cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7183240
title: Plant Terpenoid Permeability through Biological Membranes Explored via Molecular Simulations

description: Input structures for a manuscript, along with selected output data and structures. This directory structure contains a cut-down copy of the directories used to generate the simulation data and the analysis. In order to make this fit into the 50GB Zenodo limit, it was constructed with the following tar command: tar -zcvf terpenoidpermeability.tar.gz --exclude="*BAK" --exclude="*#" --exclude="*log" --exclude="*xsc" --exclude="*coor" --exclude="*vel" --exclude="*[0-9].out" --exclude="*old" --exclude="*dcd" --exclude="*tmp" --exclude="*ppm" --exclude="*png" --exclude="*pdf" --exclude="*catchy*" --exclude="*svg" --exclude="*restart*" --exclude="*history" --exclude="core.*" --exclude="FFTW_NAMD*" --exclude="*avi" --exclude="*mp4" Terpenoid-Permeability, which intentionally excludes large files. The full dataset that includes trajectories is available upon request. The data is split into two directories initially "<strong>build</strong>" and "<strong>Simulations</strong>" "<strong>build</strong>" directory is the part where initial system for unbiased and biased simulation were build using "<strong>resolvate.tcl</strong>" and "<strong>smd-single-build-system.tcl</strong>" respectively. "<strong>Simulations</strong>" directory has the different namd files for running unbiased simulation, steered molecular dynamics and replica exchange umbrella sampling. The folder structure was generated using "<strong>gendirs*.py</strong>".<br> The unbiased simulations were run using "<strong>run.namd</strong>".<br> Steered molecular dynamics namd files were with name "<strong>step*.namd</strong>" and colvars configuration file are named "<strong>step*.conf</strong>".<br> <br> Replica exchange moleuclar dynamics (REUS) system was generated using "<strong>buildreplicas.tcl</strong>".<br> Replica windows size and force constant were written into a namd configuration file using "<strong>reus-genscript.py</strong>".<br> REUS general configuration file containing the parameters and forcefield is named as "<strong>base.namd</strong>".<br> Colvars for REUS are in "<strong>replicadistZcolvars.conf</strong>".<br> Umbrella sampling is performed with "<strong>umbrella.namd</strong>".
DOI: 10.5281/zenodo.7351424
title: Supplementary Materials for 'Spatiotemporal Prediction of Air Quality Using Machine Learning Techniques'

description: This package includes supplementary materials used to implement air quality prediction in the city of Madrid. It consists of two main subdirectories: Data and Code. The Data directory contains Raw-Data (air quality, meteorological and traffic data from the period of January-June 2019 and January-June 2020, and the location of air quality and meteorological monitoring stations and traffic measurement points of the city of Madrid) and Processed-Data (the output after raws data has gone through the workflow to meet the requirements corresponding to the implementation of the proposed forecasting approaches). The Code directory contains Process Raw Data, Chapter4-ConvLSTM, Chapter5-BiConvLSTM, and Chapter6-A3T_GCN, which provides the procedure for constructing and implementing the proposed approaches.
DOI: 10.6084/m9.figshare.12233192
title: JGI PICRUSt2 genomes

description: A fasta file containing all available genomes from the JGI genome database that are used for the default PICRUSt2 reference database.
DOI: 10.6084/m9.figshare.14459535
title: Data and scripts in Huang et al. "Comparative genomic analysis reveals metabolic flexibility of Woesearchaeota"

description: This compressed file includes six folders:<br>1_single_protein_trees_of_orthologs:<br>Alignments and treefiles used in the "Selection of orthologs for phylogenetic analysis of Woesearchaeota".<br>2_phylogenetic_trees_Woese&Pace:<br>Alignments and treefiles of 152 MAGs for phylogenetic analysis based on 15 ribosomal proteins and the top-50% ranked orthologs<br>3_16S_rRNA_gene:<br>Alignments and treefiles used in the 16S rRNA gene phylogenetic analysis<br>4_individual_protein_trees:<br>Alignment and treefiles used in the phylogenetic analyses in fig.4, suppl. fig6-7, suppl. fig9-22 and suppl. fig24-41<br>5_protein_families_52_MAGs:<br>The file includes alignment and treefile of phylogenetic analysis of 52 MAGs, ALE reconciliation results and protein families files<br>6_scripts<br>Python scripts used in phylogenetic analysis and R scripts used in ecological analysis<br>7_protein_files<br>Proteins faa files and annotation files
DOI: 10.6084/m9.figshare.21786302.v1
title: Baseline Study Data - Risk Factors of COVID-19 Worsening

