cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4559541
title: QSM Reconstruction Challenge 2.0 - Data and Code Provided to Participants

description: This repository contains the data provided to applicants during Stage 1 and Stage 2 of the 2<sup>nd</sup>QSM challenge along with the functionalities used to obtain the evaluation metrics. The description of how to create such simulated ground truth can be found in the the MRM paper: "QSM Reconstruction Challenge 2.0: a realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures" here and the accompanying data sharing collection. The original submissions for Stage 1 and 2 of the challenge are publicly available in the following Zenodo Repositories Stage 1 link and Stage 2 link.<br> The full description of the submitted reconstructions and the metrics of each of those submissions can be found here.<br> The results of the challenge are fully reported in the MRM paper "QSM Reconstruction Challenge 2.0: Design and Report of Results" here
DOI: 10.5281/zenodo.4559540
title: QSM Reconstruction Challenge 2.0 - Data and Code Provided to Participants

description: This repository contains the data provided to applicants during Stage 1 and Stage 2 of the 2<sup>nd</sup>QSM challenge along with the functionalities used to obtain the evaluation metrics. The description of how to create such simulated ground truth can be found in the the MRM paper: "QSM Reconstruction Challenge 2.0: a realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures" here and the accompanying data sharing collection. The original submissions for Stage 1 and 2 of the challenge are publicly available in the following Zenodo Repositories Stage 1 link and Stage 2 link.<br> The full description of the submitted reconstructions and the metrics of each of those submissions can be found here.<br> The results of the challenge are fully reported in the MRM paper "QSM Reconstruction Challenge 2.0: Design and Report of Results" here
DOI: 10.5281/zenodo.4559550
title: PALM model system 6.0 source code, revisions r4450 and r4601

description: The dataset contains the PALM model system 6.0 source code in revision r4450 and r4601, used in the research article entitled "Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications ". The PALM model system has been developed and is maintained by the PALM group at the Institute of Meteorology and Climatology (IMUK) of Leibniz Universität Hannover, Germany.
description: MOSAIK and MOSAIK-2 are funded by the German Federal Ministry of Education and Research (BMBF) under grant 01LP1601A and 01LP1911H within the framework of Research for Sustainable Development (FONA; www.fona.de). Benchmark and test runs with PALM have been performed at the supercomputers of the North-German Super- computing Alliance (HLRN), which is gratefully acknowledged. The German Aerospace Center (DLR) provided the Geographical information data, the German Meteorological Service (DWD) provided preprocessed COSMO-DE data and developed INIFOR software utility to make COSMO data readable to PALM.
DOI: 10.5281/zenodo.4559549
title: PALM model system 6.0 source code, revisions r4450 and r4601

description: The dataset contains the PALM model system 6.0 source code in revision r4450 and r4601, used in the research article entitled "Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications ". The PALM model system has been developed and is maintained by the PALM group at the Institute of Meteorology and Climatology (IMUK) of Leibniz Universität Hannover, Germany.
description: MOSAIK and MOSAIK-2 are funded by the German Federal Ministry of Education and Research (BMBF) under grant 01LP1601A and 01LP1911H within the framework of Research for Sustainable Development (FONA; www.fona.de). Benchmark and test runs with PALM have been performed at the supercomputers of the North-German Super- computing Alliance (HLRN), which is gratefully acknowledged. The German Aerospace Center (DLR) provided the Geographical information data, the German Meteorological Service (DWD) provided preprocessed COSMO-DE data and developed INIFOR software utility to make COSMO data readable to PALM.
DOI: 10.5281/zenodo.4559367
title: SIMBA snow/ice mass balance buoy data and weather station data

