cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29595956.v2
title: P- and S-wave velocity measurement of lunar orthopyroxene up to 5.5 GPa and 1273 K: Implication for the iron content of the lunar upper mantle

description: Source data Fig.1: Experimental pressure, temperature, P- and S-wave velocities (V<sub>P</sub> and V<sub>S</sub>) and volume of orthopyroxene. Pressure, V<sub>P</sub>, V<sub>S</sub> and volume of the 300 K, 473 K, 673 K, 873 K, 1073 K and 1273 K isotherms derived from fitting experimental data by a eulerian finite strain equation of state to the 3rd order.Source data Fig.2: Fe# =Fe/(Mg+Fe), K<sub>S0</sub>, G<sub>0</sub> and volume of orthopyroxene reported in this and previous studies.Source data Fig.3: V<sub>P</sub>, V<sub>S</sub> and density of the En<sub>84</sub>Fs<sub>13</sub>Wo<sub>3</sub> orthopyroxene (64 vol.%) + Fo<sub>87</sub> olivine (36 vol.%) model and En<sub>80</sub>Fs<sub>20</sub> orthopyroxene (64 vol.%) + Fo<sub>80</sub> olivine (36 vol.%) model along the lunar geotherm. V<sub>P</sub>, V<sub>S</sub> and density of lunar seismic models reported in previous studies.
DOI: 10.15468/dl.g9dbuw
title: Occurrence Download

description: A dataset listing the 67 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Biodiversity of ants (Formicidae) in some regions of European Russia"
 ]
}

 The dataset's 67 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004538-260120142942310/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.29595956.v1
title: Inoue2025 source data.xlsx

description: Source data Fig.1: Experimental pressure, temperature, P- and S-wave velocities (V<sub>P</sub> and V<sub>S</sub>) and volume of orthopyroxene. Pressure, V<sub>P</sub>, V<sub>S</sub> and volume of the 300 K, 473 K, 673 K, 873 K, 1073 K and 1273 K isotherms derived from fitting experimental data by a eulerian finite strain equation of state to the 3rd order.Source data Fig.2: Fe# =Fe/(Mg+Fe), K<sub>S0</sub>, G<sub>0</sub> and volume of orthopyroxene reported in this and previous studies.Source data Fig.3: V<sub>P</sub>, V<sub>S</sub> and density of the En<sub>84</sub>Fs<sub>13</sub>Wo<sub>3</sub> orthopyroxene (64 vol.%) + Fo<sub>87</sub> olivine (36 vol.%) model and En<sub>80</sub>Fs<sub>20</sub> orthopyroxene (64 vol.%) + Fo<sub>80</sub> olivine (36 vol.%) model along the lunar geotherm. V<sub>P</sub>, V<sub>S</sub> and density of lunar seismic models reported in previous studies.
DOI: 10.15468/dl.vvmjtt
title: Occurrence Download

description: A dataset containing 194 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (CAN.11.9_1, CAN.11.42_1, CAN.11.90_1, CAN.11.62_1, CAN.11.12_1, CAN.11.23_1, CAN.11.64_1, CAN.11.54_1, CAN.11.29_1)",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Spartina pectinata, Spartina pectinata, Spartina pectinata pectinata, Spartina pectinata variegata, Spartina pectinata suttiei, Spartina pectinata pectinata, Sporobolus michauxianus, Spartina, Deschampsia cespitosa, Deschampsia cespitosa anadyrensis, Alnus incana, Triantha glutinosa, Prunus pumila, Prunus depressa, Triantha glutinosa glutinosa, Tofieldia glutinosa, Tofieldia glutinosa glutinosa, Tofieldia, Tofieldia, Solidago simplex, Arabis lyrata, Anemone virginiana, Anemone riparia, Schizachyrium scoparium, Danthonia spicata compressa, Packera paupercula)"
 ]
}

 The dataset includes 194 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004546-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6k7wxr
title: Occurrence Download

description: A dataset containing 2657 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Larix, Quercus mongolica, Betula platyphylla, Acer pictum mono, Tilia amurensis, Betula davurica, Ulmus davidiana japonica, Pinus koraiensis, Picea koraiensis, Populus davidiana)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is China",
 "DecimalLongitude is greater than or equal to 115.517856010571",
 "DecimalLongitude is less than or equal to 134.776778850189",
 "DecimalLatitude is greater than or equal to 38.7213387829139",
 "DecimalLatitude is less than or equal to 53.5612073597801"
 ]
}