description: This is the baseline dataset for our study titled Risk Factors of COVID-19 Clinical Worsening: A Retrospective Cohort Study in COVID-19 Referral Hospital at West Java, Indonesia
DOI: 10.6084/m9.figshare.21937997
title: Data File 5.xlsx

description: Linear response range of axial spatial dispersion in holographic lens and corresponding slopes of curves as a function of temperatures.
DOI: 10.6084/m9.figshare.21957380.v1
title: Dataset 1

description: Data underlying the results presented in this paper.
DOI: 10.17632/zz9txhw89w.1
title: Seismicity dataset of Ghana obtained by Deep Learning

description: This data repository presents waveforms, earthquake bulletin, and supporting data for a set of detected earthquakes on the Ghana Digital Seismic Network (GHDSN), consisting of 6 broadband sensors deployed in southern Ghana from 2012 to 2014. 
The earthquakes and their corresponding P and S arrival phases were detected using the EQTransformer tool, a Deep Learning model for simultaneous earthquake detection and phase picking. 
The data set comprises waveforms of 73 detected local earthquakes and a bulletin of 559 arrival times (292 P and 267 S phases) in SEISAN format. 
Additionally, some preliminary results of processing this earthquake data are presented: 
1) An accurate, updated crustal velocity model for the region obtained by performing a joint inversion on the hypocentral parameters and Vp and Vp/Vs for a 6-layers model, 
2) 3D live figures graphically representing the hypocentral parameters of the detected earthquakes and active zones in this period, 
3) an occurrence time sequence for the detected events, and 4) some statistical information of the earthquakes detected. 
This dataset is essential as it provides researchers interested in further processing the waveform of the detected events to derive more detailed information about the mechanism of the seismogenic sources and active faults in the area.
DOI: 10.3886/e158401v1
title: Data and Code for: Market Access and Quality Upgrading: Evidence from Four Experiments

description: Smallholder farming in many developing countries is characterized by low productivity and low quality output. Low quality limits the price farmers can command and their potential income. We conduct a series of experiments among maize farmers in Uganda to shed light on the barriers to quality upgrading and to study its potential. First, we document that quality is low but partly observable. Second, we show that the causal return to quality is zero, suggesting that the market for quality maize is effectively missing. Third, we generate experimental variation in access to a market for premium quality maize, combined with training on agricultural best-practices, and document large increases in both farm productivity and income. Fourth, we show that agricultural training alone does not affect agricultural outcomes. Our findings reveal the importance of demand-side constraints in limiting rural income and productivity growth.
description: Smallholder households in Uganda.
DOI: 10.5281/zenodo.3702418
title: ENTSO-E PECD (European Climate Database) from MAF 2019 in CSV and Feather formats

description: ENTSO-E has published the PECD dataset with the Mid-term Adequacy Forecast (MAF) 2019: https://www.entsoe.eu/outlooks/midterm/#download The downloadable archive contains 3 large Microsoft Excel (~350 MB each). Each file contains the hourly data for all the considered weather years (1982-2016) for all the MAF regions (grouped in tabs). Here we provide the same data but in a more open and user-friendly format. <strong>Single files</strong> Data saved in CSV and Feather format (using R package feather 0.35). Each file contains the hourly data in a wide tabular format with area, day, month, hour and year (1982-2016). The files are: PECD-MAF2019-wide-PV.csv (and .feather) PECD-MAF2019-wide-WindOffshore.csv (and .feather) PECD-MAF2019-wide-WindOnshore.csv (and .feather) <strong>Split by year</strong> We provide here three archives each one containing a file per year. The files are: PECD-MAF2019-wide-PV.single_years.tar.bz2 PECD-MAF2019-wide-WindOffShore.single_years.tar.bz2 PECD-MAF2019-wide-WindOnshore.single_years.tar.bz2
description: {"references": ["https://www.entsoe.eu/outlooks/midterm/"]}
DOI: 10.5281/zenodo.5573260
title: Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: TF binding models built by JAMS (https://github.com/csglab/JAMS), ChIP-seq peak files (from ENCODE, Najafabadi et al. 2015, Schmitges et al. 2016, and Imbeault et al. 2017; called by MACS 1.4v), ChIP-seq pulldown and control tags from said peaks, input data for JAMS, and RCADE2 motifs for C2H2 zinc finger proteins.
description: {"references": ["Hernandez-Corchado, A., Najafabadi, H.S. Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding. Genome Biol 23, 151 (2022). https://doi.org/10.1186/s13059-022-02713-y"]}
DOI: 10.5281/zenodo.7125031
title: Data for Novel Approach to Quantify Sediment Transfer and Storage in Rivers with Feldspar Single-Grain pIRIR

