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4,563 results for “correlations”
Cross-correlations of Days before the strike: precursory waveform decoherence preceding major strike-slip earthquakes
<p>Repository of </p> <h1>Days before the strike: precursory waveform decoherence preceding major strike-slip earthquakes</h1> <p>This dataset contains the cross-correlation functions of station pairs used for Ridgecrest, CA, Turkiye (EAFZ), and Aegean Sea (NAT). The dataset is compressed in a tar.gz. To decompress, use tar -xzvf filename.tar.gz. Download and decompress the cross-correlations dataset named WF_DEC_DAT_CC.tar.gz.</p> <h2>Description of the data and file structure</h2> <p>The dataset is organized by study area as follows: ZONE (Aegean, Ridgecrest, Turkey) with sub-directories CC (cross-correlation functions).</p> <p>Sub-directories CC contain sub-directories named according to station pairs (e.g., XXX_YYY) storing cross-correlation functions in numpy arrays organized by stacking (5, 10, and 20 days) and different frequency bands, adapted to use in the Ambient-Noise Seismology Package NoisePy <a href="https://github.com/noisepy/NoisePy">https://github.com/noisepy/NoisePy</a> (Jiang and Denolle, 2020).</p> <p>Data was derived from the following sources:</p> <ul> <li> <p>The raw data can be downloaded from <a href="https://ds.iris.edu/mda/CI/">https://ds.iris.edu/mda/CI/</a> (for Ridgecrest dataset) and <a href="https://www.orfeus-eu.org/data/">https://www.orfeus-eu.org/data/</a> for (Turkey and Aegean Sea datasets). The cross-correlation functions computed using MSNoise <a href="http://msnoise.org/doc/index.html">http://msnoise.org/doc/index.html/</a> Lecocq et al (2014).</p> </li> </ul> <h2>Code/Software</h2> <p>To reproduce the results and conclusion of the manuscript, use the Jupyter notebooks available at <a href="https://github.com/fjmunozb/EQ_Precursors">https://github.com/fjmunozb/EQ_Precursors</a>. Find also python environments to install MSNoise and NoisePy.</p>
Dataset for Paul et al., "Trace metals in coastal marine sediments: Natural and anthropogenic sources, correlation matrices, and proxy potentials", Science of The Total Environment (STOTEN-175789, 2024)
<p>The datafile (.xlsx format) contains the solid phase data for all study sites presented in the associated STOTEN publication <a href="https://doi.org/10.1016/j.scitotenv.2024.175789" target="_blank" rel="noopener">(10.1016/j.scitotenv.2024.175789)</a></p> <ol> <li>specifics on the ICP-MS and ICP-OES analysis</li> <li>solid-phase data (Pb, Cd, Cu, Zn, Sb, Sn, Ni, As, Tl, V, Mo, U, Re, TOC, S, Fe, Mn, and Al)</li> <li>coefficient of variation test results (as a basis for evaluating the applicability of data normalizations to the data; i.e. calculation of Enrichment Factors, cf. method section of the original publication)</li> </ol> <p>Please note that the title of the paper and the publication number has changed upon final publication. The Excel file description still refers to the original manuscript number and title "Trace metals in coastal marine sediments: anthropogenic sources, correlation patterns, and proxy potentials".</p>
Data and code for "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. 2024
