cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19782871.v1
title: Inbound Arrivals: Using weather surveillance radar to quantify the timing of spring trans-Gulf bird migration - Data Set

description: Hundreds of millions of migratory songbirds cross the Gulf of Mexico each spring en route to breeding grounds in North America, making the northern Gulf coast a critical region for these migrants as it provides the first possible stopover location after a long, nonstop trans-Gulf crossing. However, this region has high levels of anthropogenic activity, making migrants vulnerable to a multitude of potentially lethal obstacles. Understanding the timing of mass migratory arrivals along the coast is imperative for advancing conservation of this critical region through the identification of key times in which to direct conservation actions (e.g., temporary halting of wind turbines, reduction of light pollution). To this end, we assessed 10 years of weather surveillance radar data from 5 sites along the northern Gulf of Mexico coast to quantify the daily timing and intensity of trans-Gulf migrant arrival. On a daily scale, we found that migrant intensity peaked an average of 9 hours after local sunrise, occurring earliest at furthest eastern regions of the Gulf. On a seasonal level, the greatest number of arrivals occurred between late April and early May, with peak intensity occurring latest at furthest west sites. Overall intensity of migration across all ten years of data was greatest at the most western sites and decreased the further east a site was located. These findings emphasize the use of the Gulf of Mexico region by migratory birds, providing information that can both advance our understanding of trans-Gulf migration and support conservation of migratory birds in this critical region. <strong>Data Set Key </strong> <strong>site</strong>: NEXRAD radar station ID <strong>deviance_explained</strong>: r2 value, the amount of variation explained by a generalized additive model with a response of migration intensity and a predictor of hour after sunrise. <strong>arrival_time:</strong> The time (hours after sunrise) in which migratory intensity was at its peak. <strong>peak_intensity</strong>: the peak of migration intensity measured on a given day as a value of eta - a measurement of radar reflectivity (i.e., the density of birds in the airspace). <strong>min_possible</strong> and <strong>max_possible</strong>: Range of data for a given day, the earliest and latest possible arrival time in hours after sunrise.
DOI: 10.6073/pasta/890e4c11f4348b3ceda802732ffa48b4
title: Time series of high-frequency meteorological data at Falling Creek Reservoir, Virginia, USA 2015-2020

description: This dataset consists of meteorological variables measured by a research-grade Campbell Scientific meteorological station deployed on the dam of Falling Creek Reservoir. Falling Creek Reservoir (Vinton, Virginia, USA), is owned and operated by the Western Virginia Water Authority as a primary water source. The meteorological variables include photosynthetically active radiation, barometric pressure, ambient air temperature, relative humidity, rainfall, wind speed and direction, shortwave radiation, infrared radiation, and albedo. All variables were measured every 5 minutes from 2015-07-07 16:45:00 to 2015-07-13 12:20:00 (YYYY-MM-DD hh:mm:ss) and every minute thereafter to the end of the dataset at 2020-12-31 23:59:00. We applied substantial quality assurance/quality control protocols to the raw observations, as described therein.
DOI: 10.6073/pasta/5448f9d415fd09e0090a46b9d4020ccc
title: Time series of high-frequency profiles of depth, temperature, dissolved oxygen, conductivity, specific conductivity, chlorophyll a, turbidity, pH, oxidation-reduction potential, photosynthetic active radiation, and descent rate for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in Southwestern Virginia, USA 2013-2020

description: Depth profiles of depth, temperature, dissolved oxygen, conductivity, specific conductivity, chlorophyll a, turbidity were collected with a CTD (Conductivity, Temperature, and Depth) profiler fitted with a SBE 43 Dissolved Oxygen sensor and an ECO Triplet Fluorometer and Backscattering Sensor from 2013 to 2020. From 2017-2020, pH and oxidation-reduction potential (ORP) were also collected with a SBE 27 pH and O.R.P. (redox) sensor. CTD profiles were collected in five drinking water reservoirs in southwestern Virginia, USA. All variables were measured every 0.25 seconds, resulting in depth profiles at approximately ten centimeter resolution. The five study reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the town of Pulaski, Virginia. The dataset consists of CTD depth profiles measured at the deepest site of each reservoir adjacent to the dam as well as other reservoir sites on a transect upstream in Carvins Cove Reservoir and Falling Creek Reservoir. The profiles were collected approximately fortnightly in the spring months, weekly in the summer and early autumn, and monthly in the late autumn and winter. Beaverdam Reservoir, Carvins Cove Reservoir, and Falling Creek Reservoir were sampled every year in the dataset (2013-2020); Spring Hollow Reservoir was not in sampled in 2018 or 2020; and Gatewood Reservoir was only sampled in 2016.
DOI: 10.6073/pasta/88896f4a7208c9b7bddcf498258edf78
title: Time series of high-frequency sensor data measuring water temperature, dissolved oxygen, pressure, conductivity, specific conductance, total dissolved solids, chlorophyll a, phycocyanin, and fluorescent dissolved organic matter at discrete depths in Falling Creek Reservoir, Virginia, USA in 2018-2020

