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The data and programs replicate tables and figures from "From Hyperinflation to Stable Prices: Argentina's Evidence on Menu Cost Models", by Alvarez, Beraja, Gonzalez-Rozada, and Neumeyer. Please see the Readme file for additional details. CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/C8ZOAS&version=2.2
Replication Data for: "Nonparametric Welfare and Demand Analysis with Unobserved Individual Heterogeneity" CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/SDUGGM&version=1.2
Academic Data and Datasets
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The dataset contains genotype (tped and tfam files) and phenotype data GWAS analyses on canine hip dysplasia. See README file for more information.
Source: https://figshare.com/articles/dataset/Genetic_dissection_of_canine_hip_dysplasia_phenotypes_and_osteoarthritis_reveals_three_novel_loci/10096595/1
Academic Data and Datasets
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Filtered genotype calls from high coverage sequencing data of Alca Tarma (LOP-868), IVP101, PL4, and three selected dihaploids
Source: https://figshare.com/articles/dataset/Dataset_S3_tsv_Genomic_outcomes_of_haploid_induction_crosses_in_potato/10052357/1
Academic Data and Datasets
by Raymond Haggerty
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Contains all the input and output files used to generate figure 4 IN_[stress].mat are the input files for each stress (glucose, H2O2, KCl) OUT_[stress].mat are the output files run through MISC corresponding to each of the input files.
Source: https://figshare.com/articles/dataset/Figure_4_Reproduction_Files/11383662/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA18951. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA18951/7892684/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03095. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03095/7890959/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01682. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01682/7897922/1
Academic Data and Datasets
by tw70455@gmail.com tw70455@gmail.com
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For the paper 'Spontaneous thought-related network connectivity predicts sertraline effect on major depressive disorder'
Source: https://figshare.com/articles/dataset/sertraline_effect_on_major_depressive_disorder/8135552/1
Academic Data and Datasets
by Katarina Kleinova
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The CT data of Zootoca vivipara NHMW 32438-1 from Čerňanský and Syromyatnikova Plos One. It can by open by winrar and volume graphics.
Source: https://figshare.com/articles/dataset/Cernansky_and_Syromyatnikova_Zootoca_vivipara_NHMW_32438-1/8396822/1
Academic Data and Datasets
by Michael Lee
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angus 2019 genomes from metagenomes
Source: https://figshare.com/articles/dataset/angus_2019_genomes_from_metagenomes/8863388/1
Academic Data and Datasets
by Hyung Rae Cho; Saehoon Kim
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This file contains the EEG raw data of 14 participants in the laboratory experiment and of 89 participants in the fieldwork in Nangok-dong. As stated in the manuscript, this EEG dataset was analysed to investigated valence values that show positive/negative emotions. This data was analysed by MATLAB and EEGLAB. The EEG raw data of 10 participants in the fieldwork were removed in the final analysis due to the issue of poor connection between laptop and EEG device.
Source: https://figshare.com/articles/dataset/EEG_raw_data_zip/9958946/1
Academic Data and Datasets
by Bolivar Samuel Sosa Madrid; agustin blasco; noelia ibañez escriche
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Genomic Data from divergently selected lines for intramuscular fat in rabbits. This database was used for the analyses of the article titled: "Genomic regions influencing intramuscular fat in divergently selected rabbit lines." Animal Genetics - Journal, accepted in 2019.
Source: https://figshare.com/articles/dataset/Genomic_Data_from_divergently_selected_lines_for_intramuscular_fat_in_rabbits/9934058/2
This dataset contains data files and identifiers for original data sources for 39 gene expression datasets from over 7,000 individuals with estrogen receptor positive (ER-positive) Breast Cancer (BC). Background The related study developed a novel in silico approach to assess activation of different signalling pathways. The phosphatidylinositol 3-kinase (PI3K)/AKT/mTOR signalling pathway mediates key cellular functions, including growth, proliferation and survival and is frequently involved in...
