lsmyrnaios
/
dnet-hadoop
forked from D-Net/dnet-hadoop
1
0
Fork 0
Code Pull Requests Activity

tests to generate the XML records for the index for the EDITH demo on digital twins, integrating output from the FoS classifier

This commit is contained in:
Alessia Bardi 2023-04-21 16:46:30 +02:00
parent 24c41806ac
commit 382f46a8e4
4 changed files with 1125 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

17
dhp-workflows/dhp-graph-provision/src/test/java/eu/dnetlib/dhp/oa/provision/IndexRecordTransformerTest.java
View File

@ -128,6 +128,23 @@ public class IndexRecordTransformerTest {
testRecordTransformation(record);
}
@Test
public void testForEdithDemo() throws IOException, TransformerException {
final String record = IOUtils.toString(getClass().getResourceAsStream("edith-demo/10.1098-rsta.2020.0257.xml"));
testRecordTransformation(record);
}
@Test
public void testForEdithDemoCovid() throws IOException, TransformerException {
final String record = IOUtils.toString(getClass().getResourceAsStream("edith-demo/10.3390-pr9111967-covid.xml"));
testRecordTransformation(record);
}
@Test
public void testForEdithDemoEthics() throws IOException, TransformerException {
final String record = IOUtils.toString(getClass().getResourceAsStream("edith-demo/10.2196-33081-ethics.xml"));
testRecordTransformation(record);
}
@Test
void testDoiUrlNormalization() throws MalformedURLException {

596
dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/edith-demo/10.1098-rsta.2020.0257.xml Normal file
View File

@ -0,0 +1,596 @@
<record>
<result xmlns:dri="http://www.driver-repository.eu/namespace/dri"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<header>
<dri:objIdentifier>doi_dedup___::e225555a08a082ad8f53f179bc59c5d0</dri:objIdentifier>
<dri:dateOfCollection>2023-01-27T05:32:10Z</dri:dateOfCollection>
</header>
<metadata>
<oaf:entity xmlns:oaf="http://namespace.openaire.eu/oaf"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://namespace.openaire.eu/oaf http://namespace.openaire.eu/oaf http://www.openaire.eu/schema/0.2/oaf-0.2.xsd">
<oaf:result>
<collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2"/>
<collectedfrom name="UnpayWall" id="openaire____::8ac8380272269217cb09a928c8caa993"/>
<collectedfrom name="ORCID" id="openaire____::806360c771262b4d6770e7cdf04b5c5a"/>
<collectedfrom name="Microsoft Academic Graph" id="openaire____::5f532a3fc4f1ea403f37070f59a7a53a"/>
<collectedfrom name="Oxford University Research Archive"
id="opendoar____::2290a7385ed77cc5592dc2153229f082"/>
<collectedfrom name="PubMed Central" id="opendoar____::eda80a3d5b344bc40f3bc04f65b7a357"/>
<collectedfrom name="Europe PubMed Central" id="opendoar____::8b6dd7db9af49e67306feb59a8bdc52c"/>
<originalId>10.1098/rsta.2020.0257</originalId>
<originalId>50|doiboost____::e225555a08a082ad8f53f179bc59c5d0</originalId>
<originalId>3211056089</originalId>
<originalId>50|od______1064::83eb0f76b60445d72bb7428a1b68ef1a</originalId>
<originalId>oai:ora.ox.ac.uk:uuid:9fc4563a-07e1-41d1-8b99-31ce2f8ac027</originalId>
<originalId>50|od_______267::6d978e42c57dfc79d61a84ab5be28cb8</originalId>
<originalId>oai:pubmedcentral.nih.gov:8543046</originalId>
<originalId>od_______267::6d978e42c57dfc79d61a84ab5be28cb8</originalId>
<originalId>34689630</originalId>
<originalId>PMC8543046</originalId>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types">10.1098/rsta.2020.0257
</pid>
<pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:crosswalk:repository"
trust="0.9">PMC8543046
</pid>
<pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types" schemename="dnet:pid_types"
inferred="false" provenanceaction="sysimport:crosswalk:repository" trust="0.9">34689630
</pid>
<measure id="influence" score="5.534974E-9" class="C"/>
<measure id="popularity" score="2.0811036E-8" class="C"/>
<measure id="influence_alt" score="8" class="C"/>
<measure id="popularity_alt" score="2.736" class="C"/>
<measure id="impulse" score="8" class="C"/>
<measure id="downloads" count="1"/>
<measure id="views" count="4"/>
<title classid="alternative title" classname="alternative title" schemeid="dnet:dataCite_title"
schemename="dnet:dataCite_title">A completely automated pipeline for 3D reconstruction of
human heart from 2D cine magnetic resonance slices.
