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22 results for “correlation coefficient”
An efficient not-only-linear correlation coefficient based on clustering: Supplementary Files
<p>Supplementary Files for the manuscript "An efficient not-only-linear correlation coefficient based on machine learning" available at https://doi.org/10.1101/2022.06.15.496326</p> <ul> <li>Supplementary File 1: All pairwise gene correlations using Pearson, Spearman and CCC among the top 5,000 genes in GTEx’s whole blood with the largest variance. Columns indicates whether the gene pair was categorized in the top or bottom 30% of each coefficient, the correlation value, and the significance of the association. Significance is only present for the top 10 gene pairs of each intersection in the “Disagreements” group (Figure 3a, right) where CCC disagrees with Pearson, Spearman or both.</li> <li>Supplementary File 2: Percentiles of the coefficient values for the top 5,000 genes in GTEx’s whole blood.</li> <li>Supplementary File 3: Pearson, Spearman and CCC correlations values and their significance for two gene pairs (<em>UTY</em> - <em>KDM6A</em> and <em>DDX3Y</em> - <em>KDM6A</em>) across all tissues in GTEx.</li> </ul>
Correlations for aerodynamic force coefficients of non-spherical particles in compressible flows
<div> <div><span># Data repository for the paper</span></div> <br> <div><span># </span><span>_Correlations for aerodynamic force coefficients of non-spherical particles in compressible flows_</span></div> <br> <div><span>Corresponding author:</span></div> <div><span>Berend.van.Wachem@multiflow.org</span></div> <br> <div><span>This repository consists of the data and exemplary python scripts for the paper "Correlations for aerodynamic force coefficients of non-spherical particles in compressible flows" by Christian Gorges, Victor Chéron, Anjali Chopra, Fabian Denner and Berend van Wachem. The data stored in this repository have the following data format:</span></div> <br> <div><span>-</span><span> .csv files consisting the raw data of the simulations used for the coefficient plots in the results' chapter of the paper</span></div> <div><span> </span></div> <div><span>-</span><span> .py files containing python scripts serving as examples on how to use and plot the raw data of the .csv files and the correlations</span></div> <br> <div><span>The main folders of this repository are named as the non-spherical particle shapes (Oblate, Prolate, Rod-like) and a folder with the data on which the correlations are based.</span></div> <br> <div><span>The folders named after the non-spherical particle shapes contain the raw simulation data. For instance, the Oblate folder contains the individual .csv files of all simulations of the oblate spheroid for all Reynolds numbers, Mach numbers, and angles of attack.</span></div> <br> <div><span>The folder Correlations/ consists of the temporally averaged drag, lift and torque coefficients, which are written in .csv files and stored in the folder ResultsCoefficients/, as well as Python scripts for plotting the correlations. </span></div> <br> <div><span>The naming style of the raw data files and the subfolders for each section is explained in the following:</span></div> <br> <div><span>The file names of the .csv files within the particle shape folders consist of the Reynolds number, followed by the Mach number and the angle of attack. For example "log_Re100M2_0_alpha_90.csv" consists of the data for a Reynolds number of 100, a Mach number of 2.0 and an angle of attack of 90 degrees. The content in the .csv files is given as: "%f,%f,%f,%f\n" which corresponds to "Physical time, drag coefficient, lift coefficient, torque coefficient". The first row in each file gives the headers of each column.</span></div> <br> <div><span>The .csv files in the folder Correlations/ResultsCoefficients/ are split per coefficient, shape, and particle Reynolds numbers, which can be identified by the name of the .csv file. For instance, the results obtained for the lift coefficient of</span></div> <div><span>the prolate spheroid particle for at a particle Reynolds numbers 100 for all orientation angles and Mach numbers are given in the file:</span></div> <div><span>"Prolate_100_CL.csv". In these files, the results are ordered per orientation angle (rows) and Mach</span></div> <div><span>number (column). </span></div> <br> <div><span>The python scripts have been tested with Python 3.11.5.</span></div> <br> <div><span>PlotCoefficients.py is an example python script to read the .csv files and plot the aerodynamic force coefficients as it is done in the results section of the paper.</span></div> <br> <div><span>The python scripts in the directory Correlations/ are split in three main functions in two files:</span></div> <div><span>-</span><span> Getter.py (read the .csv files storing the coefficients - separate functions</span></div> <div><span> for the drag, lift and torque coefficients)</span></div> <div><span>-</span><span> ManuscriptCorrelation.py with all the correlations derived in this work for an</span></div> <div><span> effective implementation in any solver, and a plotting function to have visual</span></div> <div><span> representation of the correlations.</span></div> <div><span>-</span><span> generalmain.py (calls Getter and Plotter)</span></div> <br> <div><span>The Getter is called from the generalmain.py file. (run python3 generalmain.py) so that all coefficients can be gathered in a 3D array.</span></div> <div><span>First dimension : Reynolds number</span></div> <div><span>Second dimension : Orientation angle</span></div> <div><span>Third dimension : Mach number</span></div> <div><span>The user just needs to give the absolute path to the folder ResultsCoefficients/.</span></div> <br> <div><span>This project has received funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), grant number 447633787.</span></div> </div>