<p>This data and code is made available to support the article: "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. 2024".</p> <p>Includes: TMOC method output tide correlation, Antarctic Peninsula grounding line, DInSAR data, TMOC Code.</p> <p> </p> <p><strong>For the data:</strong></p> <p>These data are made available to acompany the article "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. (2024)</p> <p>This datset contains:</p> <p>AP_TMOC_tide_correlation_2019_2020.tif - Significance adjusted tide correlation values for the TMOC method for 2019-2020 for the Antarctic Peninsula.</p> <p>AP_GL_TMOC_2019_2020.shp - A continuous grounding line made from TMOC data and British Antarctic Survey Coastline Data. Intended for use by others.</p> <p>AP_GL_TMOC_2019_2020_source.shp - A discontinuous grounding line made from TMOC data and British Antarctic Survey Coastline Data including the source of each line segment.</p> <p>The folder 'Interferograms' contains the DInSAR products used in the manuscript, sorted by Sentinel-1 frame</p> <p> </p> <p><strong>For the code:</strong></p> <p>This code is made available to support the article "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al.</p> <p>The authors take no responsibility for the quality of results derived using this code.</p> <p>This code is licensed under a Creative Commons Attribution 4.0 International Licence: http://creativecommons.org/licenses/by/4.0/</p> <p>external functions required:<br>geoimread - https://uk.mathworks.com/matlabcentral/fileexchange/46904-geoimread<br>polarstreo_inv - https://uk.mathworks.com/matlabcentral/fileexchange/32907-polar-stereographic-coordinate-transformation-map-to-lat-lon<br>CATS208 tide model and TMD 2.5 matlab toolbox - https://www.esr.org/research/polar-tide-models/tmd-software/</p> <p>The function TMOC_GL_v8 implements the TMOC method descibed in Wallis et al. 2024. This is a 'bring your own data' version.</p> <p>The script pp_folder prost-processes the outputs using the functuon LPfilt_cc</p> <p> </p>
Antagonism correlates with metabolic similarity in diverse bacteria
<p>Data and code for the PNAS article:</p> <p>Antagonism correlates with metabolic similarity in diverse bacteria</p>
Correlating Movies score and Unemployed rate
<p>A study showing the relationship between the unemployed and the average rating of movies in the same years</p>
Data - Medial gastrocnemius muscle remodeling correlates with reduced plantar flexor kinetics fourteen weeks following Achilles tendon rupture
<p>ultrasound images and biodex data published used in analysis.</p> <p>study timeline:</p> <p>s1 - week 0</p> <p>s2 - week 2</p> <p>s3 - week 4</p> <p>s4 - week 6</p> <p>s5 - week 10</p> <p>s6 - week 14</p>
Effects of earthquake spatial slip correlation on variability of tsunami intensity variables
<p>Data entry to reproduce the tsunamis with the aid of GeoClaw, as well as the spatial earthquake slip rupture.</p>
data set related to article Broad phenotypic spectrum and genotype-phenotype correlations in GMPPB-related dystroglycanopathies: an Italian cross-sectional study
<p>This record contains raw data related to article Broad phenotypic spectrum and genotype-phenotype correlations in GMPPB-related dystroglycanopathies: an Italian cross-sectional study</p>
Ground reaction force metrics are not strongly correlated with tibial bone load when running across speeds and slopes: implications for science, sport and wearable tech
<p>An interactive user interface and the raw data from the manuscript titled: "Ground reaction force metrics are not strongly correlated with tibial bone load when running across speeds and slopes: implications for science, sport and wearable tech". </p>
Fine Three-Dimensional VHF Lightning Mapping Using Waveform Cross-Correlation TOA Method
<p>In a manuscript entitled “Fine Three-Dimensional VHF Lightning Mapping Using Waveform Cross-Correlation TOA Method”, the lightning data obtained by an improved VHF 3-D location system were analyzed. The data supports the aforementioned manuscript and can be used freely for scientific purposes with appropriate citation.</p>
Academic Excellence, Website Quality, SEO Performance: Is there a Correlation? - Dataset of measurements, test results and calculated ratings.
