cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5834633
title: Replication Package for ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems

description: <strong>Replication Package for ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems</strong> This is the replication package for the paper, ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems, which has been accepted at the International Conference on Software Architecture (ICSA), 2021. A preprint of the paper is included in this replication package (paper.pdf). This artifact is archived on Zenodo with the following DOI: https://doi.org/10.5281/zenodo.5834633 The study associated with this artifact was carried out by the following investigators: Christopher S. Timperley (Carnegie Mellon University) Tobias Dürschmid (Carnegie Mellon University) Bradley Schmerl (Carnegie Mellon University) David Garlan (Carnegie Mellon University) Claire Le Goues (Carnegie Mellon University) If you have any questions regarding the research or the replication package, you should contact Christopher, Tobias, or Bradley. <strong>Abstract</strong> Robot systems are growing in importance and complexity. Ecosystems for robot software, such as the Robot Operating System (ROS), provide libraries of reusable software components that can be configured and composed into larger systems. To support compositionality, ROS uses late binding and architecture configuration via “launch files” that describe how to initialize the components in a system. However, late binding often leads to systems failing silently due to misconfiguration, for example by misrouting or dropping messages entirely. In this paper we present ROSDiscover, which statically recovers the run-time architecture of ROS systems to find such architecture misconfiguration bugs. First, ROSDiscover constructs component level architectural models (ports, parameters) from source code. Second, architecture configuration files are analyzed to compose the system from these component models and derive the connections in the system. Finally, the reconstructed architecture is checked against architectural rules described in first-order logic to identify potential misconfigurations. We present an evaluation of ROSDiscover on real world, off-the-shelf robotic systems, measuring the accuracy, effectiveness, and practicality of our approach. To that end, we collected the first data set of architecture configuration bugs in ROS from popular open-source systems and measure how effective our approach is for detecting configuration bugs in that set.
DOI: 10.5281/zenodo.5834632
title: Replication Package for ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems

description: <strong>Replication Package for ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems</strong> This is the replication package for the paper, ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems, which has been accepted at the International Conference on Software Architecture (ICSA), 2021. A preprint of the paper is included in this replication package (paper.pdf). This artifact is archived on Zenodo with the following DOI: https://doi.org/10.5281/zenodo.5834633 The study associated with this artifact was carried out by the following investigators: Christopher S. Timperley (Carnegie Mellon University) Tobias Dürschmid (Carnegie Mellon University) Bradley Schmerl (Carnegie Mellon University) David Garlan (Carnegie Mellon University) Claire Le Goues (Carnegie Mellon University) If you have any questions regarding the research or the replication package, you should contact Christopher, Tobias, or Bradley. <strong>Abstract</strong> Robot systems are growing in importance and complexity. Ecosystems for robot software, such as the Robot Operating System (ROS), provide libraries of reusable software components that can be configured and composed into larger systems. To support compositionality, ROS uses late binding and architecture configuration via “launch files” that describe how to initialize the components in a system. However, late binding often leads to systems failing silently due to misconfiguration, for example by misrouting or dropping messages entirely. In this paper we present ROSDiscover, which statically recovers the run-time architecture of ROS systems to find such architecture misconfiguration bugs. First, ROSDiscover constructs component level architectural models (ports, parameters) from source code. Second, architecture configuration files are analyzed to compose the system from these component models and derive the connections in the system. Finally, the reconstructed architecture is checked against architectural rules described in first-order logic to identify potential misconfigurations. We present an evaluation of ROSDiscover on real world, off-the-shelf robotic systems, measuring the accuracy, effectiveness, and practicality of our approach. To that end, we collected the first data set of architecture configuration bugs in ROS from popular open-source systems and measure how effective our approach is for detecting configuration bugs in that set.
DOI: 10.5281/zenodo.5935181
title: Constructing a histocytometry pipeline suitable for high dimensional reduction analysis of using graphical user interface software

description: Image, worksheet and reference files for a Current Protocols journal article
DOI: 10.3886/e101740v2-107963
title: U.S. Energy Information Administration: Monthly Energy Review, Renewables, 1950-2017

