cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18739/a2fn10t1c
title: Updated Meteorological, Radiation, and Soil Temperature Data, Kuparuk River and Nearby Watersheds: Lower Kuparuk (LK) station, 1992-1995.

description: The data files in this data set contain climate information from sites on the North Slope of Alaska in or near the Kuparuk River basin. The data was collected for a hydrologic study of rivers in the North Slope region between 1985-present. Hydro-meteorological stations were established at various locations throughout the Kuparuk, but also in the Putuligayuk and Sagavanirktok watersheds. The variables collected at most stations were air temperature, humidity, wind speed and direction, soil temperature, snow temperature, precipitation, snow depth, and radiation. In the Kuparuk watershed, the Lower Kuparuk (LK) Coastal Plain meteorological station operated from 1992-1995. IMPORTANT NOTE: Updates and corrections were made to the original datasets by the investigators, and all of the previously published data files should be replaced with this updated dataset. The following corrections were made to the datasets originally published in 2008 and 2010 (data collected 1985-2008): 1) data from annual .csv files were merged into one .csv file (for each station) containing all years of data, 2) appended new data collected from 2008 to 2018 into the .csv file 3) standardized file headers, 4) standardized variable names, units, and sensor installation height above ground surface 5) reviewed all data for quality assurance and added qualifiers to erroneous data, 6) added a data qualifier to wind data during periods of extensive riming on wind sensors, 7) added a qualifier when air temperatures are below -39 degrees Celsius (C) (minimum reporting temperature of some air temperature sensors), and 8) removed duplicative data and fixed timestamp issues. See https://arcticdata.io/catalog/view/urn%3Auuid%3Ad5fa4cfa-b84b-4970-926a-8dd10b418e6d for additional climate data from other nearby stations in the project.
DOI: 10.5281/zenodo.5138107
title: Van_et_al_2021_Supplementary_files

description: Supplementary Tables 1 and 2 for the manuscript "The ecophysiological performance and traits of genera within the Stichococcus-like clade (Trebouxiophyceae) under matric and osmotic stress"
DOI: 10.5281/zenodo.4907720
title: Van_et_al_2021_Supplementary_files

description: Supplementary Tables 1 and 2 for the manuscript "The ecophysiological performance and traits of genera within the Stichococcus-like clade (Trebouxiophyceae) under matric and osmotic stress"
DOI: 10.5517/cctdl5y
title: CCDC 756870: Experimental Crystal Structure Determination

description: Related Article: X.Fu, P.T.Ma, J.S.Wang, J.Y.Niu|2010|Koord.Khim.|36|626|
DOI: 10.5517/ccdc.csd.cc236rnr
title: CCDC 1942914: Experimental Crystal Structure Determination

description: Related Article: Marcelo Melotti, Matheus S. S. Paqui, André L. Amorim, Carla P. de Paula, Marina C. Rocha, Iran Malavazi, Anderson Cunha, Francielli S. Santana, Ronny R. Ribeiro, Rogério A. Gariani, Samuel R. Mendes, Fernando R. Xavier|2021|New J.Chem.|45|12902|doi:10.1039/D0NJ00895H
DOI: 10.5517/ccdc.csd.cc26n0lh
title: CCDC 2045026: Experimental Crystal Structure Determination

description: Related Article: Marco Bortoluzzi, Jesús Castro, Andrea Di Vera, Alberto Palù, Valentina Ferraro|2021|New J.Chem.|45|12871|doi:10.1039/D1NJ02053F
DOI: 10.5517/ccdc.csd.cc26qr8z
title: CCDC 2047651: Experimental Crystal Structure Determination

description: Related Article: Chenfei Zhu, Chengjian Li, Li Wen, Qingbao Song, Kai Wang, Chunyan Lv, Yujiang Zhang|2021|New J.Chem.|45|12895|doi:10.1039/D1NJ01945G
DOI: 10.5517/ccdc.csd.cc26qr90
title: CCDC 2047652: Experimental Crystal Structure Determination

description: Related Article: Chenfei Zhu, Chengjian Li, Li Wen, Qingbao Song, Kai Wang, Chunyan Lv, Yujiang Zhang|2021|New J.Chem.|45|12895|doi:10.1039/D1NJ01945G
DOI: 10.5517/ccdc.csd.cc24vnym
title: CCDC 1991841: Experimental Crystal Structure Determination

