4 datasets found
  1. f

    Population and GDP/GNI/CO2 emissions (2019, raw data)

    • figshare.com
    txt
    Updated Feb 23, 2023
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    Liang Zhao (2023). Population and GDP/GNI/CO2 emissions (2019, raw data) [Dataset]. http://doi.org/10.6084/m9.figshare.22085060.v6
    Explore at:
    txtAvailable download formats
    Dataset updated
    Feb 23, 2023
    Dataset provided by
    figshare
    Authors
    Liang Zhao
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Original dataset The original year-2019 dataset was downloaded from the World Bank Databank by the following approach on July 23, 2022.

    Database: "World Development Indicators" Country: 266 (all available) Series: "CO2 emissions (kt)", "GDP (current US$)", "GNI, Atlas method (current US$)", and "Population, total" Time: 1960, 1970, 1980, 1990, 2000, 2010, 2017, 2018, 2019, 2020, 2021 Layout: Custom -> Time: Column, Country: Row, Series: Column Download options: Excel

    Preprocessing

    With libreoffice,

    remove non-country entries (lines after Zimbabwe), shorten column names for easy processing: Country Name -> Country, Country Code -> Code, "XXXX ... GNI ..." -> GNI_1990, etc (notice '_', not '-', for R), remove unnesssary rows after line Zimbabwe.

  2. e

    Data from: Superconductor-ferromagnet hybrids for non-reciprocal electronics...

    • ekoizpen-zientifikoa.ehu.eus
    Updated 2023
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    Zhuoran Geng; Hijano, Alberto; Ilic, Stefan; Ilyn, Maxim; Maasilta, Ilari J.; Monfardini, Alessandro; Spies, Maria; Strambini, Elia; Virtanen, Pauli; Calvo, Martino; Gonzales-Orellana, Carmen; Helenius, Ari P.; Khorshidian, Sara; Clodoaldo I. Levartoski De Araujo; Levy-Bertrand, Florence; Rogero, Celia; Giazotto, Francesco; F. Sebastian Bergeret; Heikkilä, Tero T.; Zhuoran Geng; Hijano, Alberto; Ilic, Stefan; Ilyn, Maxim; Maasilta, Ilari J.; Monfardini, Alessandro; Spies, Maria; Strambini, Elia; Virtanen, Pauli; Calvo, Martino; Gonzales-Orellana, Carmen; Helenius, Ari P.; Khorshidian, Sara; Clodoaldo I. Levartoski De Araujo; Levy-Bertrand, Florence; Rogero, Celia; Giazotto, Francesco; F. Sebastian Bergeret; Heikkilä, Tero T. (2023). Superconductor-ferromagnet hybrids for non-reciprocal electronics and detectors [Dataset]. https://ekoizpen-zientifikoa.ehu.eus/documentos/668fc45cb9e7c03b01bdb054
    Explore at:
    Dataset updated
    2023
    Authors
    Zhuoran Geng; Hijano, Alberto; Ilic, Stefan; Ilyn, Maxim; Maasilta, Ilari J.; Monfardini, Alessandro; Spies, Maria; Strambini, Elia; Virtanen, Pauli; Calvo, Martino; Gonzales-Orellana, Carmen; Helenius, Ari P.; Khorshidian, Sara; Clodoaldo I. Levartoski De Araujo; Levy-Bertrand, Florence; Rogero, Celia; Giazotto, Francesco; F. Sebastian Bergeret; Heikkilä, Tero T.; Zhuoran Geng; Hijano, Alberto; Ilic, Stefan; Ilyn, Maxim; Maasilta, Ilari J.; Monfardini, Alessandro; Spies, Maria; Strambini, Elia; Virtanen, Pauli; Calvo, Martino; Gonzales-Orellana, Carmen; Helenius, Ari P.; Khorshidian, Sara; Clodoaldo I. Levartoski De Araujo; Levy-Bertrand, Florence; Rogero, Celia; Giazotto, Francesco; F. Sebastian Bergeret; Heikkilä, Tero T.
    Description