description: This data set comes from a monthly publication of recent and historical energy statistics produced by the US Energy Information Administration, part of the Department of Energy. Renewable energy production includes hydroelectric, geothermal, solar, wind, and biomass, and consumption includes residential, commercial, industrial, transportation, and electric power consumption.
description: Energy statistics produced by the US Energy Information Administration.
DOI: 10.3886/e113381v1-107964
title: Replication data for: The Criminal Justice Response to Policy Interventions: Evidence from Immigration Reform

description: Changes in the treatment of individuals by the criminal justice system following a policy intervention may bias estimates of the effects of the intervention on underlying criminal activity. We explore the importance of such changes in the context of the Immigration Reform and Control Act of 1986 (IRCA). Using administrative data from San Antonio, Texas, we examine variation across neighborhoods and ethnicities in police arrests and in the rate at which those arrests are prosecuted. We find that changes in police behavior around IRCA confound estimates of the effects of the policy and its restrictions on employment on criminal activity.
description: All felony and misdemeanor arrests as well as prosecutorial acceptance rates by census block group and month in Bexar County, Texas, USA.
DOI: 10.25505/fiz.icsd.cc1zzbr1
title: CSD 1846414: Experimental Crystal Structure Determination

description: Related Article: Katherine E. Woo, Juli-Anna Dolyniuk, Kirill Kovnir|2019|Inorg.Chem.|58|4997|doi:10.1021/acs.inorgchem.9b00017
DOI: 10.5517/ccdc.csd.cc21mmy8
title: CCDC 1895710: Experimental Crystal Structure Determination

description: Related Article: N. Phiromphu, K. Chainok, A. Songsasen, T. Duangthongyou|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|354|doi:10.1107/S205698901900207X
DOI: 10.25505/fiz.icsd.cc21mqcs
title: CSD 1895785: Experimental Crystal Structure Determination

description: Related Article: K. Schwendtner, U. Kolitsch|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|346|doi:10.1107/S2056989019002081
DOI: 10.25505/fiz.icsd.cc21nj4d
title: CSD 1896553: Experimental Crystal Structure Determination

description: Related Article: Jürgen Nuss, Reinhard K. Kremer, Gohil S. Thakur, Martin Jansen|2019|Z.Anorg.Allg.Chem.|645|882|doi:10.1002/zaac.201900026
DOI: 10.25505/fiz.icsd.cc21d09s
title: CSD 1888374: Experimental Crystal Structure Determination

description: Related Article: Corey E. Frank, Emma E. McCabe, Fabio Orlandi, Pascal Manuel, Xiaoyan Tan, Zheng Deng, Mark Croft, Vanessa Cascos, Thomas Emge, Hai L. Feng, Saul Lapidus, Changqing Jin, MeiXia Wu, Man Rong Li, Steven Ehrlich, Syed Khalid, Nicholas Quackenbush, Shuang Yu, David Walker, Martha Greenblatt|2019|Chem.Commun.|55|3331|doi:10.1039/C9CC00038K
DOI: 10.5517/ccdc.csd.cc21pcjn
title: CCDC 1897371: Experimental Crystal Structure Determination

description: Related Article: B. Hni, N.K. Sebbar, T. Hökelek, Y. Ouzidan, A. Moussaif, J.T. Mague, E.M. Essassi|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|372|doi:10.1107/S2056989019002354
DOI: 10.5517/ccdc.csd.cc21qbhm
title: CSD 1898300: Experimental Crystal Structure Determination

description: Related Article: F.-E. N'Faoui, J. Aride, A. Boukhari, M.'H. Taibi, M. Saadi, L. El Ammari|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|388|doi:10.1107/S2056989019002597
DOI: 10.25505/fiz.icsd.cc21qj8l
title: CSD 1898479: Experimental Crystal Structure Determination

description: Related Article: James A. Sommers, Danielle C. Hutchison, Nicolas P. Martin, Karoly Kozma, Douglas A. Keszler, May Nyman|2019|J.Am.Chem.Soc.|141|16894|doi:10.1021/jacs.9b08627
DOI: 10.25505/fiz.icsd.cc21qpm3
title: CSD 1898645: Experimental Crystal Structure Determination

