cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24171672
title: Datasets for Crime Hotspot Prediction Project

description: Datasets: This repository includes a folder titled Datasets that contains all crime and park event tables. These tables consist of event observations across street segments (columns) with time steps (rows). This is a crucial aspect of the project. Additionally, the folder contains Python pickles that store network information, street segment details, and crime location information. Each file in this folder is required by the script to generate predictions.Predictions: The folder also contains predictions across all the models (e.g., theft daily, robbery shift). These files have two columns: actual and predicted values, respectively. The structure is 2459 rows by test days. This means that the first 2459 rows represent predictions for each segment on the first day, the next 2459 rows represent predictions for the second day, and so on.
DOI: 10.7910/dvn/26907/ads9ex
title: LorenzRauhutKittel_DataFigures.r
DOI: 10.7910/dvn/26907/cw8bzp
title: LorenzRauhutKittel_Regressions.do
DOI: 10.7910/dvn/26907/qzmima
title: data_v2.tab
DOI: 10.7910/dvn/26907/svzdxr
title: data.tab
DOI: 10.7910/dvn/26907/wxurbe
title: groups.tab
DOI: 10.7910/dvn/26907/mfdsjn
title: LorenzRauhutKittel_DataFigures_v2.r
DOI: 10.6073/pasta/ff155aa242a3ba881f2a2b18971e65fe
title: MCR LTER: Coral Reef: Gump Station Meteorological Data, ongoing since 2006

description: These data provide meteorological information measured at the GUMP research station on the north shore of Moorea island, French Polynesia. Data collection began in August, 2006 and include air temperature, relative humidity, wind speed and direction, solar radiation, atmospheric pressure, and integrated rainfall. All sensors are sampled every 5 minutes. Post processing of these data is limited to some unit conversion and exclusion of corrupted data records. Aggregate data are provided in daily, weekly, monthly and yearly time bins. ClimDB data for station GUMPM were derived from the same data source. This material uses data collected by the U.S. National Science Foundation's (NSF) Moorea Coral Reef Long Term Ecological research (MCR LTER) site under Grant No. OCE 2224354 (and earlier awards). Additional financial support to the MCR LTER site was provided through a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2023).
DOI: 10.5517/ccdc.csd.cc2gj4hn
title: CCDC 2279631: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Genzink, Matthew D. Rossler, Herman Recendiz, Tehshik P. Yoon|2023|J.Am.Chem.Soc.|145|19182|doi:10.1021/jacs.3c07132
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.cc2gj4jp
title: CCDC 2279632: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Genzink, Matthew D. Rossler, Herman Recendiz, Tehshik P. Yoon|2023|J.Am.Chem.Soc.|145|19182|doi:10.1021/jacs.3c07132
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: 10.15468/77gqm7
title: Selected Methods for Monitoring Physical and Biological Parameters for Use in the Mesoamerican Region: Fishes Checklist

description: The Mesoamerican Barrier Reef System (MBRS), extending from Isla Contoy on the north of the Yucatan Peninsula to the Bay Islands of Honduras, includes the second longest barrier reef in the world. It is approximately 1,000 km long and spans over four countries and two trans-boundary areas: Chetumal Bay, between Belize and Mexico; and the Gulf of Honduras, between Belize, Guatemala and Honduras. The MBRS is unique in the Western Hemisphere due to its length, composition of reef types, and diverse assemblage of corals and related species. The MBRS contributes to the stabilization and protection of coastal landscapes, maintenance of coastal water quality, and serves as breeding and feeding grounds for marine mammals, reptiles, fish and invertebrates, many of which are of commercial importance. The MBRS is also of immense socioeconomic significance providing employment and a source of income to an estimated one million people living in adjacent coastal areas.
DOI: 10.6073/pasta/6df0e22fed9b33540c05e8ec59e8c96a
title: SBC LTER: Ocean: Time-series: nearshore calibrated pH and temperature outside of reefs, ongoing since 2011

description: Calibrated pH (Total scale, SeaFET sensor) data was collected from 10 reefs in the Santa Barbara Channel along with in situ temperature. Most pH sensors are deployed together with SBC long-term mooring instruments. Data collection intervals and SeaFET sensor depths vary based on the site location.
DOI: 10.6084/m9.figshare.24171684
title: Supplemental data for “Charliecloud’s layer-free, Git-based container build cache”