</title>
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title"
schemename="dnet:dataCite_title">A completely automated pipeline for 3D reconstruction of
human heart from 2D cine magnetic resonance slices
</title>
<bestaccessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes"
schemename="dnet:access_modes"/>
<creator rank="8" URL="https://academic.microsoft.com/#/detail/2103042895">Vicente Grau</creator>
<creator rank="1" orcid="0000-0001-8198-5128"
URL="https://academic.microsoft.com/#/detail/2693349397">Abhirup Banerjee
</creator>
<creator rank="3" URL="https://academic.microsoft.com/#/detail/1425738153">Ernesto Zacur</creator>
<creator rank="6" URL="https://academic.microsoft.com/#/detail/2043191934">Robin P. Choudhury
</creator>
<creator rank="7" URL="https://academic.microsoft.com/#/detail/2166186014">Blanca Rodriguez
</creator>
<creator rank="2" URL="https://academic.microsoft.com/#/detail/2889449215">Julia Camps</creator>
<creator rank="5" URL="https://academic.microsoft.com/#/detail/264390263">Yoram Rudy</creator>
<creator rank="4" URL="https://academic.microsoft.com/#/detail/2713879776">Christopher M. Andrews
</creator>
<country classid="GB" classname="United Kingdom" schemeid="dnet:countries"
schemename="dnet:countries"/>
<dateofacceptance>2021-10-01</dateofacceptance>
<description>Cardiac magnetic resonance (CMR) imaging is a valuable modality in the diagnosis and
characterization of cardiovascular diseases, since it can identify abnormalities in structure
and function of the myocardium non-invasively and without the need for ionizing radiation.
However, in clinical practice, it is commonly acquired as a collection of separated and
independent 2D image planes, which limits its accuracy in 3D analysis. This paper presents a
completely automated pipeline for generating patient-specific 3D biventricular heart models from
cine magnetic resonance (MR) slices. Our pipeline automatically selects the relevant cine MR
images, segments them using a deep learning-based method to extract the heart contours, and
aligns the contours in 3D space correcting possible misalignments due to breathing or subject
motion first using the intensity and contours information from the cine data and next with the
help of a statistical shape model. Finally, the sparse 3D representation of the contours is used
to generate a smooth 3D biventricular mesh. The computational pipeline is applied and evaluated
in a CMR dataset of 20 healthy subjects. Our results show an average reduction of misalignment
artefacts from 1.82 ± 1.60 mm to 0.72 ± 0.73 mm over 20 subjects, in terms of distance from the
final reconstructed mesh. The high-resolution 3D biventricular meshes obtained with our
computational pipeline are used for simulations of electrical activation patterns, showing
agreement with non-invasive electrocardiographic imaging. The automatic methodologies presented
here for patient-specific MR imaging-based 3D biventricular representations contribute to the
efficient realization of precision medicine, enabling the enhanced interpretability of clinical
data, the digital twin vision through patient-specific image-based modelling and simulation, and
augmented reality applications.
This article is part of the theme issue ‘Advanced computation in cardiovascular physiology: new
challenges and opportunities’.
</description>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">General Physics and Astronomy
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">General Engineering
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">General Mathematics
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Pipeline (computing)
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Cine mri
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Structure and function
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Cardiac magnetic resonance
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Magnetic resonance imaging
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.5338496">medicine.diagnostic_test
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.5338496">medicine
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Human heart
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Modality (human–computer interaction)
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">3D reconstruction
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Computer science
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Nuclear magnetic resonance
</subject>
<subject classid="SDG" classname="Sustainable Development Goals"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:sdg">3. Good health
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">03 medical and health sciences
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0302 clinical medicine
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">030218 Nuclear Medicine &amp;
Medical Imaging
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">03021801 Radiology/Image
segmentation
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">medical ---- image ----
learning ---- deep ---- medical image ---- deep learning ---- learn ---- datum ---- imaging ----
ai
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">deep learning
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">datum
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">030204 Cardiovascular System
&amp; Hematology
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">03020401 Aging-associated
diseases/Heart diseases
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">030217 Neurology &amp;
Neurosurgery
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">03021701 Brain/Neural circuits
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">Articles
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">Research Articles
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">cardiac mesh reconstruction
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">cine MRI
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">misalignment correction
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">electrophysiological
simulation
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">ECGI
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.9">Heart
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.9">Humans
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.9">Imaging, Three-Dimensional
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.9">Magnetic Resonance Imaging
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.9">Magnetic Resonance Imaging, Cine
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.9">Magnetic Resonance Spectroscopy
</subject>
<language classid="und" classname="Undetermined" schemeid="dnet:languages"
schemename="dnet:languages"/>
<relevantdate classid="created" classname="created" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date">2021-10-25
</relevantdate>
<relevantdate classid="published-online" classname="published-online" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date">2021-10-25
</relevantdate>
<relevantdate classid="published-print" classname="published-print" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date">2021-12-13
</relevantdate>
<relevantdate classid="UNKNOWN" classname="UNKNOWN" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">2021-01-01
