cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7284/128703
title: Gravimeter data collected during research cruise SKQ201617S using a Bell BGM-3 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128709
title: Gyrocompass data collected during research cruise SKQ201617S using a Sperry NAVIGAT 2100 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128710
title: Gyrocompass data collected during research cruise SKQ201617S using a Sperry NAVIGAT 2100 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128722
title: INS (Inertial Navigation System) data collected during research cruise SKQ201617S using a Kongsberg Seapath 320+ instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128711
title: Meteorological Station data collected during research cruise SKQ201617S using a Vaisala WXT520 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128712
title: Radiometer data collected during research cruise SKQ201617S using a RMR Co. PRP instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128713
title: Radiometer data collected during research cruise SKQ201617S using a Biospherical QSR-2150 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.26180/5bd37e5012f67
title: WRR_data.tar

description: Data from two trays, measured by an ARG 1000 raingauge.<br>
DOI: 10.7284/128706
title: Rain Gauge data collected during research cruise SKQ201617S using a RM Young 50202 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128719
title: Water Temperature data collected during research cruise SKQ201617S using a HEITRONICS CT15.10 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/128716
title: TSG (Thermosalinograph) data collected during research cruise SKQ201617S using a Sea-Bird SBE-45 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/127138
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise SKQ201701S using a Hawaii UHDAS instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261598
title: JARVIS ML Training Data

description: Various properties of 24,759 bulk and 2D materials computed with the OptB88vdW and TBmBJ functionals taken from the JARVIS DFT database. <br><br>This dataset was modified from the JARVIS ML training set developed by NIST (1-2). The custom descriptors have been removed, the column naming scheme revised, and a composition column created. This leaves the training set as a dataset of composition and structure descriptors mapped to a diverse set of materials properties.<br><br>Available as Monty Encoder encoded JSON and as the source Monty Encoder encoded JSON file. Recommended access method is with the matminer Python package using the datasets module.<br>Note on citations: If you found this dataset useful and would like to cite it in your work, please be sure to cite its original sources below rather than or in addition to this page.<br>Dataset discussed in: <br>Machine learning with force-field-inspired descriptors for materials: Fast screening and mapping energy landscape Kamal Choudhary, Brian DeCost, and Francesca Tavazza Phys. Rev. Materials <b>2</b>, 083801<br>Original Data file sourced from:choudhary, kamal (2018): JARVIS-ML-CFID-descriptors and material properties. figshare. Dataset.
DOI: 10.7284/127155
title: Anemometer data collected during research cruise SKQ201701S using a Gill WindObserver 75 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261580
title: contamination datasets

description: please contact Arthur Pightling at apightling@gmail.com before using<br>
DOI: 10.7284/127156
title: Anemometer data collected during research cruise SKQ201701S using a Gill WindObserver 75 instrument system onboard the platform RV Sikuliaq

description: Processed data created by vessel technician during a Field_expedition
DOI: 10.7284/127140
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise SKQ201701S using a Sea-Bird SBE-911+ instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/127142
title: Flowmeter data collected during research cruise SKQ201701S using a Omega FP-2541 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/127143
title: Flowmeter data collected during research cruise SKQ201701S using a Krohne Optiflux 5000 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261469.v1
title: MagnetoGUI

description: This Matlab GUI script is used to analyzed tif stack files.
DOI: 10.7284/127145
title: Fluorometer data collected during research cruise SKQ201701S using a Turner Cyclops-7 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/127146
title: GNSS (Global Navigation Satellite System) data collected during research cruise SKQ201701S using a C&C C-Nav 3050 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261448
title: Co-functional network data and app

description: Data as reported in Boyle, Pritchard and Greenleaf 2018. Enclosed is a Shiny app capable of visualizing the gene-gene edges called by co-essentiality in whole genome CRISPR screens
DOI: 10.6084/m9.figshare.7261448.v1
title: Co-functional network data and app

description: Data as reported in Boyle, Pritchard and Greenleaf 2018. Enclosed is a Shiny app capable of visualizing the gene-gene edges called by co-essentiality in whole genome CRISPR screens
DOI: 10.7284/127141
title: Gravimeter data collected during research cruise SKQ201701S using a Bell BGM-3 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261469.v2
title: MagnetoGUI