description: These supplemental data accompany our article “Charliecloud’s layer-free, Git-based container build cache” in the CANOPIE workshop at Supercomputing 2023, DOI~10.1145/3624062.3624585, which describes a novel container build cache architecture and shows that its performance is competitive with and possibly superior to existing layered caches. They include all figures and data for the paper as well as the experiment and analysis code to reproduce them.
DOI: 10.6084/m9.figshare.24171684.v1
title: Supplemental data for “Charliecloud’s layer-free, Git-based container build cache”

description: These supplemental data accompany our article “Charliecloud’s layer-free, Git-based container build cache” in the CANOPIE workshop at Supercomputing 2023, DOI~10.1145/3624062.3624585, which describes a novel container build cache architecture and shows that its performance is competitive with and possibly superior to existing layered caches. They include all figures and data for the paper as well as the experiment and analysis code to reproduce them.
DOI: 10.5281/zenodo.8365082
title: list of materials

description: list of materials used for the BLAZE project
DOI: 10.5281/zenodo.8365081
title: list of materials

description: list of materials used for the BLAZE project
DOI: 10.5281/zenodo.8349161
title: Prioritizing equity in urban heat reduction: Beyond cooling as a metric

description: Archived simulations for five heat wave events happened over Houston from 2017 - 2019 with different urban overheating mitigation strategies.
DOI: 10.5281/zenodo.8349160
title: Prioritizing equity in urban heat reduction: Beyond cooling as a metric

description: Archived simulations for five heat wave events happened over Houston from 2017 - 2019 with different urban overheating mitigation strategies.
DOI: 10.6084/m9.figshare.24171066.v1
title: multi-focus-wbc-dataset

description: A large WBC classification dataset that contains multi-focus images.
DOI: 10.18120/ts18-m231
title: Thalamic coordinated reset deep brain stimulation for upper extremity essential tremor: proof of principle study
DOI: 10.5281/zenodo.8033658
title: Monthly averaged fast-ice thickness in McMurdo Sound from a sea-ice monitoring station

description: Updated monthly averaged fast-ice thickness on level first year fast ice in McMurdo Sound, Antarctica from a sea-ice monitoring station. Fast-ice thickness is derived from temperature measurements and manual drill hole measurements, and linearly interpolated to produce mid-month values. Do not use the original version (SIMS_thickness.xlsx) as an error has been discovered. SIMS_thickness_V2.xlsx is the corrected dataset. A description of the stations and the methods used can be found in Gough et al., 2012 and Richter et al. 2022. Gough, A. J., Mahoney, A. R., Langhorne, P. J., Williams, M. J. M., Robinson, N. J., & Haskell, T. G. (2012). Signatures of supercooling: McMurdo Sound platelet ice. Journal of Glaciology, 58 (207), 38–50. doi:10.3189/2012jog10j218 Richter, M. E., Leonard, G. H., Smith, I. J., Langhorne, P. J., Mahoney, A. R., & Parry, M. (2022). Accuracy and precision when deriving sea-ice thickness from thermistor strings: a comparison of methods. Journal of Glaciology, 1–20. doi:10.1017/jog.2022.108
description: Thermistor data collected in McMurdo Sound between 1996 and 2003 are available under \url{https://drive.google.com/drive/folders/1ooUH9dPvWT66afFC51Cb0JOHg66rn0sy}, data collected in 2002 and 2003 were part of the project ``Measurements and Improved Parameterization of the Thermal Conductivity and Heat Flow through First-Year Sea Ice'', OPP-0126007*. Data collected in 2009, 2010 and 2013 are available at the data repository PANGAEA \cite{gough2017data2009a, smith2017data2010, smith2017data2013, gough2017data2009b}. The thermistor data in McMurdo Sound collected after 2009 were collected with the following funding and logistics support: IRL Subcontract to the University of Otago (2010, 2011); University of Otago Research Grants (2010, 2011, 2014, 2015 (Event Manager: Inga Smith)); NIWA subcontract to University of Otago, ``Antarctic and High Latitude Climate'' (2013-2018); Contribution from MBIE-funded project ``Antarctic sea ice thickness: harbinger of change in the Southern Ocean'' (2013 (PIs: Pat Langhorne and Wolfgang Rack)); Contribution from MBIE-funded Curious Minds public engagement project ``Far from Frozen'' (2016, (leader: Craig Grant, Otago Museum)); US Fulbright Scholar Award (Cecilia Bitz, 2013); NZARI (2015 (PIs: Pat Langhorne and Craig Stevens), 2017, 2018 (PI: Greg Leonard)) Deep South National Science Challenge project TOPIMASI (2016-2018 (PI: Pat Langhorne)); Antarctic Science Platform Project 4 (Sea ice and carbon cycles) (2019, 2020 (Event Manager: Greg Leonard)); Marsden Fund project ``Supercooling measurements under ice shelves'' (2020 (PI: Inga Smith)).
DOI: 10.5281/zenodo.8033659
title: Monthly averaged fast-ice thickness in McMurdo Sound from a sea-ice monitoring station