</relevantdate>
<relevantdate classid="available" classname="available" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">2023-01-05
</relevantdate>
<relevantdate classid="Accepted" classname="Accepted" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">2021-05-28
</relevantdate>
<relevantdate classid="issued" classname="issued" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">2023-01-05
</relevantdate>
<publisher>The Royal Society</publisher>
<source>Crossref</source>
<source/>
<source>Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
</source>
<resulttype classid="publication" classname="publication" schemeid="dnet:result_typologies"
schemename="dnet:result_typologies"/>
<resourcetype classid="UNKNOWN" classname="UNKNOWN" schemeid="dnet:dataCite_resource"
schemename="dnet:dataCite_resource"/>
<journal issn="1364-503X" eissn="1471-2962" vol="379">Philosophical Transactions of the Royal
Society A: Mathematical, Physical and Engineering Sciences
</journal>
<context id="dth" label="Digital Twins in Health" type="community"></context>
<context id="EC" label="European Commission" type="funding">
<category id="EC::H2020" label="Horizon 2020 Framework Programme">
<concept id="EC::H2020::RIA" label="Research and Innovation action"/>
</category>
</context>
<datainfo>
<inferred>true</inferred>
<deletedbyinference>false</deletedbyinference>
<trust>0.8</trust>
<inferenceprovenance>dedup-result-decisiontree-v3</inferenceprovenance>
<provenanceaction classid="sysimport:dedup" classname="Inferred by OpenAIRE"
schemeid="dnet:provenanceActions" schemename="dnet:provenanceActions"/>
</datainfo>
<rels>
<rel inferred="false" trust="0.9" inferenceprovenance="" provenanceaction="sysimport:actionset">
<to class="hasAuthorInstitution" scheme="dnet:result_organization_relations"
type="organization">openorgs____::6a7b1b4c40a067a1f209de6867fe094d
</to>
<country classid="GB" classname="United Kingdom" schemeid="dnet:countries"
schemename="dnet:countries"/>
<legalname>University of Oxford</legalname>
<legalshortname>University of Oxford</legalshortname>
</rel>
<rel inferred="false" trust="0.9" inferenceprovenance="" provenanceaction="sysimport:actionset">
<to class="IsSupplementedBy" scheme="dnet:result_result_relations" type="publication">
doi_dedup___::015b27b0b7c55649236bf23a5c75f817
</to>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">10.6084/m9.figshare.15656924.v2
</pid>
<dateofacceptance>2021-01-01</dateofacceptance>
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title"
schemename="dnet:dataCite_title">Implementation Details of the Reconstruction
Pipeline and Electrophysiological Inference Results from A completely automated pipeline
for 3D reconstruction of human heart from 2D cine magnetic resonance slices
</title>
<publisher>The Royal Society</publisher>
<collectedfrom name="Datacite" id="openaire____::9e3be59865b2c1c335d32dae2fe7b254"/>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">10.6084/m9.figshare.15656924
</pid>
</rel>
<rel inferred="false" trust="0.9" inferenceprovenance="" provenanceaction="sysimport:actionset">
<to class="isProducedBy" scheme="dnet:result_project_relations" type="project">
corda__h2020::27f89b49dee12d828cc0f90f51727204
</to>
<code>823712</code>
<funding>
<funder id="ec__________::EC" shortname="EC" name="European Commission"
jurisdiction="EU"/>
<funding_level_0 name="H2020">ec__________::EC::H2020</funding_level_0>
<funding_level_1 name="RIA">ec__________::EC::H2020::RIA</funding_level_1>
</funding>
<acronym>CompBioMed2</acronym>
<title>A Centre of Excellence in Computational Biomedicine</title>
</rel>
<rel inferred="false" trust="0.9" inferenceprovenance="" provenanceaction="sysimport:actionset">
<to class="IsSupplementedBy" scheme="dnet:result_result_relations" type="dataset">
doi_dedup___::be1ef3b30a8d7aa7e4dfe1570d5febf7
</to>
<dateofacceptance>2021-01-01</dateofacceptance>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">10.6084/m9.figshare.15656927
</pid>
<publisher>The Royal Society</publisher>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">10.6084/m9.figshare.15656927.v1
</pid>
<collectedfrom name="Datacite" id="openaire____::9e3be59865b2c1c335d32dae2fe7b254"/>
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title"
schemename="dnet:dataCite_title">Montage Video of the Stepwise Performance of 3D
Reconstruction Pipeline on All 20 Patients from A completely automated pipeline for 3D
reconstruction of human heart from 2D cine magnetic resonance slices
</title>
</rel>
<rel inferred="false" trust="0.9" inferenceprovenance="" provenanceaction="sysimport:actionset">
<to class="IsSupplementedBy" scheme="dnet:result_result_relations" type="dataset">
doi_________::9f9f2328e11d379b14cb888209e33088
</to>
<dateofacceptance>2021-01-01</dateofacceptance>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">10.6084/m9.figshare.15656924.v1
</pid>
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title"
schemename="dnet:dataCite_title">Implementation Details of the Reconstruction
Pipeline and Electrophysiological Inference Results from A completely automated pipeline
for 3D reconstruction of human heart from 2D cine magnetic resonance slices
</title>
<publisher>The Royal Society</publisher>
<collectedfrom name="Datacite" id="openaire____::9e3be59865b2c1c335d32dae2fe7b254"/>
</rel>
</rels>
<children>
<result objidentifier="pmid________::9c855c9c4a8018df23f9d51f879b62b1">
<dateofacceptance>2021-10-01</dateofacceptance>
<pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">34689630
</pid>
<collectedfrom name="PubMed Central" id="opendoar____::eda80a3d5b344bc40f3bc04f65b7a357"/>
<pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">34689630
</pid>
<publisher>The Royal Society</publisher>
<collectedfrom name="Europe PubMed Central"
id="opendoar____::8b6dd7db9af49e67306feb59a8bdc52c"/>
<pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">PMC8543046
</pid>
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title"
schemename="dnet:dataCite_title" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">A completely automated
pipeline for 3D reconstruction of human heart from 2D cine magnetic resonance slices
</title>
<pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">PMC8543046
</pid>
</result>
<result objidentifier="od______1064::83eb0f76b60445d72bb7428a1b68ef1a">
<dateofacceptance>2023-01-05</dateofacceptance>
<publisher>Royal Society</publisher>
<collectedfrom name="Oxford University Research Archive"
id="opendoar____::2290a7385ed77cc5592dc2153229f082"/>
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title"
schemename="dnet:dataCite_title" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">A completely automated
pipeline for 3D reconstruction of human heart from 2D cine magnetic resonance slices
</title>
</result>
<result objidentifier="doi_________::e225555a08a082ad8f53f179bc59c5d0">
<dateofacceptance>2021-10-25</dateofacceptance>
<publisher>The Royal Society</publisher>
<collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2"/>
<title classid="alternative title" classname="alternative title"
schemeid="dnet:dataCite_title" schemename="dnet:dataCite_title">A completely
automated pipeline for 3D reconstruction of human heart from 2D cine magnetic resonance
slices.
