao|2020|ACS Sustain.Chem.Eng.|8|13185|doi:10.1021/acssuschemeng.0c01736
DOI: 10.5517/ccdc.csd.cc24lp9r
title: CCDC 1984164: Experimental Crystal Structure Determination

description: Related Article: Zhiyuan He, Xiaolian Xue, Yilan Liu, Na Yu, Jeremy P. Krogman|2020|Dalton Trans.|49|12586|doi:10.1039/D0DT00570C
DOI: 10.5517/ccdc.csd.cc24lpct
title: CCDC 1984166: Experimental Crystal Structure Determination

description: Related Article: Zhiyuan He, Xiaolian Xue, Yilan Liu, Na Yu, Jeremy P. Krogman|2020|Dalton Trans.|49|12586|doi:10.1039/D0DT00570C
DOI: 10.5517/ccdc.csd.cc24lpdv
title: CCDC 1984167: Experimental Crystal Structure Determination

description: Related Article: Zhiyuan He, Xiaolian Xue, Yilan Liu, Na Yu, Jeremy P. Krogman|2020|Dalton Trans.|49|12586|doi:10.1039/D0DT00570C
DOI: 10.5517/ccdc.csd.cc24lpfw
title: CCDC 1984168: Experimental Crystal Structure Determination

description: Related Article: Zhiyuan He, Xiaolian Xue, Yilan Liu, Na Yu, Jeremy P. Krogman|2020|Dalton Trans.|49|12586|doi:10.1039/D0DT00570C
DOI: 10.5517/ccdc.csd.cc24lpgx
title: CCDC 1984169: Experimental Crystal Structure Determination

description: Related Article: Zhiyuan He, Xiaolian Xue, Yilan Liu, Na Yu, Jeremy P. Krogman|2020|Dalton Trans.|49|12586|doi:10.1039/D0DT00570C
DOI: 10.5517/ccdc.csd.cc24m4zx
title: CCDC 1984619: Experimental Crystal Structure Determination

description: Related Article: Yue Gui, Xin Yao, Ilia Guzei, Michael M. Aristov, Junguang Yu, Lian Yu|2020|Chem.Mater.|32|7754|doi:10.1021/acs.chemmater.0c02209
DOI: 10.5517/ccdc.csd.cc24m5vt
title: CCDC 1984646: Experimental Crystal Structure Determination

description: Related Article: Yue Gui, Xin Yao, Ilia Guzei, Michael M. Aristov, Junguang Yu, Lian Yu|2020|Chem.Mater.|32|7754|doi:10.1021/acs.chemmater.0c02209
DOI: 10.6084/m9.figshare.11687064.v3
title: Example Dataset for BIDS Manager

description: This folder contains data from a fictional participant that you can use to test BIDS Manager (https://github.com/Dynamap/BIDS_Manager).
DOI: 10.5519/qd.p6onq6rj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (838 records)
DOI: 10.5281/zenodo.4071407
title: Annealing simulations of a lipid membrane with different transmembrane proteins

description: soon...
DOI: 10.5281/zenodo.4071406
title: Annealing simulations of a lipid membrane with different transmembrane proteins

description: soon...
DOI: 10.25392/leicester.data.12063096
title: Adherence to stay-at-home advice: Insights from a US survey on adherence to stay-at-home advice and personality during the COVID-19 pandemic.

description: Variables included in the dataset.<br><br>Gender<br><br>Stay-at-home factor score<br><br>Age<br><br>Employment status<br><br>Current living arrangements<br><br>Covid-19-like symptoms<br><br>Distancing - “self-isolating” item<br><br>Distancing - “social-distancing” item<br><br>Distancing - “reduced contact” item<br><br>Extraversion<br><br>Agreeableness<br><br>Conscientiousness<br><br>Emotional stability<br><br>Openness to experience<br><br>Social connectedness <br>
DOI: 10.25392/leicester.data.12063096.v2
title: Adherence to stay-at-home advice: Insights from a US survey on adherence to stay-at-home advice and personality during the COVID-19 pandemic.

description: Variables included in the dataset.<br><br>Gender<br><br>Stay-at-home factor score<br><br>Age<br><br>Employment status<br><br>Current living arrangements<br><br>Covid-19-like symptoms<br><br>Distancing - “self-isolating” item<br><br>Distancing - “social-distancing” item<br><br>Distancing - “reduced contact” item<br><br>Extraversion<br><br>Agreeableness<br><br>Conscientiousness<br><br>Emotional stability<br><br>Openness to experience<br><br>Social connectedness <br>
DOI: 10.25392/leicester.data.12063096.v1
title: Adherence to stay-at-home advice: Insights from a US survey on adherence to stay-at-home advice and personality during the COVID-19 pandemic.