description: This Matlab GUI script is used to analyzed tif stack files. Run Save MagnetoGUI.m and MagnetoGUI.fig in the same folder before running MagnetoGUI.m in Matlab.<br>Instructions for Use:1. Click Load mRuby and select mRuby file2. Adjust threshold and disk size (if appropriate). Click enter to setnew value3. Click Detect Cells4. Inspect image to assure that all cells are being detected. Adjustparameters if necessary and click Detect cells again. Repeat until allcells are delected5. Click Load Video6. Select Fluo4 or ArcLight and THEN adjust fps, StimON, StimDUR,PeakH, PeakW as necessary. Click enter to set new value. This stepcan really be done anytime before step 7. Don't mess with these whilethe analysis is running though; it'll confuse it.7. Click Detect Cells (the one below Load Video).1. This detects all the cells in the field of view. It's used togenerate transfection stats; if you're not going to save the data,you don't need to worry about this step. Just hit Detect Cells so theAnalyze button is enabled. It'll run a little faster if you set thethreshold higher because it won't detect any cells :)7. Click Analyze8. If plots are acceptable, click Save or adjust parameters and clickAnalyze again1. Clicking Saves the mRuby + cell detection, first video frame +cell detection, panel 2 and enclosed plots, the raster plot, anddata sufficient to rerun analysis in a new folder in the samefolder the data analyzed was found2. Checking Categorized Save sorts the data into the appropriatefolder based on the construct and stimulation type. It also savesthe integral data and transfection stats in the appropriate foldersfor creating the heat map/3D bar plot and transfection stats table9. If you would like to reload data, make sure it has been analyzed bythis GUI before (to ensure that the necessary parameters have beenproperly saved) and click Load Old Data to display the analysis10. Data can be reanalyzed by adjusting the parameters and clickinganalyze<br>
DOI: 10.6084/m9.figshare.7261430
title: The use of microsatellite markers for species delimitation in Antarctic <i>Usnea</i> subgenus <i>Neuropogon</i>

description: Lichens are symbiotic associations consisting of a fungal (mycobiont) and one or more photosynthetic (photobionts) partners and are the dominant component, and most important primary producers, of Antarctic terrestrial ecosystems. The most common lichens in the maritime Antarctic are <i>Usnea antarctica</i> and <i>U. aurantiacoatra</i>, a so-called “species pair” in which <i>U. antarctica</i> shows asexual reproduction and propagation via soredia and <i>U. aurantiacoatra</i> forms ascospores in apothecia. Previous molecular analyses were not able to unambiguously distinguish the two morphotypes as species. Therefore, the goal of this study was to find out whether fast-evolving SSR (single sequence repeat) markers are able to separate morphotypes more clearly and help to clarify their taxonomy. We investigate 190 individuals from five mixed stands of both morphotypes collected in King George Island and Elephant Island (South Shetland Islands, Antarctica). Based on 23 microsatellite markers designed from sequenced genomes, discriminant analysis of principal components (DAPC), Bayesian clustering analysis, and coalescent-based estimation of gene flow show clear evidence for the existence of two different species distinguishable by reproductive mode. We did not detect any statistical association between genetic clusters and three previously reported chemical races of each species.
DOI: 10.7284/127147
title: Gyrocompass data collected during research cruise SKQ201701S using a Sperry NAVIGAT 2100 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261430.v1
title: The use of microsatellite markers for species delimitation in Antarctic <i>Usnea</i> subgenus <i>Neuropogon</i>

description: Lichens are symbiotic associations consisting of a fungal (mycobiont) and one or more photosynthetic (photobionts) partners and are the dominant component, and most important primary producers, of Antarctic terrestrial ecosystems. The most common lichens in the maritime Antarctic are <i>Usnea antarctica</i> and <i>U. aurantiacoatra</i>, a so-called “species pair” in which <i>U. antarctica</i> shows asexual reproduction and propagation via soredia and <i>U. aurantiacoatra</i> forms ascospores in apothecia. Previous molecular analyses were not able to unambiguously distinguish the two morphotypes as species. Therefore, the goal of this study was to find out whether fast-evolving SSR (single sequence repeat) markers are able to separate morphotypes more clearly and help to clarify their taxonomy. We investigate 190 individuals from five mixed stands of both morphotypes collected in King George Island and Elephant Island (South Shetland Islands, Antarctica). Based on 23 microsatellite markers designed from sequenced genomes, discriminant analysis of principal components (DAPC), Bayesian clustering analysis, and coalescent-based estimation of gene flow show clear evidence for the existence of two different species distinguishable by reproductive mode. We did not detect any statistical association between genetic clusters and three previously reported chemical races of each species.
DOI: 10.7284/127148
title: Gyrocompass data collected during research cruise SKQ201701S using a Sperry NAVIGAT 2100 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261424
title: Reverse dosimetry modeling of toluene exposure concentrations based on biomonitoring levels from the Canadian health measures survey

