cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18112/openneuro.ds003670.v1.0.0
title: Dataset of Concurrent EEG, ECG, and Behavior with Multiple Doses of transcranial Electrical Stimulation - BIDS
DOI: 10.5281/zenodo.4976481
title: Evaluation results for When a Computer Cracks a Joke: Automated Generation of Humorous Headlines

description: Evaluation results for the paper: Alnajjar, K., & Hämäläinen, M. (2021) When a Computer Cracks a Joke: Automated Generation of Humorous Headlines. In<em> The Proceedings of the Twelfth International Conference on Computational Creativity, ICCC’21</em>. The table has the aggregated evaluation results for each evaluation question. The left and right columns are the title before and after the replacement word. The replacement column show the humorous word and original column the word that existed in the headline before the replacement. The system column indicates whether the humorous headline was produced by our system or by a human.
DOI: 10.5281/zenodo.4976480
title: Evaluation results for When a Computer Cracks a Joke: Automated Generation of Humorous Headlines

description: Evaluation results for the paper: Alnajjar, K., & Hämäläinen, M. (2021) When a Computer Cracks a Joke: Automated Generation of Humorous Headlines. In<em> The Proceedings of the Twelfth International Conference on Computational Creativity, ICCC’21</em>. The table has the aggregated evaluation results for each evaluation question. The left and right columns are the title before and after the replacement word. The replacement column show the humorous word and original column the word that existed in the headline before the replacement. The system column indicates whether the humorous headline was produced by our system or by a human.
DOI: 10.25345/c5hj93
title: MassIVE MSV000087649 - RasimBarutcu_MingkunWu_et_al_APEX_2021
title: This dataset consists of 26 raw MS files and associated peak lists and result files, acquired on a TripleTOF 6600 mass spectrometer operated in Data Dependent Acquisition mode. Samples were generated by Rasim Barutcu and Mingkun Wu (some clones also generated by Boris Dyakov). Streptavidin affinity purification and mass spectrometric acquisition was performed by Zhen-Yuan Lin. Mass Spectrometry data analysis was performed by Boris Dyakov. The files are associated with a manuscript submitted for publication by Barutcu et al. that identifies functionally distinct proteins and retained intron RNAs associated with nuclear domains (speckles and lamina) using APEX2-mediated proximity labeling. ("Systematic mapping of nuclear domain associated transcripts reveals speckles and lamina as hubs of functionally distinct populations of retained introns") Benjamin Blencowe is the corresponding author of the manuscript (b.blencowe@utoronto.ca). Anne-Claude Gingras should be contacted for questions about this dataset (gingras@lunenfeld.ca).
DOI: 10.5066/p9c7hyrv
title: Satellite-Derived Training Data for Automated Flood Detection in the Continental U.S.

description: Remotely sensed imagery is increasingly used by emergency managers to monitor and map the impact of flood events to support preparedness, response, and critical decision making throughout the flood event lifecycle. To reduce latency in delivery of imagery-derived information, ensure consistent and reliably derived map products, and facilitate processing of an increasing volume of remote sensing data-streams, automated flood mapping workflows are needed. The U.S. Geological Survey is facilitating the development and integration of machine-learning algorithms in collaboration with NASA, National Geospatial Intelligence Agency (NGA), University of Alabama, and University of Illinois to create a workflow for rapidly generating improved flood-map products. A major bottleneck to the training of robust, generalizable machine learning algorithms for pattern recognition is a lack of training data that is representative across the landscape. To overcome this limitation for the training of algorithms capable of detection of surface inundation in diverse contexts, this publication includes the data developed from MAXAR Worldview sensors that is input as training data for machine learning. This data release consists of 100 thematic rasters, in GeoTiff format, with image labels representing five discrete categories: water, not water, maybe water, clouds and background/no data. Specifically, these training data were created by labeling 8-band, multispectral scenes from the MAXAR-Digital Globe, Worldview-2 and 3 satellite-based sensors. Scenes were selected to be spatially and spectrally diverse and geographically representative of different water features within the continental U.S. The labeling procedures used a hybrid approach of unsupervised classification for the initial spectral clustering, followed by expert-level manual interpretation and QA/QC peer review to finalize each labeled image. The 100 raster files that make up the training data are available to download here (doi:10.5066/P9C7HYRV).
DOI: 10.6073/pasta/7ef1c7473716b65cdcae352162ab81be
title: Snow grain data for Niwot Ridge and Green Lakes Valley, 1995 - ongoing.

