cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/k57gbw78d9.1
title: Preservation of Organic Carbon in Dolomitized Cambrian Stromatolites and Implications for Microbial Biosignatures in Diagenetically Replaced Carbonate Rock: Supplementary Materials

description: ****Please view the README.txt file for more detailed documentation of data.**** Contact information: Ashley E. Murphy Rutgers University Newark, New Jersey, U.S.A. ashley.murphy@rutgers.edu Dates of data collection: 2017/02 - 2020/01 Geographic location: New Jersey, U.S.A. Funding sources: NASA ASTEP; NASA NAI ENIGMA – Rutgers University. License: CC BY 4.0CC BY 4.0 This directory contains the following supplementary materials: Murphyetal2020_Allentown_SuppMaterials.xlsx: supplement of text and additional figures and tables Table S1: Inductively Coupled Plasma - Optical Emission Spectrometry (ICP-OES) carbonate geochemistry results table Table S2: Electronprobe Microanalysis (EPMA) dolomite spot analyses elemental results Table S3: Carbonate and organic carbon isotopic data and total organic carbon results Table S4a: Raman data from Cluster method including geothermometry Table S4b: Raman data from Gaussian method including geothermometry Figure S1: XRD results in a waterfall plot Figure S2: SEM/EDS results for minor mineral phases Figure S3a: D and G peaks from cluster analysis corresponding to Table S4a Figure S3b: D and G peaks from Gaussian analysis corresponding to Table S4b Figure S4: Raman t-Test results of D and G band variations
DOI: 10.21227/k7za-4s69
title: ExoNet Database: Wearable Camera Images of Human Locomotion Environments

description: Abstract: Recent advances in computer vision and artificial intelligence have allowed researchers to develop environment recognition systems for robotic lower-limb exoskeletons and prostheses. However, small-scale and private training datasets have impeded the widespread development and dissemination of image classification algorithms for human locomotion environment recognition, respectively. To address these shortcomings, we developed “ExoNet” - the first open-source, large-scale hierarchical database of high-resolution wearable camera images of human locomotion environments. Unparalleled in scale and diversity, ExoNet comprises over 5.6 million images of different indoor and outdoor real-world walking environments, which were collected using a lightweight wearable smartphone camera system throughout the summer, fall, and winter seasons. Approximately 940,000 images in ExoNet were human-annotated using a 12-class hierarchical labelling architecture. Available publicly through the IEEE DataPort repository, ExoNet offers an unprecedented community-based platform for training, developing, and comparing next-generation image classification algorithms for human locomotion environment recognition. Beyond the predictive control of lower-limb exoskeletons and prostheses, applications of ExoNet extend to humanoid and autonomous legged robotics.Reference: Laschowski B, McNally W, Wong A, and McPhee J. (2020). ExoNet Database: Wearable Camera Images of Human Locomotion Environments. Under Review.
DOI: 10.3886/e115282
title: Data and Code for: "Why Special Economic Zones? Using Trade Policy to Discriminate Across Importers"

description: Tariffs are generally assumed to depend on the product, not the identity of the importer. However, special economic zones are a common, economically important policy used worldwide to lower tariffs on selected goods for selected manufacturers. I show this is motivated by policymakers' desire to discriminate across buyers when a tax is intended to raise prices for sellers, through a mechanism distinct from existing theories of optimal taxation. Using a new dataset compiled from public records and exogenous changes in imports of intermediate goods, I find the form, composition, and size of U.S. zones are consistent with the theory.<br><br>
DOI: 10.3886/e115282v1
title: Data and Code for: "Why Special Economic Zones? Using Trade Policy to Discriminate Across Importers"

description: Tariffs are generally assumed to depend on the product, not the identity of the importer. However, special economic zones are a common, economically important policy used worldwide to lower tariffs on selected goods for selected manufacturers. I show this is motivated by policymakers' desire to discriminate across buyers when a tax is intended to raise prices for sellers, through a mechanism distinct from existing theories of optimal taxation. Using a new dataset compiled from public records and exogenous changes in imports of intermediate goods, I find the form, composition, and size of U.S. zones are consistent with the theory.<br><br>
DOI: 10.5281/zenodo.3765260
title: High resolution WRF simulation of Hurricane Sandy (2012) wind during landfall