description: Monthly averaged fast-ice thickness on level first year fast ice in McMurdo Sound, Antarctica from a sea-ice monitoring station. Fast-ice thickness is derived from temperature measurements and manual drill hole measurements, and linearly interpolated to produce mid-month values. A description of the stations and the methods used can be found in Gough et al., 2012 and Richter et al. 2022. Gough, A. J., Mahoney, A. R., Langhorne, P. J., Williams, M. J. M., Robinson, N. J., & Haskell, T. G. (2012). Signatures of supercooling: McMurdo Sound platelet ice. Journal of Glaciology, 58 (207), 38–50. doi:10.3189/2012jog10j218 Richter, M. E., Leonard, G. H., Smith, I. J., Langhorne, P. J., Mahoney, A. R., & Parry, M. (2022). Accuracy and precision when deriving sea-ice thickness from thermistor strings: a comparison of methods. Journal of Glaciology, 1–20. doi:10.1017/jog.2022.108
description: Thermistor data collected in McMurdo Sound between 1996 and 2003 are available under \url{https://drive.google.com/drive/folders/1ooUH9dPvWT66afFC51Cb0JOHg66rn0sy}, data collected in 2002 and 2003 were part of the project ``Measurements and Improved Parameterization of the Thermal Conductivity and Heat Flow through First-Year Sea Ice'', OPP-0126007*. Data collected in 2009, 2010 and 2013 are available at the data repository PANGAEA \cite{gough2017data2009a, smith2017data2010, smith2017data2013, gough2017data2009b}. The thermistor data in McMurdo Sound collected after 2009 were collected with the following funding and logistics support: IRL Subcontract to the University of Otago (2010, 2011); University of Otago Research Grants (2010, 2011, 2014, 2015 (Event Manager: Inga Smith)); NIWA subcontract to University of Otago, ``Antarctic and High Latitude Climate'' (2013-2018); Contribution from MBIE-funded project ``Antarctic sea ice thickness: harbinger of change in the Southern Ocean'' (2013 (PIs: Pat Langhorne and Wolfgang Rack)); Contribution from MBIE-funded Curious Minds public engagement project ``Far from Frozen'' (2016, (leader: Craig Grant, Otago Museum)); US Fulbright Scholar Award (Cecilia Bitz, 2013); NZARI (2015 (PIs: Pat Langhorne and Craig Stevens), 2017, 2018 (PI: Greg Leonard)) Deep South National Science Challenge project TOPIMASI (2016-2018 (PI: Pat Langhorne)); Antarctic Science Platform Project 4 (Sea ice and carbon cycles) (2019, 2020 (Event Manager: Greg Leonard)); Marsden Fund project ``Supercooling measurements under ice shelves'' (2020 (PI: Inga Smith)).
DOI: 10.5281/zenodo.8353757
title: Monthly averaged fast-ice thickness in McMurdo Sound from a sea-ice monitoring station