description: Variables included in the dataset.<br><br>Gender<br><br>Stay-at-home factor score<br><br>Age<br><br>Employment status<br><br>Current living arrangements<br><br>Covid-19-like symptoms<br><br>Distancing - “self-isolating” item<br><br>Distancing - “social-distancing” item<br><br>Distancing - “reduced contact” item<br><br>Extraversion<br><br>Agreeableness<br><br>Conscientiousness<br><br>Emotional stability<br><br>Openness to experience<br><br>Social connectedness <br>
DOI: 10.6084/m9.figshare.13060598
title: Supplementary Material for: “Ich denke, also sage ich vorher”: Wie “Predictive Processing-Modelle den Einsatz von Verhaltensexperimenten bei Depressionen optimieren können

description: Verhaltensexperimente stellen eine wichtige Interventionsform bei depressiven Störungen dar, um dysfunktionale Annahmen zu modifizieren. Häufig ist jedoch zu beobachten, dass Patient*innen trotz einer fachgerechten Durchführung von Verhaltensexperimenten weiter an negativen Annahmen festhalten. Vor diesem Hintergrund diskutieren wir in diesem Artikel, wie der Einsatz von Verhaltensexperimenten bei Depressionen optimiert werden kann und beziehen uns dabei auf ein neues Störungsmodell, das interessante Implikationen hierzu liefern könnte. Dieses Störungsmodell aus der neurowissenschaftlichen Forschung zu “Predictive Processing” geht davon aus, dass depressive Störungen durch zwei Kernaspekte gekennzeichnet sind: (1) stark negative Erwartungen, die im Sinne von selbsterfüllenden Pro­phezeiungen zu negativen Erlebnissen führen und zuneh­mend “immun” gegen gegenteilige Erfahrungen machen; (2) das Fehlen von positiven Erwartungen, wodurch die Wahr­scheinlichkeit von positiven Erlebnissen reduziert wird. Darauf aufbauend beschreiben wir zunächst, dass zur Modifikation negativer Erwartungen in einer ausführlichen Vorbesprechung erarbeitet werden sollte, welche möglichen positiven Erfahrungen aus dem Verhaltensexperiment die Patient*innen als glaubwürdig betrachten und zur Veränderung ihrer negativen Erwartungen nutzen würden. Auf diese sollte bei der Durchführung besonders geachtet werden, damit positive Erwartungsverletzungen auch als solche wahrgenommen werden. Zum anderen stellen wir dar, dass es nicht ausreichend ist, nur negative Erwartungen zu redu­zieren, sondern auch explizit positive Erwartungen durch weitere Verhaltensexperimente gefördert werden sollten.
DOI: 10.6084/m9.figshare.13060598.v1
title: Supplementary Material for: “Ich denke, also sage ich vorher”: Wie “Predictive Processing-Modelle den Einsatz von Verhaltensexperimenten bei Depressionen optimieren können

description: Verhaltensexperimente stellen eine wichtige Interventionsform bei depressiven Störungen dar, um dysfunktionale Annahmen zu modifizieren. Häufig ist jedoch zu beobachten, dass Patient*innen trotz einer fachgerechten Durchführung von Verhaltensexperimenten weiter an negativen Annahmen festhalten. Vor diesem Hintergrund diskutieren wir in diesem Artikel, wie der Einsatz von Verhaltensexperimenten bei Depressionen optimiert werden kann und beziehen uns dabei auf ein neues Störungsmodell, das interessante Implikationen hierzu liefern könnte. Dieses Störungsmodell aus der neurowissenschaftlichen Forschung zu “Predictive Processing” geht davon aus, dass depressive Störungen durch zwei Kernaspekte gekennzeichnet sind: (1) stark negative Erwartungen, die im Sinne von selbsterfüllenden Pro­phezeiungen zu negativen Erlebnissen führen und zuneh­mend “immun” gegen gegenteilige Erfahrungen machen; (2) das Fehlen von positiven Erwartungen, wodurch die Wahr­scheinlichkeit von positiven Erlebnissen reduziert wird. Darauf aufbauend beschreiben wir zunächst, dass zur Modifikation negativer Erwartungen in einer ausführlichen Vorbesprechung erarbeitet werden sollte, welche möglichen positiven Erfahrungen aus dem Verhaltensexperiment die Patient*innen als glaubwürdig betrachten und zur Veränderung ihrer negativen Erwartungen nutzen würden. Auf diese sollte bei der Durchführung besonders geachtet werden, damit positive Erwartungsverletzungen auch als solche wahrgenommen werden. Zum anderen stellen wir dar, dass es nicht ausreichend ist, nur negative Erwartungen zu redu­zieren, sondern auch explizit positive Erwartungen durch weitere Verhaltensexperimente gefördert werden sollten.
DOI: 10.6084/m9.figshare.12924755
title: Metadata record for: A cross-country database of COVID-19 testing

