cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2b83zq
title: CCDC 2152763: Experimental Crystal Structure Determination

description: Related Article: Magnus R. Buchner, Nils Spang, Sergei I. Ivlev|2022|Z.Naturforsch.,B:Chem.Sci.|77|381|doi:10.1515/znb-2022-0015
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: 10.6084/m9.figshare.24092456
title: Overcoming Repeated Testing Schedule Bias in Estimates of Disease Prevalence

description: During the COVID-19 pandemic, many institutions such as universities and workplaces implemented testing regimens with every member of some population tested longitudinally, and those testing positive isolated for some time. Although the primary purpose of such regimens was to suppress disease spread by identifying and isolating infectious individuals, testing results were often also used to obtain prevalence and incidence estimates. Such estimates are helpful in risk assessment and institutional planning and various estimation procedures have been implemented, ranging from simple test-positive rates to complex dynamical modeling. Unfortunately, the popular test-positive rate is a biased estimator of prevalence under many seemingly innocuous longitudinal testing regimens with isolation. We illustrate how such bias arises and identify conditions under which the test-positive rate is unbiased. Further, we identify weaker conditions under which prevalence is identifiable and propose a new estimator of prevalence under longitudinal testing. We evaluate the proposed estimation procedure via simulation study and illustrate its use on a dataset derived by anonymizing testing data from The Ohio State University. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24092456.v1
title: Overcoming Repeated Testing Schedule Bias in Estimates of Disease Prevalence

description: During the COVID-19 pandemic, many institutions such as universities and workplaces implemented testing regimens with every member of some population tested longitudinally, and those testing positive isolated for some time. Although the primary purpose of such regimens was to suppress disease spread by identifying and isolating infectious individuals, testing results were often also used to obtain prevalence and incidence estimates. Such estimates are helpful in risk assessment and institutional planning and various estimation procedures have been implemented, ranging from simple test-positive rates to complex dynamical modeling. Unfortunately, the popular test-positive rate is a biased estimator of prevalence under many seemingly innocuous longitudinal testing regimens with isolation. We illustrate how such bias arises and identify conditions under which the test-positive rate is unbiased. Further, we identify weaker conditions under which prevalence is identifiable and propose a new estimator of prevalence under longitudinal testing. We evaluate the proposed estimation procedure via simulation study and illustrate its use on a dataset derived by anonymizing testing data from The Ohio State University. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24092452
title: Optimal Dynamic Treatment Regimes and Partial Welfare Ordering

description: Dynamic treatment regimes are treatment allocations tailored to heterogeneous individuals (e.g., via previous outcomes and covariates). The optimal dynamic treatment regime is a regime that maximizes counterfactual welfare. We introduce a framework in which we can partially learn the optimal dynamic regime from observational data, relaxing the sequential randomization assumption commonly employed in the literature but instead using (binary) instrumental variables. We propose the notion of sharp partial ordering of counterfactual welfares with respect to dynamic regimes and establish mapping from data to partial ordering via a set of linear programs. We then characterize the identified set of the optimal regime as the set of maximal elements associated with the partial ordering. We relate the notion of partial ordering with a more conventional notion of partial identification using topological sorts. Practically, topological sorts can be served as a policy benchmark for a policymaker. We apply our method to understand returns to schooling and post-school training as a sequence of treatments by combining data from multiple sources. The framework of this article can be used beyond the current context, for example, in establishing rankings of multiple treatments or policies across different counterfactual scenarios. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24092452.v1
title: Optimal Dynamic Treatment Regimes and Partial Welfare Ordering