description: Snow pits were excavated at various locations on Niwot Ridge and within the Green Lakes Valley. Temperature and snow density were measured at various depths throughout the snow cover profiles to characterize the temperature and snow water equivalent (SWE) of the snowpack throughout the year. Snow density was measured at 10-cm intervals using a 1000-ml cutter. Data on snow grain qualities were collected beginning in the 1994-95 snow season.
DOI: 10.6073/pasta/56449623e6a53dda597b85ca16b02f81
title: Snow water equivalent data for Niwot Ridge and Green Lakes Valley, 1993 - ongoing.

description: Snow pits were excavated at various locations on Niwot Ridge and within the Green Lakes Valley. Temperature and snow density were measured at various depths throughout the snow cover profiles to characterize the temperature and snow water equivalent (SWE) of the snowpack throughout the year. Snow density was measured at 10-cm intervals using a 1000-ml cutter. Data on snow grain qualities were collected beginning in the 1994-95 snow season.
DOI: 10.18112/openneuro.ds003670.v1.1.0
title: Dataset of Concurrent EEG, ECG, and Behavior with Multiple Doses of transcranial Electrical Stimulation - BIDS
DOI: 10.5517/ccdc.csd.cc1ltsbj
title: CCDC 1484538: Experimental Crystal Structure Determination

description: Related Article: Nicolas Vogt, Aaron Sandleben, Lukas Kletsch, Sascha Schäfer, Mason T. Chin, David A. Vicic, Gerald Hörner, Axel Klein|2021|Organometallics|40|1776|doi:10.1021/acs.organomet.1c00237
DOI: 10.5517/ccdc.csd.cc27ssvp
title: CCDC 2079413: Experimental Crystal Structure Determination

description: Related Article: Sumi Changmai, Sabera Sultana, Bipul Sarma, Sanjib Gogoi|2021|Chem.Commun.|57|6027|doi:10.1039/D1CC02155A
DOI: 10.5517/ccdc.csd.cc27vcvb
title: CCDC 2080932: Experimental Crystal Structure Determination

description: Related Article: Rafail P. Machattos, Nikos Panagiotou, Anastasios J. Tasiopoulos|2021|Polyhedron|205|115299|doi:10.1016/j.poly.2021.115299
DOI: 10.5517/ccdc.csd.cc27vcwc
title: CCDC 2080933: Experimental Crystal Structure Determination

description: Related Article: Rafail P. Machattos, Nikos Panagiotou, Anastasios J. Tasiopoulos|2021|Polyhedron|205|115299|doi:10.1016/j.poly.2021.115299
DOI: 10.5517/ccdc.csd.cc27vcxd
title: CCDC 2080934: Experimental Crystal Structure Determination

description: Related Article: Rafail P. Machattos, Nikos Panagiotou, Anastasios J. Tasiopoulos|2021|Polyhedron|205|115299|doi:10.1016/j.poly.2021.115299
DOI: 10.15468/xmrdcw
title: Neoxabea mexicana sp. nov. (Gryllidae: Oecanthinae): A new species from Mexico and a key for Neoxabea in North and Central America

description: This dataset contains the digitized treatments in Plazi based on the original journal article Collins, Nancy, Velazco-Macias, Carlos Gerardo (2021): Neoxabea mexicana sp. nov. (Gryllidae: Oecanthinae): A new species from Mexico and a key for Neoxabea in North and Central America. Journal of Orthoptera Research 30 (2): 99-106, DOI: http://dx.doi.org/10.3897/jor.30.62000, URL: http://dx.doi.org/10.3897/jor.30.62000
DOI: 10.15468/pcpgfv
title: Unravelling unexplored diversity of cercosporoid fungi (Mycosphaerellaceae, Mycosphaerellales, Ascomycota) in tropical Africa