description: This dataset contains key characteristics about the data described in the Data Descriptor A cross-country database of COVID-19 testing. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.6084/m9.figshare.12924755.v1
title: Metadata record for: A cross-country database of COVID-19 testing

description: This dataset contains key characteristics about the data described in the Data Descriptor A cross-country database of COVID-19 testing. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.17632/cvwwks2fmj.1
title: Supplementary Table 1

description: Characteristics of 18 pediatric alopecia areata patients on dupilumab therapy
DOI: 10.5281/zenodo.4071463
title: DNA methylation regulates transcription factor specific neurodevelopmental but not sexually dimorphic gene expression dynamics in zebra finch telencephalon

description: Supplementary Information for the manuscript: "DNA methylation regulates transcription factor specific neurodevelopmental but not sexually dimorphic gene expression dynamics in zebra finch telencephalon"
DOI: 10.15161/oar.it/73165
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.6084/m9.figshare.13060643.v1
title: bai

description: bai file<br>
DOI: 10.6084/m9.figshare.13060643
title: bai

description: bai file<br>
DOI: 10.6084/m9.figshare.13060466
title: bam

description: bam file<br>
DOI: 10.15139/s3/358pgx
title: Vision Zero: No traffic deaths by 2030 in Montgomery County (2020). Montgomery County, Maryland

description: Vision Zero is a strategy to reduce all traffic fatalities and severe injuries to zero, while increasing safe, equitable, and healthy mobility for all. Vision Zero Plans help guide municipalities, counties, and other areas to address these strategies considering the local context.
DOI: 10.6084/m9.figshare.13060466.v1
title: bam

description: bam file<br>
DOI: 10.6084/m9.figshare.13060241
title: R9.7z

description: Smart meter data for the residence in SEIL-R dataset.
DOI: 10.5517/cc1k54wr
title: CCDC 1434924: Experimental Crystal Structure Determination

description: Related Article: Xuxue Zhang, Song Cao|2015|CSD Communication|||
description: Related Article: Xuxue Zhang, Chuan Liu, Yupian Deng, Song Cao|2020|Org.Biomol.Chem.|18|7540|doi:10.1039/D0OB01821J
DOI: 10.5517/ccdc.csd.cc23tzb8
title: CCDC 1961380: Experimental Crystal Structure Determination

description: Related Article: Dong Zhang, Zhishan Su, Qianwen He, Zhikun Wu, Yuqiao Zhou, Chenjing Pan, Xiaohua Liu, Xiaoming Feng|2020|J.Am.Chem.Soc.|142|15975|doi:10.1021/jacs.0c07066
DOI: 10.5517/ccdc.csd.cc2405y9
title: CCDC 1966390: Experimental Crystal Structure Determination

description: Related Article: Govindasamy Vinoth, Sekar Indira, Madheswaran Bharathi, Luis G. Alves, Ana M. Martins, Kuppannan Shanmuga Bharathi|2021|Inorg.Chim.Acta|514|120006|doi:10.1016/j.ica.2020.120006
DOI: 10.5517/ccdc.csd.cc24m701
title: CCDC 1984682: Experimental Crystal Structure Determination

description: Related Article: Xu Yin, Hongli Jia, Qingying Zhang, Yong Jiang, Pengfei Tu|2020|Bioorg.Chem.|104|104251|doi:10.1016/j.bioorg.2020.104251
DOI: 10.5517/ccdc.csd.cc24m7rs
title: CCDC 1984705: Experimental Crystal Structure Determination

description: Related Article: Thomas Q. Davies, Michael J. Tilby, Jack Ren, Nicholas A. Parker, David Skolc, Adrian Hall, Fernanda Duarte, Michael C. Willis|2020|J.Am.Chem.Soc.|142|15445|doi:10.1021/jacs.0c06986
DOI: 10.5517/ccdc.csd.cc24m7st
title: CCDC 1984706: Experimental Crystal Structure Determination

description: Related Article: Thomas Q. Davies, Michael J. Tilby, Jack Ren, Nicholas A. Parker, David Skolc, Adrian Hall, Fernanda Duarte, Michael C. Willis|2020|J.Am.Chem.Soc.|142|15445|doi:10.1021/jacs.0c06986
DOI: 10.5517/ccdc.csd.cc24m7tv
title: CCDC 1984707: Experimental Crystal Structure Determination

