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4,376 results for “magnetization”
Derivation of Hemispheric Ionospheric Current Functions From Ground-Level Magnetic Fields
<p>These files provide the input and output data for the Figures shown in the paper "Derivation of<br> Hemispheric Ionospheric Current Functions From Ground-Level Magnetic Fields" by Daniel Weimer, published in the Journal of Geophysical Research, Space Physics, paper number 2018JA026191, doi:10.1029/2018JA026191</p> <p>Two IDL program files and the original, PDF versions of the figures are included.</p> <p>The data are provided as IDL "SAVE" files, readable in IDL with the "RESTORE" command. NetCDF<br> versions are included, readable with any NetCDF software library. These NetCDF files have the same<br> names as the ".xdr" files, except they have the extension ".nc". Scalar variables (length 1) are put<br> into the Global Attributes in these files.</p> <p>The files in this archive are:</p> <p>Figures:<br> Figure_1.PDF<br> Figure_2.PDF<br> Figure_3.PDF<br> Figure_4.PDF<br> Figure_5.PDF<br> Figure_6.PDF</p> <p>IDL Programs:<br> spherical_cap_90_fits.pro : Routines for fitting magnetic field data on a hemispheric cap (90<br> degrees), using spherical harmonics having both internal and external sources (or external alone),<br> and functions for evaluating the results as equivalent currents, or the magnetic field components.</p> <p> AllLegendre.pro : Required by spherical_cap_90_fits.pro, provides computations of Associated<br> Legendre Polynominals as arrays, for all combinations of l and m, up to Lmax and Mmax, as well as first derivatives.</p> <p>Data Files:</p> <p> Figures_1_2_3_4_dB_ModelData.xdr : Magnetic field values (output from the 2013 empirical model),<br> shown in Figure 1, and used to calculate the coefficients used to make Figures 2, 3, and 4.<br> Contents:<br> ALLLATS FLOAT = Array[8640] , array of latitude values, degrees<br> ALLMLTS FLOAT = Array[8640] , array of Magnetic Local Time (MLT) values, hours<br> DBNS FLOAT = Array[8640] , array of northward magnetic field values<br> DBES FLOAT = Array[8640] , array of eastward magnetic field values<br> DBVS FLOAT = Array[8640] , array of vertical (downward) magnetic field values<br> NLATS FLOAT = 180.000<br> NMLTS INT = 48<br> empirical model inputs:<br> BT FLOAT = 10.0000 , magnitude of the IMF<br> ANGLE FLOAT = 180.000 , IMF clock angle<br> F107 FLOAT = 120.000 , F10.7 solar index<br> SWVEL FLOAT = 400.000 , solar wind velocity<br> TILTA FLOAT = 0.00000 , dipole tilt angle</p> <p> Figures_2_3_4_SCHA90FitResults.xdr : The coefficients obtained from the fits, used to generate<br> Figures 2, 3, and 4.<br> Contents:<br> SPHCE DOUBLE = Array[115] , external spherical harmonic coefficients<br> SPHCI DOUBLE = Array[115] , interal spherical harmonic coefficients<br> NOINT_SPHCE DOUBLE = Array[115] , external spherical harmonic coefficients,<br> derived without using the internal terms in the fitting of the magnetic potential<br> The following variables are documented in the IDL program spherical_cap_90_fits.pro:<br> MAXL INT = 34<br> MAXM INT = 3<br> ODD INT = 1<br> EVEN INT = 0<br> CSIZE INT = 115<br> LS INT = Array[115]<br> MS INT = Array[115]<br> AB BYTE = Array[115]</p> <p> Figures_3_4_dB_ModelData-Dst.xdr : Magnetic field values, after subtraction of the ring current<br> magnetic field, used to calculate the coefficients to make Figures 3 and 4.<br> Contents: Same variables as in file Figures_1_2_3_4_dB_ModelData.xdr</p> <p> Figures_3_4_SCHA90FitResults-Dst.xdr : The coefficients obtained from fitting the magnetic field<br> that had the ring current subtracted, used to make Figures 3, and 4.<br> Contents: Same variables as in file Figures_2_3_4_SCHA90FitResults.xdr</p> <p> Figure_5_dB_ModelDataTilt3x-Dst.xdr : eight sets of magnetic field values, after subtraction of the<br> ring current magnetic field, used to calculate the coefficients to generate Figure 5.<br> Contents: Similar variables as in file Figures_1_2_3_4_dB_ModelData.xdr, except that TILTA is<br> replaced by TILTS, an array with the eight dipole tilt angles. The magnetic field values are<br> replaced by these arrays:<br> DBN3X FLOAT = Array[180, 48, 3] , northward magnetic field, eight sets<br> DBE3X FLOAT = Array[180, 48, 3] , eastward magnetic field, eight sets<br> DBV3X FLOAT = Array[180, 48, 3] , vertical magnetic field, eight sets</p> <p> Figure_5_SCHA90FitResultsTilt3x-Dst.xdr : eight sets of coefficients obtained from fitting the<br> magnetic field, used to make Figure 5.<br> Contents: Same variables as in file Figures_2_3_4_SCHA90FitResults.xdr, except for these arrays:<br> SPHCE3X DOUBLE = Array[115, 3] , external spherical harmonic coefficients, eight sets<br> SPHCI3X DOUBLE = Array[115, 3] , internal spherical harmonic coefficients, eight sets</p> <p> Figure_6_dB_ModelDataClock8x-Dst.xdr : Eight sets of magnetic field values, after subtraction of<br> the ring current magnetic field, used to calculate the coefficients to generate Figure 6.