description: Related Article: Amal Das, Pranay Sharma, Antonio Frontera, Miquel Barcelo-Oliver, Akalesh K. Verma, Ruksana Sultana Ahmed, Sahid Hussain, Manjit K. Bhattacharyya|2021|New J.Chem.|45|13040|doi:10.1039/D1NJ00619C
DOI: 10.5517/ccdc.csd.cc24vnxl
title: CCDC 1991840: Experimental Crystal Structure Determination

description: Related Article: Amal Das, Pranay Sharma, Antonio Frontera, Miquel Barcelo-Oliver, Akalesh K. Verma, Ruksana Sultana Ahmed, Sahid Hussain, Manjit K. Bhattacharyya|2021|New J.Chem.|45|13040|doi:10.1039/D1NJ00619C
DOI: 10.5517/ccdc.csd.cc27njq5
title: CCDC 2075317: Experimental Crystal Structure Determination

description: Related Article: Jun Cheng, Chengrong Lu, Bei Zhao|2021|New J.Chem.|45|13096|doi:10.1039/D1NJ02460D
DOI: 10.5517/ccdc.csd.cc27njr6
title: CCDC 2075318: Experimental Crystal Structure Determination

description: Related Article: Jun Cheng, Chengrong Lu, Bei Zhao|2021|New J.Chem.|45|13096|doi:10.1039/D1NJ02460D
DOI: 10.5517/ccdc.csd.cc27nk4m
title: CCDC 2075330: Experimental Crystal Structure Determination

description: Related Article: Jun Cheng, Chengrong Lu, Bei Zhao|2021|New J.Chem.|45|13096|doi:10.1039/D1NJ02460D
DOI: 10.5517/ccdc.csd.cc27nk8r
title: CCDC 2075334: Experimental Crystal Structure Determination

description: Related Article: Jun Cheng, Chengrong Lu, Bei Zhao|2021|New J.Chem.|45|13096|doi:10.1039/D1NJ02460D
DOI: 10.5517/ccdc.csd.cc27nkbt
title: CCDC 2075336: Experimental Crystal Structure Determination

description: Related Article: Jun Cheng, Chengrong Lu, Bei Zhao|2021|New J.Chem.|45|13096|doi:10.1039/D1NJ02460D
DOI: 10.5517/ccdc.csd.cc27qkk3
title: CCDC 2077265: Experimental Crystal Structure Determination

description: Related Article: Marco Bortoluzzi, Jesús Castro, Andrea Di Vera, Alberto Palù, Valentina Ferraro|2021|New J.Chem.|45|12871|doi:10.1039/D1NJ02053F
DOI: 10.5517/ccdc.csd.cc27qkl4
title: CCDC 2077266: Experimental Crystal Structure Determination

description: Related Article: Marco Bortoluzzi, Jesús Castro, Andrea Di Vera, Alberto Palù, Valentina Ferraro|2021|New J.Chem.|45|12871|doi:10.1039/D1NJ02053F
DOI: 10.5517/ccdc.csd.cc27dbpp
title: CCDC 2067442: Experimental Crystal Structure Determination

description: Related Article: Govu Radha, T. Leelasree, D. Muthukumar, Renjith S. Pillai, Himanshu Aggarwal|2021|New J.Chem.|45|12931|doi:10.1039/D1NJ02343H
DOI: 10.6073/pasta/7720837daaa177285e4f091dab5448ec
title: Zooplankton density for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER 2003 - 2017 (Reformatted to the ecocomDP Design Pattern)

description: This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-arc/10272/5. The abstract below was extracted from the Level 0 data package and is included for context: Zooplankton density,were taken with a 30 cm diameter plankton net with 156 um mesh plankton netting, for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER from 2003 - 2017. The Arctic is one of the most rapidly warming regions on Earth. Responses to this warming involve acceleration of processes common to other ecosystems around the world (e.g., shifts in plant community composition) and changes to processes unique to the Arctic (e.g., carbon loss from permafrost thaw). The objectives of the Arctic Long-Term Ecological Research (LTER) Project for 2017-2023 are to use the concepts of biogeochemical and community “openness” and “connectivity” to understand the responses of arctic terrestrial and freshwater ecosystems to climate change and disturbance. These objectives will be met through continued long-term monitoring of changes in undisturbed terrestrial, stream, and lake ecosystems in the vicinity of Toolik Lake, Alaska, observations of the recovery of these ecosystems from natural and imposed disturbances, maintenance of existing long-term experiments, and initiation of new experimental manipulations. Based on these data, carbon and nutrient budgets and indices of species composition will be compiled for each component of the arctic landscape to compare the biogeochemistry and community dynamics of each ecosystem in relation to their responses to climate change and disturbance and to the propagation of those responses across the landscape.
DOI: 10.6084/m9.figshare.14776187
title: Blood-based prognostic biomarkers in Crohn’s Disease patients on biologics: a promising tool to predict endoscopic outcomes