 The dataset includes 2657 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004547-260120142942310/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.31120219
title: <i>sirt5</i>, a target of miR-21-y, acts as a negative regulator of <i>mavs</i>-dependent antiviral immunity in rainbow trout (<i>Oncorhynchus mykiss</i>)

description: Raw numerical data and statistical calculations for plotting graphs generated in our study
DOI: 10.6084/m9.figshare.31120219.v1
title: <i>sirt5</i>, a target of miR-21-y, acts as a negative regulator of <i>mavs</i>-dependent antiviral immunity in rainbow trout (<i>Oncorhynchus mykiss</i>)

description: Raw numerical data and statistical calculations for plotting graphs generated in our study
DOI: 10.15468/dl.marr3q
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.24926000000001 24.45773, 89.172118 24.452153, 89.096896 24.435561, 89.025463 24.408366, 88.959592 24.371244, 88.900914 24.325119, 88.850877 24.271133, 88.81071 24.210626, 88.781392 24.145095, 88.763631 24.07616, 88.757846 24.005522, 88.764161 23.934923, 88.7824 23.866098, 88.81209699999999 23.800738, 88.852508 23.740447, 88.902629 23.686701, 88.961223 23.640814, 89.02685 23.603908, 89.097904 23.576885, 89.172648 23.560402, 89.24926000000001 23.554863, 89.325872 23.560402, 89.400616 23.576885, 89.47167 23.603908, 89.537297 23.640814, 89.59589099999999 23.686701, 89.646012 23.740447, 89.686423 23.800738, 89.71612 23.866098, 89.734359 23.934923, 89.740674 24.005522, 89.734889 24.07616, 89.717128 24.145095, 89.68781 24.210626, 89.647643 24.271133, 89.597606 24.325119, 89.538928 24.371244, 89.473057 24.408366, 89.401624 24.435561, 89.326402 24.452153, 89.24926000000001 24.45773))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004550-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18335047
title: SARI-Hospitalisierungsinzidenz

description: Im Datensatz "SARI-Hospitalisierungsinzidenz" des Robert Koch-Instituts werden die wöchentlichen Inzidenzen schwerer akuter respiratorischer Infektionen (SARI) auf Bundesebene in Deutschland bereitgestellt. Die Daten stammen aus der syndromischen Krankenhaussurveillance ICOSARI, die auf ICD-10-Diagnosecodes aus etwa 70 Sentinelkliniken basiert. Der Datensatz umfasst Hospitalisierungsinzidenzen pro 100.000 Einwohner, aufgeschlüsselt nach Altersgruppen, Saison und Kalenderwoche. Neben der Gesamtheit aller SARI-Fälle werden auch Fälle mit zusätzlicher COVID-19-, Influenza- oder RSV-Diagnose separat erfasst. Die Surveillance liefert entscheidende Informationen zur Krankheitslast akuter respiratorischer Erkrankungen und dient als Grundlage für epidemiologische Bewertungen und Empfehlungen für gesundheitspolitische Maßnahmen.
DOI: 10.5281/zenodo.18335046
title: GrippeWeb - Daten des Wochenberichts

description: Im Datensatz "GrippeWeb - Daten des Wochenberichts" des Robert Koch-Instituts werden wöchentliche, bevölkerungsbasierte Schätzungen zur Inzidenz akuter respiratorischer Erkrankungen (ARE) und grippeähnlicher Erkrankungen (ILI) in Deutschland bereitgestellt. GrippeWeb als Online-Portal zur partizipativen syndromischen Surveillance nutzt Selbstauskünfte freiwilliger, pseudonym registrierter Teilnehmender ab 16 Jahren zu Symptomen wie Husten, Fieber und Halsschmerzen. Daraus werden Inzidenzen nach Altersgruppen und Regionen errechnet. Die erhobenen Daten unterstützen die Überwachung saisonaler Infektionen und dienen der Risikobewertung in Pandemien wie COVID-19.
DOI: 10.15468/dl.yrc2qw
title: Occurrence Download

description: A dataset containing 87 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cenchrus americanus",
 "Year 1960-2010"
 ]
}

 The dataset includes 87 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004551-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nvs4ge
title: Occurrence Download

description: A dataset containing 171 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Hibernating Ichneumonidae records in the Western Palearctic",
 "Country is Belgium"
 ]
}