description: A 96-hour high-resolution simulation of Hurricane Sandy was conducted using the Advanced Research version 3.3.1 of the Weather Research and Forecasting (WRF) model initialized at 1200 UTC 26 October 2012 (Johnsen et al., 2013) and using a horizontal resolution of 500 m. Domain size was 2,660x2,500 km with 150 vertical layers. The Yonsei University planetary boundary layer (PBL) scheme, the Noah land model, and the MM5 Monin-Obukhov similarity theory surface layer model were used. Cloud physics was modeled using WSM6 6-class microphysics with graupel. Convection parameterization was not used for this high-spatial-resolution simulation. National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analyses were used for initialization and boundary conditions, with the latter updated every 6 hours. Data herein is a landfall-regime subset (Schiavone et al., 2016) of the full simulation. The spatial domain is 500x500 km containing the 50 lowest layers, with a time domain that spans the 12-hour period beginning at1200 UTC 29 October 2012 and with 3-hour time steps. Format is NetCDF containing detailed metadata. Three-dimensional meteorological field variables include the 3 wind components, potential temperature, water vapor mixing ratio, geopotential, and atmospheric pressure. Two-dimensional variables include horizontal wind components at 10 m AGL, potential temperature and water vapor mixing ratio at 2 m AGL, atmospheric pressure at the surface, terrain height, and the Coriolis sine latitude term, which is required to calculate potential vorticity. These WRF simulation data were used, along with WSR-88D Doppler radar data and surface wind observations, to demonstrate that roll vortices occurred in the atmospheric boundary layer over the landfall region during Hurricane Sandy's landfall period (Schiavone et al., 2020).
description: {"references": ["Johnsen, P., M. Straka, M. Shapiro, A. Norton, and T. Galarneau, 2013: Petascale WRF Simulation of Hurricane Sandy: Deployment of NCSA's Cray XE6 Blue Waters. SC13, International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, USA \u2014 November 17-21, 2013.", "Schiavone, J. A., P. Johnsen, D. A. Robinson, M. Gerbush, and A. Norton, 2016: Mesoscale comparison of simulated and observed winds during Sandy's landfall on New Jersey. WRF Users' Workshop, Boulder, CO USA. June 28, 2016.", "Schiavone, J. A., K. Gao, D. A. Robinson, P. J. Johnsen, and M. R. Gerbush, 2020: Large Roll Vortices Exhibited by Post-tropical Cyclone Sandy During Landfall. (Full citation to be provided upon publication)."]}
DOI: 10.5281/zenodo.3765261
title: High resolution WRF simulation of Hurricane Sandy (2012) wind during landfall