<br> Contents: Similar variables as in file Figures_1_2_3_4_dB_ModelData.xdr, except that ANGLE is<br> replaced by ANGLES, an array with the eight IMF clock angles. The magnetic field values are<br> replaced by these arrays:<br> DBN8X FLOAT = Array[180, 48, 8] , northward magnetic field, eight sets<br> DBE8X FLOAT = Array[180, 48, 8] , eastward magnetic field, eight sets<br> DBV8X FLOAT = Array[180, 48, 8] , vertical magnetic field, eight sets</p> <p> Figure_6_SCHAFitResultsClock8x-Dst.xdr : Eight sets of coefficients obtained from fitting the<br> magnetic field, used to make Figure 6.<br> Contents: Same variables as in file Figures_2_3_4_SCHA90FitResults.xdr, except for these arrays:<br> SPHCE8X DOUBLE = Array[115, 8] , external spherical harmonic coefficients, eight sets<br> SPHCI8X DOUBLE = Array[115, 8] , internal spherical harmonic coefficients, eight sets<br> </p>
EMAG2: Earth Magnetic Anomaly Grid (2-arc-minute resolution) compressed for NumPy
<p>A compressed NumPy version of the <a href="https://www.ngdc.noaa.gov/geomag/emag2.html">EMAG2 (v3)</a> global Earth Magnetic anomaly grid compiled from satellite, ship, and airborne magnetic measurements. The original CSV data was imported, transformed, and saved to a compressed NumPy archive as follows:</p> <pre><code class="language-python">import numpy as np mag_data = np.loadtxt('EMAG2_V3_20170530.csv', delimiter=',', usecols=(2,3,4,5,7)) lon_mask = mag_data[:,0] > 180.0 mag_data[lon_mask,0] -= 360.0 np.savez_compressed('EMAG2_V3_20170530.npz', data=mag_data.astype(np.float32))</code></pre> <p>The NumPy archive (contained in this repository) can be efficiently loaded in Python workflows. It contains the following columns:</p> <ol> <li>Longitude - geographic longitudinal coordinates in decimal degrees (WGS84)</li> <li>Latitude - geographic latitudinal coordinates in decimal degrees (WGS84)</li> <li>SeaLevel - magnetic anomaly value at sea level (nT)</li> <li>UpCont - magnetic anomaly value at continuous 4km altitude (nT)</li> <li>Error - Error estimate (nT)</li> </ol> <p>Code 888 is assigned in certain cells on grid edges where the data source is ambiguous and assigned an error of -888 nT.<br> Code 999 is assigned in cells where no data is reported with the anomaly value assigned 99999 nT and an error of -999 nT.</p> <p><strong>Reference</strong></p> <p>Brian Meyer, Richard Saltus, Arnaud Chulliat (2017): EMAG2: Earth Magnetic Anomaly Grid (2-arc-minute resolution) Version 3. National Centers for Environmental Information, NOAA. Model. doi:10.7289/V5H70CVX</p>
Continuous magnetic phase transition in artificial square ice
<p>Open access data set for manuscript "Continuous magnetic phase transition in artificial square ice" published in Physical Review B, <strong>99</strong>, 214430 (2019)</p>
The complex non-collinear magnetic orderings in Ba2YOsO6: A new approach to tuning spin-lattice interactions and controlling magnetic orderings in frustrated complex oxides
<p><strong>Project abstract</strong>: Frustrated magnets are one class of fascinating materials that host many intriguing phases such as spin ice, spin liquid and complex long-range magnetic orderings at low temperatures. In this work we use first-principles calculations to find that in a wide range of magnetically frustrated oxides, at zero temperature a number of non-collinear magnetic orderings are more stable than the type-I collinear ordering that is observed at finite temperatures. The emergence of non-collinear orderings in those complex oxides is due to higher-order exchange interactions that originate from second-row and third-row transition metal elements. This implies a collinear-to-noncollinear spin transition at sufficiently low temperatures in those frustrated complex oxides. Furthermore, we find that in a particular oxide Ba2YOsO6, experimentally feasible uniaxial strain can tune the material between two different non-collinear magnetic orderings. Our work predicts new non- collinear magnetic orderings in frustrated complex oxides at very low temperatures and provides a mechanical route to tuning complex non-collinear magnetic orderings in those materials. <br> <br> <strong>About this entry</strong>: We provide the input files of our DFT calculations for the studied complex oxides. The structures in POSCAR format and the INCAR files for all stabilized magnetic orderings in our study are all included. These files can be directly used into DFT calculations with VASP. Only the versions of PAW potentials are included in POT.info files owing to the VASP license restrictions.</p>
Magnetic data grids of the Northern Vosges, surveys EOST2008 and GPR2015.