</title>
<collectedfrom name="UnpayWall" id="openaire____::8ac8380272269217cb09a928c8caa993"/>
<collectedfrom name="ORCID" id="openaire____::806360c771262b4d6770e7cdf04b5c5a"/>
<collectedfrom name="Microsoft Academic Graph"
id="openaire____::5f532a3fc4f1ea403f37070f59a7a53a"/>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types">10.1098/rsta.2020.0257
</pid>
</result>
<instance>
<accessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes"
schemename="dnet:access_modes"/>
<collectedfrom name="Oxford University Research Archive"
id="opendoar____::2290a7385ed77cc5592dc2153229f082"/>
<hostedby name="Oxford University Research Archive"
id="opendoar____::2290a7385ed77cc5592dc2153229f082"/>
<dateofacceptance>2023-01-05</dateofacceptance>
<instancetype classid="0038" classname="Other literature type"
schemeid="dnet:publication_resource" schemename="dnet:publication_resource"/>
<alternateidentifier classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">34689630
</alternateidentifier>
<alternateidentifier classid="doi" classname="Digital Object Identifier"
schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">
10.1098/rsta.2020.0257
</alternateidentifier>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels"
schemename="dnet:review_levels"/>
<license>http://creativecommons.org/licenses/by/4.0/</license>
<webresource>
<url>https://ora.ox.ac.uk/objects/uuid:9fc4563a-07e1-41d1-8b99-31ce2f8ac027</url>
</webresource>
</instance>
<instance>
<accessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes"
schemename="dnet:access_modes"/>
<collectedfrom name="UnpayWall" id="openaire____::8ac8380272269217cb09a928c8caa993"/>
<hostedby
name="Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences"
id="issn___print::c72e72d9860ed6d9ec013e20c9421ba0"/>
<instancetype classid="0001" classname="Article" schemeid="dnet:publication_resource"
schemename="dnet:publication_resource"/>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types">10.1098/rsta.2020.0257
</pid>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels"
schemename="dnet:review_levels"/>
<webresource>
<url>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8543046</url>
</webresource>
</instance>
<instance>
<accessright classid="CLOSED" classname="Closed Access" schemeid="dnet:access_modes"
schemename="dnet:access_modes"/>
<collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2"/>
<hostedby
name="Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences"
id="issn___print::c72e72d9860ed6d9ec013e20c9421ba0"/>
<dateofacceptance>2021-10-25</dateofacceptance>
<instancetype classid="0001" classname="Article" schemeid="dnet:publication_resource"
schemename="dnet:publication_resource"/>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types">10.1098/rsta.2020.0257
</pid>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels"
schemename="dnet:review_levels"/>
<license>https://royalsociety.org/journals/ethics-policies/data-sharing-mining/</license>
<webresource>
<url>https://doi.org/10.1098/rsta.2020.0257</url>
</webresource>
</instance>
<instance>
<accessright classid="UNKNOWN" classname="not available" schemeid="dnet:access_modes"
schemename="dnet:access_modes"/>
<collectedfrom name="Europe PubMed Central"
id="opendoar____::8b6dd7db9af49e67306feb59a8bdc52c"/>
<hostedby name="Unknown Repository" id="openaire____::55045bd2a65019fd8e6741a755395c8c"/>
<dateofacceptance>2021-10-25</dateofacceptance>
<instancetype classid="0001" classname="Article" schemeid="dnet:publication_resource"
schemename="dnet:publication_resource"/>
<pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">34689630
</pid>
<pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset"
trust="0.9">PMC8543046
</pid>
<alternateidentifier classid="doi" classname="Digital Object Identifier"
schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:actionset" trust="0.9">
10.1098/rsta.2020.0257
</alternateidentifier>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels"
schemename="dnet:review_levels"/>
<webresource>
<url>https://pubmed.ncbi.nlm.nih.gov/34689630</url>
</webresource>
</instance>
<instance>
<accessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes"
schemename="dnet:access_modes"/>
<collectedfrom name="PubMed Central" id="opendoar____::eda80a3d5b344bc40f3bc04f65b7a357"/>
<hostedby name="Europe PubMed Central" id="opendoar____::8b6dd7db9af49e67306feb59a8bdc52c"/>
<dateofacceptance>2021-10-01</dateofacceptance>
<instancetype classid="0001" classname="Article" schemeid="dnet:publication_resource"
schemename="dnet:publication_resource"/>
<pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">34689630
</pid>
<pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">PMC8543046
</pid>
<alternateidentifier classid="doi" classname="Digital Object Identifier"
schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:crosswalk:repository" trust="0.9">
10.1098/rsta.2020.0257
</alternateidentifier>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels"
schemename="dnet:review_levels"/>
<webresource>
<url>http://europepmc.org/articles/PMC8543046</url>
</webresource>
</instance>
</children>
</oaf:result>
</oaf:entity>
</metadata>
</result>
</record>

289
dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/edith-demo/10.2196-33081-ethics.xml Normal file
View File

@ -0,0 +1,289 @@
<record>
<result xmlns:dri="http://www.driver-repository.eu/namespace/dri"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<header>
<dri:objIdentifier>doi_dedup___::88a9861b26cdda1c3dd162d11f0bedbe</dri:objIdentifier>
<dri:dateOfCollection>2023-03-13T00:12:27+0000</dri:dateOfCollection>
<dri:dateOfTransformation>2023-03-13T04:39:52.807Z</dri:dateOfTransformation>
</header>
<metadata>
<oaf:entity xmlns:oaf="http://namespace.openaire.eu/oaf"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://namespace.openaire.eu/oaf http://namespace.openaire.eu/oaf http://www.openaire.eu/schema/0.2/oaf-0.2.xsd">
<oaf:result>
<collectedfrom name="NARCIS" id="openaire____::fdb035c8b3e0540a8d9a561a6c44f4de" />
<collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2" />
<collectedfrom name="UnpayWall" id="openaire____::8ac8380272269217cb09a928c8caa993" />
<collectedfrom name="ORCID" id="openaire____::806360c771262b4d6770e7cdf04b5c5a" />