description: Raw data of feldspar post infra-red infra-red (pIRIR) stimulated luminescence signal from modern sand from New Zealand rivers (Rakaia, six samples; Waimakariri, height samples) used in the paper Guyez et al. (2022) submitted to JGR: Earth Surface. The samples were collected in February 2020 by S. Bonnet and A. Guyez. They were measured in the Netherlands Center for Luminescence dating (Wageningen University and Research).
DOI: 10.17632/by4gbgr9gd.1
title: PCAWG Intra-Tumor Heterogeneity Simulations

description: This resource contains the simutated samples that go with the paper `Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes` which is available at the URL in the Related Links section below. Please find a full description of these data in the supplementary information of this paper, as well as the full author list and credit for creation of these data. Please find below a description of the included files. PhylogicNDT500: Note difference between directories marked with and without "_all". It is recommended to not use files in "_all" directories, as they contain mutations below the detection limit of 3 variant reads. * Copynumber: Segments/ directory - Subclonal copynumber is encoded via multiple reports of the same segment with a different CCF * Variants: VCF/ directory - These follow PCAWG consensus basic read count annotations * Purity/ploidy: PP_Table/ directory * Truth clusters: Subclonal_Structure/ directory * Truth assignments: Mut_Assign/ directory * Truth mutations: Mafs_Real_Info/ directory SimClone1000 - testing: * Copynumber: *_segments.txt in each sample directory - There is no subclonal copynumber * Variants: *.vcf - These follow PCAWG consensus basic read count annotations * Purity/ploidy: Included purity_ploidy.txt file SimClone1000 - truth: * Every simulation has its own directory tree. * Truth clusters (cluster position in CCF): [samplename]/simulated_0001/truth_tree/simulated_0001_subclonal_structure.txt * Truth assignments: [samplename]/simulated_0001/truth_tree/simulated_0001_mutation_assignments.txt * Truth mutations: [samplename]/simulated_0001/simulated_0001_0001/truth/simulated_0001_0001_multiplicity.txt
DOI: 10.17632/yg6jvvxpwm.1
title: Measured data to reproduce the results of the article "Modeling of the overcharge behavior of lithium-ion battery cells protected by a voltage-switchable resistive polymer layer"

description: poly[Ni(CH3OSalen)].txt contains data to reproduce resistance vs cell voltage dependence of the poly[Ni(CH3OSalen)] protective layer from the Figure 2(b) UocpPos.txt contains data to reproduce OCP curve of the positive LiFePO4 electrode from the Figure 3(a) OverchargePotential.txt contains data that were used to build overcharge potential curve of the positive LiFePO4 electrode from the Figure 3(b)
DOI: 10.5281/zenodo.4074290
title: June Lake Tephra Dataset

description: This dataset describes a sequence of tephra layers recovered from a Holocene sediment core taken at June Lake, California, USA. It includes tephra sediment stratigraphy, sample information, tephra layer thicknesses, tephra grain size data, volcanic glass geochemistry, Fe-Ti oxide geochemistry, SEM imagery, and method information. The tephra layers originate from the Mono-Inyo volcanic system. Most of this information is contained in a series of spreadsheets that follow tephra community recommended best practices. The listed files below follow the naming convention and format of Abbott et al. (2020) version 2.0, and they serve as worked examples of that format. See DOI: 10.5281/zenodo.3866266 for more information. June Lake Collection2b.xlsx (location information, sample information, stratigraphy) June Lake Sample_Processing.xlsx (sample preparation) June Lake Physical_analysis2b.xlsx (maximum grain size data, pumice class density) June Lake Physical_Microanalysis2.xlsx (SEM-EDS images, sample mount images) June Lake Geochemical_Analysis2.xlsx (EPMA method details) Glass and Fe-Ti oxide geochemistry by EPMA may be found in the following files: June Lake Glass DATA.xlsx June Lake Fe-Ti Oxides DATA.xlsx SEM and other images may be found in the following file: June Lake EPMA Images.zip
DOI: 10.17632/5jx3g3tt8w.1
title: Meteorological dataset of the Shiyang River Basin for 2019

description: This dataset contains regular meteorological elements for the surrounding area of Qingtu Lake within the Shiyang River Basin in 2019.
DOI: 10.7924/r4s75hv98
title: Data and scripts from: Localized orbital scaling correction for periodic systems