<p>Grid computation and details are explained in Gavazzi et al., 2019 [1] and exploited in Bertrand et al., [2].<br> This file contains non-null grid elements.</p> <p>PARAMETERS<br> Format : ASCII<br> Number of elements : 86902<br> Grid cell size : 125 m</p> <p>FIELDS<br> - LON : grid cell WGS84 longitude (°East);<br> - LAT : grid cell WGS84 latitude (°North );<br> - ALT : grid cell altitude amsl (m) - this grid was computed at a constant altitude of 1400 m above mean sea level;<br> - TMI : total magnetic intensity anomaly (nT);<br> - RTP : (double) reduction to the pole of the TMI (nT) - mean regional field direction Inclination=1.60°, Declination=64.14°;<br> - DV : vertical derivative of the RTP at order 0.5 (nT/m);<br> - DH : horizontal derivative of the RTP at order 1 (nT/m);</p> <p>[1] Gavazzi, B., Bertrand, L., Munschy, M., Mercier de Lépinay, J., Diraison, M. & Géraud, Y. (submitted). On the use of aeromagnetism for geological interpretation part I: comparison of 1 scalar and vector magnetometers for aeromagnetic surveys and an equivalent source 2 interpolator for combining, gridding and transform fixed altitude and draping 3 datasets, Journal of Geophysical Research: Solid Earth (2019).</p> <p>[2] Bertrand, L., Gavazzi, B., Mercier de Lépinay, J., Diraison, M., Géraud, Y. & Munschy, M. (submitted). On the use of aeromagnetism for geological interpretation part II: geological interpretation on outcropping basement rocks for geothermal energy prospection, Journal of Geophysical Research: Solid Earth (2019).</p>
MetaboScope: A statistical toolbox for analyzing 1H nuclear magnetic resonance spectra from human clinical studies.
<p>MetaboScope is purposefully built as a pipeline where each module accepts the output generated by the previous one. This provides flexibility and simplicity of use, while being straightforward to maintain. The system and its libraries were developed in JavaScript and run as a web app; therefore, all the operations are performed on the local computer, circumventing the need to upload data. The code is open source (DOI: https://www.cheminfo.org/flavor/metabolomics/index.html) and can be readily installed locally. We provide module notes and video tutorials, in addition to clinical spectral datasets for modelling purposes.</p> <p>View data:</p> <p><a title="nmrium.org" href="https://www.nmrium.org/nmrium#?toc=https://zenodo.org/api/records/12916741/files/toc.json/content" target="_blank" rel="noopener">https://www.nmrium.org/nmrium#?toc=https://zenodo.org/api/records/12916741/files/toc.json/content</a></p>
Magnetic Field Measurements above a Phonolite Diatreme near Rockeskyll, West Eifel, Germany
Open the record for dataset details and reuse information.
Reducing cardiac-induced noise in brain maps of R2* and magnetic susceptibility
<p>This high resolution dataset contain MR images of one participant acquired with a standard linear sampling and a cartesian pseudo-spiral sampling, with 3 repetitions each. It also contain the corresponding R2* and QSM maps shown in the paper. The data are presented both as .nii and .mat files.</p>
BepiColombo magnetic field data (MPO-MAG) from the two Venus flybys
<p> </p> <p>Vector magnetic field data from the first two Venus flybys (highres and 1-sec res).</p> <p>*Data will be properly archived on ESA's PSA, once the data has been finalized and/or cleaned*</p> <p>Reference frame: VSO</p> <p>Trajectory information is also included. </p>
IODP Expedition 398 Magnetic susceptibility (Kappabridge)
Bulk magnetic susceptibility and anisotropy of magnetic susceptibility (AMS) were measured on discrete samples using an Agico KLY-4 Kappabridge susceptibility meter. Report includes individual and average principal susceptibilities, inclination and declination of principal susceptibilities, and volume-corrected bulk susceptibility.