description: Related Article: Patrick Schmidt,  Amira Siai,  Philipp Schneiderhan,  Markus Ströbele,  H.-Jürgen Meyer|2020|Eur.J.Inorg.Chem.|2020|716|doi:10.1002/ejic.201901337
DOI: 10.5517/ccdc.csd.cc21qs7t
title: CCDC 1898726: Experimental Crystal Structure Determination

description: Related Article: B. Hni, N.K. Sebbar, T. Hökelek, Y. Ouzidan, A. Moussaif, J.T. Mague, E.M. Essassi|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|372|doi:10.1107/S2056989019002354
description: Related Article: J.-J. Liu, L.-Z. Li, C.-P. Chen, J.-Z. Wei, F.-X. Cheng|2019|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|75|372|doi:10.1107/S2053229619002663
DOI: 10.5517/ccdc.csd.cc21qth3
title: CCDC 1898765: Experimental Crystal Structure Determination

description: Related Article: Dae Ho Hong, Brian J. Knight, Vincent J. Catalano, Leslie J. Murray|2019|Dalton Trans.|48|9570|doi:10.1039/C9DT00799G
description: Related Article: Sylvain Sudan, Andrzej Gladysiak, Bardiya Valizadeh, Jung-Hoon Lee, Kyriakos C. Stylianou|2020|Inorg.Chem.|59|9029|doi:10.1021/acs.inorgchem.0c00883
DOI: 10.5517/ccdc.csd.cc21qwd2
title: CSD 1898824: Experimental Crystal Structure Determination

description: Related Article: Ruling Tang, Chunli Hu, Jianghe Feng, Zhi Fang, Yan Chen, Fang Kong, Jianggao Mao|2020|Dalton Trans.|49|3743|doi:10.1039/C9DT03839F
DOI: 10.25505/fiz.icsd.cc21r2qm
title: CSD 1899020: Experimental Crystal Structure Determination

description: Related Article: Vladislav V. Klepov, Mark D. Smith, Hans-Conrad zur Loye|2019|Inorg.Chem.|58|8275|doi:10.1021/acs.inorgchem.9b01307
DOI: 10.25505/fiz.icsd.cc21r2rn
title: CSD 1899021: Experimental Crystal Structure Determination

description: Related Article: Vladislav V. Klepov, Mark D. Smith, Hans-Conrad zur Loye|2019|Inorg.Chem.|58|8275|doi:10.1021/acs.inorgchem.9b01307
DOI: 10.25505/fiz.icsd.cc21r7nq
title: CSD 1899173: Experimental Crystal Structure Determination

description: Related Article: I.A. Trussov, L.L. Driscoll, L.L. Male, M.L. Sanjuan, A. Orera, P.R. Slater|2019|J.Solid State Chem.|276|37|doi:10.1016/j.jssc.2019.04.036
DOI: 10.25505/fiz.icsd.cc21rkjx
title: CSD 1899479: Experimental Crystal Structure Determination

description: Related Article: Jian Yan, Ruichun Xiao, Xuan Luo, Hongyan Lv, Ranran Zhang, Yan Sun, Peng Tong, Wenjian Lu, Wenhai Song, Xuebin Zhu, Yuping Sun|2019|Inorg.Chem.|58|9036|doi:10.1021/acs.inorgchem.9b00432
DOI: 10.6084/m9.figshare.19100603
title: Additional file 1.sav

description: This is a dataset of a cross-sectional study that assessed psychosocial hazards among traffic police officers in Kathmandu Metropolitan City, Nepal.
DOI: 10.26186/146180
title: Southern Gulf of Carpentaria bathymetry survey (GA0276)

description: This resource includes bathymetry data acquired during the Southern Gulf of Carpentaria bathymetry survey using Simrad EM300 and Reson Seabat 8101 multibeam sonar systems. Southern Gulf of Carpentaria bathymetry survey (GA0276) was led by Dr. Peter Harris (Geoscience Australia) aboard the Marine National Facility's research vessel Southern Surveyor, from the 23rd of March to the 13th of April 2005. The primary objective of the expedition was to map submerged reefs to ascertain their geomorphic nature and document the benthic communities and fauna. This dataset contains four 4m to 7m resolution 32-bit floating point geotiff files of the bathymetry in five study areas and transits, derived from the processed EM300 and Reson 8101 bathymetry data, using CARIS HIPS and SIPS software. A detailed report on the survey is provided in: Harris, P et al. 2006. Submerged coral reefs and benthic habitats of the southern Gulf of Carpentaria: Post-Survey Report - GA Survey 276, RV Southern Surveyor (https://pid.geoscience.gov.au/dataset/ga/65073). This dataset is not to be used for navigational purposes. This dataset is published with the permission of the CEO, Geoscience Australia.
DOI: 10.26186/146178
title: Vernon Islands bathymetry survey (B-1/GA4871)