description: Updated monthly averaged fast-ice thickness on level first year fast ice in McMurdo Sound, Antarctica from a sea-ice monitoring station. Fast-ice thickness is derived from temperature measurements and manual drill hole measurements, and linearly interpolated to produce mid-month values. Do not use the original version (SIMS_thickness.xlsx) as an error has been discovered. SIMS_thickness_V2.xlsx is the corrected dataset. A description of the stations and the methods used can be found in Gough et al., 2012 and Richter et al. 2022. Gough, A. J., Mahoney, A. R., Langhorne, P. J., Williams, M. J. M., Robinson, N. J., & Haskell, T. G. (2012). Signatures of supercooling: McMurdo Sound platelet ice. Journal of Glaciology, 58 (207), 38–50. doi:10.3189/2012jog10j218 Richter, M. E., Leonard, G. H., Smith, I. J., Langhorne, P. J., Mahoney, A. R., & Parry, M. (2022). Accuracy and precision when deriving sea-ice thickness from thermistor strings: a comparison of methods. Journal of Glaciology, 1–20. doi:10.1017/jog.2022.108
description: Thermistor data collected in McMurdo Sound between 1996 and 2003 are available under \url{https://drive.google.com/drive/folders/1ooUH9dPvWT66afFC51Cb0JOHg66rn0sy}, data collected in 2002 and 2003 were part of the project ``Measurements and Improved Parameterization of the Thermal Conductivity and Heat Flow through First-Year Sea Ice'', OPP-0126007*. Data collected in 2009, 2010 and 2013 are available at the data repository PANGAEA \cite{gough2017data2009a, smith2017data2010, smith2017data2013, gough2017data2009b}. The thermistor data in McMurdo Sound collected after 2009 were collected with the following funding and logistics support: IRL Subcontract to the University of Otago (2010, 2011); University of Otago Research Grants (2010, 2011, 2014, 2015 (Event Manager: Inga Smith)); NIWA subcontract to University of Otago, ``Antarctic and High Latitude Climate'' (2013-2018); Contribution from MBIE-funded project ``Antarctic sea ice thickness: harbinger of change in the Southern Ocean'' (2013 (PIs: Pat Langhorne and Wolfgang Rack)); Contribution from MBIE-funded Curious Minds public engagement project ``Far from Frozen'' (2016, (leader: Craig Grant, Otago Museum)); US Fulbright Scholar Award (Cecilia Bitz, 2013); NZARI (2015 (PIs: Pat Langhorne and Craig Stevens), 2017, 2018 (PI: Greg Leonard)) Deep South National Science Challenge project TOPIMASI (2016-2018 (PI: Pat Langhorne)); Antarctic Science Platform Project 4 (Sea ice and carbon cycles) (2019, 2020 (Event Manager: Greg Leonard)); Marsden Fund project ``Supercooling measurements under ice shelves'' (2020 (PI: Inga Smith)).
DOI: 10.6084/m9.figshare.24171720
title: Elucidating the effects on polyphenol oxidase activity and allelic variation of polyphenol oxidase genes on dough and whole wheat-derived product color parameters

description: Polyphenol oxidase (PPO) activity is a primary cause of the development of unattractive dark brown discoloration of wheat-based end products. The present study aims to evaluate a set of 41 diverse wheat genotypes grown at three different locations in India for grain phenol color reaction, PPO activity and molecular marker-based characterization of alleles of PPO genes. Relationships among these parameters were analyzed along with the effects of grain PPO activity on dough and <i>chapati</i> color at different time intervals. The mean PPO activity ranged from 7.42 to 27.57 min<sup>−1</sup> g<sup>−1</sup> 10<sup>−3</sup> among the genotypes and it showed a significant negative correlation with color brightness (L*) of dough rested for 0 min (<i>r</i> = -0.406), 15 min (<i>r</i> = -0.406), 2 h (<i>r</i> = -0.502) and 4 h (<i>r</i> = -0.551) and whole wheat flour-derived <i>chapati</i> rested for 2 h (<i>r</i> = -0.267) and 4 h (<i>r</i> = -0.424). The overall quality color score was negatively correlated with PPO activity (<i>r</i> = -0.863) and showed a positive correlation with both dough and <i>chapati</i> visual color measured at different time intervals. PPO activity in the genotypes carrying different alleles was found to be <i>Ppo-A1a</i>&gt;<i>Ppo-A1b</i>; <i>Ppo-B2d</i>&gt;<i>Ppo-B2a;</i> and <i>Ppo-D1b</i>&gt;<i>Ppo-D1a</i>. The allelic constitution <i>Ppo-A1bPpo-B2aPpo-D1a</i> and <i>Ppo-A1bPpo-B2dPpo-D1</i> was found to produce the lowest PPO activity, and thus these alleles are recommended to be used in marker assisted breeding for low PPO activity genotypes to minimize the discoloration of wheat-based end-products.
DOI: 10.6084/m9.figshare.24171720.v1
title: Elucidating the effects on polyphenol oxidase activity and allelic variation of polyphenol oxidase genes on dough and whole wheat-derived product color parameters