description: This dataset contains the digitized treatments in Plazi based on the original journal article Meswaet, Yalemwork, Mangelsdorff, Ralph, Yorou, Nourou S., Piepenbring, Meike (2021): Unravelling unexplored diversity of cercosporoid fungi (Mycosphaerellaceae, Mycosphaerellales, Ascomycota) in tropical Africa. MycoKeys 81: 69-138, DOI: http://dx.doi.org/10.3897/mycokeys.81.67850, URL: http://dx.doi.org/10.3897/mycokeys.81.67850
DOI: 10.15468/n7wsjk
title: Taxonomic revision of Sageretia (Rhamnaceae) from China I: identities of S. lucida, S. thea var. cordiformis and S. yunlongensis, with the description of a new species S. ellipsoidea

description: This dataset contains the digitized treatments in Plazi based on the original journal article Yang, Yi, Peng, Hua, Sun, Hang (2021): Taxonomic revision of Sageretia (Rhamnaceae) from China I: identities of S. lucida, S. thea var. cordiformis and S. yunlongensis, with the description of a new species S. ellipsoidea. PhytoKeys 179: 13-28, DOI: http://dx.doi.org/10.3897/phytokeys.179.64750, URL: http://dx.doi.org/10.3897/phytokeys.179.64750
DOI: 10.15468/rdn3sh
title: Begonia catbensis (sect. Coelocentrum, Begoniaceae), a new species from northern Vietnam

description: This dataset contains the digitized treatments in Plazi based on the original journal article Dong, Li-Na, Nguyen, Khang Sinh, Shui, Yu-Min, Nguyen, Hieu Quang, Xu, Wei-Bin, Nguyen, Xuan Khu (2021): Begonia catbensis (sect. Coelocentrum, Begoniaceae), a new species from northern Vietnam. PhytoKeys 179: 1-12, DOI: http://dx.doi.org/10.3897/phytokeys.179.65812, URL: http://dx.doi.org/10.3897/phytokeys.179.65812
DOI: 10.15468/79me5r
title: Taxonomy of Vincetoxicum s. str. (Asclepiadoideae, Apocynaceae) from southern Asia including three new species and resurrected names

description: This dataset contains the digitized treatments in Plazi based on the original journal article Shah, Sayed Afzal, Sultan, Amir, Wen, Jun, Ullah, Zahid, Nisa, Surat Un, Ren, Zhumei, Alam, Muhammad Maqsood, Iqbal, Javed, Mumtaz, Abdul Samad (2021): Taxonomy of Vincetoxicum s. str. (Asclepiadoideae, Apocynaceae) from southern Asia including three new species and resurrected names. PhytoKeys 179: 35-73, DOI: http://dx.doi.org/10.3897/phytokeys.179.62514, URL: http://dx.doi.org/10.3897/phytokeys.179.62514
DOI: 10.15468/w7bxpe
title: On the recognition of the long neglected Vitis adenoclada Hand. - Mazz. (Vitaceae) from southern China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wen, Jun, Ma, Zhi-Yao (2021): On the recognition of the long neglected Vitis adenoclada Hand. - Mazz. (Vitaceae) from southern China. PhytoKeys 179: 29-33, DOI: http://dx.doi.org/10.3897/phytokeys.179.65519, URL: http://dx.doi.org/10.3897/phytokeys.179.65519
DOI: 10.6084/m9.figshare.13373828
title: Reducing planetary health risks through short-lived climate forcer mitigation by source sector

description: Surface PM<sub>2.5</sub> concentrations from NASA ModelE2-YIBS simulations using year 2005 IIASA GAINS ECLIPSE v5a emissions. The model has 2° x 2.5° latitude by longitude horizontal resolution. The model output is provided for 9 simulations, a control simulation denoted 'CTRL' and 8 mitigation experiments where all air pollutant precursor emissions have been reduced by 50% from 8 key economic sectors. The 50% sector mitigation experiments have been labelled by the source sector for which the emissions have been halved: agriculture (AGR), agricultural waste burning (AWB), domestic (DOM), energy (ENE), industry (IND), transportation (TRA), waste/landfill (WST), shipping (SHP). The global surface PM<sub>2.5</sub> data for each simulation is provided for model output years 15-24, a total of 10 years.
DOI: 10.5281/zenodo.4977114
title: UKESM1-forced BORIS-1 seafloor biomass under CMIP6 SSPs