description: The data sets here are for a manuscript entitled as "<strong>Inter-annual variation of lake ice composition in the Arctic region: Results from observed high-resolution thermistor string"</strong> The high spatial resolution (2cm) vertical air-snow-ice-water temperature time series have been measured in an Arctic lake during winter seasons 2009-2020. Snow depth, ice thickness as well as the lake ice composition are retrieved from temperature time series. High quality meteorological parameters are available from Sodankylä weather station in the vicinity (12 km) from the lake. The readers may considered to create a few <strong>sub-directories</strong> to save the packed files: <strong>SIMBA_rawdata</strong>\ You can save SIMBA_rawdata.zip here and if you unzip, you will find a number of SIMBA original data files, see readme for details. <strong>SIMBA_rawdata1</strong>\ You can save SIMBA_rawdata1.zip here and if you unzip, you will find a number of SIMBA combined data files, see readme for details. <strong>SIMBA_RESULT</strong>\You can save SIMBA_RESULT.zip here and if you unzip, you will find a number of SIMBA processed data files, see readme for details. <strong>Weather_station_data</strong>\You can save Weather_station_data.zip here and if you unzip, you will find a number of weather station data files, see readme for details. <strong>SIMBA_D&R_all_Years.docx</strong>: This file describes SIMBA deployment for each winter season. There are a few excel file here. Those are lake snow and ice manual observation for 09/10, 10/11, 11/12 and 12/13
DOI: 10.5281/zenodo.4153388
title: Input data for performing chemistry coupled PALM model system 6.0 simulations with different chemical mechanisms

description: The data presented here comprised of input files that have been used to run chemistry coupled PALM model system 6.0 simulations for the article entitled "Development of an atmospheric chemistry model coupled to the PALM model system 6.0: Implementation and first applications". In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence resolving PALM model system 6.0. List of the input data required for performing chemistry model simulations with different chemical mechanisms is given below. A text file comprised of measured concentrations of NO, NO<sub>2</sub> and O<sub>3</sub> is also added. Fortran parameter (PARIN) files for four mechanisms and one meteorology-only simulation. Static file Dynamic file Two files (shortwave and longwave input data) for rrtmg radiation model Observation from two air quality stations in Berlin, Germany . PALM model source code revision 4450 (palm_trunk_rev-4450.tar.gz) PALM model source code revision 4601 (palm_trunk_rev-4601.tar.gz) The PALM model system 6.0 revision 4451 and 4601 (for chemistry flux profiles only) have been used for these simulations.
description: MOSAIK and MOSAIK-2 are funded by the German Federal Ministry of Education and Research (BMBF) under grant 01LP1601 and 01LP1911H within the framework of Research for Sustainable Development (FONA; www.fona.de). Benchmark and test runs with PALM have been performed at the supercomputers of the North-German Super- computing Alliance (HLRN), which is gratefully acknowledged. Wieke Heldens and Julian Zeidler of the German Aerospace Center (DLR) provided the Geographical information data, Kristina Winderlich and Eckhard Kadasch of German Meteorological Service (DWD) provided preprocessed COSMO-DE data and developed INIFOR software utility to make COSMO data readable to PALM.
DOI: 10.5281/zenodo.4020560
title: Input data for performing chemistry coupled PALM model system 6.0 simulations with different chemical mechanisms

description: The data presented here comprised of input files that have been used to run chemistry coupled PALM model system 6.0 simulations for the article entitled "Development of an atmospheric chemistry model coupled to the PALM model system 6.0: Implementation and first applications". In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence resolving PALM model system 6.0. List of the input data required for performing chemistry model simulations with different chemical mechanisms is given below. A text file comprised of measured concentrations of NO, NO<sub>2</sub> and O<sub>3</sub> is also added. Fortran parameter (PARIN) files for four mechanisms and one meteorology-only simulation. Static file Dynamic file Two files (shortwave and longwave input data) for rrtmg radiation model Observation from two air quality stations in Berlin, Germany . PALM model source code revision 4450 (palm_trunk_rev-4450.tar.gz) PALM model source code revision 4601 (palm_trunk_rev-4601.tar.gz) The PALM model system 6.0 revision 4451 and 4601 (for chemistry flux profiles only) have been used for these simulations.
description: MOSAIK and MOSAIK-2 are funded by the German Federal Ministry of Education and Research (BMBF) under grant 01LP1601 and 01LP1911H within the framework of Research for Sustainable Development (FONA; www.fona.de). Benchmark and test runs with PALM have been performed at the supercomputers of the North-German Super- computing Alliance (HLRN), which is gratefully acknowledged. Wieke Heldens and Julian Zeidler of the German Aerospace Center (DLR) provided the Geographical information data, Kristina Winderlich and Eckhard Kadasch of German Meteorological Service (DWD) provided preprocessed COSMO-DE data and developed INIFOR software utility to make COSMO data readable to PALM.
DOI: 10.5281/zenodo.4559527
title: Formalizing Formalism: An Empirical Study of the Rhetoric of Formalism in Israeli Supreme Court Opinions over Time