 The dataset includes 171 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004553-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.33095
title: 250637 Enhance publishing丨Performance Analysis for Self-Sustainable Intelligent Metasurface BasedReliable and Secure Communication Strategies (Appendix)
title: 250637增强出版丨自供能智能超表面可靠安全通信策略与性能分析

description: Solemnly declare: If you use this open source content in papers, books, academic reports and other works, please quote the following documents(The original link has the latest citation format):Paper：Performance Analysis for Self-Sustainable Intelligent Metasurface BasedReliable and Secure Communication StrategiesAuthor: QU YayunAffiliation: Engineering University of Information Support ForcesDOI: 10.11999/JEIT250637Contact Email: QU Yayun，quyayun@nudt.edu.cnOriginal link: https://jeit.ac.cn/cn/article/doi/10.11999/JEIT250637Open Access Date: December 4, 2025Open Access Content: Proofs of Theorem 1 to Theorem 5
description: Solemnly declare: If you use this open source content in papers, books, academic reports and other works, please quote the following documents(The original link has the latest citation format):Paper：Performance Analysis for Self-Sustainable Intelligent Metasurface BasedReliable and Secure Communication StrategiesAuthor: QU YayunAffiliation: Engineering University of Information Support ForcesDOI: 10.11999/JEIT250637Contact Email: QU Yayun，quyayun@nudt.edu.cnOriginal link: https://jeit.ac.cn/cn/article/doi/10.11999/JEIT250637Open Access Date: December 4, 2025Open Access Content: Proofs of Theorem 1 to Theorem 5
DOI: 10.6084/m9.figshare.31046415
title: Crossing the borders of flood risk adaptation and nature conservation: an insider's perspective on navigating a wicked problem-solution space

description: The interconnectedness of climate change and biodiversity challenges necessitates integrative approaches and cross-sectoral collaboration. Although this is widely acknowledged, it remains poorly understood how actors at the operational level can address multiple environmental challenges simultaneously. To close this knowledge gap, we examine the dynamics of cross-sectoral integration. We apply three dimensions of wickedness – contestation, complexity, and uncertainty – to deduce problems and solutions. These three dimensions constitute the empirical problem–solution space where actors strive to integrate problems <i>and</i> solutions across sectors. The integration of flood risk adaptation and nature conservation challenges in the Netherlands serves as a case study. Data were collected through participatory action research in a Community of Practice (CoP). Over a period of 2.5 years, the CoP brought together actors from flood risk and nature sectors. They sought integration by crossing borders, on maps, across sectors, and between projects. <i>Contestation</i> was triggered by diverging understandings of nature and flood risk<i>.</i> Systemic and organizational factors increased <i>complexity</i> which caused actors to feel confined. Nature-based solutions are seen as promising, but their effectiveness and legal procedures are <i>uncertain</i>. Our results indicate that cross-sectoral collaboration enlarges the problem–solution space. Therefore, integrative approaches require additional space for navigating wickedness. We confirm that collaborative learning and producing knowledge are essential for the convergence of wicked problem–solution spaces. The CoP provided actors with a sense of belonging and space for creativity and innovation. This allowed them to collectively learn about the wickedness of integrating flood risk adaptation and nature conservation. Cross-sectoral integration increases contestation, complexity and uncertainty.In our case, integration was hampered by false assumptions, sectoral practices and discourses.Collaborative activities were essential for understanding, navigating and converging wickedness.A community of practice provided a sense of belonging and space for innovation and creativity. Cross-sectoral integration increases contestation, complexity and uncertainty. In our case, integration was hampered by false assumptions, sectoral practices and discourses. Collaborative activities were essential for understanding, navigating and converging wickedness. A community of practice provided a sense of belonging and space for innovation and creativity.
DOI: 10.6084/m9.figshare.31046415.v1
title: Crossing the borders of flood risk adaptation and nature conservation: an perspective on navigating a wicked problem–solution space