description: Dynamic treatment regimes are treatment allocations tailored to heterogeneous individuals (e.g., via previous outcomes and covariates). The optimal dynamic treatment regime is a regime that maximizes counterfactual welfare. We introduce a framework in which we can partially learn the optimal dynamic regime from observational data, relaxing the sequential randomization assumption commonly employed in the literature but instead using (binary) instrumental variables. We propose the notion of sharp partial ordering of counterfactual welfares with respect to dynamic regimes and establish mapping from data to partial ordering via a set of linear programs. We then characterize the identified set of the optimal regime as the set of maximal elements associated with the partial ordering. We relate the notion of partial ordering with a more conventional notion of partial identification using topological sorts. Practically, topological sorts can be served as a policy benchmark for a policymaker. We apply our method to understand returns to schooling and post-school training as a sequence of treatments by combining data from multiple sources. The framework of this article can be used beyond the current context, for example, in establishing rankings of multiple treatments or policies across different counterfactual scenarios. Supplementary materials for this article are available online.
DOI: 10.5517/ccdc.csd.cc2b840s
title: CCDC 2152764: Experimental Crystal Structure Determination

description: Related Article: Magnus R. Buchner, Nils Spang, Sergei I. Ivlev|2022|Z.Naturforsch.,B:Chem.Sci.|77|381|doi:10.1515/znb-2022-0015
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.cc2b841t
title: CCDC 2152765: Experimental Crystal Structure Determination

description: Related Article: Magnus R. Buchner, Nils Spang, Sergei I. Ivlev|2022|Z.Naturforsch.,B:Chem.Sci.|77|381|doi:10.1515/znb-2022-0015
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.cc2b842v
title: CCDC 2152766: Experimental Crystal Structure Determination

description: Related Article: Magnus R. Buchner, Nils Spang, Sergei I. Ivlev|2022|Z.Naturforsch.,B:Chem.Sci.|77|381|doi:10.1515/znb-2022-0015
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: 10.5281/zenodo.8322542
title: Augustus training parameters for CP genome predictions

description: Augustus training parameters for CP genome predictions
DOI: 10.5281/zenodo.8322541
title: Augustus training parameters for CP genome predictions

description: Augustus training parameters for CP genome predictions
DOI: 10.6084/m9.figshare.24082362.v2
title: Nathaniel Palmer OBS data (2000)

description: OBS data from Nathaniel Palmer expedition in 2000.
DOI: 10.6084/m9.figshare.24082362
title: Nathaniel Palmer OBS data (2000)

description: OBS data from Nathaniel Palmer expedition in 2000.
DOI: 10.5066/p9ouhj8n
title: Concentration of sertraline and acetaminophen in freshwater mussel (Sagittunio subrostratus) and water from an exposure bioassay

description: Dataset consists of water and freshwater mussel concentrations of two pharmaceuticals, sertraline and acetaminophen, collected from a 14-day accumulation and 7-day elimination study. Samples (4 replicates) were collected at 0, 4, 12, 48, 96, 168, and 336 hours during the uptake phase of the exposure. Samples (4 replicates) were collected at time point 348, 360, 408, and 504 hours during the elimination phase of the exposure. Note the time points are sequential with the uptake portion of the study followed by the elimination portion of the study.
DOI: 10.6084/m9.figshare.24082350.v2
title: Polar Duke Antarctic seismic expedition (1987)

description: Seismic data acquired by Polar Duke campaign at Bransfield Strait in 1987
DOI: 10.6084/m9.figshare.24082350.v1
title: Polar Duke seismic expedition (1987)

description: Seismic data acquired by Polar Duke campaign at Bransfield Strait in 1987
DOI: 10.6084/m9.figshare.24082350
title: Polar Duke Antarctic seismic expedition (1987)

description: Seismic data acquired by Polar Duke campaign at Bransfield Strait in 1987
DOI: 10.5281/zenodo.8322577
title: CEGMA and BUSCO output files

description: CEGMA and BUSCO output files
DOI: 10.5281/zenodo.8322576
title: CEGMA and BUSCO output files

description: CEGMA and BUSCO output files
DOI: 10.5066/p9vh5bix
title: Geologic maps of the Descartes region of the Moon Apollo 16 pre-mission maps