description: There is a growing need for biomarkers to predict therapeutic outcome in Crohn’s disease (CD). The aim was to evaluate whether NLR (neutrophil-to-lymphocyte ratio), PLR (platelet-to-lymphocyte ratio), ELR (eosinophil-to-lymphocyte ratio), and ENLR (eosinophil*neutrophil-to-lymphocyte ratio), could be prognostic biomarkers of endoscopic response (ER) when starting biologics. Patients with CD who started biologics were enrolled. Multivariate analysis was used to evaluate whether NLR, PLR, ELR and ENLR at baseline and at w12 could predict ER (Simple Endoscopic Score for Crohn’s disease [SES-CD] ≤2 or SES-CD≤2 and Rutgeerts i0-i1) after 52 weeks of treatment. Area under the curve (AUC) was calculated to find the cutoffs. 107 patients were included. Patients who achieved ER had significantly lower baseline NLR (p = 0.025), ELR (p = 0.013), and ENLR (p = 0.020) compared with those without ER; results after 12 weeks of treatment for ELR (p = 0.006) and ENLR (p = 0.003). AUC was 0.64 (p = 0.003), 0.67 (p = 0.006) and 0.65 (p = 0.014) for NLR, ELR and ENLR. Low NLR, ELR and ENLR can predict ER and could be used in clinical practice for a better management of CD patients.
DOI: 10.6084/m9.figshare.14776187.v1
title: Blood-based prognostic biomarkers in Crohn’s Disease patients on biologics: a promising tool to predict endoscopic outcomes

description: There is a growing need for biomarkers to predict therapeutic outcome in Crohn’s disease (CD). The aim was to evaluate whether NLR (neutrophil-to-lymphocyte ratio), PLR (platelet-to-lymphocyte ratio), ELR (eosinophil-to-lymphocyte ratio), and ENLR (eosinophil*neutrophil-to-lymphocyte ratio), could be prognostic biomarkers of endoscopic response (ER) when starting biologics. Patients with CD who started biologics were enrolled. Multivariate analysis was used to evaluate whether NLR, PLR, ELR and ENLR at baseline and at w12 could predict ER (Simple Endoscopic Score for Crohn’s disease [SES-CD] ≤2 or SES-CD≤2 and Rutgeerts i0-i1) after 52 weeks of treatment. Area under the curve (AUC) was calculated to find the cutoffs. 107 patients were included. Patients who achieved ER had significantly lower baseline NLR (p = 0.025), ELR (p = 0.013), and ENLR (p = 0.020) compared with those without ER; results after 12 weeks of treatment for ELR (p = 0.006) and ENLR (p = 0.003). AUC was 0.64 (p = 0.003), 0.67 (p = 0.006) and 0.65 (p = 0.014) for NLR, ELR and ENLR. Low NLR, ELR and ENLR can predict ER and could be used in clinical practice for a better management of CD patients.
DOI: 10.6073/pasta/9050796aed03192d08f99553e03507b2
title: Zooplankton density for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER 2003 - 2017 (Reformatted to a Darwin Core Archive)

description: This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/262/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-arc/10272/5. The abstract below was extracted from the Level 0 data package and is included for context: Zooplankton density,were taken with a 30 cm diameter plankton net with 156 um mesh plankton netting, for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER from 2003 - 2017. The Arctic is one of the most rapidly warming regions on Earth. Responses to this warming involve acceleration of processes common to other ecosystems around the world (e.g., shifts in plant community composition) and changes to processes unique to the Arctic (e.g., carbon loss from permafrost thaw). The objectives of the Arctic Long-Term Ecological Research (LTER) Project for 2017-2023 are to use the concepts of biogeochemical and community “openness” and “connectivity” to understand the responses of arctic terrestrial and freshwater ecosystems to climate change and disturbance. These objectives will be met through continued long-term monitoring of changes in undisturbed terrestrial, stream, and lake ecosystems in the vicinity of Toolik Lake, Alaska, observations of the recovery of these ecosystems from natural and imposed disturbances, maintenance of existing long-term experiments, and initiation of new experimental manipulations. Based on these data, carbon and nutrient budgets and indices of species composition will be compiled for each component of the arctic landscape to compare the biogeochemistry and community dynamics of each ecosystem in relation to their responses to climate change and disturbance and to the propagation of those responses across the landscape.
DOI: 10.6084/m9.figshare.14174852
title: Gull influenza and movement data