description: The interconnectedness of climate change and biodiversity challenges necessitates integrative approaches and cross-sectoral collaboration. Although this is widely acknowledged, it remains poorly understood how actors at the operational level can address multiple environmental challenges simultaneously. To close this knowledge gap, we examine the dynamics of cross-sectoral integration. We apply three dimensions of wickedness – contestation, complexity, and uncertainty – to deduce problems and solutions. These three dimensions constitute the empirical problem–solution space where actors strive to integrate problems <i>and</i> solutions across sectors. The integration of flood risk adaptation and nature conservation challenges in the Netherlands serves as a case study. Data were collected through participatory action research in a Community of Practice (CoP). Over a period of 2.5 years, the CoP brought together actors from flood risk and nature sectors. They sought integration by crossing borders, on maps, across sectors, and between projects. <i>Contestation</i> was triggered by diverging understandings of nature and flood risk<i>.</i> Systemic and organizational factors increased <i>complexity</i> which caused actors to feel confined. Nature-based solutions are seen as promising, but their effectiveness and legal procedures are <i>uncertain</i>. Our results indicate that cross-sectoral collaboration enlarges the problem–solution space. Therefore, integrative approaches require additional space for navigating wickedness. We confirm that collaborative learning and producing knowledge are essential for the convergence of wicked problem–solution spaces. The CoP provided actors with a sense of belonging and space for creativity and innovation. This allowed them to collectively learn about the wickedness of integrating flood risk adaptation and nature conservation. Cross-sectoral integration increases contestation, complexity and uncertainty.In our case, integration was hampered by false assumptions, sectoral practices and discourses.Collaborative activities were essential for understanding, navigating and converging wickedness.A community of practice provided a sense of belonging and space for innovation and creativity. Cross-sectoral integration increases contestation, complexity and uncertainty. In our case, integration was hampered by false assumptions, sectoral practices and discourses. Collaborative activities were essential for understanding, navigating and converging wickedness. A community of practice provided a sense of belonging and space for innovation and creativity.
DOI: 10.6084/m9.figshare.31046415.v2
title: Crossing the borders of flood risk adaptation and nature conservation: an insider's perspective on navigating a wicked problem-solution space

description: The interconnectedness of climate change and biodiversity challenges necessitates integrative approaches and cross-sectoral collaboration. Although this is widely acknowledged, it remains poorly understood how actors at the operational level can address multiple environmental challenges simultaneously. To close this knowledge gap, we examine the dynamics of cross-sectoral integration. We apply three dimensions of wickedness – contestation, complexity, and uncertainty – to deduce problems and solutions. These three dimensions constitute the empirical problem–solution space where actors strive to integrate problems <i>and</i> solutions across sectors. The integration of flood risk adaptation and nature conservation challenges in the Netherlands serves as a case study. Data were collected through participatory action research in a Community of Practice (CoP). Over a period of 2.5 years, the CoP brought together actors from flood risk and nature sectors. They sought integration by crossing borders, on maps, across sectors, and between projects. <i>Contestation</i> was triggered by diverging understandings of nature and flood risk<i>.</i> Systemic and organizational factors increased <i>complexity</i> which caused actors to feel confined. Nature-based solutions are seen as promising, but their effectiveness and legal procedures are <i>uncertain</i>. Our results indicate that cross-sectoral collaboration enlarges the problem–solution space. Therefore, integrative approaches require additional space for navigating wickedness. We confirm that collaborative learning and producing knowledge are essential for the convergence of wicked problem–solution spaces. The CoP provided actors with a sense of belonging and space for creativity and innovation. This allowed them to collectively learn about the wickedness of integrating flood risk adaptation and nature conservation. Cross-sectoral integration increases contestation, complexity and uncertainty.In our case, integration was hampered by false assumptions, sectoral practices and discourses.Collaborative activities were essential for understanding, navigating and converging wickedness.A community of practice provided a sense of belonging and space for innovation and creativity. Cross-sectoral integration increases contestation, complexity and uncertainty. In our case, integration was hampered by false assumptions, sectoral practices and discourses. Collaborative activities were essential for understanding, navigating and converging wickedness. A community of practice provided a sense of belonging and space for innovation and creativity.
DOI: 10.5281/zenodo.18335050
title: ACEM 9686 - supplementary files
DOI: 10.5281/zenodo.18335051
title: ACEM 9686 - supplementary files
DOI: 10.57841/casdc.0006989
title: 百米级热等静压系统的优化数据
DOI: 10.5281/zenodo.18334169
title: SuperDARN data in netCDF format (2002-Oct)

description: 2002-Oct SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6787193
title: SuperDARN data in netCDF format (2002-Oct)

description: 2002-Oct SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'