description: The evolution of the Moon’s surface shows three successive stages (Hartmann, 1970). The earliest, from the beginning of the decipherable record to the Imbrian Period, was dominated by frequent large-scale impacts which produced overlapping and interfering craters and giant multi-ringed basin with ejecta blankets. The second stage, extending through most of the Imbrian to early Eratosthenian Periods, was characterized by volcanism, producing basalt flows of the maria an varied materials on the terrae. The final and longest stage, extending through the greater part of the Eratosthenian Period and the whole of the Copernican, was one of reduced geologic activity. Major modifications of the geologic structure by large impacts of volcanism occurring only locally, although changes by small-scale impact and mass wasting affected the entire surface. The Descartes region, in the central highlands of the Moon about 500 km southeast of the center of the lunar disk, is dominated by features of the middle stage and contains an exceptionally favorable site for their study
DOI: 10.6084/m9.figshare.24082212
title: Hesperides seismic data from Antarctic Expedition (2005)

description: Former Seismic Data from Hesperides Campaign (2005)
DOI: 10.6084/m9.figshare.24082212.v2
title: Hesperides seismic data from Antarctic Expedition (2005)

description: Former Seismic Data from Hesperides Campaign (2005)
DOI: 10.5066/p9rcz7dy
title: Bathymetry of the Green River near Brownsville, Kentucky, July 2023

description: These data are bathymetry (river bottom elevation) in XYZ format (Easting, Northing, Elevation), generated from the July 24?25, 2023, and July 31, 2023, bathymetric survey of the Green River near Brownsville, Kentucky, from approximately 1.5 miles downstream from the Brownsville boat ramp to approximately 0.8 mile upstream from the former Green River Lock and Dam #6 site (3.8 miles total reach length). Hydrographic data were collected using an acoustic Doppler current profiler (ADCP) with an integrated global navigation satellite system (GNSS) smart antenna. The ADCP and GNSS antenna were mounted on a marine survey vessel, and data were collected as the survey vessel traversed the river along planned survey lines. A total of 207 survey lines were oriented approximately perpendicular to the primary flow direction at variable spacing (generally spaced 100 feet apart but at a 500-foot spacing along the downstream portion of the reach and at 10- to 50-foot spacing in two areas of interest). Data collection software integrated and stored the depth and position data from the ADCP and GNSS antenna in real time. Water-surface elevations were measured approximately every 500 feet throughout the survey area with a survey-grade integrated GNSS system with real-time kinematic (RTK) observations to convert measured bathymetric depths to elevations referenced to the North American Vertical Datum of 1988 (NAVD 88). RTK observations were made using the Kentucky Continually Operating Reference System (KYCORS) network operated by the Kentucky Transportation Cabinet. Data processing required computer software to extract the bathymetric data from the raw data files and to compile and map the information. The final comma-delimited file contains columns of Easting and Northing in feet North American Datum of 1983 (NAD83) Kentucky State Plane Single Zone (FIPS code 1600), and Elevation in feet NAVD 88.
DOI: 10.25345/c5qn5zn6g
title: MassIVE MSV000092826 - Host derived extracellular vesicles released during Pseudomonas aeruginosa infection function as a homing signal for neutrophils
title: 945418: C EV (Healthy corneal epithelial extracellular vesicle fraction) 945421: C EV (Healthy corneal epithelial extracellular vesicle fraction) 940231: C EV (Healthy corneal epithelial extracellular vesicle fraction) 945417: PA-C EV (Pseudomonas aeruginosa infected corneal epithelial extracellular vesicle fraction) 945419: PA-C EV (Pseudomonas aeruginosa infected corneal epithelial extracellular vesicle fraction) 945421: PA-C EV (Pseudomonas aeruginosa infected corneal epithelial extracellular vesicle fraction) 985295: B EV (Healthy bronchial epithelial extracellular vesicle fraction) 985296: B EV (Healthy bronchial epithelial extracellular vesicle fraction) 985297: B EV (Healthy bronchial epithelial extracellular vesicle fraction) 985301: PA-B EV (Pseudomonas aeruginosa infected bronchial epithelial extracellular vesicle fraction) 985302: PA-B EV (Pseudomonas aeruginosa infected bronchial epithelial extracellular vesicle fraction) 985303: PA-B EV (Pseudomonas aeruginosa infected bronchial epithelial extracellular vesicle fraction) 903192: C FP (Healthy corneal epithelial free protein fraction) 903193: C FP (Healthy corneal epithelial free protein fraction) 903194: C FP (Healthy corneal epithelial free protein fraction) 903195: PA-C FP (Pseudomonas aeruginosa infected corneal epithelial free protein fraction) 903196: PA-C FP (Pseudomonas aeruginosa infected corneal epithelial free protein fraction) 903197: PA-C FP (Pseudomonas aeruginosa infected corneal epithelial free protein fraction) 985298: B FP (Healthy bronchial epithelial free protein fraction) 985299: B FP (Healthy bronchial epithelial free protein fraction) 985300: B FP (Healthy bronchial epithelial free protein fraction) 985304: PA-B FP (Pseudomonas aeruginosa infected bronchial epithelial free protein fraction) 985305: PA-B FP (Pseudomonas aeruginosa infected bronchial epithelial free protein fraction) 985306: PA-B FP (Pseudomonas aeruginosa infected bronchial epithelial free protein fraction)
DOI: 10.34740/kaggle/ds/3616560
title: Face Mask Detection: Augmentation Boost
DOI: 10.17909/txm7-h277
title: SMACS0723 NIRCam Data
DOI: 10.5517/ccdc.csd.cc2g12by
title: CCDC 2265149: Experimental Crystal Structure Determination