<collectedfrom name="Microsoft Academic Graph" id="openaire____::5f532a3fc4f1ea403f37070f59a7a53a" />
<collectedfrom name="Europe PubMed Central" id="opendoar____::8b6dd7db9af49e67306feb59a8bdc52c" />
<collectedfrom name="NARCIS" id="eurocrisdris::fe4903425d9040f680d8610d9079ea14" />
<originalId>oai:pure.eur.nl:publications/70bf9bd0-5ea6-45fd-bb62-8d79b48cd69f</originalId>
<originalId>50|narcis______::3df5b8b060b819af0d439dd6751c8a77</originalId>
<originalId>10.2196/33081</originalId>
<originalId>50|doiboost____::88a9861b26cdda1c3dd162d11f0bedbe</originalId>
<originalId>3212148341</originalId>
<originalId>od_______267::276eb3ebee07cf1f3e8bfc43926fd0c2</originalId>
<originalId>35099399</originalId>
<originalId>PMC8844982</originalId>
<originalId>oai:services.nod.dans.knaw.nl:Publications/eur:oai:pure.eur.nl:publications/70bf9bd0-5ea6-45fd-bb62-8d79b48cd69f</originalId>
<originalId>50|dris___00893::107e97e645cbb06fb7b454ce2569d6c2</originalId>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types" schemename="dnet:pid_types">10.2196/33081</pid>
<pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">35099399</pid>
<pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">PMC8844982</pid>
<measure id="influence" score="4.9560573E-9" class="C" />
<measure id="popularity" score="1.6705286E-8" class="C" />
<measure id="influence_alt" score="6" class="C" />
<measure id="popularity_alt" score="2.16" class="C" />
<measure id="impulse" score="6" class="C" />
<title classid="alternative title" classname="alternative title" schemeid="dnet:dataCite_title" schemename="dnet:dataCite_title">Mapping the Ethical Issues of Digital Twins for Personalised Healthcare Service (Preprint)</title>
<title classid="subtitle" classname="subtitle" schemeid="dnet:dataCite_title" schemename="dnet:dataCite_title" inferred="false" provenanceaction="sysimport:crosswalk:datasetarchive" trust="0.9">Preliminary Mapping Study</title>
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title" schemename="dnet:dataCite_title" inferred="false" provenanceaction="sysimport:crosswalk:repository" trust="0.9">Ethical Issues of Digital Twins for Personalized Health Care Service: Preliminary Mapping Study</title>
<bestaccessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes" schemename="dnet:access_modes" />
<creator rank="2" URL="https://academic.microsoft.com/#/detail/3211925536" orcid="0000-0001-9882-0389">Ki-hun Kim</creator>
<creator rank="1" URL="https://academic.microsoft.com/#/detail/3214669734" orcid="0000-0001-5334-8615">Pei-hua Huang</creator>
<creator rank="3" URL="https://academic.microsoft.com/#/detail/3214611946" orcid="0000-0003-4283-9659">Maartje Schermer</creator>
<contributor>Public Health</contributor>
<country classid="NL" classname="Netherlands" schemeid="dnet:countries" schemename="dnet:countries" />
<dateofacceptance>2022-01-01</dateofacceptance>
<description>Background: The concept of digital twins has great potential for transforming the existing health care system by making it more personalized. As a convergence of health care, artificial intelligence, and information and communication technologies, personalized health care services that are developed under the concept of digital twins raise a myriad of ethical issues. Although some of the ethical issues are known to researchers working on digital health and personalized medicine, currently, there is no comprehensive review that maps the major ethical risks of digital twins for personalized health care services. Objective This study aims to fill the research gap by identifying the major ethical risks of digital twins for personalized health care services. We first propose a working definition for digital twins for personalized health care services to facilitate future discussions on the ethical issues related to these emerging digital health services. We then develop a process-oriented ethical map to identify the major ethical risks in each of the different data processing phases. MethodsWe resorted to the literature on eHealth, personalized medicine, precision medicine, and information engineering to identify potential issues and developed a process-oriented ethical map to structure the inquiry in a more systematic way. The ethical map allows us to see how each of the major ethical concerns emerges during the process of transforming raw data into valuable information. Developers of a digital twin for personalized health care service may use this map to identify ethical risks during the development stage in a more systematic way and can proactively address them. ResultsThis paper provides a working definition of digital twins for personalized health care services by identifying 3 features that distinguish the new application from other eHealth services. On the basis of the working definition, this paper further layouts 10 major operational problems and the corresponding ethical risks. ConclusionsIt is challenging to address all the major ethical risks that a digital twin for a personalized health care service might encounter proactively without a conceptual map at hand. The process-oriented ethical map we propose here can assist the developers of digital twins for personalized health care services in analyzing ethical risks in a more systematic manner. </description>
<subject classid="mesh" classname="Medical Subject Headings" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="true" inferenceprovenance="iis::document_classes" provenanceaction="iis" trust="0.891">education</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies">Health Informatics</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies">Ethical issues</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies">Healthcare service</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies">Psychology</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies">Internet privacy</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="false" provenanceaction="sysimport:actionset" trust="0.4395309">business.industry</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="false" provenanceaction="sysimport:actionset" trust="0.4395309">business</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies">Preprint</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">Artificial Intelligence</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">Delivery of Health Care</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">Health Services</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">Humans</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">Precision Medicine</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies" schemename="dnet:subject_classification_typologies" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">Telemedicine</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">03 medical and health sciences</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0302 clinical medicine