description: Michal Alberstein, Limor Gabay-Egozi, Bryna Bogosh, Coding variables<br> related to legal formalism of 2,086 Israeli Supreme Court opinions,<br> including 664 criminal, 849 civil and 573 public law (HCJ) cases.<br> Supported by Israel Science Foundation (ISF) Individual Grant 1397/12<br> “Formalizing Formalism: An Empirical Study of the Rhetoric of<br> Formalism in Israeli Supreme Court Opinions over Time”.<br>
DOI: 10.5281/zenodo.4559526
title: Formalizing Formalism: An Empirical Study of the Rhetoric of Formalism in Israeli Supreme Court Opinions over Time

description: Michal Alberstein, Limor Gabay-Egozi, Bryna Bogosh, Coding variables<br> related to legal formalism of 2,086 Israeli Supreme Court opinions,<br> including 664 criminal, 849 civil and 573 public law (HCJ) cases.<br> Supported by Israel Science Foundation (ISF) Individual Grant 1397/12<br> “Formalizing Formalism: An Empirical Study of the Rhetoric of<br> Formalism in Israeli Supreme Court Opinions over Time”.<br>
DOI: 10.15468/a39nys
title: Ascidians collected during the 2013 Singapore Strait International Marine Biodiversity Workshop

description: This dataset contains the digitized treatments in Plazi based on the original journal article Lambert, Gretchen, Lee, Serina Siew-Chen, Teo, Serena Lay-Ming (2021): Ascidians collected during the 2013 Singapore Strait International Marine Biodiversity Workshop. Zootaxa 4933 (1): 1-38, DOI: https://doi.org/10.11646/zootaxa.4933.1.1
DOI: 10.6084/m9.figshare.14102051
title: Supplementary Material for: The Association of Cognitive and Visual Function in a Nationally Representative Study of Older Adults in India

description: <b><i>Introduction:</i></b> Due to population aging, India is poised to experience a large increase in the burden of both dementia and vision impairment (VI). Prior studies from other settings suggest that VI may be a modifiable risk factor for cognitive decline and dementia. However, to date, no studies have examined the association of impaired visual acuity and cognition in India. <b><i>Methods:</i></b> A total of 3,784 participants in wave 1 of the population-based Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India underwent visual acuity testing and a cognitive test battery. Multivariable linear regression was used to model the cross-sectional associations of mild (&lt;6/12–6/16), moderate (&lt;6/18–6/60), and severe visual acuity impairment/blindness (&lt;6/60) with cognitive performance scores corresponding to total cognition, orientation, memory, language/fluency, executive function, and informant-reported cognitive status. Models were adjusted for demographic, socioeconomic, and health characteristics. <b><i>Results:</i></b> The weighted percentage of participants with any VI was 52.6%. VI was independently associated with lower cognitive scores across all domains, even after adjustment for known dementia risk factors. In fully adjusted models of total cognition (mean score: 130.7), mild, moderate, and severe VI/blindness were associated with a significant change of −3.5 (95% CI: −6.3, −0.6), −8.2 (95% CI −10.5, −5.6), and −16.8 (95% CI −22.3, −11.3) units, respectively. A dose-response association between level of VI and cognitive function was observed for all cognitive outcomes except for language/fluency domain scores. Associations were robust when cognitive tests dependent on visual function were excluded. Across each fully adjusted model of total, domain-specific, and informant-reported cognitive performance, moderate VI was equivalent to 5–9 years of cognitive aging. <b><i>Discussion/Conclusion:</i></b> This study illustrates that VI is cross-sectionally associated with lower cognitive performance, largely in a dose-response pattern, across various cognitive domains in the Indian population. These findings are important for informing future longitudinal and interventional studies.
DOI: 10.6084/m9.figshare.14102027
title: Supplementary Material for: Positive Feedback Loop of Long Noncoding RNA OASL-IT1 and Innate Immune Response Restricts the Replication of Zika Virus in Epithelial A549 Cells