description: This resource includes bathymetry data acquired during the Vernon Islands bathymetry survey collected by University of Queensland during the period 21 – 26 May 2019 on the charter vessel Lauri-j using Bathyswath interferometric sonar system. The survey was undertaken as a project of the Australian Tidal Energy (AUSTEn; http://austen.org.au/) co-funded by the Australian Renewable Energy Agency (ARENA) for the Advancing Renewables Program. The purpose of the project was to map the country’s tidal energy resource in unprecedented detail and assess its economic feasibility and ability to contribute to Australia’s energy needs. It will aid the emerging tidal energy industry to develop commercial-scale tidal energy projects. This dataset contains a 4m resolution 32-bit floating point geotiff file of the bathymetry in study area and transits, derived from the processed Bathyswath interferometric data, using Fledermaus. A final report of the project is provided in: Penesis, I et al. 2020. Tidal Energy in Australia: Assessing Resource and Feasibility in Australia’s Future Energy Mix (https://tethys-engineering.pnnl.gov/sites/default/files/publications/tidal-energy-in-australia-2020.pdf). This dataset is not to be used for navigational purposes. This dataset is published with the permission of the CEO, Geoscience Australia.
DOI: 10.26186/146179
title: Banks Strait bathymetry survey (A-1/GA4872)

description: This resource includes bathymetry data acquired during the Banks Strait bathymetry survey collected by University of Queensland during the period 16 – 28 March 2018 on the TV Bluefin using Bathyswath interferometric sonar system. The survey was undertaken as a project of the Australian Tidal Energy (AUSTEn; http://austen.org.au/) co-funded by the Australian Renewable Energy Agency (ARENA) for the Advancing Renewables Program, led by Prof. Irene Penesis. The purpose of the project was to map the country’s tidal energy resource in unprecedented detail and assess its economic feasibility and ability to contribute to Australia’s energy needs. It will aid the emerging tidal energy industry to develop commercial-scale tidal energy projects. This dataset contains a 4m resolution 32-bit floating point geotiff file of the bathymetry in study area and transits, derived from the processed Bathyswath interferometric data, using Fledermaus. A final report of the project is provided in: Penesis, I et al. 2020. Tidal Energy in Australia: Assessing Resource and Feasibility in Australia’s Future Energy Mix (https://tethys-engineering.pnnl.gov/sites/default/files/publications/tidal-energy-in-australia-2020.pdf). This dataset is not to be used for navigational purposes. This dataset is published with the permission of the CEO, Geoscience Australia.
DOI: 10.6084/m9.figshare.13312799.v4
title: Colby et al. (2021) - Scientific Reports Data and Code

description: Data and code used in Colby et al. - Scientific Reports (2021).
DOI: 10.6084/m9.figshare.13312799
title: Colby et al. (2021) - Scientific Reports Data and Code

description: Data and code used in Colby et al. - Scientific Reports (2021).
DOI: 10.6084/m9.figshare.13312799.v3
title: Colby et al. (in review) - Scientific Reports Data and Code

description: Data and code used in Colby et al. - Scientific Reports (in review).
DOI: 10.6084/m9.figshare.19090052
title: A 3D deep learning approach incorporating coordinate information to improve the segmentation of pre- and post-operative abdominal aortic aneurysm

description: Dataset of abdominal aortic aneurysm-Non-contrast CT: train 200 cases, test 20 cases-Contrast enhanced CT: train 200 cases, test 20 cases-Non-contrast of post EVAR CT: train 20 cases, test 20 cases-Contrast enhanced of post EVAR CT 20 cases and test 20 cases.
DOI: 10.5281/zenodo.5935518
title: MetSys Node Attributes

description: Cytoscape node attribute file for visualizing GO pathway maps (sif format) from online tool - metsys.idsl.site
DOI: 10.5281/zenodo.5935517
title: MetSys Node Attributes

