cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive6791.20221219.7.1
title: Legionella micdadei Hébert et al. 1980

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6792.20220920.7
title: Legionella micdadei Hébert et al. 1980

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6792.20221219.7.1
title: Legionella micdadei Hébert et al. 1980

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6793.20220920.7
title: Legionella maceachernii Brenner et al. 1985

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6793.20221219.7.1
title: Legionella maceachernii Brenner et al. 1985

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6794.20220920.7
title: Leptonema illini Hovind-Hougen 1983

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6794.20221219.7.1
title: Leptonema illini Hovind-Hougen 1983

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6797.20220920.7
title: Leptospira inadai Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6797.20221219.7.1
title: Leptospira inadai Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6798.20220920.7
title: Leptospira meyeri Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6798.20221219.7.1
title: Leptospira meyeri Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.5513021
title: FaIR v1.6.2 calibrated and constrained parameter set

description: These .json files provides the 2237 ensemble members that are used to run the FaIR simple climate model in the IPCC's Sixth Assessment Report contributions to Working Group 1 and Working Group 3. v1.1 of this dataset includes two versions of the files: the original full parameter set `fair-1.6.2-wg3-params.json` as in v1.0 reduced file size versions `fair-1.6.2-wg3-params-slim.json` and `fair-1.6.2-wg3-params-common.json` where only the parameters that vary between ensemble members are included in the former and everything else is in the latter. This is optimised for running the Working Group 3 climate assessment. Drawn from an initial prior ensemble of 1 million, the following constraints are placed upon the results: representation of observed warming from 1850-2019, within observational uncertainty representation of observed ocean heat content change 1971-2018, within observational uncertainty reproduction of near-present day atmospheric concentrations of CO2 from the carbon cycle airborne fraction of CO2 with a distribution similar to the assessed range of Chapter 5, IPCC Working Group 1 AR6 equilibrium climate sensitivity with a similar distribution to Chapter 7, IPCC Working Group 1, AR6 transient climate response with a similar distribution to Chapter 7, IPCC Working Group 1, AR6 projected future warming that is of a similar distribution to the SSP scenarios of Chapter 4, IPCC Working Group 1, AR6, when run with prescribed concentrations <strong>Changelog</strong> v1.1: inclusion of lightweight parameter sets. v1.0: original upload full parameter sets.
DOI: 10.5281/zenodo.6390768
title: Infiller database for silicone: IPCC AR6 WGIII version

description: <strong>Download and license information</strong> The data is available for download at the AR6 Scenario Explorer. Details about the be found in the license section of the AR6 Scenario Explorer . <strong>About the data set</strong> To fill in emissions not reported for scenarios in their submission to the database, we use a large set of harmonized AR6 global emissions pathways for inferring pathways based on the relationships between concurrent species development over time observed in the larger set. Infilling ensures that all relevant anthropogenic emissions are included in each climate run for each scenario. This makes the climate assessment of alternative scenarios more comparable and reduces the risk of a biased climate assessment, because not all climatically active emission species are reported by all IAMs. The infilling methods used are from an open-source Python software package called ‘silicone’ (Lamboll et al. 2020) This file is the harmonized emissions database that was used as "infiller database" for the IPCC AR6 WGIII report on the Mitigation of Climate Change, using data from the chapter on <em>Mitigation Pathways Compatible with Long-Term Goals </em>(Riahi and Schaeffer et al. 2022)<em> </em>as available in the AR6 Scenarios Database (Byers et al. 2022). <strong>References</strong> Edward Byers, Volker Krey, Elmar Kriegler, Keywan Riahi, Roberto Schaeffer, Jarmo Kikstra, Robin Lamboll, Zebedee Nicholls, Marit Sanstad, Chris Smith, Kaj-Ivar van der Wijst, Franck Lecocq, Joana Portugal-Pereira, Yamina Saheb, Anders Strømann, Harald Winkler, Cornelia Auer, Elina Brutschin, Claire Lepault, Eduardo Müller-Casseres, Matthew Gidden, Daniel Huppmann, Peter Kolp, Giacomo Marangoni, Michaela Werning, Katherine Calvin, Celine Guivarch, Tomoko Hasegawa, Glen Peters, Julia Steinberger, Massimo Tavoni, Detlef von Vuuren, Piers Forster, Jared Lewis, Malte Meinshausen, Joeri Rogelj, Bjorn Samset, Ragnhild Skeie, Alaa Al Khourdajie.<br> <em>AR6 Scenarios Database hosted by IIASA</em><br> International Institute for Applied Systems Analysis, 2022.<br> doi: 10.5281/zenodo.5886912 | url: data.ene.iiasa.ac.at/ar6/ Keywan Riahi, Roberto Schaeffer, et al.<br> <em>Mitigation Pathways Compatible with Long-Term Goals</em>, in "Mitigation of Climate Change".<br> Intergovernmental Panel on Climate Change, Geneva, 2022.<br> url: Sixth Assessment Report Working Group III Lamboll, R.D., Nicholls, Z.R., Kikstra, J.S., Meinshausen, M. and<br> Rogelj, J., 2020. Silicone v1. 0.0: an open-source Python package for<br> inferring missing emissions data for climate change research. <em>Geoscientific Model Development</em>, <em>13</em>(11), pp.5259-5275.
description: J.S.K. was supported by the Natural Environment Research Council under grant agreement NE/S007415/1.
DOI: 10.13145/bacdive6799.20220920.7
title: Leptospira meyeri Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6799.20221219.7.1
title: Leptospira meyeri Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.17196/novac.telica.001
title: SO2 flux of TELICA volcano, from the NOVAC data-base