description: Dataset for the analysis and figures in "Age and season predict influenza A virus dynamics in urban gulls: consequences for natural hosts in unnatural landscapes". Ecological Applications (2021).
DOI: 10.6084/m9.figshare.15056967.v1
title: STAR_test_Smart

description: Toy dataset for running ISOTOPE tutorial.
DOI: 10.6084/m9.figshare.15056967
title: STAR_test_Smart

description: Toy dataset for running ISOTOPE tutorial.
DOI: 10.3886/e122241
title: The Protestant Legacy: Missions, Gender, and Human Capital in India

description: We study the long-term impact of Protestant missions in colonial India on present-day literacy, education,and gender equality in human capital outcomes. We combine contemporary administrativeand survey data with archival information on the spatial distribution of missions and the gendercomposition of missionaries in early twentieth-century India. We document a positive long-runlink between Protestant missions and human capital today. The relationship is particularly strongfor women and for missions with higher female presence. While the data to fully explore the underlyingmechanisms are limited, we show that exposure to Protestant missionaries may have inducedshifts in gender attitudes.
DOI: 10.3886/e122241v3
title: The Protestant Legacy: Missions, Gender, and Human Capital in India

description: We study the long-term impact of Protestant missions in colonial India on present-day literacy, education,and gender equality in human capital outcomes. We combine contemporary administrativeand survey data with archival information on the spatial distribution of missions and the gendercomposition of missionaries in early twentieth-century India. We document a positive long-runlink between Protestant missions and human capital today. The relationship is particularly strongfor women and for missions with higher female presence. While the data to fully explore the underlyingmechanisms are limited, we show that exposure to Protestant missionaries may have inducedshifts in gender attitudes.
DOI: 10.5066/p95g2szc
title: Input Files and Code for: Machine learning can accurately assign geologic basin to produced water samples using major geochemical parameters

description: As more hydrocarbon production from hydraulic fracturing and other methods produce large volumes of water, innovative methods must be explored for treatment and reuse of these waters. However, understanding the general water chemistry of these fluids is essential to providing the best treatment options optimized for each producing area. Machine learning algorithms can often be applied to datasets to solve complex problems. In this study, we used the U.S. Geological Survey?s National Produced Waters Geochemical Database (USGS PWGD) in an exploratory exercise to determine if systematic variations exist between produced waters and geologic environment that could be used to accurately classify a water sample to a given geologic province. Two datasets were used, one with fewer attributes (n = 7) but more samples (n = 58,541) named PWGD7, and another with more attributes (n = 9) but fewer samples (n = 33,271) named PWGD9. The attributes of interest were specific gravity, pH, HCO3, Na, Mg, Ca, Cl, SO4, and total dissolved solids. The two datasets, PWGD7 and PWGD9, contained samples from 20 and 19 geologic provinces, respectively. Outliers across all attributes for each province were removed at a 99% confidence interval. Both datasets were divided into a training and test set using an 80/20 split and a 90/10 split, respectively. Random forest, Na?ve Bayes, and k-Nearest Neighbors algorithms were applied to the two different training datasets and used to predict on three different testing datasets. Overall model accuracies across the two datasets and three applied models ranged from 23.5% to 73.5%. A random forest algorithm (split rule = extratrees, mtry = 5) performed best on both datasets, producing an accuracy of 67.1% for a training set based on the PWGD7 dataset, and 73.5% for a training set based on the PWGD9 dataset. Overall, the three algorithms predicted more accurately on the PWGD7 dataset than PWGD9 dataset, suggesting that either a larger sample size and/or fewer attributes lead to a more successful predicting algorithm. Individual balanced accuracies for each producing province ranged from 50.6% (Anadarko) to 100% (Raton) for PWGD7, and from 44.5% (Gulf Coast) to 99.8% (Sedgwick) for PWGD9. Results from testing the model on recently published data outside of the USGS PWGD suggests that some provinces may be lacking information about their true geochemical diversity while others included in this dataset are well described. Expanding on this effort could lead to predictive tools that provide ranges of contaminants or other chemicals of concern within each province to design future treatment facilities to reclaim wastewater. We anticipate that this classification model will be improved over time as more diverse data are added to the USGS PWGD.
DOI: 10.6084/m9.figshare.15054489
title: pascal dataset

description: dataset for testing
DOI: 10.6084/m9.figshare.15054489.v2
title: pascal dataset

description: dataset for testing
DOI: 10.6084/m9.figshare.15054489.v1
title: pascal

description: dataset for testing
DOI: 10.25934/00005642.0
title: Available IPD datapackage for study 'A randomised, double dummy controlled, parallel group study of the efficacy and safety of Mabthera (rituximab) alone or in combination with either cyclophosphamide or methotrexate, in patients with rheumatoid arthritis.'