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">030212 General &amp; Internal Medicine
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0301 basic medicine
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">030104 Developmental Biology
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0303 health sciences
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">030304 Developmental Biology
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">Health care/Health care quality
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">medication ---- alert ---- drug ---- error ---- patient ---- clinical ---- order ---- pharmacist ---- result ---- interaction
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">nurse ---- patient ---- nursing ---- hospital ---- staff ---- staffing ---- care ---- mortality ---- level ---- outcome
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">health ---- public ---- service ---- care ---- healthcare ---- decision ---- policy ---- health care ---- engagement ---- make
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">structure ---- protein ---- structural ---- pdb ---- bind ---- data ---- crystal ---- datum ---- base ---- bank
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">datum
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">health care
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">electronic health
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">intelligence
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">artificial intelligence
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">ethical
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">datum management
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">06 humanities and the arts</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0603 philosophy, ethics and religion
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">060301 Applied Ethics
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">Bioethics/Coordinates on Wikidata
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">ai ---- moral ---- technology ---- human ---- artificial ---- responsibility ---- value ---- intelligence ---- ethical ---- artificial intelligence
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">genomic ---- africa ---- biobanking ---- datum ---- ethical ---- country ---- researcher ---- health ---- biobank ---- sample
</subject>
<language classid="eng" classname="English" schemeid="dnet:languages" schemename="dnet:languages" />
<relevantdate classid="created" classname="created" schemeid="dnet:dataCite_date" schemename="dnet:dataCite_date">2021-11-17</relevantdate>
<relevantdate classid="published-online" classname="published-online" schemeid="dnet:dataCite_date" schemename="dnet:dataCite_date">2022-01-31</relevantdate>
<relevantdate classid="issued" classname="issued" schemeid="dnet:dataCite_date" schemename="dnet:dataCite_date" inferred="false" provenanceaction="sysimport:crosswalk:datasetarchive" trust="0.9">2022-01-01</relevantdate>
<source>Crossref</source>
<source />
<source>Journal of Medical Internet Research, 24(1):e33081. Journal of medical Internet Research</source>
<source>urn:issn:1439-4456</source>
<source>VOLUME=24;ISSUE=1;ISSN=1439-4456;TITLE=Journal of Medical Internet Research</source>
<format>application/pdf</format>
<resulttype classid="publication" classname="publication" schemeid="dnet:result_typologies" schemename="dnet:result_typologies" />
<resourcetype classid="0001" classname="0001" schemeid="dnet:dataCite_resource" schemename="dnet:dataCite_resource" />
<context id="knowmad" label="Knowmad Institut" type="community" />
<context id="dth" label="Digital Twins in Health" type="community"/>
<datainfo>
<inferred>true</inferred>
<deletedbyinference>false</deletedbyinference>
<trust>0.8</trust>
<inferenceprovenance>dedup-result-decisiontree-v3</inferenceprovenance>
<provenanceaction classid="sysimport:dedup" classname="Inferred by OpenAIRE" schemeid="dnet:provenanceActions" schemename="dnet:provenanceActions" />
</datainfo>
<rels />
<children>
<result objidentifier="narcis______::3df5b8b060b819af0d439dd6751c8a77">
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title" schemename="dnet:dataCite_title" inferred="false" provenanceaction="sysimport:crosswalk:repository" trust="0.9">Ethical Issues of Digital Twins for Personalized Health Care Service: Preliminary Mapping Study</title>
<collectedfrom name="NARCIS" id="openaire____::fdb035c8b3e0540a8d9a561a6c44f4de" />
<dateofacceptance>2022-01-01</dateofacceptance>
</result>
<result objidentifier="pmid________::70f4213809e44f787bf9f6ffa50ff98f">
<pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">PMC8844982</pid>
<collectedfrom name="Europe PubMed Central" id="opendoar____::8b6dd7db9af49e67306feb59a8bdc52c" />
<dateofacceptance>2021-08-23</dateofacceptance>
<title classid="main title" classname="main title" schemeid="dnet:dataCite_title" schemename="dnet:dataCite_title" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">Ethical Issues of Digital Twins for Personalized Health Care Service: Preliminary Mapping Study.</title>
<pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">35099399</pid>
</result>
<result objidentifier="dris___00893::107e97e645cbb06fb7b454ce2569d6c2">
<title classid="subtitle" classname="subtitle" schemeid="dnet:dataCite_title" schemename="dnet:dataCite_title" inferred="false" provenanceaction="sysimport:crosswalk:datasetarchive" trust="0.9">Preliminary Mapping Study</title>