description: Biomonitoring might provide useful estimates of population exposure to environmental chemicals. However, data uncertainties stemming from interindividual variability are common in large population biomonitoring surveys. Physiologically based pharmacokinetic (PBPK) models might be used to account for age- and gender-related variability in internal dose. The objective of this study was to reconstruct air concentrations consistent with blood toluene measures reported in the third Canadian Health Measures Survey using reverse dosimetry PBPK modeling techniques. Population distributions of model’s physiological parameters were described based upon age, weight, and size for four subpopulations (12–19, 20–39, 40–59, and 60–79 years old). Monte Carlo simulations applied to PBPK modeling allowed converting the distributions of venous blood measures of toluene obtained from CHMS into related air levels. Based upon blood levels observed at the 50<sup>th</sup>, 90<sup>th</sup> and 95<sup>th</sup> percentiles, corresponding air toluene concentrations were estimated for teenagers aged 12–19 years as being, respectively, 0.009, 0.04 and 0.06 ppm. Similarly, values were computed for adults aged 20–39 years (0.007, 0.036, and 0.06 ppm), 40–59 years (0.007, 0.036 and 0.06 ppm) and 60–79 years (0.006, 0.022 and 0.04 ppm). These estimations are well below Health Canada’s maximum recommended chronic air guidelines for toluene. In conclusion, PBPK modeling and reverse dosimetry may be combined to help interpret biomonitoring data for chemical exposure in large population surveys and estimate the associated toxicological health risk.
DOI: 10.6084/m9.figshare.7261424.v1
title: Reverse dosimetry modeling of toluene exposure concentrations based on biomonitoring levels from the Canadian health measures survey

description: Biomonitoring might provide useful estimates of population exposure to environmental chemicals. However, data uncertainties stemming from interindividual variability are common in large population biomonitoring surveys. Physiologically based pharmacokinetic (PBPK) models might be used to account for age- and gender-related variability in internal dose. The objective of this study was to reconstruct air concentrations consistent with blood toluene measures reported in the third Canadian Health Measures Survey using reverse dosimetry PBPK modeling techniques. Population distributions of model’s physiological parameters were described based upon age, weight, and size for four subpopulations (12–19, 20–39, 40–59, and 60–79 years old). Monte Carlo simulations applied to PBPK modeling allowed converting the distributions of venous blood measures of toluene obtained from CHMS into related air levels. Based upon blood levels observed at the 50<sup>th</sup>, 90<sup>th</sup> and 95<sup>th</sup> percentiles, corresponding air toluene concentrations were estimated for teenagers aged 12–19 years as being, respectively, 0.009, 0.04 and 0.06 ppm. Similarly, values were computed for adults aged 20–39 years (0.007, 0.036, and 0.06 ppm), 40–59 years (0.007, 0.036 and 0.06 ppm) and 60–79 years (0.006, 0.022 and 0.04 ppm). These estimations are well below Health Canada’s maximum recommended chronic air guidelines for toluene. In conclusion, PBPK modeling and reverse dosimetry may be combined to help interpret biomonitoring data for chemical exposure in large population surveys and estimate the associated toxicological health risk.
DOI: 10.7284/127159
title: INS (Inertial Navigation System) data collected during research cruise SKQ201701S using a Kongsberg Seapath 320+ instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261406
title: Gaps in health insurance coverage and emergency department use among children with asthma

