cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2fq47k
title: CCDC 2255598: Experimental Crystal Structure Determination

description: Related Article: Hua Liu, Quan-Quan Li, Li Zhou, Bing Deng, Peng-Hui Pan, Shu-Ya Zhao, Ping Liu, Yao-Yu Wang, Jian-Li Li|2023|J.Am.Chem.Soc.|145|17588|doi:10.1021/jacs.3c02379
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fq48l
title: CCDC 2255599: Experimental Crystal Structure Determination

description: Related Article: Hua Liu, Quan-Quan Li, Li Zhou, Bing Deng, Peng-Hui Pan, Shu-Ya Zhao, Ping Liu, Yao-Yu Wang, Jian-Li Li|2023|J.Am.Chem.Soc.|145|17588|doi:10.1021/jacs.3c02379
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fq49m
title: CCDC 2255600: Experimental Crystal Structure Determination

description: Related Article: Hua Liu, Quan-Quan Li, Li Zhou, Bing Deng, Peng-Hui Pan, Shu-Ya Zhao, Ping Liu, Yao-Yu Wang, Jian-Li Li|2023|J.Am.Chem.Soc.|145|17588|doi:10.1021/jacs.3c02379
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.18739/a2901zh52
title: The Eurasian Arctic Ocean along the MOSAiC drift (2019-2020): Core hydrographic parameters

description: The Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC, 2019/2020), a year-long drift with the Arctic sea ice, has provided the scientific community with an unprecedented, multidisciplinary dataset from the Eurasian Arctic Ocean, covering from high atmosphere to deep ocean across all seasons. However, the heterogeneity of data and the superposition of spatial and temporal variability intrinsic to a drift campaign complicate the interpretation of observations. Here, we compile a quality-controlled dataset with best coverage and derived parameters, and provide daily average values of: drift speed, friction velocity, ocean temperature and salinity (full profiles and surface), mixed layer depth, mixing layer depth, heat flux over the halocline and thermocline. The presented core parameters offer valuable context for interdisciplinary research, fostering an improved understanding of the complex, coupled Arctic System. Results based on this dataset are described in Schulz, Koenig, Muilwijk et al.: "The Eurasian Arctic Ocean along the MOSAiC drift (2019-2020): An interdisciplinary perspective on properties and processes" (Elementa: Science of the Anthropocene, tentatively submitted September 2023). When using the parameter in this data set, we strongly advise to also cite the respective original data sets, linked in the description of methods here.
DOI: 10.6084/m9.figshare.24066234.v1
title: the polyketide to fatty acid transition in the evolution of animal lipid metabolism:the animal FAS-like PKSs

description: Animals use a distinct fatty acid synthase (FAS) most closely related to the type I polyketide synthase (PKS) enzymes. While FASs synthesize simple lipids, PKSs produce complex specialized metabolites. The evolutionary origin of the animal FAS, and its relationship to the diversity of PKSs, remain surprisingly mysterious despite the critical role of lipid synthesis in cellular metabolism. Previously, an enzyme EcPKS1 from sacoglossan molluscs was described that was closely related to animal FAS enzymes, but instead preformed PKS-like chemistry. A few other related enzymes were apparent in molluscs, mostly in the photosynthetic sacoglossans. Here, we asked whether such enzymes were limited to a small subset of species, and whether they might answer the mystery of the origin of animal lipid biosynthesis. We performed a sequence-based analysis, unexpectedly discovering a huge diversity of widespread EcPKS1-like enzymes that form a grade separating PKS from the animal FAS clade in phylogenetic analyses. PKSs and FASs are widespread among major animal phyla except for sponges and ctenophores, where they are apparently absent. Surprisingly, molluscs and arthropods contain abundant EcPKS1-like enzymes, correlated with their rich polyketide chemistry. Molluscan EcPKS1 relatives are associated with a lack of other defenses, consistent with the hypothesis that AFPKs provide a chemical defense for some lineages. By contrast, shelled molluscs (physically defended) generally contain PKSs instead. Arthropods have few or no PKSs, but their abundant EcPKS1-like enzymes contributed to their ecological and evolutionary success. For example, some of the genes found in the EcPKS1 clade were previously associated with cuticular hydrocarbon and pheromone biosynthesis. Based upon the biochemical, genetic, and phylogenetic features of these enzymes, we propose that they comprise a new family, the animal FAS-like PKSs (AFPKS). Although animal metabolism is well studied, surprising new metabolic enzyme classes such as AFPKs still await discovery and may be unrecognized drivers of hyperdiverse animal radiations including gastropods, beetles and spiders.
DOI: 10.5066/p9h591a9
title: Geologic map of the Wichmann CA region of the Moon, Lunar Orbiter Site III P-11, Oceanus Procellarum including Apollo landing sites 4 and 4R