description: Change in total simulated seafloor biomass between the 2090s (2090-2099) and late-Historical (1995-2014) under the SSP scenarios 126 to 585. Simulation uses the benthic BORIS model (Kelly-Gerreyn et al., Biogeosciences, 2014) forced using output from the UKESM1 model (Sellar et al., JAMES, 2019; Yool et al., GMD, 2021) in the same experimental design used in Yool et al. (GCB, 2017).
description: THIS IS TEST OUTPUT
description: {"references": ["Yool et al., Global Change Biology, 2017, doi:10.1111/gcb.13680"]}
DOI: 10.5517/ccdc.csd.cc27vmxn
title: CCDC 2081182: Experimental Crystal Structure Determination

description: Related Article: Paul Bourbon, Emeline Appert, Agnès Martin-Mingot, Bastien Michelet, Sébastien Thibaudeau|2021|Org.Lett.|23|4115|doi:10.1021/acs.orglett.1c00994
DOI: 10.5517/ccdc.csd.cc24xhzk
title: CCDC 1993609: Experimental Crystal Structure Determination

description: Related Article: Tsuneomi Kawasaki, Yoshiyasu Kaimori, Seiya Shimada, Natsuki Hara, Susumu Sato, Kenta Suzuki, Toru Asahi, Arimasa Matsumoto, Kenso Soai|2021|Chem.Commun.|57|5999|doi:10.1039/D1CC02162A
DOI: 10.5517/ccdc.csd.cc24xj8w
title: CCDC 1993618: Experimental Crystal Structure Determination

description: Related Article: Tsuneomi Kawasaki, Yoshiyasu Kaimori, Seiya Shimada, Natsuki Hara, Susumu Sato, Kenta Suzuki, Toru Asahi, Arimasa Matsumoto, Kenso Soai|2021|Chem.Commun.|57|5999|doi:10.1039/D1CC02162A
DOI: 10.5517/ccdc.csd.cc281sfk
title: CCDC 2087088: Experimental Crystal Structure Determination

description: Related Article: M. Seiss, S. Schmitz, M. Börner, K.Y. Monakhov|2021|Acta Crystallogr.,Sect.E:Cryst.Commun.|77|703|doi:10.1107/S2056989021005594
DOI: 10.5517/ccdc.csd.cc2826zk
title: CCDC 2087508: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Effendy, Allan H. White|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc282b7y
title: CCDC 2087609: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Effendy, Allan H. White|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc282hrm
title: CCDC 2087780: Experimental Crystal Structure Determination

description: Related Article: W. Clegg|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc282hsn
title: CCDC 2087781: Experimental Crystal Structure Determination

description: Related Article: W. Clegg|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc282htp
title: CCDC 2087782: Experimental Crystal Structure Determination

description: Related Article: W. Clegg, M.R.J. Elsegood, A.J. Edwards|2021|CSD Communication|||
DOI: 10.5281/zenodo.4977133
title: Dateset for FMGDM_v1.0 evaluation

description: Dateset for FMGDM_v1.0 evaluation, used in the manuscript: <em>A Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application in the green tides of the Yellow Sea.</em>
DOI: 10.5281/zenodo.4977132
title: Dateset for FMGDM_v1.0 evaluation

description: Dateset for FMGDM_v1.0 evaluation, used in the manuscript: <em>A Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application in the green tides of the Yellow Sea.</em>
DOI: 10.6084/m9.figshare.14681100
title: Mitochondrial genomes withing bark lica (insecta: Psocodea: Psocomorpha) reveal novel gene rearrangements containing phylogenetic signal. Supp. Data.

description: Supplementary data belonging to the article " Mitochondrial genomes withing bark lice (insecta: Psocodea: Psocomorpha) reveal novel gene rearrangements containing phylogenetic signal". This repository include phylogenetic analyses datasets, figures resulted from phylogenetic analyses plus gene rearrangements dataset and phylogenetic tree used in TreeREx analysis.<br>
DOI: 10.6084/m9.figshare.14681100.v1
title: Mitochondrial genomes withing bark lica (insecta: Psocodea: Psocomorpha) reveal novel gene rearrangements containing phylogenetic signal. Supp. Data.