description: This data-set presents volcanic gas emission data from NOVAC, the global Network for Observation of Volcanic and Atmospheric Change. For each volcano, data from one or several NOVAC Scanning mini-DOAS instruments are combined with meteorological information to derive daily statistics of total SO2 emission from the volcano. Different versions of the data exist, depending on the algorithms and meteorological information used in the evaluations. Data is kindly made publicly available by the volcanological observatories and institutions responsible for data collection and evaluation, on the condition that credit is given according to the NOVAC Data Use Agreement.
DOI: 10.18462/iir.gl2022.0261
title: CO2 heat pump/chiller system for a hotel in a tropical climate: a numerical investigation.
DOI: 10.6084/m9.figshare.12720989
title: Data.zip

description: This comprehensive data set contains China's anthropogenic methane emissions from 13 inventories that are used in a paper published in ESSD (https://doi.org/10.5194/essd-2020-210). It includes one Excel file that includes annual total and sectoral emissions (in unit of Tg CH4 per year), and 28 TIF files for total and sectoral gridded emissions (in unit of g CH4 per square meters per year).
DOI: 10.13145/bacdive6800.20220920.7
title: Leptospira noguchii Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.18434/t42p4c
title: Ground Levels and Ionization Energies for the Neutral Atoms, NIST Standard Reference Database 111
DOI: 10.35090/gatech/65537
title: Meridional Overturning Circulation Observed by the OSNAP (Overturning in the Subpolar North Atlantic Program) Array from August 2014 to May 2018 - Corrected Data
DOI: 10.3886/e182865v1
title: ECIN Replication Package for "Let There Be Light: Daylight Saving Time and Road Traffic Collisions"

description: This is the data and code for "Let There Be Light: Daylight Saving Time and Road Traffic Collisions".This paper examines the impact of Daylight Saving Time (DST) on fatal road crashes in Australia. I exploit within year transitions to and from DST in a regression discontinuity in time framework. To examine the long run effect of the policy, I use trials of DST implemented in various states, and a DST extension due to the Sydney Olympics. Neither the transition to or out of DST, nor the long run effects of DST have an impact on fatalities on the road. However, there is evidence of reallocation of accidents over the day due to ambient light.<br><br>
DOI: 10.4121/13562270.v2
title: Meteorological forcing, and corresponding hydrological model input and output used in the paper: The impact of hydrological model structure on the simulation of extreme runoff events.