Source: https://springernature.figshare.com/articles/dataset/Gene_expression_data_sources_for_in_silico_approach_to_assessing_activation_of_AKT_mTOR_signalling_pathway_in_ER-positive_early_Breast_Cancer/7461776/1
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat based peak NDVI image Year 1993 Tile 14
Source: https://springernature.figshare.com/articles/dataset/Landsat_based_peak_NDVI_image_Year_1993_Tile_14/7769750/1
Academic Data and Datasets
by Matt Giesler; SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/2639767
Academic Data and Datasets
by OPEGIEKA
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Data from Sentinel-1 SLC product was used to determine the extent of the urbanised area. Such a solution is necessary in the case of rapidly developing cities, as in the case of the capital of India - New Dehli. Links to the presentation: http://fabspace.pl/wp-content/uploads/2017/11/Urban-area-on-S-1.pdf  
Source: https://zenodo.org/record/2582988
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19463. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19463/7929641/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02142. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02142/7927550/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19429. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19429/7929002/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03977. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03977/7929782/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03926. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03926/7929389/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA20344. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA20344/7936628/1
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3275525
Academic Data and Datasets
by Antonis Michalas
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Text files of different size and structure. More precisely, we selected random data from the Gutenberg dataset. This artefact contains five different datasets with random text files (i.e. e-books in .txt format) from the Gutenberg database. The datasets that we selected ranged from text files with a total size of 184MB to a set of text files with a total size of 1.7GB. More precisely, the following datasets can be found in this package: 1. 184MB 2. 357MB 3. 670MB 4. 1GB 5. 1.7GB In our case, we...
Source: https://zenodo.org/record/3360392
Academic Data and Datasets
by emmanuel levy; Benjamin Dubreuil
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Supplementary Dataset from the work "Rules of amino acid composition by which disordered regions adjust to high expression". This table contains amino-acid level information of human proteins.
Source: https://figshare.com/articles/dataset/Dataset_2_2_Human_amino-acids_raw_data/8058854/1
Academic Data and Datasets
by figshare admin cellimagelibrary
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Single computed slice through a tomographic reconstruction of a protoplasmic astrocyte in a 0.5 um thick section from the hippocampus of a 1 month old male mouse, imaged with intermediate voltage electron microscopy. This reconstruction is the 14th in a series of 26 serial reconstructions through the cell soma. The complete reconstruction can be viewed under MP7503.
Source: https://cellimagelibrary.figshare.com/articles/dataset/CCDB_6727_jpg/8179529/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG00097.
Source: https://figshare.com/articles/dataset/gVCF_HG00097/7841411/1
Academic Data and Datasets
by Andrew D. Richardson; David Y. Hollinger; Julie Shoemaker; Holly Hughes; Kathleen Savage; Eric A. Davidson
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Carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) are the greenhouse gases largely responsible for anthropogenic climate change. Natural plant and microbial metabolic processes play a major role in the global atmospheric budget of each. We have been studying ecosystem-atmosphere trace gas exchange at a sub-boreal forest in the northeastern United States for over two decades. Historically our emphasis was on turbulent fluxes of CO 2 and water vapor. In 2012 we embarked on an...
Source: https://figshare.com/articles/dataset/Tower-_and_chamber-based_greenhouse_gas_flux_measurements_from_Howland_Forest_Maine_2012-2018_/7445657/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA18864. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA18864/7890737/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01624. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01624/7895774/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03452. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03452/7901339/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01950. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01950/7911317/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03558. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03558/7907651/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19185. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19185/7927103/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19475. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19475/7929941/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03812. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03812/7928066/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02286. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02286/7928966/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03874. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03874/7928795/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02561. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02561/7931462/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02554. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02554/7931255/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA18504. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA18504/7944293/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA20786. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA20786/7944296/1
Academic Data and Datasets
by Soon-Chun Jeong; Myung-Shin Kim; Ji Hong Kim; Youn Young Hur
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Candidate SNP variants detected by analysis of genome resequencing data from 33 grape accessions
Source: https://figshare.com/articles/dataset/33Grapes_Total_SNP_final_chr06_vcf_gz/8116106/1
Academic Data and Datasets
by Hacking Materials
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Matbench v0.1 test dataset for predicting DFT PBE band gap from structure. Adapted from Materials Project database. Removed entries having a formation energy (or energy above the convex hull) more than 150meV and those containing noble gases. Retrieved April 2, 2019.