description: Density functional theory offers accurate structure prediction at acceptable computational cost, but commonly used approximations suffer from delocalization error; this results in inaccurate predictions of quantities such as energy band gaps of finite and bulk systems, energy level alignments, and electron distributions at interfaces. The localized orbital scaling correction (LOSC) was developed to correct delocalization error by using orbitals localized in space and energy. These localized orbitals span both the occupied and unoccupied spaces and can have fractional occupations in order to correct both the total energy and the one-electron energy eigenvalues. We extend the LOSC method to periodic systems, in which the localized orbitals employed are dually localized Wannier functions. In light of the effect of the bulk environment on the electrostatic interaction between localized orbitals, we modify the LOSC energy correction to include a screened Coulomb kernel. For a test set of semiconductors and large-gap insulators, we show that the screened LOSC method consistently improves the band gap compared to the parent density functional approximation.
DOI: 10.21227/m8xk-dr55
title: Drone RCS measurements (26-40 GHz)

description: The dataset contains measurement results of Radar Cross Section of different Unmanned Aerial Vehicles at 26-40 GHz. The measurements have been performed fro quasi-monostatic case (when the transmitter and receiver are spatially co-located) in the anechoic chamber. The data shows how radio waves are scattered by different UAVs at the specified frequency range.
DOI: 10.3886/e164661v1
title: Data and Code for: When Choices Are Mistakes

description: This contains the data and code to produce the results in When Choices Are Mistakes.
description: Response Rates: We collected 13 sessions in-person at Ohio State University's experimental economics lab for a total of 224 subjects. All subjects who were registered finished the experiment. We separately recruited 500 subjects on Prolific.
description: There are approximately 36,000 participants registered for experiments at OSU. We randomly invited individuals from this sample.<br><br>Subjects on Prolific were recruited through their random sampling.
description: on-site questionnaire;
DOI: 10.5065/d6542kq2
title: Alaska North Slope 100 m Digital Elevation Model, Version 1.0

description: This data set is a 100-m resolution Digital Elevation Model (DEM) for the Brooks Range and the North Slope of Alaska. The DEM was created by merging 100 National Elevation Dataset DEM tiles for areas of Alaska north of 67 degrees north latitude. A small area of Canada, derived from the global GTOPO30 DEM, is also included. The resulting DEM is in the Alaska Albers conical equal area projection, using the North American Datum of 1927 (NAD27). Data are available in GeoTIFF, Arc/INFO grid, and binary Band Interleaved by Line (BIL) formats.
DOI: 10.5066/f7959gf5
title: USGS Gap Analysis Project Additional Data: National Gap Land Cover Ver 1.0 (2001)

description: The Land Cover Data - Version 1.0 represents a highly thematically detailed land cover map of the U.S. The map legend includes types described by NatureServe's Ecological Systems Classification (Comer et al. 2002) as well as land use classes described in the National Land Cover Dataset 2001 (Homer et al. 2007). This version of the land cover data was used to support the USGS Gap Analysis Project's (GAP) Vertebrate Species Modeling efforts. These data cover the entire continental U.S. and are a continuous data layer. These raster data have a 30 m x 30 m cell resolution. GAP used the best information available to create the aspect data; however GAP seeks to improve and update these data as new information becomes available.
DOI: 10.5281/zenodo.3236413
title: Updated MCMC chains and subsamples for Hector calibration paper

description: These csvs contain MCMC chains and sampled subsets for calibration of the Hector simple climate model (https://github.com/JGCRI/hector, DOI:10.5194/gmd-8-939-2015). This series of five calibrations with different observational constraints and free parameters is described in Vega-Westhoff et al. (2019, DOI:10.1029/2018EF001082; see their table 1).

The calibrations use a version of Hector that includes the BRICK sea-level module (https://github.com/scrim-network/BRICK, DOI:10.5194/gmd-10-2741-2017). Hector with BRICK is available on my fork of the Hector model (https://github.com/bvegawe/hector/tree/dev_slr). The calibration process is also adapted from BRICK. The code used to produce these chains can be found at https://github.com/bvegawe/hector_probabilistic, DOI:10.5281/zenodo.3236411.