description: A 96-hour high-resolution simulation of Hurricane Sandy was conducted using the Advanced Research version 3.3.1 of the Weather Research and Forecasting (WRF) model initialized at 1200 UTC 26 October 2012 (Johnsen et al., 2013) and using a horizontal resolution of 500 m. Domain size was 2,660x2,500 km with 150 vertical layers. The Yonsei University planetary boundary layer (PBL) scheme, the Noah land model, and the MM5 Monin-Obukhov similarity theory surface layer model were used. Cloud physics was modeled using WSM6 6-class microphysics with graupel. Convection parameterization was not used for this high-spatial-resolution simulation. National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analyses were used for initialization and boundary conditions, with the latter updated every 6 hours. Data herein is a landfall-regime subset (Schiavone et al., 2016) of the full simulation. The spatial domain is 500x500 km containing the 50 lowest layers, with a time domain that spans the 12-hour period beginning at1200 UTC 29 October 2012 and with 3-hour time steps. Format is NetCDF containing detailed metadata. Three-dimensional meteorological field variables include the 3 wind components, potential temperature, water vapor mixing ratio, geopotential, and atmospheric pressure. Two-dimensional variables include horizontal wind components at 10 m AGL, potential temperature and water vapor mixing ratio at 2 m AGL, atmospheric pressure at the surface, terrain height, and the Coriolis sine latitude term, which is required to calculate potential vorticity. These WRF simulation data were used, along with WSR-88D Doppler radar data and surface wind observations, to demonstrate that roll vortices occurred in the atmospheric boundary layer over the landfall region during Hurricane Sandy's landfall period (Schiavone et al., 2020).
description: {"references": ["Johnsen, P., M. Straka, M. Shapiro, A. Norton, and T. Galarneau, 2013: Petascale WRF Simulation of Hurricane Sandy: Deployment of NCSA's Cray XE6 Blue Waters. SC13, International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, USA \u2014 November 17-21, 2013.", "Schiavone, J. A., P. Johnsen, D. A. Robinson, M. Gerbush, and A. Norton, 2016: Mesoscale comparison of simulated and observed winds during Sandy's landfall on New Jersey. WRF Users' Workshop, Boulder, CO USA. June 28, 2016.", "Schiavone, J. A., K. Gao, D. A. Robinson, P. J. Johnsen, and M. R. Gerbush, 2020: Large Roll Vortices Exhibited by Post-tropical Cyclone Sandy During Landfall. (Full citation to be provided upon publication)."]}
DOI: 10.5281/zenodo.3765398
title: Linked COVID-19 Data: Johns Hopkins University (JHU) and European Centre for Disease Prevention and Control (ECDC)

description: Linked COVID-19 Data derived from <strong>Johns Hopkins University</strong> and <strong>European Centre for Disease Prevention and Control</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828 developed for the Linked COVID-19 Data Dashboard: http://covid19data.link This files include data for covid19.ttl - COVID-19 data collected by the JHU and ECDC This RDF files are based on https://pomber.github.io/covid19/timeseries.json https://opendata.ecdc.europa.eu/covid19/casedistribution/json/
DOI: 10.15161/oar.it/23608
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.3886/e111185
title: Optimal climate policy when damages are unknown

description: Integrated assessment models (IAMs) are economists' primary tool for analyzing the optimal carbon tax. Damage functions, which link temperature to economic impacts, have come under fire because of their assumptions that may be incorrect in significant, but a priori unknowable ways. Here I develop recursive IAM frameworks to model uncertainty, learning, and concern for misspecification about damages. I decompose the carbon tax into channels capturing state uncertainty, insurance motives, and precautionary saving. Damage learning improves ex ante welfare by $750 billion. If damage functions are misspecified and omit the potential for catastrophic damages, robust control may be beneficial ex post.
DOI: 10.5281/zenodo.3766701
title: Linked COVID-19 Data: Johns Hopkins University (JHU) and European Centre for Disease Prevention and Control (ECDC)

description: Linked COVID-19 Data derived from <strong>Johns Hopkins University</strong> and <strong>European Centre for Disease Prevention and Control</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828 developed for the Linked COVID-19 Data Dashboard: http://covid19data.link This files include data for covid19.ttl - COVID-19 data collected by the JHU and ECDC This RDF files are based on https://pomber.github.io/covid19/timeseries.json https://opendata.ecdc.europa.eu/covid19/casedistribution/json/
DOI: 10.26300/ks4j-dg34
title: Data from "Dehydration Reaction Weakening of Antigorite Driven by Feedback Between Fault Slip and Compliance"
DOI: 10.5281/zenodo.3766170
title: Early Medieval handwriting data

description: The data consists of metadata and handwriting metrics produced by Script Analyzer for a sample of 20 Early Medieval Latin charters. The data set is related to an upcoming publication.
DOI: 10.5281/zenodo.3766171
title: Early Medieval handwriting data

description: The data consists of metadata and handwriting metrics produced by Script Analyzer for a sample of 20 Early Medieval Latin charters. The data set is related to an upcoming publication.
DOI: 10.5281/zenodo.3766168
title: Dataset for Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice

description: The dataset consists of (1) Benchmark files<br> (2) the logfile (outputs) generated by ApproxMC4 and ApproxMC5 respectively (3) A summary of the results for the files where at least one of ApproxMC4 or ApproxMC5 did not time out and took more than 1 second. The corresponding paper titled "Scalable Approximate Model Counting via Concentrated Hashing]{Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice" will appear in the Proceedings of Logic in Computer science(LICS), 2020.
DOI: 10.5281/zenodo.3766704
title: Linked COVID-19 Data: Robert Koch-Institut (RKI)

description: Linked COVID-19 Data derived from <strong>Robert Koch Institute</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828 developed for the Linked COVID-19 Data Dashboard: http://covid19data.link This files include data for covid19_rki*.ttl - single COVID-19 cases per day, collected by the RKI https://www.arcgis.com/home/item.html?id=dd4580c810204019a7b8eb3e0b329dd6 "confirmed" is calcaulated by the column "Refdatum" covid19_rki_ger.ttl - COVID-19 cases per day for Germany, collected by the RKI covid19_rki_ger_cum.ttl - COVID-19 cases accumulated per day for Germany, collected by the RKI covid19_rki_fs.ttl - COVID-19 cases per day for the federal states in Germany, collected by the RKI covid19_rki_fs_cum.ttl - COVID-19 cases accumulated per day for the federal states in Germany, collected by the RKI This RDF files are based on the NPGEO Corona Hub 2020 https://opendata.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0.geojson https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0/data
DOI: 10.5281/zenodo.3766167
title: Dataset for Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice

description: The dataset consists of (1) Benchmark files<br> (2) the logfile (outputs) generated by ApproxMC4 and ApproxMC5 respectively (3) A summary of the results for the files where at least one of ApproxMC4 or ApproxMC5 did not time out and took more than 1 second. The corresponding paper titled "Scalable Approximate Model Counting via Concentrated Hashing]{Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice" will appear in the Proceedings of Logic in Computer science(LICS), 2020.
DOI: 10.21227/5dhc-0f84
title: Gender Recognition from Voice

description: Each voice sample is stored as a .WAV file, which is then pre-processed for acoustic analysis using the specan function from theWarbleRR package. Specan measures 22 acoustic parameters on acoustic signals for which the start and end times are provided.The output from the pre-processed WAV files were saved into a CSV file, containing 3168 rows and 21 columns (20 columns for each feature and one label column for the classification of male or female).ACOUSTIC PROPERTIES MEASUREDThe following acoustic properties of each voice are measured:duration: length of signalmeanfreq: mean frequency (in kHz)sd: standard deviation of frequencymedian: median frequency (in kHz)Q25: first quantile (in kHz)Q75: third quantile (in kHz)IQR: interquantile range (in kHz)skew: skewness (see note in specprop description)kurt: kurtosis (see note in specprop description)sp.ent: spectral entropysfm: spectral flatnessmode: mode frequencycentroid: frequency centroid (see specprop)peakf: peak frequency (frequency with highest energy)meanfun: average of fundamental frequency measured across acoustic signalminfun: minimum fundamental frequency measured across acoustic signalmaxfun: maximum fundamental frequency measured across acoustic signalmeandom: average of dominant frequency measured across acoustic signalmindom: minimum of dominant frequency measured across acoustic signalmaxdom: maximum of dominant frequency measured across acoustic signaldfrange: range of dominant frequency measured across acoustic signalmodindx: modulation index. Calculated as the accumulated absolute difference between adjacent measurements of fundamental frequencies divided by the frequency rangeNote, the features for duration and peak frequency (peakf) were removed from training. Duration refers to the length of the recording, which for training, is cut off at 20 seconds. Peakf was omitted from calculation due to time and CPU constraints in calculating the value. In this case, all records will have the same value for duration (20) and peak frequency (0).
DOI: 10.21227/v62v-g267
title: Gender Recognition from Voice