description: Related Article: Dmitry Yufit|2023|CSD Communication|||
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.cc2g191w
title: CCDC 2265357: Experimental Crystal Structure Determination

description: Related Article: Yoichi Hoshimoto|2023|CSD Communication|||
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.cc2g192x
title: CCDC 2265358: Experimental Crystal Structure Determination

description: Related Article: Yoichi Hoshimoto|2023|CSD Communication|||
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.cc2g193y
title: CCDC 2265359: Experimental Crystal Structure Determination

description: Related Article: Yoichi Hoshimoto|2023|CSD Communication|||
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: 10.5066/p912kci6
title: Geologic maps of the Taurus-Littrow region of the Moon Apollo 17 pre-mission maps

description: The Taurus-Littrow region is mainly a highland area at the juncture of Mare Serenitatis and Mare Tranquillitatis (Scott and Pohn, 1972). Highland materials cover most of the area, forming a group or rugged massifs close to the center of the map and more subdued terrain to the east. The highland units (pItm, IpIh) are probably mostly breccias formed by the Serenitatis impact and pre-existing breccias excavated by this event. Younger Crisium and Imbrium ejecta may also be present but cannot be distinguished. To the west and southwest materials typical of lunar maria, almost certainly basalts, encroach upon and embay the highland terrain. Also in the west is a unit of special interest, a relatively young, usually dark material that mantles both terra and mare. It is draped over a wide variety of terrains in much of the western half of the map area and is interpreted as pyroclastic volcanics. The Apollo 17 site lies on this dark mantling material where it covers an embayment of mare materials between upland massifs. At this locality, therefore, relatively young volcanic can be samples as well as the ancient deposits that form the highland massifs.
DOI: 10.5281/zenodo.8320050
title: Strengthening E-cadherin adhesion via antibody mediated binding stabilization