description: Expression of host noncoding RNAs and coding mRNAs is significantly altered by viral infection. In the current study, we screened the transcriptional profile of human lung epithelial A549 cells infected with Zika virus (ZIKV) by microarray assay. Seventy-nine long noncoding RNAs (lncRNAs) and 140 mRNAs were differentially expressed (DE). The bioinformatics analysis revealed that the mRNAs adjacent to the DE lncRNAs were closely related to the host responses to viral infection. We selected 7 lncRNAs from the top 50 hits for validation. The quantitative real-time PCR data confirmed that expression of selected lncRNAs was induced by ZIKV infection. Moreover, the expression of 7 lncRNAs was induced by infection of dengue virus, Japanese encephalitis virus, or vesicular stomatitis virus, or by treatment of poly(I:C) and IFN-β. Furthermore, loss of innate immune adaptor IPS-1 or receptor IFNAR1 resulted in lower induction levels of several lncRNAs by ZIKV. Overexpression of 3 lncRNAs (RPL27-OT1, OASL-IT1, and REC8-OT3) reduced the virus yields of ZIKV. Knockout of OASL-IT1 significantly enhanced ZIKV replication. In OASL-IT1 knockout cells, the levels of interferons (IFNs) and the activation of 3 innate immune signaling pathways triggered by ZIKV were dramatically reduced. Collectively, our work found a positive feedback loop in the IFN system, in which IFNs and OASL-IT1 regulate each other, thereby promoting establishment of antiviral defense.
DOI: 10.6084/m9.figshare.14102027.v1
title: Supplementary Material for: Positive Feedback Loop of Long Noncoding RNA OASL-IT1 and Innate Immune Response Restricts the Replication of Zika Virus in Epithelial A549 Cells

description: Expression of host noncoding RNAs and coding mRNAs is significantly altered by viral infection. In the current study, we screened the transcriptional profile of human lung epithelial A549 cells infected with Zika virus (ZIKV) by microarray assay. Seventy-nine long noncoding RNAs (lncRNAs) and 140 mRNAs were differentially expressed (DE). The bioinformatics analysis revealed that the mRNAs adjacent to the DE lncRNAs were closely related to the host responses to viral infection. We selected 7 lncRNAs from the top 50 hits for validation. The quantitative real-time PCR data confirmed that expression of selected lncRNAs was induced by ZIKV infection. Moreover, the expression of 7 lncRNAs was induced by infection of dengue virus, Japanese encephalitis virus, or vesicular stomatitis virus, or by treatment of poly(I:C) and IFN-β. Furthermore, loss of innate immune adaptor IPS-1 or receptor IFNAR1 resulted in lower induction levels of several lncRNAs by ZIKV. Overexpression of 3 lncRNAs (RPL27-OT1, OASL-IT1, and REC8-OT3) reduced the virus yields of ZIKV. Knockout of OASL-IT1 significantly enhanced ZIKV replication. In OASL-IT1 knockout cells, the levels of interferons (IFNs) and the activation of 3 innate immune signaling pathways triggered by ZIKV were dramatically reduced. Collectively, our work found a positive feedback loop in the IFN system, in which IFNs and OASL-IT1 regulate each other, thereby promoting establishment of antiviral defense.
DOI: 10.5281/zenodo.4559626
title: Geospatial datasets of deforestation scenarios in Colombia (2018-2050)

description: The Geospatial datasets correspond to deforestation scenarios in Colombia: Business As Usual (BAU) and Governance (GOV). This dataset was obtained from an environmental modeling exercise executed in Dinamica EGO. Primary data of deforestation were derived from the Global Forest Change 2000-2018 v1.6 dataset (https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.6.html).
DOI: 10.5281/zenodo.4559625
title: Geospatial datasets of deforestation scenarios in Colombia (2018-2050)

description: The Geospatial datasets correspond to deforestation scenarios in Colombia: Business As Usual (BAU) and Governance (GOV). This dataset was obtained from an environmental modeling exercise executed in Dinamica EGO. Primary data of deforestation were derived from the Global Forest Change 2000-2018 v1.6 dataset (https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.6.html).
DOI: 10.5517/ccdc.csd.cc232hsh
title: CCDC 1938826: Experimental Crystal Structure Determination