<dateofacceptance>2022-01-01</dateofacceptance>
<collectedfrom name="NARCIS" id="eurocrisdris::fe4903425d9040f680d8610d9079ea14" />
</result>
<result objidentifier="doi_________::88a9861b26cdda1c3dd162d11f0bedbe">
<dateofacceptance>2022-01-31</dateofacceptance>
<title classid="alternative title" classname="alternative title" schemeid="dnet:dataCite_title" schemename="dnet:dataCite_title">Mapping the Ethical Issues of Digital Twins for Personalised Healthcare Service (Preprint)</title>
<collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2" />
<collectedfrom name="UnpayWall" id="openaire____::8ac8380272269217cb09a928c8caa993" />
<collectedfrom name="ORCID" id="openaire____::806360c771262b4d6770e7cdf04b5c5a" />
<collectedfrom name="Microsoft Academic Graph" id="openaire____::5f532a3fc4f1ea403f37070f59a7a53a" />
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types" schemename="dnet:pid_types">10.2196/33081</pid>
<publisher>JMIR Publications Inc.</publisher>
</result>
<instance>
<accessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes" schemename="dnet:access_modes" />
<collectedfrom name="Europe PubMed Central" id="opendoar____::8b6dd7db9af49e67306feb59a8bdc52c" />
<hostedby name="Journal of Medical Internet Research" id="doajarticles::972bc6f95b43b5ad42f75695b1d8e948" />
<dateofacceptance>2021-08-23</dateofacceptance>
<instancetype classid="0001" classname="Article" schemeid="dnet:publication_resource" schemename="dnet:publication_resource" />
<pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">35099399</pid>
<pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">PMC8844982</pid>
<alternateidentifier classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">10.2196/33081</alternateidentifier>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels" schemename="dnet:review_levels" />
<webresource>
<url>https://pubmed.ncbi.nlm.nih.gov/35099399</url>
</webresource>
</instance>
<instance>
<accessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes" schemename="dnet:access_modes" />
<collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2" />
<collectedfrom name="NARCIS" id="eurocrisdris::fe4903425d9040f680d8610d9079ea14" />
<hostedby name="Journal of Medical Internet Research" id="doajarticles::972bc6f95b43b5ad42f75695b1d8e948" />
<dateofacceptance>2022-01-01</dateofacceptance>
<dateofacceptance>2022-01-31</dateofacceptance>
<instancetype classid="0001" classname="Article" schemeid="dnet:publication_resource" schemename="dnet:publication_resource" />
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types" schemename="dnet:pid_types">10.2196/33081</pid>
<alternateidentifier classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:crosswalk:datasetarchive" trust="0.9">10.2196/33081</alternateidentifier>
<alternateidentifier classid="urn" classname="urn" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:crosswalk:datasetarchive" trust="0.9">urn:nbn:nl:ui:15-70bf9bd0-5ea6-45fd-bb62-8d79b48cd69f</alternateidentifier>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels" schemename="dnet:review_levels" />
<webresource>
<url>https://doi.org/10.2196/33081</url>
</webresource>
</instance>
<instance>
<accessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes" schemename="dnet:access_modes" />
<collectedfrom name="NARCIS" id="openaire____::fdb035c8b3e0540a8d9a561a6c44f4de" />
<hostedby name="NARCIS" id="openaire____::fdb035c8b3e0540a8d9a561a6c44f4de" />
<dateofacceptance>2022-01-01</dateofacceptance>
<instancetype classid="0001" classname="Article" schemeid="dnet:publication_resource" schemename="dnet:publication_resource" />
<alternateidentifier classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:crosswalk:repository" trust="0.9">10.2196/33081</alternateidentifier>
<alternateidentifier classid="urn" classname="urn" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:crosswalk:repository" trust="0.9">urn:nbn:nl:ui:15-70bf9bd0-5ea6-45fd-bb62-8d79b48cd69f</alternateidentifier>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels" schemename="dnet:review_levels" />
<webresource>
<url>https://pure.eur.nl/en/publications/70bf9bd0-5ea6-45fd-bb62-8d79b48cd69f</url>
</webresource>
</instance>
</children>
</oaf:result>
</oaf:entity>
</metadata>
</result>
</record>

223
dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/edith-demo/10.3390-pr9111967-covid.xml Normal file
View File

@ -0,0 +1,223 @@
<record>
<result xmlns:dri="http://www.driver-repository.eu/namespace/dri"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<header>
<dri:objIdentifier>doi_________::c166d06aeaed817937a79a400906a4b9</dri:objIdentifier>
<dri:dateOfCollection>2023-03-09T00:12:02.045Z</dri:dateOfCollection>
<dri:dateOfTransformation>2023-03-09T00:24:00.8Z</dri:dateOfTransformation>
</header>
<metadata>
<oaf:entity xmlns:oaf="http://namespace.openaire.eu/oaf"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://namespace.openaire.eu/oaf http://namespace.openaire.eu/oaf http://www.openaire.eu/schema/0.2/oaf-0.2.xsd">
<oaf:result>
<collectedfrom name="OpenAPC Global Initiative"
id="apc_________::e2b1600b229fc30663c8a1f662debddf"/>
<collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2"/>
<collectedfrom name="UnpayWall" id="openaire____::8ac8380272269217cb09a928c8caa993"/>
<collectedfrom name="ORCID" id="openaire____::806360c771262b4d6770e7cdf04b5c5a"/>
<collectedfrom name="Microsoft Academic Graph" id="openaire____::5f532a3fc4f1ea403f37070f59a7a53a"/>
<originalId>50|openapc_____::c166d06aeaed817937a79a400906a4b9</originalId>
<originalId>10.3390/pr9111967</originalId>
<originalId>pr9111967</originalId>
<originalId>50|doiboost____::c166d06aeaed817937a79a400906a4b9</originalId>
<originalId>3209532762</originalId>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types" inferred="false"
provenanceaction="sysimport:crosswalk:datasetarchive" trust="0.9">10.3390/pr9111967
</pid>
<measure id="influence" score="5.187591E-9" class="C"/>
<measure id="popularity" score="2.4479982E-8" class="C"/>
<measure id="influence_alt" score="10" class="C"/>
<measure id="popularity_alt" score="3.6" class="C"/>
<measure id="impulse" score="10" class="C"/>