    Data for the manuscript "Superconductor-ferromagnet hybrids for non-reciprocal electronics and detectors", submitted to Superconductor Science and Technology, arXiv:2302.12732. This archive contains the data for all plots of numerical data in the manuscript. ## Fig. 4
    Data of Fig. 4 in the WDX (Wolfram Data Exchange) format (unzip to extract the files). Contains critical exchange fields and critical thicknesses as functions of the temperature. Can be opened with Wolfram Mathematica with the command: Import[FileNameJoin[{NotebookDirectory[],"filename.wdx"}]] ## Fig. 5
    Data of Fig. 5 in the WDX (Wolfram Data Exchange) format (unzip to extract the files). Contains theoretically calculated I(V) curves and the rectification coefficient R of N/FI/S junctions. Can be opened with Wolfram Mathematica with the command Import[FileNameJoin[{NotebookDirectory[],"filename.wdx"}]]. ## Fig. 7a
    Data of Fig. 7a in the ascii format. Contains G in uS as a function of B in mT and V in mV. ## Fig. 7c
    Data of Fig. 7c in the ascii format. Contains G in uS as a function of B in mT and V in mV. ## Fig. 7e
    Data of Fig. 7e in the ascii format. Contains G in uS as a function of B in mT and V in mV. The plots 7b, d, and f are taken from the plots a, c and e as indicated in the caption of the figure. ## Fig. 8
    Data of Fig. 8 in the ascii format. Contains G in uS as a function V in mV for several values of B in mT. ## Fig. 8 inset
    Data of Fig. 8 inset in the ascii format. Contains G_0/G_N as a function of B in mT. ## Fig9a_b First raw Magnetic field values in T, first column voltage drop in V,
    rest of the columns differential conductance in S ## Fig9b_FIT First raw Magnetic field values in T, first column voltage drop in V,
    rest of the columns differential conductance in S ## Fig9c First raw Magnetic field values in T, first column voltage drop in V,
    rest of the columns R (real number) ## Fig9c inset First raw Magnetic field values in T, odd columns voltage drop in V,
    even columns injected current in A ## Fog9d Foist column magnetic field in T, second column conductance ration (real
    number), sample name in the file name. ## Fig. 12
    Data of Fig. 12 in the ascii format. Contains energy resolution as functions of temperature and tunnel resistance with current and voltage readout. ## Fig. 13
    Data of Fig. 13 in the ascii format. Contains energy resolution as functions of (a) exchange field, (b) polarization, (c) dynes, and (d) absorber volume with different amplifier noises. ## Fig. 14
    Data of Fig. 14 in the ascii format. Contains detector pulse current as functions of (a) temperature change (b) time with different detector parameters.
    ## Fig. 17
    Data of Fig. 17 in the ascii format. Contains dIdV curves as function of the voltage for different THz illumination frequency and polarization. ## Fig. 18
    Data of Fig. 18 in the ascii format. Contains the current flowing throughout the junction as function time (arbitrary units) for ON and OFF illumination at 150 GHz for InPol and CrossPol polarization. ## Fig. 21
    Data of Fig. 21c in the ascii format. Contains the magnitude of readout line S43 as frequency.
    Data of Fig. 21d in the ascii format. Contains the magnitude of iKID line S21 as frequency.

  3. d

    Young and older adult vowel categorization responses

    • datadryad.org
    zip
    Updated Mar 14, 2024
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    Mishaela DiNino (2024). Young and older adult vowel categorization responses [Dataset]. http://doi.org/10.5061/dryad.brv15dvh0
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    zipAvailable download formats
    Dataset updated
    Mar 14, 2024
    Dataset provided by
    Dryad
    Authors
    Mishaela DiNino
    Description

    Young and older adult vowel categorization responses

    https://doi.org/10.5061/dryad.brv15dvh0

    On each trial, participants heard a stimulus and clicked a box on the computer screen to indicate whether they heard "SET" or "SAT." Responses of "SET" are coded as 0 and responses of "SAT" are coded as 1. The continuum steps, from 1-7, for duration and spectral quality cues of the stimulus on each trial are named "DurationStep" and "SpectralStep," respectively. Group (young or older adult) and listening condition (quiet or noise) information are provided for each row of the dataset.

  4. e

    A global database of long-term changes in insect assemblages

    • knb.ecoinformatics.org
    • search-dev.test.dataone.org
    • +4more
    Updated Jan 26, 2022
    + more versions
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    Roel van Klink; Diana E. Bowler; Jonathan M. Chase; Orr Comay; Michael M. Driessen; S.K. Morgan Ernest; Alessandro Gentile; Francis Gilbert; Konstantin Gongalsky; Jennifer Owen; Guy Pe'er; Israel Pe'er; Vincent H. Resh; Ilia Rochlin; Sebastian Schuch; Ann E. Swengel; Scott R. Swengel; Thomas L. Valone; Rikjan Vermeulen; Tyson Wepprich; Jerome Wiedmann (2022). A global database of long-term changes in insect assemblages [Dataset]. http://doi.org/10.5063/F1ZC817H
    Explore at:
    Dataset updated
    Jan 26, 2022
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    Roel van Klink; Diana E. Bowler; Jonathan M. Chase; Orr Comay; Michael M. Driessen; S.K. Morgan Ernest; Alessandro Gentile; Francis Gilbert; Konstantin Gongalsky; Jennifer Owen; Guy Pe'er; Israel Pe'er; Vincent H. Resh; Ilia Rochlin; Sebastian Schuch; Ann E. Swengel; Scott R. Swengel; Thomas L. Valone; Rikjan Vermeulen; Tyson Wepprich; Jerome Wiedmann
    Time period covered
    Jan 1, 1925 - Jan 1, 2018
    Area covered
    Variables measured
    End, Link, Year, Realm, Start, CRUmnC, CRUmnK, Metric, Number, Period, and 63 more
    Description