These five sets of MCMC chains were produced using hector_calib_driver.R. Inputs used to create each calibration are specified below: 

T.csv:  Rscript hector_calib_driver.R -f *output folder* -n 200000 --forcing TRUE --np 10 --model_set onlyT_model --obs_set onlyT_obs

TOHC.csv: Rscript hector_calib_driver.R -f *output folder* --forcing TRUE --np 10 --model_set doeclim_model --obs_set doeclim_obs

TOHCGICGISAIS.csv: Rscript hector_calib_driver.R -f *output folder* --forcing TRUE --np 10 --model_set noTE_model --obs_set noTE_obs

TTE.csv: Rscript hector_calib_driver.R -f *output folder* --forcing TRUE --np 10 --model_set onlyTE_model --obs_set doeclimTE_obs

TTEGICGISAIS.csv: Rscript hector_calib_driver.R -f *output folder* --forcing TRUE --np 10 --model_set all_model --obs_set noOcheat_obs

 

V1.1 - Updated with new calibrations. Previously only included two calibration files, wSLR_calib.csv, which was a 'full' model calibration, including both ocean heat and thermosteric sea level historical constraints, and woSLR_calib.csv, which included only ocean heat and temperature constraints. After review, we redid the calibration experiment, including additional combinations of constraints, and removing the 'full' calibration, which treated the ocean heat and thermosteric sea level constraints as independent.
DOI: 10.5281/zenodo.7540840
title: Datasets of binary and quaternary alloys with Curie temperature and magnetization for the eRSM

description: <pre>binary_alloys: A material dataset containing 100 transition-rare earth metal binary alloys, comprising nickel (Ni), manganese (Mn), cobalt (Co), or iron (Fe), and the corresponding Curie temperatures ($T_{C}$). This dataset was collected from the Atomwork database of the National Institute of Materials Science \cite{paulingfile,atomwork}. Each binary alloy in $\mathcal{D}_{binary}$ is represented using seven descriptors: (1,2) the atomic number of transition metal ($Z_T$) and rare-earth ($Z_R$) constituents; (3) projection of the spin magnetic moment onto the total angular moment of the $4f$ elections ($J_{4f}\left(1-g_{j}\right)$); (4, 5) covalent radius ($r_{covT}$) and first ionization (${IP}_T$) of the transition metal; (6, 7) concentration of the transition metal ($C_T$) and rare-earth metal ($C_R$). </pre> <pre>quaternary_alloys: A material dataset contains 990 equiatomic quaternary high-entropy alloys, which comprise $14$ transition metals {Ag, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pd, Rh, Ru, Tc, Zn}, and the corresponding calculated magnetizations and Curie temperatures in the BCC phase. The dataset was collected from an original dataset of 147,630 equiatomic quaternary high-entropy alloys calculated using Korringa-Kohn-Rostoker coherent approximation method . Each alloy in the dataset is represented using 135 compositional descriptors, including the means, standard deviations, and covariance of the atomic representations of their constituent elements and four categorical features indicating the elements comprising the quaternary alloy. </pre>
DOI: 10.6073/pasta/c988d7a134ee77cda29624eeeb4ddf66
title: Baltimore Ecosystem Study: November 21, 2019 Download of TreeBaltimore data in support of Anderson et al 2022, Ecosphere

description: Tree Baltimore (treebaltimore.org) hired Davey Tree to conduct a census of all publicly owned trees and tree pits in the city of Baltimore. This census was completed by arborists in 2017-2018, documenting over 192,000 trees and potential tree sites that reflect the public component of Baltimore’s urban forest. Entries in this dataset include trees in parkways (street trees), mown areas of public parks (forest patches excluded), meridian trees, and vacant spaces for tree planting. Data is continuously updated and the current vintage can be found at https://baltimore.maps.arcgis.com/apps/webappviewer/index.html?id=d2cfbbe9a24b4d988de127852e6c26c8.
DOI: 10.6084/m9.figshare.11351138.v2
title: A Reliability Test System Used for Electricity-Gas Integrated Energy System Reliability Evaluation

description: A Reliability Test System Used for Electricity-Gas Integrated Energy System Reliability Evaluation
DOI: 10.6084/m9.figshare.21937991
title: Data File 3.xlsx

description: Spatial distribution of dispersion spectrum in 3-dimensions with various temperatures and Two-dimensional profiles of peak intensities.
DOI: 10.6084/m9.figshare.21937994
title: Data File 4.xlsx

description: Extracted peak wavelength as a function of temperature. The symbol is experimental data and the solid line is a linear fitting curve.
DOI: 10.5281/zenodo.7118408
title: data for 2022EA002624

description: In-flight calibrations of the near-infrared spectra acquired by the Zhurong rover.
DOI: 10.5281/zenodo.7788614
title: Bicelle size and lipid/surfactant ratio screening - Gwalp tail anchor dimer simulation - 80 Lipids - q0.38 - PBS neutralized - CHARMM36m - 310K - OPC water model

description: Bicelle size and lipid to surfactant ratio screening to investigate the influence on spin relaxation data with monomers of a given peptide.