description: Each voice sample is stored as a .WAV file, which is then pre-processed for acoustic analysis using the specan function from theWarbleRR package. Specan measures 22 acoustic parameters on acoustic signals for which the start and end times are provided.The output from the pre-processed WAV files were saved into a CSV file, containing 3168 rows and 21 columns (20 columns for each feature and one label column for the classification of male or female).ACOUSTIC PROPERTIES MEASUREDThe following acoustic properties of each voice are measured:duration: length of signalmeanfreq: mean frequency (in kHz)sd: standard deviation of frequencymedian: median frequency (in kHz)Q25: first quantile (in kHz)Q75: third quantile (in kHz)IQR: interquantile range (in kHz)skew: skewness (see note in specprop description)kurt: kurtosis (see note in specprop description)sp.ent: spectral entropysfm: spectral flatnessmode: mode frequencycentroid: frequency centroid (see specprop)peakf: peak frequency (frequency with highest energy)meanfun: average of fundamental frequency measured across acoustic signalminfun: minimum fundamental frequency measured across acoustic signalmaxfun: maximum fundamental frequency measured across acoustic signalmeandom: average of dominant frequency measured across acoustic signalmindom: minimum of dominant frequency measured across acoustic signalmaxdom: maximum of dominant frequency measured across acoustic signaldfrange: range of dominant frequency measured across acoustic signalmodindx: modulation index. Calculated as the accumulated absolute difference between adjacent measurements of fundamental frequencies divided by the frequency rangeNote, the features for duration and peak frequency (peakf) were removed from training. Duration refers to the length of the recording, which for training, is cut off at 20 seconds. Peakf was omitted from calculation due to time and CPU constraints in calculating the value. In this case, all records will have the same value for duration (20) and peak frequency (0).
DOI: 10.5281/zenodo.3766698
title: JGR-Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China during the Meiyu Seasons

description: The dataset for the JGR article "Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China during the Meiyu Seasons"
DOI: 10.5281/zenodo.3766699
title: JGR-Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China during the Meiyu Seasons

description: The dataset for the JGR article "Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China during the Meiyu Seasons"
DOI: 10.5281/zenodo.3766198
title: Linked COVID-19 Data: Johns Hopkins University (JHU) and European Centre for Disease Prevention and Control (ECDC)

description: Linked COVID-19 Data derived from <strong>Johns Hopkins University</strong> and <strong>European Centre for Disease Prevention and Control</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828 developed for the Linked COVID-19 Data Dashboard: http://covid19data.link This files include data for covid19.ttl - COVID-19 data collected by the JHU and ECDC This RDF files are based on https://pomber.github.io/covid19/timeseries.json https://opendata.ecdc.europa.eu/covid19/casedistribution/json/
DOI: 10.5281/zenodo.3766656
title: Description of full chain Techno-Economic Sustainability Assessment (TESA) methodology

description: The dataset provides a preliminary description for techno-economic sustainability principles and criteria in relation to SAT-ProBio blueprint.
DOI: 10.5281/zenodo.3766661
title: Deliverable [D4.1] Techno-economic sustainability analysis methodology on resources for bio-based products, conversion routes and end-of-life alternative valorisation options

description: Techno-economic sustainability analysis (TESA) is a methodology framework to evaluate the performance of a process under technical and economic perspective. A process can be divided into three main sections, the resources required for bio-based products, the conversion routes for the production and finally, the end-of-life alternative valorisation options. Consequently, TESA is carried out separately in the three sections and evaluates the likelihood of their different technology scales and applications and their economic feasibility.
DOI: 10.5281/zenodo.3766662
title: Deliverable [D4.1] Techno-economic sustainability analysis methodology on resources for bio-based products, conversion routes and end-of-life alternative valorisation options

description: Techno-economic sustainability analysis (TESA) is a methodology framework to evaluate the performance of a process under technical and economic perspective. A process can be divided into three main sections, the resources required for bio-based products, the conversion routes for the production and finally, the end-of-life alternative valorisation options. Consequently, TESA is carried out separately in the three sections and evaluates the likelihood of their different technology scales and applications and their economic feasibility.