description: Polyphenol oxidase (PPO) activity is a primary cause of the development of unattractive dark brown discoloration of wheat-based end products. The present study aims to evaluate a set of 41 diverse wheat genotypes grown at three different locations in India for grain phenol color reaction, PPO activity and molecular marker-based characterization of alleles of PPO genes. Relationships among these parameters were analyzed along with the effects of grain PPO activity on dough and <i>chapati</i> color at different time intervals. The mean PPO activity ranged from 7.42 to 27.57 min<sup>−1</sup> g<sup>−1</sup> 10<sup>−3</sup> among the genotypes and it showed a significant negative correlation with color brightness (L*) of dough rested for 0 min (<i>r</i> = -0.406), 15 min (<i>r</i> = -0.406), 2 h (<i>r</i> = -0.502) and 4 h (<i>r</i> = -0.551) and whole wheat flour-derived <i>chapati</i> rested for 2 h (<i>r</i> = -0.267) and 4 h (<i>r</i> = -0.424). The overall quality color score was negatively correlated with PPO activity (<i>r</i> = -0.863) and showed a positive correlation with both dough and <i>chapati</i> visual color measured at different time intervals. PPO activity in the genotypes carrying different alleles was found to be <i>Ppo-A1a</i>&gt;<i>Ppo-A1b</i>; <i>Ppo-B2d</i>&gt;<i>Ppo-B2a;</i> and <i>Ppo-D1b</i>&gt;<i>Ppo-D1a</i>. The allelic constitution <i>Ppo-A1bPpo-B2aPpo-D1a</i> and <i>Ppo-A1bPpo-B2dPpo-D1</i> was found to produce the lowest PPO activity, and thus these alleles are recommended to be used in marker assisted breeding for low PPO activity genotypes to minimize the discoloration of wheat-based end-products.
DOI: 10.5281/zenodo.8364828
title: High Energy Lightning Emission Network (HELEN) Flight 7a 06/19/2023

description: Data gathered during the flight of the High Energy Lightning Emission Network (HELEN) on June 19th, 2023. The first file, 1-Flight7a-Raw Data.zip, is the raw data taken directly from the payloads' micro SD cards. In the second file, 2-Flight7a-Data to Process.zip, the data has been cleaned and is suitable for further processing. The third file, 3-Flight7a-Processed Data.zip, contains data that has been combined and temporally synced. This data can be easily read into MATLAB and used to reproduce results.
description: {"references": ["https://github.com/pbbp0904/HELEN_PST_MATLAB"]}
DOI: 10.6084/m9.figshare.24171693
title: chexnet_repro_pytorch.h5

description: weightschexnet<br>
DOI: 10.6084/m9.figshare.24171693.v1
title: chexnet_repro_pytorch.h5

description: weightschexnet<br>
DOI: 10.5517/ccdc.csd.cc29gqn5
title: CCDC 2129317: Experimental Crystal Structure Determination

description: Related Article: Juliana Morais Missina,  Rubia Camila Ronqui Bottini,  Gabriel Barros Baptistella,  Francielli Sousa Santana,  Danilo Stinghen,  Eduardo Lemos de Sá,  Giovana Gioppo Nunes|2022|J.Coord.Chem.|75|1|doi:10.1080/00958972.2022.2135993
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: 10.34740/kaggle/dsv/6507953
title: BBC News
DOI: 10.6084/m9.figshare.22307347
title: Datasets for Experiments

description: The datasets are generated by the matlab, and are used for quantum classifiers.
DOI: 10.3886/e192222
title: Data and Code for: The Changing Firm and Country Boundaries of US Manufacturers in Global Value Chains

description: This paper documents how US firms organize goods production across firm and country boundaries. Most US firms that perform physical transformation tasks in-house using foreign manufacturing plants in 2007 also own US manufacturing plants; moreover manufacturing comprises their main domestic activity. By contrast, “factoryless goods producers” outsource all physical transformation tasks to arm's-length contractors, focusing their in-house efforts on design and marketing. This distinct firm type is missing from standard analyses of manufacturing, growing in importance, and increasingly reliant on foreign suppliers. Physical transformation “within-the-firm” thus coincides with substantial physical transformation “within-the-country,” whereas its performance “outside-the-firm” often also implies “outside-the-country.” Despite these differences, factoryless goods producers and firms with foreign and domestic manufacturing plants both employ relatively high shares of US knowledge workers. These patterns call for new models and data to capture the potential for foreign production to support domestic innovation, which US firms leverage around the world.
description: None used
description: Response Rates: See appendix tables.
description: Presence of Common Scales: NA
description: See appendix.
description: There are two data sources in the paper:<br><br>1. All US firms that manufacture anywhere in the world in 2007.<br><br>2. Firms with wholesale establishments in 2017 that do not have any US manufacturing plants, and that respond to the 2017 Census of Wholesale trade Special Inquiry questions. These firms are followed back in time to 1992. . Smallest Geographic Unit: countries
description: other;