description: This map shows the geology in and around two potential early Apollo landing sites in the equatorial belt. The Wichmann CA region is in the Oceanus Procellarum, south of the equator, approximately 320 km south of the crater Kepler. It is covered by mare material with numerous ridges, low domes, craters, and crater clusters. Relatively few of the craters are larger than 200 m across. Terra material is absent. The relative freshness of the low domes and prominent mare ridges suggest that the mare material here is relatively young. On an earlier, small-scale reconnaissance geologic map of the Letronne region (Marshall, 1963), mare material in the Wichmann CA region was mapped as Imbrian; but Orbiter photographs show that the oldest craters on the surface are relatively young Eratosthenian craters and mare material is now believed to be Eratosthenian.
DOI: 10.5281/zenodo.8306687
title: Collection of n-body simulations including tidal dissipation in a planet and a satellite

description: This zip file contains roughly 6000 n-body gravity simulations used in Kisare & Fabrycky (2023)<em>.</em> Included in the zip file is a README that with more details on how to navigate and interpret the data.
description: N-body code from Mardling & Lin (2002) was kindly provided by R. Mardling. We thank the Research Computing Center at the University of Chicago for use of the Midway2 cluster, where our runs were completed. This work was supported by the University of Chicago Jeff Metcalf Fellowship Grant
DOI: 10.5281/zenodo.8306686
title: Collection of n-body simulations including tidal dissipation in a planet and a satellite

description: This zip file contains roughly 6000 n-body gravity simulations used in Kisare & Fabrycky (2023)<em>.</em> Included in the zip file is a README that with more details on how to navigate and interpret the data.
description: N-body code from Mardling & Lin (2002) was kindly provided by R. Mardling. We thank the Research Computing Center at the University of Chicago for use of the Midway2 cluster, where our runs were completed. This work was supported by the University of Chicago Jeff Metcalf Fellowship Grant
DOI: 10.57967/hf/1062
title: llm4security
DOI: 10.57967/hf/1061
title: llm4security
DOI: 10.6084/m9.figshare.23586949
title: Measurement of the centrifugal particle mass analyzer transfer function

description: Particle mass analyzers, in particular the centrifugal particle mass analyzer (CPMA) and the aerosol particle mass analyzer (APM), have provided new possibilities for aerosol science through their ability to classify particles by their mass-to-charge ratio. The performance of the CPMA in classifying particles is characterized by a probability distribution known as a transfer function. This study shows the theoretical models of the CPMA’s transfer function that exist in the literature cannot accurately predict the CPMA’s actual performance. In this study, a tandem CPMA (TCPMA) measurement technique was used to experimentally evaluate the deviation of the actual CPMA transfer function from its idealized triangular transfer function. This deviation was measured by three factors: (<i>i</i>) the width factor (μ), (<i>ii</i>) the height factor (η), and (<i>iii</i>) the mass set point agreement (i.e<i>.,</i> the agreement between the set points of the two CPMAs, m12∗); such that concurrent values of 1 for all three factors implied no deviation between the actual and theoretical triangular CPMA transfer functions. These factors were derived by adjusting them to fit TCPMA data with the convolution of two triangular transfer functions with identical widths. TCPMA data were collected for a wide range of CPMA resolutions, flow rates, and mass set points ranging from 2 to 15, 0.3 to 8 LPM, and 0.05 to 100 fg, respectively. The mass set point agreement remained relatively constant over a range of CPMA mass set points and increased slightly with decreasing CPMA resolutions. Neglecting outliers, the average mass set point agreement was m12∗=1.02±0.03, suggesting good reproducibility among the CPMAs. The width factor showed a functional dependence on the mass set point, resolution, and flow rate. It was observed that the CPMA transfer function was generally narrower (μ&gt;1) than the idealized transfer function except at a low flow rate (0.3 LPM) and low mass set points (m∗&lt;1 fg), and the width factor approached unity at higher mass set points (m∗&gt;1 fg) and higher resolutions (Rm&gt;6). As expected, the height factor depends on the mass set point, resolution, and flow rate: it decreases with lower mass set points, lower flow rates and higher resolutions. Both the width and height factors were fitted robustly using multivariate non-linear fitting models so that CPMA users can easily calculate its transfer function over a wide range of operating conditions. Copyright © 2023 American Association for Aerosol Research
DOI: 10.6084/m9.figshare.23586949.v1
title: Measurement of the centrifugal particle mass analyzer transfer function