description: Cytoscape node attribute file for visualizing GO pathway maps (sif format) from online tool - metsys.idsl.site
DOI: 10.6084/m9.figshare.19100618
title: Experimental result with unsupervised features

description: This excel file contained experimental results with unsupervised features.
DOI: 10.6084/m9.figshare.19100561.v1
title: Table 1

description: lithology, sampling locations, and zircon U–Pb ages
DOI: 10.6084/m9.figshare.19100561
title: Table 1

description: lithology, sampling locations, and zircon U–Pb ages
DOI: 10.6084/m9.figshare.19100564
title: Table 2

description: Elemental and Sr–Nd–Pb isotopic results
DOI: 10.6084/m9.figshare.19100564.v1
title: Table 2

description: Elemental and Sr–Nd–Pb isotopic results
DOI: 10.6084/m9.figshare.19100567.v1
title: Supporting information

description: Supporting information for Cenozoic granitic magmatism
DOI: 10.6084/m9.figshare.19100567
title: Supporting information

description: Supporting information for Cenozoic granitic magmatism
DOI: 10.6084/m9.figshare.19100630.v1
title: Cenozoic granitic magmatism in the SE Tibetan Plateau: New insights from geochronology, elemental, and Sr–Nd–Pb–Hf isotopic composition

description: <b>geological maps and geochemical figures for Cenozoic granitic magmatism in the SE Tibetan Plateau</b>
DOI: 10.6084/m9.figshare.19100630
title: Cenozoic granitic magmatism in the SE Tibetan Plateau: New insights from geochronology, elemental, and Sr–Nd–Pb–Hf isotopic composition

description: <b>geological maps and geochemical figures for Cenozoic granitic magmatism in the SE Tibetan Plateau</b>
DOI: 10.4121/12764330.v1
title: Chemical profiling of fingerprints - Mass spectrometry data

description: Mass spectrometry datafiles containing LC-MS and GC-MS data of fingerprints collected at Lowlands Science 2016.
DOI: 10.4121/12764330
title: Chemical profiling of fingerprints - Mass spectrometry data

description: Mass spectrometry datafiles containing LC-MS and GC-MS data of fingerprints collected at Lowlands Science 2016.
DOI: 10.6084/m9.figshare.18316529
title: BackgroundMatchingData.xlsx

description: Field survival data and image analysis data from my PhD thesis. Field survival data is derived from in-situ predation experiments on paper moth models that had been placed on different background treatments. Image analysis data includes results from colour, luminance, and pattern analyses derived from the MICA and QCPA toolboxes.
DOI: 10.25505/fiz.icsd.cc21sh0c
title: CSD 1900362: Experimental Crystal Structure Determination

description: Related Article: Eirini Armakola, Inés R. Salcedo, Montse Bazaga-García, Pascual Olivera-Pastor, Gellert Mezei, Aurelio Cabeza, Tiago A. Fernandes, Alexander M. Kirillov, Konstantinos D. Demadis|2019|Inorg.Chem.|58|11522|doi:10.1021/acs.inorgchem.9b01376
DOI: 10.5517/ccdc.csd.cc21slzf
title: CSD 1900485: Experimental Crystal Structure Determination

description: Related Article: Dominique Laniel, Maxim Bykov, Timofey Fedotenko, Alena V. Ponomareva, Igor A. Abrikosov, Konstantin Glazyrin, Volodymyr Svitlyk, Leonid Dubrovinsky, Natalia Dubrovinskaia|2019|Inorg.Chem.|58|9195|doi:10.1021/acs.inorgchem.9b00830
DOI: 10.5517/ccdc.csd.cc21sm0h
title: CSD 1900486: Experimental Crystal Structure Determination

description: Related Article: Dominique Laniel, Maxim Bykov, Timofey Fedotenko, Alena V. Ponomareva, Igor A. Abrikosov, Konstantin Glazyrin, Volodymyr Svitlyk, Leonid Dubrovinsky, Natalia Dubrovinskaia|2019|Inorg.Chem.|58|9195|doi:10.1021/acs.inorgchem.9b00830
DOI: 10.25505/fiz.icsd.cc21t2kj
title: CSD 1900937: Experimental Crystal Structure Determination