description: Supplementary data belonging to the article " Mitochondrial genomes withing bark lice (insecta: Psocodea: Psocomorpha) reveal novel gene rearrangements containing phylogenetic signal". This repository include phylogenetic analyses datasets, figures resulted from phylogenetic analyses plus gene rearrangements dataset and phylogenetic tree used in TreeREx analysis.<br>
DOI: 10.6084/m9.figshare.14792172
title: Inhibitory_novel_familiar_data_subset

description: A subset of the data from the Allen Brain Observatory Visual Behavior 2P dataset.<br>Contains data for final familiar session and first novel session. All in parquet format.<br>Files are:* Experiment table - table of experiment metadata* Stimulus data - table with data describing every stimulus* Neural data - table with recordings from every neuron* Precomputed traces around each stimulus omisson<br>After downloading, files are opened using```import pandas as pddata = pd.read_parquet(FILENAME)```
DOI: 10.6084/m9.figshare.14792172.v5
title: Inhibitory_novel_familiar_data_subset

description: A subset of the data from the Allen Brain Observatory Visual Behavior 2P dataset.<br>Contains data for final familiar session and first novel session. All in parquet format.<br>Files are:* Experiment table - table of experiment metadata* Stimulus data - table with data describing every stimulus* Neural data - table with recordings from every neuron* Precomputed traces around each stimulus omisson<br>After downloading, files are opened using```import pandas as pddata = pd.read_parquet(FILENAME)```
DOI: 10.6084/m9.figshare.14792172.v4
title: Inhibitory_novel_familiar_data_subset

description: A subset of the data from the Allen Brain Observatory Visual Behavior 2P dataset.<br>Contains data for final familiar session and first novel session. All in parquet format.<br>Files are:* Experiment table - table of experiment metadata* Stimulus data - table with data describing every stimulus* Neural data - table with recordings from every neuron* Precomputed traces around each stimulus omisson<br>After downloading, files are opened using```import pandas as pddata = pd.read_parquet(FILENAME)```
DOI: 10.25739/bc4f-x382
title: Optimization of Temporal UAS-Based Imagery Analysis to Estimate Plant Maturity Date for Soybean Breeding

description: The datasets included were collected from the UMN soybean breeding project sites in planting seasons 2018 and 2019. Specific planting season includes the orthomosaic generated using the raw images, plot boundary delimitations (.shp), the ground control points (GCPs), and the ground-truth notes to perform the georeferencing corrections. Specific readme files for each season are included in the directory. /UMNSoybeans_Planting_Season_2018: This directory contains 4 folders /a._GCPs_coordinates /b._Orthomosaics /c._Shapefiles /d._Ground_notes /UMNSoybeans_Planting_Season_2019: This directory contains 4 folders /a._GCPs_coordinates /b._Orthomosaics /c._Shapefiles /d._Ground_notes For general information or questions about the temporal UAS-based imagery analysis to estimate date of plant maturity (DPM) analysis, please contact lore0149@umn.edu (Aaron J. Lorenz). For questions regarding released datasets, contact: Orthomosaics and shapefiles: volpa008@umn.edu (Leonardo Volpato) - first author GCPs coordinates: dobbe045@umn.edu (Austin A. Dobbels) - co-author. A pipeline software tool and scripts for data extraction and analysis were developed to accomplish the activities ranging from image capture to statistical analysis of extracted features. The UAS-based maturity date scripts and processes used to perform the image analyses and trait extract are available at https://github.com/volpatoo/HTP-via-drone-imagery
DOI: 10.25739/nv2q-ct31
title: A full hydrological dataset suite for the Upper Colorado River Basin from 1983 to 2019

description: This dataset is a full hydro-meteorological dataset suite with an hourly temporal resolution and 1-km spatial resolution from October 1982 to September 2019 over the Upper Colorado River Basin (UCRB). The dataset consists of simulation outputs of an integrated hydrological model, ParFlow-CLM. The dataset was validated over the 37-year time period with a combination of point observations and remotely sensed products. The simulated results accurately capture dynamic changes of the hydrological cycle throughout the period in terms of relative bias and Spearman-Rho with average values of 0.124 and 0.696, respectively. The dataset provides continuous hydrological inputs such as streamflow, water table depth, snow water equivalent (SWE) and evapotranspiration (ET) for almost four decades.
DOI: 10.5281/zenodo.4976859
title: Crowdsourcing vibration data stemming from different transportation usages