Source: https://figshare.com/articles/dataset/mp_gap/9461444/1
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3303264
Academic Data and Datasets
by Matt Giesler; SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3307421
Academic Data and Datasets
by Raphaël Nussbaumer; Lionel Benoit; Grégoire Mariethoz; Felix Liechti; Silke Bauer; Baptiste Schmid
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This dataset contains the interpolated values of bird density and bird flight speed (N-S and E-W) resulting from the methodology presented in [reference].The methodology is explained in less detail at  rafnuss-postdoc.github.io/BMM . The resulting interpolation is a probability distribution (define the probability of each value to occurs). Only the median, quantile 10 and 90 are given in this file.  The spatio-temporal grid has a resolution of 0.2° in latitude (43°-68°) and longitude...
Source: https://zenodo.org/record/3243466
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat based peak NDVI image Year 1997 Tile 14
Source: https://springernature.figshare.com/articles/dataset/Landsat_based_peak_NDVI_image_Year_1997_Tile_14/7769753/1
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat based peak NDVI image Year 2018 Tile 13
Source: https://springernature.figshare.com/articles/dataset/Landsat_based_peak_NDVI_image_Year_2018_Tile_13/7769732/1
Academic Data and Datasets
by Janet Loebach; Kate Tilleczek; Brent Chaisson; Brian Sharp
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The Young Lives Research Laboratory is concerned with the lives of modern youth from education to technology to mental health. Technology is ubiquitous in the day to day lives of young people in Canada but little is known about the ways in which digital media affects their mental health, especially for Indigenous youth. Research seldom engages youth to clarify and or interrogate digital media and well-being. This paper addresses the dearth of empirical work and supports the development of...
Source: https://tandf.figshare.com/articles/dataset/_i_Keyboard_warriors_i_Visualising_technology_and_well-being_i_with_for_i_and_i_by_i_indigenous_youth_through_digital_stories/11106794/1
Academic Data and Datasets
by Musfiqur Rahman
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English - code parallel corpus from StackOverflow
Source: https://figshare.com/articles/dataset/SOParallelData_zip/7673927/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02095. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02095/7927067/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19359. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19359/7928666/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19795. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19795/7932278/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA21144. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA21144/7951910/1
Academic Data and Datasets
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Data files for four species. Each species has 9 data files (3 niche model approaches X 3 RCPs). Each individual file has lat/lon gridded projection output for 5 future time periods during the 21st century, for each of 18 Earth system climate models. This is provided for both a probability of occurrence based niche model and a delta biomass approach (separate files for each). NOTE: this data set pertains to a manuscript that is presently in review (as of June 2019). Contact...
Source: https://figshare.com/articles/dataset/Projection_uncertainty_ensemble_members_Morley_et_al_2019/8256815/1
Academic Data and Datasets
by Johannes Abeler
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Merged data set of all raw data of the meta study
Source: https://figshare.com/articles/dataset/truth_telling_meta_study_merged_data_csv/8850767/1
Optotrak recordings of Fitts task paradigm as presented in Valk et al. (2019) 'During rhythmic pointing, joint-angles are temporary linked in different synergies with similar relative joint-angle coupling across task constraints'
Source: https://figshare.com/articles/dataset/Dataset_During_rhythmic_pointing_joint-angles_are_temporary_linked_in_different_synergies_with_similar_relative_joint-angle_coupling_across_task_constraints_/8280893/1
Academic Data and Datasets
by Ben Dichter; Edward F Chang
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The enclosed data is collected using a high-density 256-channel electrocorticography array implanted in a human patient during treatment for epilepsy. The subjects are reading aloud consonant-vowel syllables from a list. The data was collected by Dr. Edward Chang at the University of California, San Francisco, and curated by Ben Dichter. Data is organized by subject ID, and each file is a continuous recording session in Neurodata Without Borders: Neurophysiology (NWB:N) 2.0 format. Voltage...