<title classid="alternative title" classname="alternative title" schemeid="dnet:dataCite_title"
schemename="dnet:dataCite_title">Digital Twins for Continuous mRNA Production
</title>
<bestaccessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes"
schemename="dnet:access_modes"/>
<dateofacceptance>2021-11-04</dateofacceptance>
<description>The global coronavirus pandemic continues to restrict public life worldwide. An
effective means of limiting the pandemic is vaccination. Messenger ribonucleic acid (mRNA)
vaccines currently available on the market have proven to be a well-tolerated and effective
class of vaccine against coronavirus type 2 (CoV2). Accordingly, demand is presently
outstripping mRNA vaccine production. One way to increase productivity is to switch from the
currently performed batch to continuous in vitro transcription, which has proven to be a crucial
material-consuming step. In this article, a physico-chemical model of in vitro mRNA
transcription in a tubular reactor is presented and compared to classical batch and continuous
in vitro transcription in a stirred tank. The three models are validated based on a distinct and
quantitative validation workflow. Statistically significant parameters are identified as part of
the parameter determination concept. Monte Carlo simulations showed that the model is precise,
with a deviation of less than 1%. The advantages of continuous production are pointed out
compared to batchwise in vitro transcription by optimization of the space–time yield.
Improvements of a factor of 56 (0.011 µM/min) in the case of the continuously stirred tank
reactor (CSTR) and 68 (0.013 µM/min) in the case of the plug flow reactor (PFR) were found.
</description>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Process Chemistry and Technology
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Chemical Engineering (miscellaneous)
</subject>
<subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Bioengineering
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Coronavirus
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.4019353">medicine.disease_cause
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="false"
provenanceaction="sysimport:actionset" trust="0.4019353">medicine
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Continuous production
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Messenger RNA
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Continuous stirred-tank reactor
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Plug flow reactor model
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Mathematics
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">In vitro transcription
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Biological system
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Yield (chemistry)
</subject>
<subject classid="MAG" classname="Microsoft Academic Graph classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies">Public life
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">03 medical and health sciences
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0301 basic medicine
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">030104 Developmental Biology
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0303 health sciences
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">030304 Developmental Biology
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">02 engineering and technology
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0210 nano-technology
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">021001 Nanoscience &amp;
Nanotechnology
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">01 natural sciences
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">0104 chemical sciences
</subject>
<subject classid="FOS" classname="Fields of Science and Technology classification"
schemeid="dnet:subject_classification_typologies"
schemename="dnet:subject_classification_typologies" inferred="true"
inferenceprovenance="update" provenanceaction="subject:fos">010405 Organic Chemistry
</subject>
<language classid="UNKNOWN" classname="UNKNOWN" schemeid="dnet:languages"
schemename="dnet:languages"/>
<relevantdate classid="created" classname="created" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date">2021-11-05
</relevantdate>
<relevantdate classid="published-online" classname="published-online" schemeid="dnet:dataCite_date"
schemename="dnet:dataCite_date">2021-11-04
</relevantdate>
<source>Crossref</source>
<source/>
<resulttype classid="publication" classname="publication" schemeid="dnet:result_typologies"
schemename="dnet:result_typologies"/>
<resourcetype classid="0001" classname="Article" schemeid="dnet:publication_resource"
schemename="dnet:publication_resource"/>
<processingchargeamount>2146.08</processingchargeamount>
<processingchargecurrency>EUR</processingchargecurrency>
<journal issn="2227-9717">Processes</journal>
<context id="covid-19" label="COVID-19" type="community"/>
<context id="dth" label="Digital Twins in Health" type="community"/>
<datainfo>
<inferred>false</inferred>
<deletedbyinference>false</deletedbyinference>
<trust>0.9</trust>
<inferenceprovenance>null</inferenceprovenance>
<provenanceaction classid="sysimport:actionset" classname="Harvested"
schemeid="dnet:provenanceActions" schemename="dnet:provenanceActions"/>
</datainfo>
<rels/>
<children>
<instance>
<accessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes"
schemename="dnet:access_modes"/>
<collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2"/>
<hostedby name="Processes" id="doajarticles::9c4841602dcae937ac9c86cfb03c5ee1"/>
<dateofacceptance>2021-11-04</dateofacceptance>
<instancetype classid="0001" classname="Article" schemeid="dnet:publication_resource"
schemename="dnet:publication_resource"/>
<pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
schemename="dnet:pid_types">10.3390/pr9111967
</pid>
<refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels"
schemename="dnet:review_levels"/>
<license>https://creativecommons.org/licenses/by/4.0/</license>
<webresource>
<url>https://doi.org/10.3390/pr9111967</url>
</webresource>
</instance>
</children>
</oaf:result>
</oaf:entity>
</metadata>
</result>
</record>