description: Related Article: Jean-François Vigier, Karin Popa, Laura Martel, Dario Manara, Oliver Dieste Blanco, Daniel Freis, Rudy J. M. Konings|2019|Inorg.Chem.|58|9118|doi:10.1021/acs.inorgchem.9b00679
DOI: 10.25505/fiz.icsd.cc21t2hg
title: CSD 1900935: Experimental Crystal Structure Determination

description: Related Article: Jean-François Vigier, Karin Popa, Laura Martel, Dario Manara, Oliver Dieste Blanco, Daniel Freis, Rudy J. M. Konings|2019|Inorg.Chem.|58|9118|doi:10.1021/acs.inorgchem.9b00679
DOI: 10.25505/fiz.icsd.cc21t2sr
title: CSD 1900944: Experimental Crystal Structure Determination

description: Related Article: Jean-François Vigier, Karin Popa, Laura Martel, Dario Manara, Oliver Dieste Blanco, Daniel Freis, Rudy J. M. Konings|2019|Inorg.Chem.|58|9118|doi:10.1021/acs.inorgchem.9b00679
DOI: 10.5517/ccdc.csd.cc21tg5j
title: CCDC 1901297: Experimental Crystal Structure Determination

description: Related Article: M. Muthukumar, A. Karthikeyan, M. Poovarasan, V. Ruckmani, D. Rajaram, S. Jegan Jeniferc, I. Abdul Razak|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|443|doi:10.1107/S2056989019003189
DOI: 10.5517/ccdc.csd.cc21tl4m
title: CCDC 1901420: Experimental Crystal Structure Determination

description: Related Article: A.J. Cigler, J.A. Kaduk|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|432|doi:10.1107/S2056989019003190
DOI: 10.5517/ccdc.csd.cc21tl6p
title: CCDC 1901422: Experimental Crystal Structure Determination

description: Related Article: A.J. Cigler, J.A. Kaduk|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|432|doi:10.1107/S2056989019003190
DOI: 10.25505/fiz.icsd.cc21v2ww
title: CSD 1901908: Experimental Crystal Structure Determination

description: Related Article: Biplab Koley, Partha P. Jana|2019|J.Solid State Chem.|274|215|doi:10.1016/j.jssc.2019.03.016
DOI: 10.25505/fiz.icsd.cc21v1nm
title: CSD 1901870: Experimental Crystal Structure Determination

description: Related Article: J. Hyoung, H.W. Lee, S.J. Kim, H.R. Shin, S.-T. Hong|2019|Acta Crystallogr.,Sect.E:Cryst.Commun.|75|447|doi:10.1107/S2056989019003335
DOI: 10.25505/fiz.icsd.cc21vjp4
title: CSD 1902336: Experimental Crystal Structure Determination

description: Related Article: Alexander S. Gzyl, Anton O. Oliynyk, Lawrence A. Adutwum, Arthur Mar
|2019|Inorg.Chem.|58|9280|doi:10.1021/acs.inorgchem.9b00987
DOI: 10.25505/fiz.icsd.cc21w739
title: CSD 1903000: Experimental Crystal Structure Determination

description: Related Article: Mathis Antlauf, Takashi Taniguchi, Jörg Wagler, Marcus R. Schwarz, Edwin Kroke|2019|Cryst.Growth Des.|19|5538|doi:10.1021/acs.cgd.9b00333
DOI: 10.25505/fiz.icsd.cc21w74b
title: CSD 1903001: Experimental Crystal Structure Determination

description: Related Article: Mathis Antlauf, Takashi Taniguchi, Jörg Wagler, Marcus R. Schwarz, Edwin Kroke|2019|Cryst.Growth Des.|19|5538|doi:10.1021/acs.cgd.9b00333
DOI: 10.5517/ccdc.csd.cc21wslb
title: CCDC 1903542: Experimental Crystal Structure Determination

description: Related Article: Avijit Maiti, Jessica Stubbe, Nicolás I. Neuman, Pankaj Kalita, Prakash Duari, Carola Schulzke, Vadapalli Chandrasekhar, Biprajit Sarkar, Anukul Jana|2020|Angew.Chem.,Int.Ed.|59|6729|doi:10.1002/anie.201915802