description: Depth profiles of water temperature on 1-m intervals from 0.1 to 9 m depth; dissolved oxygen at 5 and 9 m depth; pressure at 9 m depth; and temperature, dissolved oxygen, conductivity, specific conductance, chlorophyll a, phycocyanin, total dissolved solids, fluorescent dissolved organic matter, and pressure at ~1.6 m depth were collected with a suite of high-frequency sensors at Falling Creek Reservoir (Vinton, Virginia, USA) on the 10-minute scale in 2018-2020. Falling Creek Reservoir is owned and managed by the Western Virginia Water Authority as a primary drinking water source for Roanoke, Virginia. This data product consists of one dataset compiled from water temperature data measured at multiple depths by thermistors, two dissolved oxygen sensors at multiple depths, pressure measured at one depth, and a sonde that measures temperature, dissolved oxygen, pressure, conductivity, specific conductance, chlorophyll a, phycocyanin, total dissolved solids, and fluorescent dissolved organic matter measured at the deepest site of the reservoir adjacent to the dam.
DOI: 10.5517/ccdc.csd.cc29xl2x
title: CCDC 2142629: Experimental Crystal Structure Determination

description: Related Article: Lixia Guo, Xue Han, Yujie Ma, Jiangnan Li, Wanpeng Lu, Weiyao Li, Daniel Lee, Ivan da Silva, Yongqiang Cheng, Svemir Rudić, Pascal Manuel, Mark D. Frogley, Anibal J. Ramirez-Cuesta, Martin Schröder, Sihai Yang|2022|Chem.Commun.|58|5753|doi:10.1039/D2CC01197B
DOI: 10.5517/ccdc.csd.cc29xl3y
title: CCDC 2142630: Experimental Crystal Structure Determination

description: Related Article: Lixia Guo, Xue Han, Yujie Ma, Jiangnan Li, Wanpeng Lu, Weiyao Li, Daniel Lee, Ivan da Silva, Yongqiang Cheng, Svemir Rudić, Pascal Manuel, Mark D. Frogley, Anibal J. Ramirez-Cuesta, Martin Schröder, Sihai Yang|2022|Chem.Commun.|58|5753|doi:10.1039/D2CC01197B
DOI: 10.5517/ccdc.csd.cc29xlvp
title: CCDC 2142653: Experimental Crystal Structure Determination

description: Related Article: Marc Lehr, Tjorge Neumann, Christian Näther, Anna J. McConnell|2022|Dalton Trans.|51|6936|doi:10.1039/D2DT00835A
DOI: 10.6084/m9.figshare.19758640
title: Penalties for Industrial Accidents - PLOS ONE

description: Data on reputation and stock market returns. Codebook for analyzing the impact of BP's 2010 Deepwater Horizon oil spill on BP's reputation and stock market returns.
DOI: 10.7294/16568412.v1
title: Effects of Non-Photosynthetic Vegetation on Dust Emissions

description: This data repository contains the simulated soil concentrations from CMAQ model paired with observations from the IMPROVE network. Results from two CMAQ simulations are included, namely the TOTAL run and the FPAR run. The documentation of the CMAQ version 5.3 used in this study is available at https://www.epa.gov/cmaq/cmaq-documentation, and the model source code is freely available via https://github.com/usepa/cmaq. Details about the model configuration and inputs are described in the associated paper or can be found at Appel et al. (2021).<br>
DOI: 10.5281/zenodo.6555245
title: Monthly-Mean Model Output for Paper Titled "Do Nudging Tendencies Depend on the Nudging Timescale Chosen in Atmospheric Models?"