Correlated k coefficients for H2-He atmospheres; 196 spectral windows and 1060 pressure-temperature points
<p>There are 72 correlated k-coefficients datasets, using the naming convention m-xxx_coyyy.data.196.tar.zip, where xxx is the metallicity in dex relative to solar, and yyy is the C/O ratio relative to solar, as a multiplication factor. For example a metallicity of 0.0 and a C/O ratio of 1.0 indicates solar abundances. There are an additional 5 datasets that do not include the TiO and VO opacities, as indicated by the "_noTiOVO" designation in the file name. We use the Lodders et al. 2010 value for the solar C/O=0.458. The spectral windows are listed in the file 196_windows.txt (intervals defined as starting at lambda1 and ending at lambda2), and the k-coefficients can be read in and checked using the script in the IDL code read_k_coefficients.pro. The k-coefficients are calculated for a grid of 1060 pressure-temperature points listed in the file PT_list_1060.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, where the abundances for each metallicity-C/O combination have been calculated using equilibrium chemistry, as described in Marley et al. 2021. There are 12 Fe/H values: 0.0, 0.5, 0.7, 1.0, 1.5, 1.5, 1.7, 2.0, -0.25, -0.3, -0.5, -0.75, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5.</p> <p> The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, FeH, H2O, H2S, HCN, LiCl, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The references for the line lists and broadening parameters used in these opacity calculations can also be found in Marley et al 2021, and are included here for convenience in the file Table_2_Marley_et.al.2021.png</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>cp_all: contains the mean molecular weight for each layer. The head capacity values do not include the proper H2 heat capacity and should not be used.</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1060-point pressure-temperature grid.</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_cia: relative abundances for the species that could be used for calculating collision-induced absorption (CIA)</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Correlated k coefficients for H2-He atmospheres; 11 spectral windows and 1060 pressure-temperature points
<p>There are 72 correlated k-coefficients datasets, using the naming convention m-xxx_coyyy.data.11.tar.zip, where xxx is the metallicity in dex relative to solar, and yyy is the C/O ratio relative to solar, as a multiplication factor. For example a metallicity of 0.0 and a C/O ratio of 1.0 indicates solar abundances. There are an additional 10 datasets that do not include the TiO and VO opacities, as indicated by the "_noTiOVO" designation in the file name. We use the Lodders et al. 2010 value for the solar C/O=0.458. The spectral windows are listed in the file 11_windows.txt (intervals defined as starting at lambda1 and ending at lambda2), and the k-coefficients can be read in and checked using the script in the IDL code read_k_coefficients.pro. The k-coefficients are calculated for a grid of 1060 pressure-temperature points listed in the file PT_list_1060.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, where the abundances for each metallicity-C/O combination have been calculated using equilibrium chemistry, as described in Marley et al. 2021. There are 12 Fe/H values: 0.0, 0.5, 0.7, 1.0, 1.5, 1.5, 1.7, 2.0, -0.25, -0.3, -0.5, -0.75, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5.</p> <p> The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, FeH, H2O, H2S, HCN, LiCl, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The references for the line lists and broadening parameters used in these opacity calculations can also be found in Marley et al 2021, and are included here for convenience in the file Table_2_Marley_et.al.2021.png</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>cp_all: contains the mean molecular weight for each layer. The head capacity values do not include the proper H2 heat capacity and should not be used.</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1060-point pressure-temperature grid.</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_cia: relative abundances for the species that could be used for calculating collision-induced absorption (CIA)</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Fig. 3. Correlation coefficients estimated between water quality indicators and morphological Fig. 4 in Investigation Of Common Reed Regrowth On The Shores Of Recreational Lakes
Fig. 3. Correlation coefficients estimated between water quality indicators and morphological Fig. 4. The number of holidaymakers near parameters of common reeds on the shores of Bridvaisis, Gaustvinis and Gilius lakes (in the Bridvaisis, Gaustvinis and Gilius Lakes. The order from the bottom to the top) and differences boundary of the continuous line side indicates in morphological parameters of plants after the cases where p <0.01; dashed lines, where p <0.05. holidaymakers' visits.