Source: https://figshare.com/articles/dataset/EC9_B46_nwb/9631880/1
Academic Data and Datasets
by Nadja Grammes
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PLSDB files from 2019.06.05
Source: https://figshare.com/articles/dataset/PLSDB_2019_06_05/9959750/1
Academic Data and Datasets
by Sanjna Banerjee; Shrey Grover; Suhas Ganesh; Devarajan Sridharan
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Supplemental data and raw data sources for Banerjee, Grover, Ganesh and Sridharan, J. Neurophys. (2019)
Source: https://figshare.com/articles/dataset/Supplemental_Data_Banerjee_Grover_Ganesh_and_Sridharan_J_Neurophys_2019_/9751766/1
Academic Data and Datasets
by Mario Looso
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Output folder of TOBIAS software (https://github.com/loosolab/TOBIAS/), applied to Hendrikson et al. 2017 dataset
Source: https://figshare.com/articles/dataset/bias_correction_zip/9975926/1
Academic Data and Datasets
by Tannaz Pak; Nathaly Lopes Archilha; Iara Frangiotti Mantovani; Anderson Camargo Moreira; Ian B. Butler
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Segmented oil phase for image: WI-Filtered Segmentation performed using Watershed segmentation in Avizo. Image Dimension: 1024×1024×845 Image Type: 8 bit
Source: https://springernature.figshare.com/articles/dataset/WI-Segmented-Oil/6959327/1
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat NDVI difference 1990 2018 Tile 6
Source: https://springernature.figshare.com/articles/dataset/Landsat_NDVI_difference_1990_2018_Tile_6/7767695/1
Academic Data and Datasets
by Tony Alfredo Stabile; Claudia Mascandola; Marco Massa; Sara Amoroso; Deborah Di Naccio; Salomon Hailemikael; Lucia Luzi; Daniela Famiani; Fabrizio Cara; Giovanna Cultrera; Gaetano Riccio; Paola Bordoni; Augusto Bucci; Alessia Mercuri; Giuliano Milana; Marta Pischiutta; Luciana Cantore; Giuseppe Di Giulio; Maurizio Vassallo; Rocco Cogliano; Antonio Fodarella; Stefania Pucillo; Maria D'Amico; Simona Carannante; Chiara Felicetta; Gianlorenzo Franceschina; Giovanni Lanzano; Sara Lovati; Francesca...
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Seismic traces in binary MiniSeed format recorded by station MZ27. The daily records are separated in folders representing the channels: EHE.D, EHN.D, EHZ.D for the velocimetric data and HNE.D, HNN.D and HNZ.D for the accelerometric data. Both velocimetric and accelerometric data are available from October 10, 2016 to November 22, 2016.
Source: https://springernature.figshare.com/articles/dataset/Seismic_traces_recorded_by_station_MZ27/7803164/1
Academic Data and Datasets
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Last of four zipfiles providing all data and Python code necessary to replicate any of the 13 development potential indexes (DPIs) described within Oakleaf et al. (2019), “Mapping global development potential for renewable energy, fossil fuels, mining and agriculture sectors”. A README.pdf guides users on setting up environment necessary to use data and run Python code. To run Python code with accompanying spatial data, 64 GBs of disk space is required. Additionally ArcPY, a python module...
Source: https://springernature.figshare.com/articles/dataset/Spatial_Data_and_Python_Code_for_13_Development_Potential_Indices_part_04_/7890935/1
Dioxin response elements were computationally identified and matrix similarity scores estimated as previously described (PMIDs: 15328365, 21762485, and 26582802) CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JASCVZ&version=1.0
Academic Data and Datasets
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In this study, Beijing, the capital of China, is selected as the study area. Hourly mean concentrations of six regulatory air pollutants including O3 (μg/m3), SO2 (μg/m3), NO2 (μg/m3), PM2.5 (μg/m3), PM10 (μg/m3), and CO (mg/m3) were collected from 35 air quality monitoring stations labeled by 1 to 35 from 01/01/2017 to 05/30/2018. The data was provided by the Ministry of Environmental Protection (MEP) of China. Hourly averaged meteorological data in the same period were first accessed...
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/USXCAK&version=1.0
Academic Data and Datasets
by Rahul Rao Madarapu
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Bike ride data of a month
Source: https://figshare.com/articles/dataset/two_json/10277954/1
Academic Data and Datasets
by Han, Xueyuan
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Preprocessed edgelist data of ta1-fivedirections-e3-official. CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/NVQFY0&version=1.0
Academic Data and Datasets
by Martin Jinye Zhang
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Toy data for the diversity score analysis in Tabula Muris Senis
Source: https://figshare.com/articles/dataset/Diversity_score_toy_data/11340128/1
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3319012
Academic Data and Datasets
by Tony Chu; Kidder, Larry; Pfeiffer, Harald; Scheel, Mark; Boyle, Michael; Hemberger, Dan; Lovelace, Geoffrey; Szilagyi, Bela
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3274549
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3273341
Academic Data and Datasets
by Jonathan Blackman; SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3272877
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3307711
Academic Data and Datasets
by Shunliu Zhao; Matthew G. Russell; Amir Hakami; Shannon L. Capps; Matthew D. Turner; Daven K. Henze; Peter B. Percell; Jaroslav Resler; Huizhong Shen; Armistead G. Russell; Athanasios Nenes; Amanda J. Pappin; Sergey L. Napelenok; Jesse O. Bash; Kathleen M. Fahey; Gregory R. Carmichael; Charles O. Stanier; Tianfeng Chai
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The data set that is used for testing the adjoint model.