description: These tarballs contains monthly-mean model output, which was primarily what was presented in the AGU JAMES paper titled "Do nudging tendencies depend on the nudging timescale chosen in atmospheric models?". Also included are the scripts used to set up these simulations, allowing reproducibility of the portion of the paper that used 3-hourly output. The 3-hourly output was not included, as it totaled ~7TB.
DOI: 10.6084/m9.figshare.19728871.v1
title: Examining the benefits of digitally selectable meals called “À La Carte Digital-Select” in cancer chemotherapy patients

description: We explored the benefits of a digitized bedside terminal with a touchscreen for selectable hospital meals called “à la carte digital-select” in cancer chemotherapy patients. The subjects used “à la carte digital-select” for 35 days, from November to December 2015. On average, 253 (between 196 to 288) patients accessed this system per day, and 40 patients used it daily (15.9%). Subjects included 75 patients (cancer chemotherapy: chem-digital-select patients, female: 47) and 12 patients (concurrent chemo radiotherapy: CRT-digital-select patients, female: 6) with a repeat rate of 87% (65) and 100% (12). The average length of hospital stay in chem-digital-select patients was six days (1-35) , the average number of days using “à la carte digital-select” was three days (1-24) ; a correlation was observed between these factors (<em>r</em> = 0.80; <em>p</em> &lt;0.01). The eating rate of chemotherapy patients and CRT-digital-select patients was high (81%,81%), and no differences were observed between the rate in the cisplatin group (80%) with 28 patients, the non-cisplatin group (81%) with 47 patients, CRT-digital-select patients (81%) with 12 patients (<em>p</em>=0.59; ANOVA). Registered dietitians provided no nutritional intervention in any of the cases. We found that “à la carte digital-select” can contribute to supporting cancer chemotherapy and the dietary needs of cancer patients undergoing chemotherapy.
DOI: 10.5281/zenodo.6558396
title: Simulation of Receptor Binding Domain of SARS-CoV-2 spike protein (WT and variants) in complex with neutralizing antibodies.

description: This repository contains the molecular dynamics trajectories of the SARS-CoV-2 Spike RBD bound to BD23 and B38 monoclonal antibodies. The simulations for the RBD only systems are also provided. The trajectories are available for the WT spike protein as well as for four different variants (alpha, beta, kappa and delta). The simulations of the RBD only system are propagated for 300 ns and for the RBD-Antibody complex for 500 ns. The trajectories are saved at 100 ps interval. The Steered MD simulation trajectories (WT_RBD_B38_SMD_1.dcd etc.) and collective variables files are also included (WT_RBD_B38_SMD_1.colvars.traj etc.). There are 5 SMD trajectories for each RBD antibody pair. The details of the simulation can be obtained from the preprint: https://doi.org/10.1101/2021.08.13.456317
description: Funding: NSF MCB 2028443 Computing Resources: University of California Irvine HPC3, San Diego Supercomputer Center
DOI: 10.5281/zenodo.5676393
title: Simulation of Receptor Binding Domain of SARS-CoV-2 spike protein (WT and variants) in complex with neutralizing antibodies.

description: This repository contains the molecular dynamics trajectories of the SARS-CoV-2 Spike RBD bound to BD23 and B38 monoclonal antibodies. The simulations for the RBD only systems are also provided. The trajectories are available for the WT spike protein as well as for four different variants (alpha, beta, kappa and delta). The simulations of the RBD only system are propagated for 300 ns and for the RBD-Antibody complex for 500 ns. The trajectories are saved at 100 ps interval. The Steered MD simulation trajectories (WT_RBD_B38_SMD_1.dcd etc.) and collective variables files are also included (WT_RBD_B38_SMD_1.colvars.traj etc.). There are 5 SMD trajectories for each RBD antibody pair. The details of the simulation can be obtained from the preprint: https://doi.org/10.1101/2021.08.13.456317
description: Funding: NSF MCB 2028443 Computing Resources: University of California Irvine HPC3, San Diego Supercomputer Center
DOI: 10.5281/zenodo.6555157
title: Dataset of Jupyter Notebooks from the paper "A Large-Scale Comparison of Python Code in Jupyter Notebooks and Scripts"