description: Related Article: Theanchai Wiwasuku, Jaursup Boonmak, Rodjana Burakham, Sarinya Hadsadee, Siriporn Jungsuttiwong, Sareeya Bureekaew, Vinich Promarak, Sujittra Youngme|2021|Inorg.Chem.Front.|8|977|doi:10.1039/D0QI00947D
DOI: 10.5517/ccdc.csd.cc232htj
title: CCDC 1938827: Experimental Crystal Structure Determination

description: Related Article: Theanchai Wiwasuku, Jaursup Boonmak, Rodjana Burakham, Sarinya Hadsadee, Siriporn Jungsuttiwong, Sareeya Bureekaew, Vinich Promarak, Sujittra Youngme|2021|Inorg.Chem.Front.|8|977|doi:10.1039/D0QI00947D
DOI: 10.5517/ccdc.csd.cc24h4tm
title: CCDC 1980770: Experimental Crystal Structure Determination

description: Related Article: Carlo Andrea Mattei, Vincent Montigaud, Frédéric Gendron, Sandrine Denis-Quanquin, Vincent Dorcet, Nicolas Giraud, François Riobé, Gilles Argouarch, Olivier Maury, Boris Le Guennic, Olivier Cador, Claudia Lalli, Fabrice Pointillart|2021|Inorg.Chem.Front.|8|947|doi:10.1039/D0QI01192D
DOI: 10.5517/ccdc.csd.cc24lgy5
title: CCDC 1983967: Experimental Crystal Structure Determination

description: Related Article: Abdullah M. Abudayyeh, Olivier Schott, Humphrey L. C. Feltham, Garry S. Hanan, Sally Brooker|2021|Inorg.Chem.Front.|8|1015|doi:10.1039/D0QI01247E
DOI: 10.5517/ccdc.csd.cc24lgz6
title: CCDC 1983968: Experimental Crystal Structure Determination

description: Related Article: Abdullah M. Abudayyeh, Olivier Schott, Humphrey L. C. Feltham, Garry S. Hanan, Sally Brooker|2021|Inorg.Chem.Front.|8|1015|doi:10.1039/D0QI01247E
DOI: 10.5517/ccdc.csd.cc24yd9t
title: CCDC 1994456: Experimental Crystal Structure Determination

description: Related Article: Carlo Andrea Mattei, Vincent Montigaud, Vincent Dorcet, François Riobé, Gilles Argouarch, Olivier Maury, Boris Le Guennic, Olivier Cador, Claudia Lalli, Fabrice Pointillart|2021|Inorg.Chem.Front.|8|963|doi:10.1039/D0QI01193B
DOI: 10.5517/ccdc.csd.cc24ydbv
title: CCDC 1994457: Experimental Crystal Structure Determination

description: Related Article: Carlo Andrea Mattei, Vincent Montigaud, Vincent Dorcet, François Riobé, Gilles Argouarch, Olivier Maury, Boris Le Guennic, Olivier Cador, Claudia Lalli, Fabrice Pointillart|2021|Inorg.Chem.Front.|8|963|doi:10.1039/D0QI01193B
DOI: 10.5517/ccdc.csd.cc24ydcw
title: CCDC 1994458: Experimental Crystal Structure Determination

description: Related Article: Carlo Andrea Mattei, Vincent Montigaud, Vincent Dorcet, François Riobé, Gilles Argouarch, Olivier Maury, Boris Le Guennic, Olivier Cador, Claudia Lalli, Fabrice Pointillart|2021|Inorg.Chem.Front.|8|963|doi:10.1039/D0QI01193B
DOI: 10.5517/ccdc.csd.cc24yddx
title: CCDC 1994459: Experimental Crystal Structure Determination

description: Related Article: Carlo Andrea Mattei, Vincent Montigaud, Vincent Dorcet, François Riobé, Gilles Argouarch, Olivier Maury, Boris Le Guennic, Olivier Cador, Claudia Lalli, Fabrice Pointillart|2021|Inorg.Chem.Front.|8|963|doi:10.1039/D0QI01193B
DOI: 10.5517/ccdc.csd.cc24zlj8
title: CCDC 1995610: Experimental Crystal Structure Determination