Source: https://zenodo.org/record/3473444
Academic Data and Datasets
by Kevin Barkett; SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3303728
Academic Data and Datasets
by Michael Lee
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https://astrobiomike.github.io/amplicon/dada2_workflow_ex
Source: https://figshare.com/articles/dataset/dada2_amplicon_ex_workflow_tar_gz/6225761/3
Academic Data and Datasets
by Andrea Capiluppi
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These are the raw java classes of the projects parsed off SourceForge. The projects are categorised by application domain
Source: https://figshare.com/articles/dataset/raw_data_Java_source_code_for_MSR_data_track_2019/7673264/1
Academic Data and Datasets
by Stephan Rasp
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Sample data
Source: https://figshare.com/articles/dataset/WB_Sample_Data/11370675/2
Academic Data and Datasets
by Dalberg
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The State of Aadhaar survey is the largest primary dataset collected on digital identity, globally. The dataset contains; 1. Household and member-level data collected for the in-depth and pulse survey 2. R codes used for analysis and visualisations 3. Additional spatial and meta data required for analysis and visuals The data, and all materials, are shared under Creative Commons Attribution 4.0 International license (CC-BY 4.0). You are free to: Share — copy and redistribute the material in...
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/M9RWZN&version=1.1
Academic Data and Datasets
by Benjamin Arnold Krekeler Hartz
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Radiation: Interface for Matlab Spectroscopy Calculations (RadISpeC) is a program that use HITRAN/HITEMP data to generate Line-by-Line (LBL) spectra at a wanted spectral resolution and environment. These data can be used with Discrete Transfer Methods (DTM), Ray Tracing (RT) etc. solvers to estimate high precision radiation in heated flow problems. It was created as a part of the article "Experimental and theoretical evaluation of spectral radiative transfer in high-pressure flames"...
Source: https://figshare.com/articles/dataset/RadISpeC_program_code_m_files_and_GUI_for_Matlab_IDE_/6988997/4
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01347. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01347/7890095/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03464. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03464/7901504/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA20282. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA20282/7934999/1
Academic Data and Datasets
by Xiaoyue Yang; Zefu Wang; Lei Zhang; Guoqian Hao; Yongzhi Yang
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This collection of files stems from the annotation (gene model predicted, annotation for repetitive elements and non-coding genes, nucleotide sequences for coding and non-coding genes, protein sequences for coding genes) of the Carpinus fangiana genome.
Source: https://figshare.com/articles/dataset/Supplemental_material_for_the_Carpinus_fangiana_genome/8549204/2
Academic Data and Datasets
by Jinshi Jian; Ryan Stewart; Xuan Du
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Here, we compiled data from a set of soil health measurements collected across 41 countries around the world, named SoilHealthDB, which includes 5,241 data entries from 281 published studies. The SoilHealthDB includes 42 soil health indicators and 45 background indicators that describe factors such as climate, elevation, and soil type. A primary goal of SoilHealthDB is to enable the research community to perform comprehensive analyses, e.g., meta-analyses, of soil health changes related to...
Source: https://figshare.com/articles/dataset/SoilHealthDB/8292176/8
Academic Data and Datasets
by Jean Armengaud
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We sequenced the transcriptomes of a male individual and a female individual for seven different taxonomical groups: Gammarus fossarum A, G. fossarum B, G. fossarum C, Gammarus wautieri, Gammarus pulex, Echinogammarus berilloni and Echinogammarus marinus. Translations of coding sequence regions were produced for each transcriptome by Transdecoder from stop to stop codons, analysing only top strand with 500 top longest ORFs used for training, and retaining 600 base pair ORFs and only proteins...