description: <pre>This archive contains the dataset of properly-licensed Jupyter notebooks from the MSR'22 paper "A Large-Scale Comparison of Python Code in Jupyter Notebooks and Scripts". The dataset contains 847,881 notebooks stored in the PostgreSQL dump file. You can find the details about the database in the README file. To transform the notebooks into this convenient format and to calcuate the structural metrics, we used our library called Matroskin, which can be found here: https://github.com/JetBrains-Research/Matroskin. </pre>
DOI: 10.5281/zenodo.6383114
title: Dataset of Jupyter Notebooks from the paper "A Large-Scale Comparison of Python Code in Jupyter Notebooks and Scripts"

description: <pre>This archive contains the dataset of properly-licensed Jupyter notebooks from the MSR'22 paper "A Large-Scale Comparison of Python Code in Jupyter Notebooks and Scripts". The dataset contains 847,881 notebooks stored in the PostgreSQL dump file. You can find the details about the database in the README file. To transform the notebooks into this convenient format and to calcuate the structural metrics, we used our library called Matroskin, which can be found here: https://github.com/JetBrains-Research/Matroskin. </pre>
DOI: 10.5281/zenodo.6557771
title: Dynamic data of body weight and feed intake in fattening pigs and the determination of energetic allocation factors using a dynamic linear model

description: This is the R script (DLM_script.R) to characterize the evolution of the energetic allocation factor (α<sub>t</sub>) which represents the link between the cumulative net energy available (estimated from feed intake) and cumulative weight gain during fattening period. The data for the 100 fattening pigs are stored in the csv file (DataAxiom.csv) and structured as follows: ID (pig identification number); t (time in days since the transfer to fattening room); Wt (median weight at day t for a given ID); FIt (total feed intake at day t for a given ID). For detail description of the procedure please see article.
DOI: 10.34740/kaggle/dsv/3653163
title: Google Analytics Capstone ; Cyclistic case study 1
DOI: 10.5517/ccdc.csd.cc2bbsl2
title: CCDC 2155324: Experimental Crystal Structure Determination

description: Related Article: Chunyu Wang, Huijuan Wang, Jing Wang|2022|J.Mol.Struct.|1264|133257|doi:10.1016/j.molstruc.2022.133257
DOI: 10.5517/ccdc.csd.cc2bbsm3
title: CCDC 2155325: Experimental Crystal Structure Determination

description: Related Article: Chunyu Wang, Huijuan Wang, Jing Wang|2022|J.Mol.Struct.|1264|133257|doi:10.1016/j.molstruc.2022.133257
DOI: 10.6084/m9.figshare.19782898
title: Supplementary material of the study result

description: supplementary material of in silico Tinospora crispa study for PLOSone publication
DOI: 10.6084/m9.figshare.19782898.v1
title: Supplementary material of the study result

description: supplementary material of in silico Tinospora crispa study for PLOSone publication
DOI: 10.5281/zenodo.6558497
title: NevzorvData_ECCC

description: Nevzorov data were collected by ECCC from the NRC Convair-580 research aircraft during seven field campaigns from 1994 to 2004.
description: This is a raw Nezororov data set passed data quality control. For calculations of LWC and IWC, the corrections on the residual effect of ice on the LWC sensor and the correction on the collection efficiency of ice by the TWC sensor should be applied.
DOI: 10.5281/zenodo.6558496
title: Temperature effect on non-Darcian flow in low-permeability porous media

description: This dataset includes the measured threshold gradients and permeabilities of low permeability porous at 3 temperatures, and the measured hydraulic gradients and flow velocities of different permeabilities at 3 temperatures. The experiment is designed to reveal the temperature effects on the non-Darcian flow in low permeability porous media.
DOI: 10.5281/zenodo.6338519
title: Temperature effect on non-Darcian flow in low-permeability porous media

description: This dataset includes the measured threshold gradients and permeabilities of low permeability porous at 3 temperatures, and the measured hydraulic gradients and flow velocities of different permeabilities at 3 temperatures. The experiment is designed to reveal the temperature effects on the non-Darcian flow in low permeability porous media.
DOI: 10.5281/zenodo.6557777
title: Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors: V4.NA.02.MAPLE