description: Vivli is an independent, non-profit organization that has developed a global data-sharing and analytics platform to serve all elements of the international research community. Our mission is to promote, coordinate, and facilitate scientific sharing and reuse of clinical research data through the creation and implementation of a sustainable global data-sharing enterprise. The Vivli platform includes an independent data repository, in-depth search engine and a cloud-based, secure analytics platform.
DOI: 10.25934/00005642.1
title: IPD datapackage for study 'A randomised, double dummy controlled, parallel group study of the efficacy and safety of Mabthera (rituximab) alone or in combination with either cyclophosphamide or methotrexate, in patients with rheumatoid arthritis.' and research request: 'Predicting the Treatment Response of Biologics for Individual Patients with Rheumatoid Arthritis: An Individual Participant Data Meta-Analysis '

description: Vivli is an independent, non-profit organization that has developed a global data-sharing and analytics platform to serve all elements of the international research community. Our mission is to promote, coordinate, and facilitate scientific sharing and reuse of clinical research data through the creation and implementation of a sustainable global data-sharing enterprise. The Vivli platform includes an independent data repository, in-depth search engine and a cloud-based, secure analytics platform.
DOI: 10.5066/p9vk2llo
title: Chemical and biological data from acute toxicity tests with road dust suppressant chemicals and five freshwater organisms

description: Dust suppressants and soil stabilizer products are applied to unpaved roads worldwide to reduce dust production and stabilize road surfaces. Although these products may enter roadside surface water through runoff or leaching, little information is available on environmental fate or aquatic toxicity. The data reported here include the acute toxicity of 27 dust suppressant/soil stabilizer products to juvenile rainbow trout (Oncorhynchus mykiss) and the acute toxicity of selected products to fatmucket mussels (Lampsilis siliquoidea), virile crayfish (Faxonius virilis), pond snails (Lymnaea stagnalis), and larval gray treefrogs (Dryophytes versicolor). Selected products were also tested after exposure to simulated weathering under UV radiation to evaluate the potential for photoenhanced toxicity. Toxicity data (based on average responses of organisms to nominal exposure concentrations of products) and average water quality data have been reported in a journal publication. In this data release we report individual biological and water quality measurements from each toxicity test.
DOI: 10.5066/p9x5hvdf
title: Arsenic datasets and other physical and chemical measurements for selected domestic well-water supplies in Maine: 2001-2 and 2006-7

description: The U.S. Geological Survey (USGS), in cooperation with the U.S. Centers for Disease Control and Prevention and the Maine Center for Disease Control and Prevention, assessed the physical and chemical characteristics and the occurrence, distribution, and oxidation state of inorganic arsenic in drinking water from selected domestic well-water supplies in Maine in 2001-2 and 2006-7. The data collected provide support for evaluating arsenic-removal efficiencies of household water-purification systems and provide information to State and local officials that can be used in determining a water-treatment approach for the removal of arsenic from drinking water.
DOI: 10.5066/p90qs9wz
title: Hourly wave-height observations from 2013 to 2017 at 32 sites throughout the Channel Islands National Park and San Nicolas Island

description: Hourly wave-height observations at 32 sites throughout the Channel Islands National Park and San Nicolas Island, site-specific hind casts from the Coastal Data Information Program (CDIP), and contemporary wave height, period, and direction from regional buoys taken during intervals between 2013 and 2017.
DOI: 10.5066/p91kh2q7
title: Hourly wave height and period hindcasts at 32 sites throughout the Channel Islands National Park and San Nicolas Island from 2000-2017

description: California's Coastal Data Information Program (CDIP) has a hind cast feature that allows one to model hourly height and period at known locations back to 2000. Fitting these hindcasts to observed height and periods indicates that the hindcasts have consistent biases that can be corrected for statistically. Past work generated bias corrections for 32 sites in the Channel Islands. We use these bias corrections to correct hourly height and period hindcasts at these sites from 2000 to 2017. Data columns include: year_utc, month_utc, day_utc, hour_utc, cdip_Hs_m, cdip_Tp_sec, cdip_Dp_degTrue, adjusted_cdip_Hs_m, mean_sensor_pressure_dbar, Transect_depth_m, ubr_Sensor, Tbr_sensor, wave_energy, date, juliand, season, wyr, waveyr, season_yr, Hs_corrected, Tp_corrected, ubr_corrected, Tbr_corrected, wave_energy_corrected.