description: The datasets used in Van Kempen et al., 2021 are included in this repository. These files consist of the original meteorological forcing, hydrological model input and hydrological model output.<br>The README provides a description of the set-up of these datasets.
DOI: 10.5066/p90rbjxs
title: Data used to model and map arsenic concentration exceedances in private wells throughout the conterminous United States for human health studies

description: This data release contains data used to develop models and maps that estimate the probabilities of exceeding various thresholds of arsenic concentrations in private domestic wells throughout the conterminous United States. Three boosted regression tree (BRT) models were developed separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, and 10 micrograms per liter (?g/L). A random forest (RF) model was developed to estimate the most probable arsenic concentration category (&amp;#8804;5, &gt;5 to &amp;#8804;10, or &gt;10 ?g/L). The models use arsenic concentration data from private domestic wells located throughout the conterminous United States and independent variables that are available as geospatial data. The models were used to produce maps that are included in this data release. The model input data (predictor variables) that were used to make the maps are within a zipped folder (Map_Input_Data.zip) that contains 85 tif-raster files, one for each model predictor variable. The map probability estimates that are outputs from the model are in a zipped folder (Map_Output_Data.zip) that contains 13 tif-raster files, one model estimate map for each of the BRT models and four for the RF model, as well as 2 confidence interval maps for each BRT model.
DOI: 10.5066/p9j35lmq
title: Hawaiian Islands datasets quantifying the effects of invasive animals and plants on native forests across the archipelago 2019

description: Dataset includes publicly available geologic and rainfall data, and environmental and ecological data derived or collected for this project. Specifically, water infiltration measurements, interpreted field-saturated hydraulic conductivity values, ungulate activity, vegetation cover, general soil and weather conditions data are included. Soil samples were collected, lab analyzed, and are included in the dataset. Field-collected data are associated with plots that encompassed approximately a 3 x 3 m area; site data represent approximately 20 x 20 m.
DOI: 10.5066/p9muwdfn
title: Debris-flow monitoring data, Chalk Cliffs, Colorado, USA, 2014

description: This data release includes 2014 time-series data from three debris-flow monitoring stations at Chalk Cliffs in Chaffee County, Colorado, USA. The data were collected to help identify the triggering conditions, magnitude, and mobility of debris flows at the site. The three stations are located sequentially along a channel draining the 0.3 km^2 study area. The Upper, Middle, and Lower stations have respective drainage areas of 0.06, 0.16, and 0.24 km^2. The location (UTM zone 13) of each station is: 396826E/4287851N (Upper), 396893E/ 4287815N (Middle), and 396929E/4287712N (Lower). See also "ChalkStationLocations.jpg" in the README.zip file. The 2014 data includes three types of time series: (1) 1-minute time series of rainfall recorded by tipping bucket rain gages at each station, (2) 10-Hz time series of flow stage recorded by laser distance meters at each station, and (3) 333-Hz time series of ground vibrations and basal normal force at the Upper station only. Ground vibrations were recorded by two 4.5 Hz triaxial geophones separated by 18 m along the channel. Basal normal force was recorded by a 232 cm^2 force plate installed in the bedrock channel bed directly beneath the laser distance meter. The 10-Hz stage data is collected only when it is raining due to data storage limitations. Similarly, the 333-Hz ground motion and force data are provided only during significant flow events. These events occurred on 4 July 2014, 31 July 2014, 1 August 2014, 4 August 2014, and 6 August 2014. The first three events are primarily debris flows and the last two events are debris floods. Note that the rain gage at the Lower station, which is partially shielded by a near-vertical cliff, is used primarily as a trigger for sampling 10-Hz stage data rather than providing an accurate representation of rainfall at the station. Details of the sensors and photos of each station are contained in the "README.zip" file. The file also contains formulas for (1) converting the distance between the laser and the flow surface (or stationary bed surface) to stage above the datum for each station, and (2) converting the raw voltage readings from the geophones and force plate transducer into engineering units of ground velocity and normal force, respectively. Additional details of the study are provided in the journal articles: McCoy, S. W., J. W. Kean, J. A. Coe, G. E. Tucker, D. M. Staley, and T. A. Wasklewicz (2012), Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment, J. Geophys. Res., 117, F03016, doi:10.1029/2011JF002278. Kean, J. W., J. A. Coe, V. Coviello, J. B. Smith, S. W. McCoy, and M. Arattano (2015), Estimating rates of debris flow entrainment from ground vibrations, Geophys. Res. Lett., 42, doi:10.1002/2015GL064811.
DOI: 10.5281/zenodo.6761727
title: Supplementary data: "Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI"