description: We estimate ground-level fine particulate matter (PM<sub>2.5</sub>) total and compositional mass concentrations over North America by combining Aerosol Optical Depth (AOD) retrievals from the NASA MODIS, MISR, and SeaWIFS instruments with the GEOS-Chem chemical transport model, and subsequently calibrated to regional ground-based observations of both total and compositional mass using Geographically Weighted Regression (GWR) as detailed in the provided reference for V4.NA.02. V4.NA.02.MAPLE further modified the V4.NA.02 GWR method with additional developments as part of the MAPLE (Mortality–Air Pollution Associations in Low-Exposure Environments) project. This adjustment was of particular value over low concentrations. The GWR method of individual components remains unchanged from V4.NA.02, but are provided are percentages to ensure mass closure and recommended to be applied to the V4.NA.02.MAPLE total PM<sub>2.5</sub>. Annual datasets are provided in NetCDF [.nc]. Gridded files use the WGS84 projection. Compositional estimates are provided for sulfate (SO4), nitrate (NO3), ammonium (NH4), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS). Percentages are denoted with a ‘p’ after component identifiers within filenames. A slight change in file name has been included for 2017, corresponding to minor internal changes compared to earlier years. Overall, however, the dataset is consistent throughout its entire time period and can be appropriately used for trend analysis. <strong>Reference:</strong><br> van Donkelaar, A., R. V. Martin, et al. (2019). <strong>Regional Estimates of Chemical Composition of Fine Particulate Matter using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors.</strong> Environmental Science & Technology, 2019, doi:10.1021/acs.est.8b06392.
description: {"references": ["van Donkelaar, A., R. V. Martin, et al. (2019). Regional Estimates of Chemical Composition of Fine Particulate Matter using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors. Environmental Science & Technology, 2019, doi:10.1021/acs.est.8b06392."]}
DOI: 10.15131/shef.data.17086472
title: Subglacial Meltwater Routes of the Scandinavian Ice Sheet

description: Mapping of subglacial meltwater routes of the Scandinavian Ice Sheet using high-resolution (1-2 m) digital elevation models.<br> Projection and datum: WGS 84 / North Pole Lambert Azimuthal Equal-Area Europe (EPSG: 3575).<br> <br> <strong>Approach</strong><br> Three types of subglacial meltwater routes are distinguished:<br> 1) esker ridges<br> 2) meltwater corridors associated with esker ridges<br> 3) additional meltwater corridors <br> <strong>Attribute table</strong><br> "Type"-field in attribute table congruent with numbers given above. Abbreviations in "Country" field: FIN=Finland, NOR=Norway, SWE=Sweden, RUS=Russia. Length values in metres.<br>
DOI: 10.15131/shef.data.17086472.v1
title: Subglacial Meltwater Routes of the Scandinavian Ice Sheet

description: Mapping of subglacial meltwater routes of the Scandinavian Ice Sheet using high-resolution (1-2 m) digital elevation models.<br> Projection and datum: WGS 84 / North Pole Lambert Azimuthal Equal-Area Europe (EPSG: 3575).<br> <br> <strong>Approach</strong><br> Three types of subglacial meltwater routes are distinguished:<br> 1) esker ridges<br> 2) meltwater corridors associated with esker ridges<br> 3) additional meltwater corridors <br> <strong>Attribute table</strong><br> "Type"-field in attribute table congruent with numbers given above. Abbreviations in "Country" field: FIN=Finland, NOR=Norway, SWE=Sweden, RUS=Russia. Length values in metres.<br>
DOI: 10.7303/syn30602564
title: xaaxa
DOI: 10.5281/zenodo.6558532
title: Serial Crystallography with Multi-stage Merging oi 1000's of Images

description: In the associated paper we discuss the issues involved in improving the sensitivity of both approaches to clustering, using, as an example, 999 5 degree wedges from lysozyme in four iso-forms: NAG: native with N-acetylglucosamine (NAG) soaked in,<br> benzamadine: native with benzamadine soaked in,<br> benzamadine plus NAG: native with both NAG and benzamadine soaked in.<br> Native: no ligands Although the cell parameters are changed sufficiently to allow recognition of the NAG soak, it is difficult to filter the benzamadine soak simply on the basis of cell parameter changes, suggesting the desirability of switching from cell-based clustering to reflection-based clustering as early in the process as possible. The data is this dataset consists of a bzipped HKL structure factor tarball and a bzipped cluster data files from the four forms tarball.
description: Available as a preprint at https://www.biorxiv.org/content/10.1101/141770. Submited to Acta F. Work supported in part by US Dept.~of Energy, Office of Science, DE-AC02-98CH10886 and E-SC0012704} US NIH National Institute of General Medical Sciences, P41RR012408, P41GM103473, and P41GM111244 HJB supported in part by Dectris, Ltd.