description: Crowdsourcing vibration data stemming from different activities and transportation usages (by trains, by buses, by bicycles by walking). We present a comprehensive dataset that provides the pattern of five activities walking, cycling, taking a train, a bus or a taxi. The measurements are carried out by embedded sensor accelerometer in smartphones. The dataset offers dynamic responses of subjects carrying smartphones in varied styles as they performing the five activities through vibrations acquired by accelerometers. The dataset contains corresponding time stamps and vibrations in three directions longitudinal, horizontal, and vertical stored in an Excel Macro-enabled Workbook (xlsm) format can be used to train an AI model in a smartphone which has potentials to collect people’s vibration data and decides what movement is being conducted. Besides, with more data are received, the database can be updated and it can be fed to train the model with a larger dataset. The prevalent of the smartphone opens the door of crowdsensing which leads to the pattern of people talking public transports can be understood. Furthermore, the time consumed in each activity is available in the dataset. Therefore, with a better understanding of people using public transports, the service and schedule can be planned perceptively. Activities to obtain the dataset are jointly funded by H2020 and Hitachi Europe.
description: {"references": ["http://edata.bham.ac.uk/655/"]}
DOI: 10.25345/c5cr8j
title: MassIVE MSV000087650 - Refractory Dissolved Organic Matter Project - Aluwihare Lab
title: Deep samples (&gt;500m) from Pacific Ocean (CCE, Station M, ETNP, GOSHIP cruise)
DOI: 10.34721/62bb-rz05
title: Competitive interactions in stream restoration
DOI: 10.5517/ccdc.csd.cc1z0h6p
title: CCDC 1817722: Experimental Crystal Structure Determination

description: Related Article: Ziyi Liu, Malliga R. Iyer, Grzegorz Godlewski, Tony Jourdan, Jie Liu, Nathan J. Coffey, Charles N. Zawatsky, Henry L. Puhl, Jürgen Wess, Jaroslawna Meister, Jeih-San Liow, Robert B. Innis, Sergio A. Hassan, Yong Sok Lee, George Kunos, Resat Cinar|2021|ACSPharmacol.Transl.Sci.|4|1175|doi:10.1021/acsptsci.1c00048
DOI: 10.5517/ccdc.csd.cc1z0h7q
title: CCDC 1817723: Experimental Crystal Structure Determination

description: Related Article: Ziyi Liu, Malliga R. Iyer, Grzegorz Godlewski, Tony Jourdan, Jie Liu, Nathan J. Coffey, Charles N. Zawatsky, Henry L. Puhl, Jürgen Wess, Jaroslawna Meister, Jeih-San Liow, Robert B. Innis, Sergio A. Hassan, Yong Sok Lee, George Kunos, Resat Cinar|2021|ACSPharmacol.Transl.Sci.|4|1175|doi:10.1021/acsptsci.1c00048
DOI: 10.5517/ccdc.csd.cc24m4kh
title: CCDC 1984606: Experimental Crystal Structure Determination

description: Related Article: Dimitry Grebenyuk, Mirijam Zobel, Maurizio Polentarutti, Liviu Ungur, Mikhail Kendin, Konstantin Zakharov, Pavel Degtyarenko, Alexander Vasiliev, Dmitry Tsymbarenko|2021|Inorg.Chem.|60|8049|doi:10.1021/acs.inorgchem.1c00581
DOI: 10.5517/ccdc.csd.cc24m4lj
title: CCDC 1984607: Experimental Crystal Structure Determination

description: Related Article: Dimitry Grebenyuk, Mirijam Zobel, Maurizio Polentarutti, Liviu Ungur, Mikhail Kendin, Konstantin Zakharov, Pavel Degtyarenko, Alexander Vasiliev, Dmitry Tsymbarenko|2021|Inorg.Chem.|60|8049|doi:10.1021/acs.inorgchem.1c00581