Source: https://figshare.com/articles/dataset/YC02_Transcriptome_translated_ORFs/8798471/1
Academic Data and Datasets
by Zong Qin; Ying-Ju Lin; Fang-Cheng Lin; Yi-Pai Huang
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An image database dedicated to color breakup evaluation, which contains 25 FHD references images that cover various image content.
Source: https://opticapublishing.figshare.com/articles/dataset/Color_Breakup_Image_Database_zip/7223039/1
Academic Data and Datasets
by Joan M. Walker; Ronel Namde
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A wealth of period literature from as early as 1856 through the 1920s promoted the toning of salted paper prints with platinum to achieve certain aesthetic effects and improve silver image permanence. A variety of toning bath compositions were proposed to achieve a range of image tones. Additionally, other platinum and matte silver photographic processes, such as kallitypes, silver-platinum prints (e.g., “Satista”), and silver-intensified platinum prints, were popular during the salted...
Source: https://tandf.figshare.com/articles/dataset/The_History_and_Chemistry_of_Platinum-toned_Salted_Paper_Prints/10033598/1
Academic Data and Datasets
by James R. Oakleaf; Christina M. Kennedy; Sharon Baruch-Mordo; Joseph Kiesecker
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This global dataset continuously ranks from >0 (minimal) to 1 (highest) all suitable lands at a 1-km resolution for metallic mining (e.g. gold, silver, copper). These data are derived from the weighted summary of four criteria maps: 1) proxy yield values based on deposit size and numbers, 2) distance to demand centers, 3) distance to major roads, and 4) distance to railways or ports. Included with these data are: a) the classified version of the continuous DPI, b) the corresponding...
Source: https://springernature.figshare.com/articles/dataset/Metallic_Mining_Development_Potential_Index/7151081/1
Academic Data and Datasets
by André R. A. Marques; Alessandro Di Spiezio; Niklas Thießen; Lina Schmidt; Joachim Grötzinger; Renate Lüllmann-Rauch; Markus Damme; Steffen E. Storck; Claus U. Pietrzik; Jens Fogh; Julia Bär; Marina Mikhaylova; Markus Glatzel; Mahmoud Bassal; Udo Bartsch; Paul Saftig
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CTSD (cathepsin D) is one of the major lysosomal proteases indispensable for the maintenance of cellular proteostasis by turning over substrates of endocytosis, phagocytosis and autophagy. Consequently, CTSD deficiency leads to a strong impairment of the lysosomal-autophagy machinery. In mice and humans CTSD dysfunction underlies the congenital variant (CLN10) of neuronal ceroid lipofuscinosis (NCL). NCLs are distinct lysosomal storage disorders (LSDs) sharing various hallmarks, namely...
Source: https://tandf.figshare.com/articles/dataset/Enzyme_replacement_therapy_with_recombinant_pro-CTSD_cathepsin_D_corrects_defective_proteolysis_and_autophagy_in_neuronal_ceroid_lipofuscinosis/8798045/1
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/2641009
Academic Data and Datasets
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The data are for the manuscript submitted to Journal of Geophysical Research-Atmospheres on 15th, August, 2019 by Huiyan Xu. 
Source: https://zenodo.org/record/4059012
Academic Data and Datasets
by Stephens, Ian
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uv (visibility) continuum and spectral line data for Per-emb-4 (Per4) CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/QLVGPG&version=1.0
Replication data for: "Geography, Ties, and Knowledge Flows: Evidence from Citations in Mathematics" CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/W4B8MB&version=1.1
With the growth of Latino and Asian-American populations, candidates frequently must appeal to diverse electorates. Strategies for doing so include emphasizing candidates’ racial/ethnic identity and securing endorsements from racial/ethnic groups. While many scholars focus on candidates’ racial/ethnic attributes, ethnic group endorsements are understudied. Whether such endorsements induce voters to choose ideologically-similar candidates (spatial voting), or choose based on race/ethnicity...
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/XYUWYJ&version=1.1
Academic Data and Datasets
by Baranga, Thomas
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The data and programs replicate tables and figures from "The Return to Protectionism", by Fajgelbaum, Goldberg, Kennedy, and Khandelwal. Please see the Readme file for additional details. CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KSOVSE&version=1.1