<p>This Dataset, in two files of xlsx format, contains the data of all measurements, test results and calculated ratings as they are described in the methodology of the research article "Academic Excellence, Website Quality, SEO Performance: Is there a Correlation".</p>
Correlation maps for Planet Scope Imagery
<p>Correlation maps used for Ridgecrest analysis </p>
Time-slide correlation analysis of post-merger Extended Emission to GW170817
<p>Nico van Kampen Colloquium, ITP, Utrecht (October 23 2019, https://zenodo.org/record/3528005) - Movie clip. Shown is the result of $\chi$-image analysis of merged (H1,L1)-spectrograms produced in time-slide correlation analysis of H1-L1 data of GW170817. Time-sliding over -32s $\le \Delta t \le 32$s, including one-sample steps around the zero-crossing $\Delta t = 0$, reveals clustering of $\chi$-peak values representing a correlated (H1,L1)-detector response to a gravitational-wave signal.</p>
Fig. 1 in Biozonation And Correlation Of Two Wells In Niger Delta Using Calcareous Nannofossils
Fig. 1 Geologic map of the Niger Delta region (after Correldor et al. 2005)
Figure 1 in Ostracoda (Crustacea) species composition and environmental correlates in different aquatic habitats of the Zonguldak and Bartın regions (Turkey)
Figure 1. Total of 105 sampling sites from Bartın (B1–B49 sites) and Zonguldak (Z1–Z56).
An attached table for "The Correlation between Dip Width and Peak Flux in Cir X-1"
<p>This is an attached table for "The Correlation between Dip Width and Peak Flux in Cir X-1".<br>The table introduces derived phases from Bayesian blocks technique and peak fluxes in Cir X-1.</p> <p>orbit: the orbits of Cir X-1 in Nicolson(2007)'s ephemeris<br>dip_in,dip_in_err,dip_out,dip_out_err: the dip-in/out phases and errors<br>dip_width,dip_width_err: the dip width and its error in every orbit<br>peak_flux,peak_flux_err: the peak flux and its error in every orbit, which are in units of Crab</p>
Self-reported preferences for Daylight Saving Time meet fundamentals of human physiology: correlations in the 2018 Public Consultation by the European Commission
<p>Dataset for the preprint entitled "Preferences for Daylight Saving Time meet fundamentals of human physiology:<br>correlations in the 2018 Public Consultation by the European Commission"</p> <p> </p> <p>Data by 2018 Member State (28 rows)</p> <p>Variables in the dataset: 19.</p> <p> </p> <p>No headers in the main csv file.</p> <p>The meta csv contains variable descriptions. One row per one variable (column) in the main dataset. </p> <p> </p> <p> </p>
Data release for the "First measurement of muon neutrino charged-current interactions on hydrocarbon without pions in the final state using multiple detectors with correlated energy spectra at T2K"
<p>### On-/Off-Axis Data Release<br>#### (Version 1.0.1, dated 2024/08/12)</p> <p>This tar archive contains the data release for ‘First measurement of muon neutrino charged-current interactions on hydrocarbon without pions in the final state using multiple detectors with correlated energy spectra at T2K’. It contains the cross-section data points and supporting information in ROOT and text format, which are detailed below:</p> <p>+ `onoffaxis_xsec_data.root`<br>This ROOT file contains the extracted cross section and the nominal MC prediction as TH1D histograms for both the flattened 1D array of bins and in the angle binning for the analysis. The ROOT file also contains both the covariance and inverted covariance matrix for the result stored as TH2D histograms. The angle bin numbering and the corresponding bin edges are detailed at the end of the README.</p> <p>+ `flux_analysis.root`<br>This ROOT file contains the nominal and post-fit flux histograms for ND280 and INGRID. Two different binnings are included: a fine binned histogram (220 bins) and a coarse binned histogram (20 bins). The coarse binned histogram corresponds to the flux parameters detailed in the paper (and bin edges listed in the appendix).</p> <p>+ `xsec_data_mc.csv`<br>The extracted cross-section data points and the nominal MC prediction for each bin is stored as a comma-separated value (CSV) file with header row.