description: Related Article: Thomas Q. Davies, Michael J. Tilby, Jack Ren, Nicholas A. Parker, David Skolc, Adrian Hall, Fernanda Duarte, Michael C. Willis|2020|J.Am.Chem.Soc.|142|15445|doi:10.1021/jacs.0c06986
DOI: 10.5517/ccdc.csd.cc24m7vw
title: CCDC 1984708: Experimental Crystal Structure Determination

description: Related Article: Thomas Q. Davies, Michael J. Tilby, Jack Ren, Nicholas A. Parker, David Skolc, Adrian Hall, Fernanda Duarte, Michael C. Willis|2020|J.Am.Chem.Soc.|142|15445|doi:10.1021/jacs.0c06986
DOI: 10.5517/ccdc.csd.cc24m7wx
title: CCDC 1984709: Experimental Crystal Structure Determination

description: Related Article: Thomas Q. Davies, Michael J. Tilby, Jack Ren, Nicholas A. Parker, David Skolc, Adrian Hall, Fernanda Duarte, Michael C. Willis|2020|J.Am.Chem.Soc.|142|15445|doi:10.1021/jacs.0c06986
DOI: 10.6084/m9.figshare.12265028
title: Supplementary table S1.docx

description: Systematic combinations of outcomes and their associated c-miRs of substantial importance for discrimination between disease and non-disease.
DOI: 10.5281/zenodo.4066963
title: Dataset for "Sorption, anomalous water transport and dynamic porosity in cement paste: A spatially localised 1H NMR relaxation study and a proposed mechanism"

description: This record is the dataset for Figures 4, 5, 6, 7, 8 and 9 in the journal article "Sorption, anomalous water transport and dynamic porosity in cement paste: A spatially localised 1H NMR relaxation study and a proposed mechanism" published in Cement and Concrete Research, Volume 133, July 2020, 106045, https://doi.org/10.1016/j.cemconres.2020.106045. Abstract: The link between anomalous water sorption and dynamic porosity in cement pastes is explored using spatially resolved GARField1H nuclear magnetic resonance (NMR) relaxation analysis. A model is developed in which the effective capillary diffusion coefficient is dependent on the instantaneous pore size distribution. This and earlier data show changes in pore size distribution resultant from changes in saturation that do not occur instantaneously with changes in degree of saturation. Therefore, it is assumed that the pore size distribution is always relaxing exponentially towards a (saturation dependent) equilibrium. It follows that the diffusivity is sample history (i.e. time) dependent as well as saturation dependent. This is sufficient to explain anomalies in rapid capillary water sorption. The same concepts are applied to slow drying. In this case, porosity changes occur on a timescale much shorter than drying so the system is always in dynamic equilibrium and anomalies are therefore not seen.
DOI: 10.5281/zenodo.4066962
title: Dataset for "Sorption, anomalous water transport and dynamic porosity in cement paste: A spatially localised 1H NMR relaxation study and a proposed mechanism"

description: This record is the dataset for Figures 4, 5, 6, 7, 8 and 9 in the journal article "Sorption, anomalous water transport and dynamic porosity in cement paste: A spatially localised 1H NMR relaxation study and a proposed mechanism" published in Cement and Concrete Research, Volume 133, July 2020, 106045, https://doi.org/10.1016/j.cemconres.2020.106045. Abstract: The link between anomalous water sorption and dynamic porosity in cement pastes is explored using spatially resolved GARField1H nuclear magnetic resonance (NMR) relaxation analysis. A model is developed in which the effective capillary diffusion coefficient is dependent on the instantaneous pore size distribution. This and earlier data show changes in pore size distribution resultant from changes in saturation that do not occur instantaneously with changes in degree of saturation. Therefore, it is assumed that the pore size distribution is always relaxing exponentially towards a (saturation dependent) equilibrium. It follows that the diffusivity is sample history (i.e. time) dependent as well as saturation dependent. This is sufficient to explain anomalies in rapid capillary water sorption. The same concepts are applied to slow drying. In this case, porosity changes occur on a timescale much shorter than drying so the system is always in dynamic equilibrium and anomalies are therefore not seen.
DOI: 10.6084/m9.figshare.12265028.v2
title: Supplementary table S1.docx

description: Systematic combinations of outcomes and their associated c-miRs of substantial importance for discrimination between disease and non-disease.
DOI: 10.6084/m9.figshare.12265028.v1
title: Supplementary table S1.docx

description: Systematic combinations of outcomes and their associated c-miRs of substantial importance for discrimination between disease and non-disease.
DOI: 10.21227/4s49-wk50
title: Experimental result of our BISR work

description: experimental data