description: Particle mass analyzers, in particular the centrifugal particle mass analyzer (CPMA) and the aerosol particle mass analyzer (APM), have provided new possibilities for aerosol science through their ability to classify particles by their mass-to-charge ratio. The performance of the CPMA in classifying particles is characterized by a probability distribution known as a transfer function. This study shows the theoretical models of the CPMA’s transfer function that exist in the literature cannot accurately predict the CPMA’s actual performance. In this study, a tandem CPMA (TCPMA) measurement technique was used to experimentally evaluate the deviation of the actual CPMA transfer function from its idealized triangular transfer function. This deviation was measured by three factors: (<i>i</i>) the width factor ( μ), (<i>ii</i>) the height factor ( η), and (<i>iii</i>) the mass set point agreement (<i>i.e.,</i> the agreement between the set points of the two CPMAs, m12∗); such that concurrent values of 1 for all three factors implied no deviation between the actual and theoretical triangular CPMA transfer functions. These factors were derived by adjusting them to fit TCPMA data with the convolution of two triangular transfer functions with identical widths. TCPMA data were collected for a wide range of CPMA resolutions, flow rates, and mass set points ranging from 2 to 15, 0.3 to 8 LPM, and 0.05 to 100 fg, respectively. The mass set point agreement remained relatively constant over a range of CPMA mass set points and increased slightly with decreasing CPMA resolutions. Neglecting outliers, the average mass set point agreement was m12∗=1.02±0.03, suggesting good reproducibility among the CPMAs. The width factor showed a functional dependence on the mass set point, resolution, and flow rate. It was observed that the CPMA transfer function was generally narrower ( μ&gt;1) than the idealized transfer function except at a low flow rate (0.3 LPM) and low mass set points ( m∗&lt;1 fg), and the width factor approached unity at higher mass set points ( m∗&gt;1 fg) and higher resolutions ( Rm&gt;6). As expected, the height factor depends on the mass set point, resolution, and flow rate: it decreases with lower mass set points, lower flow rates and higher resolutions. Both the width and height factors were fitted robustly using multivariate non-linear fitting models so that CPMA users can easily calculate its transfer function over a wide range of operating conditions.
DOI: 10.5281/zenodo.8295895
title: Survey and Analysis of Whistler- and Z-mode Emission in the Juno Extended Mission

description: This is the supporting data set for the paper by the same title published in AGU JGR Space Physics. <strong>Key Points:</strong> Whistler mode lower and upper band chorus intensities are surveyed in the extended Juno mission, increasing orbital coverage. Z-mode intensity distributions are re-analyzed with improved plasma density evaluations. Mixed Z-mode, O-mode, and W-mode emission challenges discrete mode identification. <strong>Abstract</strong> Whistler mode and Z-mode waves may have significant impact on electron scattering and acceleration at Jupiter as recent stochastic models indicate. New observations of these waves in the Juno extended mission expand the orbital coverage from previous surveys, extending especially to smaller radial distances near the magnetic equator, and to extended ranges of dusk-side magnetic local time. M-shells transiting the Io torus and the orbit of Europa are recognized as a significant source region for whistler mode lower and upper band chorus emission with intensity peaks near 9 R<sub>j</sub>. Ganymede is a significant source of intense whistler mode chorus confined to the local moon environment. New Z-mode observations now extend from a few kHz to over 80 kHz. Inferred source regions for Z-mode are consistent with the outer edge of the Io torus and with auroral field lines that may also support broadband kilometric or decametric emission.
DOI: 10.5281/zenodo.8295894
title: Survey and Analysis of Whistler- and Z-mode Emission in the Juno Extended Mission

description: This is the supporting data set for the paper by the same title published in AGU JGR Space Physics. <strong>Key Points:</strong> Whistler mode lower and upper band chorus intensities are surveyed in the extended Juno mission, increasing orbital coverage. Z-mode intensity distributions are re-analyzed with improved plasma density evaluations. Mixed Z-mode, O-mode, and W-mode emission challenges discrete mode identification. <strong>Abstract</strong> Whistler mode and Z-mode waves may have significant impact on electron scattering and acceleration at Jupiter as recent stochastic models indicate. New observations of these waves in the Juno extended mission expand the orbital coverage from previous surveys, extending especially to smaller radial distances near the magnetic equator, and to extended ranges of dusk-side magnetic local time. M-shells transiting the Io torus and the orbit of Europa are recognized as a significant source region for whistler mode lower and upper band chorus emission with intensity peaks near 9 R<sub>j</sub>. Ganymede is a significant source of intense whistler mode chorus confined to the local moon environment. New Z-mode observations now extend from a few kHz to over 80 kHz. Inferred source regions for Z-mode are consistent with the outer edge of the Io torus and with auroral field lines that may also support broadband kilometric or decametric emission.
DOI: 10.5281/zenodo.8274745
title: SuperDARN Grid data in netCDF format (2016-Jan)

description: 2016-Jan SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, 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/rstThe 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)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'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.8274746
title: SuperDARN Grid data in netCDF format (2016-Jan)

description: 2016-Jan SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, 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/rstThe 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)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'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.8274702
title: SuperDARN Grid data in netCDF format (2016-Feb)

description: 2016-Feb SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, 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/rstThe 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)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'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.8274703
title: SuperDARN Grid data in netCDF format (2016-Feb)

description: 2016-Feb SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, 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/rstThe 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)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'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.8274544
title: SuperDARN Grid data in netCDF format (2016-Jun)

description: 2016-Jun SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, 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/rstThe 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)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'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.'