</p> <p>+ `cov_matrix.csv` and `inv_matrix.csv`<br>The covariance matrix and the inverted covariance matrix are both stored as CSV files with each row stored as a single line and columns separated by commas (there is no header row). Matrix element (0,0) corresponds to the first number in the file.</p> <p>+ `nd280_analysis_binning.csv` and `ingrid_analysis_binning.csv`<br>The analysis bin edges are included as CSV files. The columns are labeled with a header row and denote the linear bin index and the lower and upper bin edge for the angle and momentum bins. The units are in cos(angle) for the angle bins and in MeV/c for the momentum bins.</p> <p>+ `calc_chisq.cxx`<br>This is an example ROOT script to calculate the chi-square between the data and the nominal MC prediction using the ROOT file in the data release. To run, open ROOT and load the script (`.L calc_chisq.cxx`) and execute the function `calc_chisq("/path/to/file.root")`.</p> <p>+ `calc_chisq.py`<br>This is an example Python script to calculate the chi-square between the data and the nominal MC prediction using the text/CSV files in the data release. The code requires NumPy as an external dependency, but otherwise uses built-in modules. To run, execute using a Python3 interpreter and give the file paths to the data/MC text file and the inverse covariance text file as the first and second arguments respectively -- e.g. `python3 calc_chisq.py /path/to/xsec_data_mc.csv /path/to/inv_matrix.csv`</p> <p>+ ND280 angle bin numbering<br> - 0: `-1.0 < cos(#theta) < 0.20`<br> - 1: `0.20 < cos(#theta) < 0.60`<br> - 2: `0.60 < cos(#theta) < 0.70`<br> - 3: `0.70 < cos(#theta) < 0.80`<br> - 4: `0.80 < cos(#theta) < 0.85`<br> - 5: `0.85 < cos(#theta) < 0.90`<br> - 6: `0.90 < cos(#theta) < 0.94`<br> - 7: `0.94 < cos(#theta) < 0.98`<br> - 8: `0.98 < cos(#theta) < 1.00`</p> <p>+ INGRID angle bin numbering<br> - 0: `0.50 < cos(#theta) < 0.82`<br> - 1: `0.82 < cos(#theta) < 0.94`<br> - 2: `0.94 < cos(#theta) < 1.00`<br> <br>### Changelog</p> <p>#### v1.0.1<br>Fix transcription error in INGRID momentum binning. The lowest momentum bin edge is at 350 MeV/c, not 300 MeV/c.</p>
New Insights into the Correlation between Bone Mineral Density at Various Sites and Dental Caries: Highlighting the Role of Head Bone Mineral Density
<p> Investigate the relationship between bone mineral density (BMD) at various body sites and dental caries.<br>Materials and methods: Based on the National Health and Nutrition Examination Survey (NHANES) database from 2011-2016, the correlation between BMD at various body sites and the DMFS index among 7044 adults aged 20-59 years was analyzed. Multiple linear regression, restricted cubic splines (RCS), piecewise linear regression, logistic regression, weighted quantile sum regression (WQS) and mediation effects analysis were integrated to explore the relationship between BMD and dental caries.<br>Results: Under the linear assumption, except for arm BMD, the BMDs of all other sites are negatively correlated with the DMFS index of dental caries. RCS analysis indicates a U-shaped relationship between head BMD and the DMFS index (p for nonlinear < 0.0001). WQS analysis indicates that mixed BMD is significantly negatively correlated with the DMFS index for dental caries (estimate, −0.023; 95% CI, −0.025 ~ −0.020), and head BMD has the most significant impact on the DMFS index (weight = 91.4%). Simple mediation analysis of the effect of dental caries on BMD levels mediated by inflammation levels showed negative results, suggesting that dental caries may not influence BMD through inflammation levels.<br>Conclusion: Monitoring BMD should be combined with appropriate oral healthcare and caries management strategies to effectively address these interconnected health issues, and particular attention should be paid to the monitoring of head BMD.</p>
FIGURE 7 in Graphic correlation of the upper Eifelian to lower Frasnian (Middle-Upper Devonian) conodont sequences in the Spanish Central Pyrenees and comparison with composite standards from other areas
FIGURE 7. Correlation of the three sections based on the results of the graphic correlation method.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.