description: Related Article: Szymon Kapuściński, Mustapha B. Abdulmojeed, Tegan E. Schafer, Anna Pietrzak, Oleksandr Hietsoi, Andrienne C. Friedli, Piotr Kaszyński|2021|Inorg.Chem.Front.|8|1066|doi:10.1039/D0QI01353F
DOI: 10.5517/ccdc.csd.cc24zlk9
title: CCDC 1995611: Experimental Crystal Structure Determination

description: Related Article: Szymon Kapuściński, Mustapha B. Abdulmojeed, Tegan E. Schafer, Anna Pietrzak, Oleksandr Hietsoi, Andrienne C. Friedli, Piotr Kaszyński|2021|Inorg.Chem.Front.|8|1066|doi:10.1039/D0QI01353F
DOI: 10.5517/ccdc.csd.cc24zllb
title: CCDC 1995612: Experimental Crystal Structure Determination

description: Related Article: Szymon Kapuściński, Mustapha B. Abdulmojeed, Tegan E. Schafer, Anna Pietrzak, Oleksandr Hietsoi, Andrienne C. Friedli, Piotr Kaszyński|2021|Inorg.Chem.Front.|8|1066|doi:10.1039/D0QI01353F
DOI: 10.5517/ccdc.csd.cc24zlmc
title: CCDC 1995613: Experimental Crystal Structure Determination

description: Related Article: Szymon Kapuściński, Mustapha B. Abdulmojeed, Tegan E. Schafer, Anna Pietrzak, Oleksandr Hietsoi, Andrienne C. Friedli, Piotr Kaszyński|2021|Inorg.Chem.Front.|8|1066|doi:10.1039/D0QI01353F
DOI: 10.5517/ccdc.csd.cc24zlnd
title: CCDC 1995614: Experimental Crystal Structure Determination

description: Related Article: Szymon Kapuściński, Mustapha B. Abdulmojeed, Tegan E. Schafer, Anna Pietrzak, Oleksandr Hietsoi, Andrienne C. Friedli, Piotr Kaszyński|2021|Inorg.Chem.Front.|8|1066|doi:10.1039/D0QI01353F
DOI: 10.5517/ccdc.csd.cc24zlpf
title: CCDC 1995615: Experimental Crystal Structure Determination

description: Related Article: Szymon Kapuściński, Mustapha B. Abdulmojeed, Tegan E. Schafer, Anna Pietrzak, Oleksandr Hietsoi, Andrienne C. Friedli, Piotr Kaszyński|2021|Inorg.Chem.Front.|8|1066|doi:10.1039/D0QI01353F
DOI: 10.5517/ccdc.csd.cc24zlqg
title: CCDC 1995616: Experimental Crystal Structure Determination

description: Related Article: Szymon Kapuściński, Mustapha B. Abdulmojeed, Tegan E. Schafer, Anna Pietrzak, Oleksandr Hietsoi, Andrienne C. Friedli, Piotr Kaszyński|2021|Inorg.Chem.Front.|8|1066|doi:10.1039/D0QI01353F
DOI: 10.5517/ccdc.csd.cc24zlrh
title: CCDC 1995617: Experimental Crystal Structure Determination

description: Related Article: Szymon Kapuściński, Mustapha B. Abdulmojeed, Tegan E. Schafer, Anna Pietrzak, Oleksandr Hietsoi, Andrienne C. Friedli, Piotr Kaszyński|2021|Inorg.Chem.Front.|8|1066|doi:10.1039/D0QI01353F
DOI: 10.5517/ccdc.csd.cc25n4qq
title: CCDC 2015363: Experimental Crystal Structure Determination

description: Related Article: Qiaomu Yang, Yusen Qiao, Alex McSkimming, Liane M. Moreau, Thibault Cheisson, Corwin H. Booth, Ekaterina Lapsheva, Patrick J. Carroll, Eric J. Schelter|2021|Inorg.Chem.Front.|8|934|doi:10.1039/D0QI00969E