description: <i>Background</i>: Gaps in health insurance coverage may complicate asthma management and increase emergency department (ED) use. Using two nationally-representative surveys, we characterize the prevalence of coverage gaps among children with asthma, and describe their association with ED visits in this population. <i>Methods</i>: De-identified data were obtained from the 2016 National Survey of Children’s Health (NSCH) and National Health Interview Survey (NHIS). Among children with asthma, we classified coverage over the past year as: (1) continuous private, (2) continuous public, (3) gap in coverage, and (4) continuously uninsured. The primary outcome was all-cause ED visits in the past year (both surveys). Secondary outcomes included unmet health care needs (NSCH), asthma-related ED visits or hospitalizations (NHIS) and asthma exacerbations (NHIS). <i>Results</i>: The analysis included 3739 (NSCH) and 854 (NHIS) children with asthma, representing a population of 5.5 million children in the US. Estimated prevalence of coverage gaps was 5% in the NSCH and 3% in the NHIS. On multivariable ordinal logistic regression using NSCH data, coverage gaps were associated with increased all-cause ED use (OR = 2.5; 95% CI: 1.3, 4.7, <i>p</i> = 0.005), compared to continuous private coverage. Further analysis confirmed higher odds of unmet health care needs, asthma exacerbations, and asthma-related ED visits among children with coverage gaps. <i>Conclusions</i>: Children with asthma who experience insurance coverage gaps have increased ED use, possibly related to poorer access to appropriate health care. Protecting insurance coverage continuity may reduce ED use and improve clinical outcomes in this population.
DOI: 10.7284/127149
title: Meteorological Station data collected during research cruise SKQ201701S using a Vaisala WXT520 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7261385
title: Supplementary files "Characterisation of faults as earthquake sources from geomorphic data in the Tongariro Volcanic Complex, New Zealand"

description: Table A1. Fault strands vertical displacement and along-strike slip distribution calculations for the Waihi Fault zone. Table A2. Fault strands vertical displacement and along-strike slip distribution calculations for the Poutu Fault zone.
DOI: 10.6084/m9.figshare.7261406.v1
title: Gaps in health insurance coverage and emergency department use among children with asthma

description: <i>Background</i>: Gaps in health insurance coverage may complicate asthma management and increase emergency department (ED) use. Using two nationally-representative surveys, we characterize the prevalence of coverage gaps among children with asthma, and describe their association with ED visits in this population. <i>Methods</i>: De-identified data were obtained from the 2016 National Survey of Children’s Health (NSCH) and National Health Interview Survey (NHIS). Among children with asthma, we classified coverage over the past year as: (1) continuous private, (2) continuous public, (3) gap in coverage, and (4) continuously uninsured. The primary outcome was all-cause ED visits in the past year (both surveys). Secondary outcomes included unmet health care needs (NSCH), asthma-related ED visits or hospitalizations (NHIS) and asthma exacerbations (NHIS). <i>Results</i>: The analysis included 3739 (NSCH) and 854 (NHIS) children with asthma, representing a population of 5.5 million children in the US. Estimated prevalence of coverage gaps was 5% in the NSCH and 3% in the NHIS. On multivariable ordinal logistic regression using NSCH data, coverage gaps were associated with increased all-cause ED use (OR = 2.5; 95% CI: 1.3, 4.7, <i>p</i> = 0.005), compared to continuous private coverage. Further analysis confirmed higher odds of unmet health care needs, asthma exacerbations, and asthma-related ED visits among children with coverage gaps. <i>Conclusions</i>: Children with asthma who experience insurance coverage gaps have increased ED use, possibly related to poorer access to appropriate health care. Protecting insurance coverage continuity may reduce ED use and improve clinical outcomes in this population.
DOI: 10.7284/127139
title: Multibeam Echosounder data collected during research cruise SKQ201701S using a Kongsberg EM302 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7260965
title: spectrophotometric data

description: Tables with spectrophotometric data of four Saffron Finches' body regions<br>
DOI: 10.6084/m9.figshare.7261385.v1
title: Supplementary files "Characterisation of faults as earthquake sources from geomorphic data in the Tongariro Volcanic Complex, New Zealand"

description: Table A1. Fault strands vertical displacement and along-strike slip distribution calculations for the Waihi Fault zone. Table A2. Fault strands vertical displacement and along-strike slip distribution calculations for the Poutu Fault zone.
DOI: 10.7284/127150
title: Radiometer data collected during research cruise SKQ201701S using a RMR Co. PRP instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7259915
title: 126chains.dcd

description: MD trajectory for self-assembly of amphiphilic molecules using a coarse-grained model.
DOI: 10.7284/127151
title: Radiometer data collected during research cruise SKQ201701S using a Biospherical QSR-2150 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/127144
title: Rain Gauge data collected during research cruise SKQ201701S using a RM Young 50202 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/127157
title: Water Temperature data collected during research cruise SKQ201701S using a HEITRONICS CT15.10 instrument system onboard the platform RV Sikuliaq

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7259207
title: Somatic embryos of Typha domingensis.xlsx

description: Sustainable methods of propagation of <i>Typha domingensis</i> through somatic embryogenesis can help mitigate its current condition of ecological marginalization and overexploitation. This study examined whether differentiation up to coleoptilar embryos could be obtained in an embryogenic line proliferated with light and high auxin concentration.