description: This repository contains processed data and result files for the paper Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI. The code for producing the processed data and the results is available at github. <strong>Data</strong> The data folder contains the feature and target data used to train the ML model: stability_input: A Folder containing training and test sets for the stability model for each area. flow_input: A Folder containing training and test sets for the flow model for each link. <em>raw_input_data.h5</em><strong> </strong>:<strong> </strong>The aggregated external features without additional engineered features. <em>input_forecast.h5 </em>and<em> input_actual.h5: </em>The day-ahead available (forecast) and ex-post available (actual) data of external features including the engineered features. <em>indicators.h5 </em>: The grid frequency stability indicators. <em>documentation_of_data_download</em>: Information files concerning the ENTSO-E raw data and its aggregation. HVDClinks: A Folder containing preprocessed time series for scheduled and unscheduled HVDC flows <strong>Data sources</strong> Most of the data is derived from ENTSO-E Transparency Platform data [1]. The grid stability indicators (indicators<em>.h5</em>) are based on publicly available data from the German Transmission System Operators (TSOs) [2]. <strong>Results</strong> The stability_results and the flow_results folder contain the results of hyperparameter optimization, model prediction and interpretation via SHAP for the respective models. <em>cv_results_gtb_full.csv</em> : Performance results for each combination in the hyperparameter optimization. <em>cv_best_params_gtb_full.csv</em> : Hyperparameters used in the final (optimized) model. <em>shap_values_gtb_full.npy</em> : First-order SHAP values calculated on different data sets: The train set, the randomized test set and the continuous test set. <em>y_pred.h5/y_pred_links.h5</em> : Predictions of daily profile predictor and Machine Learning models. <strong>Disclaimer</strong> The data might be subject to copyright or related rights. Please consult the primary data owner.
description: {"references": ["[1] ENTSO-E Transparency Platform. https://transparency.entsoe.eu/", "[2] 50Hertz Transmission GmbH, Amprion GmbH, TransnetBW GmbH and TenneT TSO GmbH, \"Regelleistung.Net\", https://www.regelleistung.net/ext/"]}
DOI: 10.5281/zenodo.7379397
title: Supplementary IGV data for Human Embryonic RNA Editome

description: Supplementary IGV data for Human Embryonic RNA Editome
DOI: 10.13145/bacdive6800.20221219.7.1
title: Leptospira noguchii Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6801.20220920.7
title: Leptospira santarosai Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6801.20221219.7.1
title: Leptospira santarosai Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6802.20220920.7
title: Leptospira weilii Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6802.20221219.7.1
title: Leptospira weilii Yasuda et al. 1987

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6803.20220920.7
title: Leptospira kirschneri Ramadass et al. 1992

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6803.20221219.7.1
title: Leptospira kirschneri Ramadass et al. 1992

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6804.20220920.7
title: Leptospira fainei Perolat et al. 1998

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6804.20221219.7.1
title: Leptospira fainei Perolat et al. 1998

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6805.20220920.7
title: Leptospira alexanderi Brenner et al. 1999

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6805.20221219.7.1
title: Leptospira alexanderi Brenner et al. 1999

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6806.20220920.7
title: Leptospira broomii Levett et al. 2006

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6806.20221219.7.1
title: Leptospira broomii Levett et al. 2006

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6807.20220920.7
title: Leptospira terpstrae Smythe et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6807.20221219.7.1
title: Leptospira terpstrae Smythe et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6808.20220920.7
title: Leptospira yanagawae Smythe et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6808.20221219.7.1
title: Leptospira yanagawae Smythe et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6809.20220920.7
title: Turneriella parva (Hovind-Hougen et al. 1982) Levett et al. 2005

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.