    UPDATED on October 15 2020 After some mistakes in some of the data were found, we updated this data set. The changes to the data are detailed on Zenodo (http://doi.org/10.5281/zenodo.4061807), and an Erratum has been submitted. This data set under CC-BY license contains time series of total abundance and/or biomass of assemblages of insect, arachnid and Entognatha assemblages (grouped at the family level or higher taxonomic resolution), monitored by standardized means for ten or more years. The data were derived from 165 data sources, representing a total of 1668 sites from 41 countries. The time series for abundance and biomass represent the aggregated number of all individuals of all taxa monitored at each site. The data set consists of four linked tables, representing information on the study level, the plot level, about sampling, and the measured assemblage sizes. all references to the original data sources can be found in the pdf with references, and a Google Earth file (kml) file presents the locations (including metadata) of all datasets. When using (parts of) this data set, please respect the original open access licenses. This data set underlies all analyses performed in the paper 'Meta-analysis reveals declines in terrestrial, but increases in freshwater insect abundances', a meta-analysis of changes in insect assemblage sizes, and is accompanied by a data paper entitled 'InsectChange – a global database of temporal changes in insect and arachnid assemblages'. Consulting the data paper before use is recommended. Tables that can be used to calculate trends of specific taxa and for species richness will be added as they become available. The data set consists of four tables that are linked by the columns 'DataSource_ID'. and 'Plot_ID', and a table with references to original research. In the table 'DataSources', descriptive data is provided at the dataset level: Links are provided to online repositories where the original data can be found, it describes whether the dataset provides data on biomass, abundance or both, the invertebrate group under study, the realm, and describes the location of sampling at different geographic scales (continent to state). This table also contains a reference column. The full reference to the original data is found in the file 'References_to_original_data_sources.pdf'. In the table 'PlotData' more details on each site within each dataset are provided: there is data on the exact location of each plot, whether the plots were experimentally manipulated, and if there was any spatial grouping of sites (column 'Location'). Additionally, this table contains all explanatory variables used for analysis, e.g. climate change variables, land-use variables, protection status. The table 'SampleData' describes the exact source of the data (table X, figure X, etc), the extraction methods, as well as the sampling methods (derived from the original publications). This includes the sampling method, sampling area, sample size, and how the aggregation of samples was done, if reported. Also, any calculations we did on the original data (e.g. reverse log transformations) are detailed here, but more details are provided in the data paper. This table links to the table 'DataSources' by the column 'DataSource_ID'. Note that each datasource may contain multiple entries in the 'SampleData' table if the data were presented in different figures or tables, or if there was any other necessity to split information on sampling details. The table 'InsectAbundanceBiomassData' provides the insect abundance or biomass numbers as analysed in the paper. It contains columns matching to the tables 'DataSources' and 'PlotData', as well as year of sampling, a descriptor of the period within the year of sampling (this was used as a random effect), the unit in which the number is reported (abundance or biomass), and the estimated abundance or biomass. In the column for Number, missing data are included (NA). The years with missing data were added because this was essential for the analysis performed, and retained here because they are easier to remove than to add. Linking the table 'InsectAbundanceBiomassData.csv' with 'PlotData.csv' by column 'Plot_ID', and with 'DataSources.csv' by column 'DataSource_ID' will provide the full dataframe used for all analyses. Detailed explanations of all column headers and terms are available in the ReadMe file, and more details will be available in the forthcoming data paper. WARNING: Because of the disparate sampling methods and various spatial and temporal scales used to collect the original data, this dataset should never be used to test for differences in insect abundance/biomass among locations (i.e. differences in intercept). The data can only be used to study temporal trends, by testing for differences in slopes. The data are standardized within plots to allow the temporal comparison, but not necessarily among plots (even within one dataset).

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Liang Zhao (2023). Population and GDP/GNI/CO2 emissions (2019, raw data) [Dataset]. http://doi.org/10.6084/m9.figshare.22085060.v6

Population and GDP/GNI/CO2 emissions (2019, raw data)

Explore at:
txtAvailable download formats
Dataset updated
Feb 23, 2023
Dataset provided by
figshare
Authors
Liang Zhao
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Original dataset The original year-2019 dataset was downloaded from the World Bank Databank by the following approach on July 23, 2022.

Database: "World Development Indicators" Country: 266 (all available) Series: "CO2 emissions (kt)", "GDP (current US$)", "GNI, Atlas method (current US$)", and "Population, total" Time: 1960, 1970, 1980, 1990, 2000, 2010, 2017, 2018, 2019, 2020, 2021 Layout: Custom -> Time: Column, Country: Row, Series: Column Download options: Excel

Preprocessing

With libreoffice,

remove non-country entries (lines after Zimbabwe), shorten column names for easy processing: Country Name -> Country, Country Code -> Code, "XXXX ... GNI ..." -> GNI_1990, etc (notice '_', not '-', for R), remove unnesssary rows after line Zimbabwe.

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