Data in the analysis of Comparative Study of the Impact of Dummy Variables on Regression Coefficients and Canonical Correlation Indices: an Empirical perspective
<p>This data is used in the analysis related to the article Comparative Study of the Impact of Dummy Variables on Regression Coefficients and Canonical Correlation Indices: an Empirical perspective. The data contain Crude Oil Prices, Exchange Rates, and Dummy variables coded 1 for the era before the Covid-19 outbreak and 0 for the era of Covid-19.</p> <p> </p>
Correlated k coefficients for H2-He atmospheres; 622 spectral windows and 1460 pressure-temperature points
<p>There are 10 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.622.tar.gz (5 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.622.tar.gz (5 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_100 should be read as 1x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 5 Fe/H values: 0.0, 0.5, 0.7, 1.0, and -0.3; and 1 C/O value: 1.0x solar. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 622_windows.txt (intervals defined as starting at lambda1 and ending at lambda2).</p> <p>The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper.</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Correlation coefficients of Bispectra
<p>Correlation coefficients of the halo bispectrum obtained from a set of 80 realizations of halo number-counts using the SLICS and BAM mock catalogs</p>
Correlated k coefficients for H2-He atmospheres; 196 spectral windows and 1460 pressure-temperature points
<p>There are 108 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.196.tar.gz (78 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.196.tar.gz (78 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_025 should be read as 0.25x C/O relative to solar, and co_200 as 2x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 13 Fe/H values: 0.0, 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7, 2.0, -0.3, -0.5, -0.7, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 196_windows.txt (intervals defined as starting at lambda1 and ending at lambda2). NB Please note that for metallicities between 1.3 and 2.0 the value of <em>max_windows</em> has changed from 200 to 1000.</p> <p>The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper.</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Correlated k coefficients for H2-He atmospheres; 180 spectral windows and 1460 pressure-temperature points
<p>There are 108 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.196.tar.gz (78 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.196.tar.gz (78 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_025 should be read as 0.25x C/O relative to solar, and co_200 as 2x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 13 Fe/H values: 0.0, 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7, 2.0, -0.3, -0.5, -0.7, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 180_windows.txt (intervals defined as starting at lambda1 and ending at lambda2). NB Please note that for metallicities between 1.3 and 2.0 the value of <em>max_windows</em> has changed from 200 to 1000.</p> <p>The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper.</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Correlated k coefficients for H2-He atmospheres; 11 spectral windows and 1460 pressure-temperature points
<p>There are 108 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.196.tar.gz (78 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.196.tar.gz (78 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_025 should be read as 0.25x C/O relative to solar, and co_200 as 2x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 13 Fe/H values: 0.0, 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7, 2.0, -0.3, -0.5, -0.7, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 11_windows.txt (intervals defined as starting at lambda1 and ending at lambda2). NB Please note that for metallicities between 1.3 and 2.0 the value of <em>max_windows</em> has changed from 200 to 1000.</p> <p>The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper.</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Correlated k coefficients for H2-He atmospheres; 30 spectral windows and 1460 pressure-temperature points
<p>There are 108 correlated k-coefficients datasets, using the naming convention sonora_2020_fehxxxx_co_yyy.data.196.tar.gz (78 models) or sonora_2020_fehxxxx_co_yyy_noTiOVO.data.196.tar.gz (78 models), where xxxx is the metallicity in 10x dex relative to solar, and yyy is the 100x C/O ratio relative to solar, as a multiplication factor. For example a metallicity of +000 and a C/O ratio of 100 indicates solar abundances, feh+070 should be read as a metallicity of +0.7 dex, feh-100 as -1.0 dex, co_025 should be read as 0.25x C/O relative to solar, and co_200 as 2x C/O relative to solar. We use the Lodders et al. 2010 value for the solar C/O=0.458. The files with “noTiOVO” in the filename contain the correlated k-coefficients calculated without the opacity of TiO and VO. The rest of the molecular abundances and opacities are the same as the equilibrium chemistry values in the regular files. These files are useful for calculating models without any TiO- and VO-induced temperature inversion in the atmosphere.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, with abundances given by equilibrium chemistry for each metallicity-C/O combination, as described in Marley et al. 2021. There are 13 Fe/H values: 0.0, 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7, 2.0, -0.3, -0.5, -0.7, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5. The k-coefficients are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list, and can be read in using the IDL script read_k_coefficients.pro. The spectral windows are listed in the file 30_windows.txt (intervals defined as starting at lambda1 and ending at lambda2). NB Please note that for metallicities between 1.3 and 2.0 the value of <em>max_windows</em> has changed from 200 to 1000.</p> <p>The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The corresponding high resolution opacities for these atoms and molecules can be found in the Zenodo repository 10.5281/zenodo.6600976. The references for the line lists used in these opacity calculations are listed in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper.</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1460-point pressure-temperature grid</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Коэффициенты корреляции повторяемости блокирования между секторами для северного и южного режимов для двух периодов. Blocking frequency correlation coefficients between sectors for northern and southern regimes for two periods.