description: Simulation files for the publication: "Strengthening E-cadherin adhesion via antibody mediated binding stabilization". This includes starting structure files, GROMACS parameters files, GROMACS run input files and sample protein trajectory files for all conditions: +ab strong (set 1), +ab weak (set 5), -ab (set 1), K14E +ab (set 1), and 1ab (set 1) conditions. Due to the limitation of the maximum upload size (50GB), only protein trajectories were uploaded without solvent.
DOI: 10.5281/zenodo.8320049
title: Strengthening E-cadherin adhesion via antibody mediated binding stabilization

description: Simulation files for the publication: "Strengthening E-cadherin adhesion via antibody mediated binding stabilization". This includes starting structure files, GROMACS parameters files, GROMACS run input files and sample protein trajectory files for all conditions: +ab strong (set 1), +ab weak (set 5), -ab (set 1), K14E +ab (set 1), and 1ab (set 1) conditions. Due to the limitation of the maximum upload size (50GB), only protein trajectories were uploaded without solvent.
DOI: 10.5281/zenodo.8322634
title: OrthologR output

description: OrthologR output
DOI: 10.5281/zenodo.8322633
title: OrthologR output

description: OrthologR output
DOI: 10.6075/j0jh3kz9
title: Boyes Creek Canyon (BCC): Processed 2-minute data. In Center for Western Weather and Water Extremes (CW3E) Surface Meteorological Observational Dataset

description: CW3E BCC Surface Met Station is instrumented with Texas Electronics 9.6” TE525MM-L tipping bucket rain gauge; Campbell Scientific CS616 soil moisture sensors and CS107 soil temperature sensors, each placed at 6 depths (5, 10, 15, 20, 50, 100 cm); CS320 Digital Thermopile Pyranometer; 05108-L RM Young Wind Monitor HD Anemometer; CS106 Barometer; CS215-L CSL Temperature/RH Probe. The CS215 was replaced with a HygroVue10 Temp/RH sensor on 28, March 2021. The files available here for download are updated every 1-2 days with most recent data. CW3E is currently working on a partly automated, partly manual QC process to clean and improve all datasets as they are downloaded from the stations, which will make the data more accessible to interested scientists and stakeholders. This is an ongoing effort and is not yet implemented.
description: Processed 2-minute data from Boyes Creek Canyon, a CW3E Surface Met Station. Each station measures temperature, relative humidity, pressure, precipitation, and soil moisture and temperature at six soil depths.
DOI: 10.18112/openneuro.ds004743.v1.0.0
title: AudioTact_YA
DOI: 10.5281/zenodo.8322667
title: Repeatmasker and repeatmodeler results

description: Repeatmasker and repeatmodeler results
DOI: 10.5281/zenodo.8322666
title: Repeatmasker and repeatmodeler results

description: Repeatmasker and repeatmodeler results
DOI: 10.5519/qd.vh8dd5pj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (166 records)
DOI: 10.6084/m9.figshare.24093639
title: Data and code for Sagi & Hawlena (2023), Ecology Letters, Climate dependence of the macrofaunal effect on litter decomposition – a global meta-regression analysis.

description: This item contains the data and code used to produce the results of the published study.
DOI: 10.3886/e147963v1-141287
title: Data and code for "Can you move to Opportunity? Evidence from the Great Migration"

description: This paper shows that racial composition shocks during the Great Migration (1940-1970) reduced the gains from growing up in the northern United States for Black families and can explain 27% of the region’s racial upward mobility gap today. I identify northern Black share increases by interacting pre-1940 Black migrants’ location choices with predicted southern county out-migration. Locational changes, not negative selection of families, explain lower upward mobility, with persistent segregation and increased crime and policing as plausible mechanisms. The case of the Great Migration provides a more nuanced view of moving to opportunity when destination reactions are taken into account.<br><br>
description: non-southern US counties and commuting zones<br>. Smallest Geographic Unit: commuting zones, counties
DOI: 10.6084/m9.figshare.23280698
title: Use of Competency Questions in Ontology Engineering - A Survey

description: Study package of a survey about the use of competency questions in ontology engineering with the complete set of collected data plus tables and graphs.