<p>Представлены коэффициенты корреляции (выше порога 0.4) повторяемости блокирования между секторами для северного (NM) и южного режимов (SM) для ноября (nov), декабря (dec), января (jan) и февраля (feb) .</p> <p>Секторы показаны в https://doi.org/10.5281/zenodo.7489504</p> <p>Correlation coefficients (above a threshold of 0.4) of blocking frequency between sectors for northern (NM) and southern (SM) modes for November (nov), December (dec), January (jan) and February (feb) are presented.</p> <p>Sectors are shown at https://doi.org/10.5281/zenodo.7489504</p>
Cross-correlation coefficient maps generated in the paper "Correlation of Venusian Mesoscale Cloud Morphology Between Images Acquired at Various Wavelengths" by Narita et al. published in Journal of Geophysical Research - Planets
<p>This data archive contains the cross-correlation coefficient maps. Unzipping the compressed file, the following directories corresponding to different wavelength pairs appear. </p> <p> IR1_IR2/ : 0.9 micron & 2.02 micron<br> UVI283_UVI365/ : 283 nm & 365 nm<br> IR2_UVI365/ : 2.02 micron &. 365 nm<br> IR2_UVI283/ : 2.02 micron & 283 nm<br> IR2_LIR/ : 2.02 micron & 10 micron</p> <p>If usual unzip tools do not work, the use of 7zip is recommended:<br> https://www.7-zip.org/download.html</p> <p>Each directory contains CSV files for the longitude-latitude distribution of the correlation coefficient. The 2880 longitude grids cover the longitude range of 0 - 360 degrees, and the 1440 latitude grids cover the latitude range of -90 - +90 degrees, with a pixel resolution of 0.125 degree/pixel. Invalid regions are filled with the value of 1.1.</p> <p>Each filename is composed of the date, the instrument (wavelength), and the time. For example, for the file "20160720_ir2_150821_hp6_IR1_150209_hp6_sb24.csv":</p> <p> 20160720 : July 20, 2016<br> ir2 : 2.02 micron filter of IR2 camera<br> 150821 : IR2 exposure at 15:08:21<br> hp6: High-pass filtering size is 6 deg x 6 deg<br> IR1 : 0.9 micron filter of IR1 camera<br> 150209 : IR1 exposure at 15:02:09<br> sb24 : Sliding box size is 24 deg x 24 deg</p>
Genetic variation, genotypic and phenotypic correlation, heritability, and path coefficient analysis of yield and yield related traits in bread wheat (Triticum aestivum L.) varieties at Gitilo Dale, western Ethiopia
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The Pearson correlation coefficient matrix for all study items (N = 507)
<p>The Pearson correlation coefficient matrix for all study items (N = 507)</p>
Data from: Establishment of the falling film evaporation model and correlation of the overall heat transfer coefficient
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Time series of the correlation coefficient at seismic stations in the Mexican subduction zone
<p>The directory structure is as follows:<br> correlation_coefficient/[STATION]/[YYMMDD]</p> <p>Each file contains the time series of the correlation coefficient every 10 seconds for the data YYMMDD.</p>
Spectral Correlation Coefficient-based TMS
ClinicalTrials.gov study NCT04040062. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Assessing software defection prediction performance: why using the Matthews correlation coefficient matters
<p>The documents include raw data and survey papers for our research. </p>
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