IODP Expedition 398 Magnetic susceptibility (whole round)
Magnetic susceptibility was measured on whole-round sections (and rarely section halves) on the Whole-Round Multisensor Logger (WRMSL) and/or Special Task Multisensor Logger (STMSL) using a Bartington MS2 meter and a 90 mm or 80 mm MS2C loop. As volume of the sample is not controlled for this experiment, susceptibility units are recorded in instrument units and are not volume-corrected.
IODP Expedition 398 Magnetic susceptibility (point or contact system)
Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).
IODP Expedition 398 Magnetic remanence (SRM-longcore)
Magnetic remanence was measured on section halves (and rarely on whole-round sections) using a 2G Enterprises 760R cryogenic magnetometer, first as natural remanent magnetization (NRM) and then after demagnetization steps were performed on the samples by alternating field (AF) demagnetizer coils mounted in-line within the instrument.
Data for "Impact of the Out-of-Plane Flow Shear on Magnetic Reconnection at the Flanks of Earth's Magnetopause"
<p>Data for Figures 3-8 in the paper (data for Figures 5 has been updated on 2024-09-20). The data is compatible with all data-analysis software. Here are the guidelines for reading and visualizing the data:</p> <p>(1) The filenames "noshear", "MA0p7", and "MA2p3" correspond to the simulation runs with no flow shear, Mach number M_A=0.7 flow shear, and M_A=2.3 flow shear.</p> <p>(2) The "upper" and "lower" mean upper and lower current sheet, corresponding to dusk-side and dawn-side reconnection respectively. For the "noshear" case, only the "upper" is considered.</p> <p>(3) Each data file (*.dat) is written in ASCII format and has multiple columns. The first row is the header.</p> <ul> <li>The first column is always the x-coordinates of the figure. </li> <li>For the line plots, all columns starting from the second column are the y-coordinates for different variables. The variables names can be found at the header. </li> <li>For the 2D image plots, the second column is the y-coordinates, and the third column is the value of the variable at a given (x,y) location. </li> </ul> <p>(4) The files "fig4_*_field_*.dat" are the magnetic potential in the x-y domain. The contour of this potential gives the in-plane field line configurations.</p>
Light-Induced Metallic and Paramagnetic Defects in Halide Perovskites from Magnetic Resonance
<p>EPR and NMR data for the research article titled "Light-Induced Metallic and Paramagnetic Defects in Halide Perovskites from Magnetic Resonance". For further details see the readme.txt file. DOI: https://doi.org/10.1021/acsenergylett.4c02557</p>
IODP Expedition 355 Magnetic susceptibility (whole round)
Magnetic susceptibility was measured on whole-round sections (and rarely section halves) on the Whole-Round Multisensor Logger (WRMSL) and/or Special Task Multisensor Logger (STMSL) using a Bartington MS2 meter and a 90 mm or 80 mm MS2C loop. As volume of the sample is not controlled for this experiment, susceptibility units are recorded in instrument units and are not volume-corrected.
IODP Expedition 355 Magnetic susceptibility (point or contact system)
Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).
Fast calculation methods for the magnetic field of particle lattices: Datasets and scripts
<div>*********************************************** README.txt **************************************************</div> <div> </div> <div>Title: Fast calculation methods for the magnetic field of particle lattices: </div> <div>Datasets and scripts</div> <div>Version: 1.0</div> <div>Date of Release: 2024/10/11</div> <div>Identifier: doi:10.5281/zenodo.13930969</div> <div>Permalink: http://dx.doi.org/10.5281/zenodo.13930969</div> <div> </div> <div>*************************************************************************************************************</div> <div> </div> <div>Associated publication: I. Royo-Silvestre, D. Gandia, J. J. Beato-López, E. Garaio, C. Gómez-Polo </div> <div>"Fast calculation methods for the magnetic field of particle lattices" </div> <div>(paper yet to be published)</div> <div> </div> <div>Link to publication: (paper yet to be published)</div> <div> </div> <div>Suggested citation: Please reference the associated publication above when using any datasets or</div> <div> materials described in this README file.</div> <div> </div> <div>Contact information: Isaac Royo Silvestre, </div> <div>Universidad Pública de Navarra, </div> <div>Pamplona, Spain, </div> <div>isaac.royo@unavarra.es</div> <div> </div> <div>License: CC BY 4.0</div> <div> </div> <div>------------------------------------------------------------------------------------------------------------</div> <div> </div> <div>This directory contains the following datasets and supplementary materials:</div> <div> </div> <div> ------------------------------</div> <div> SCRIPTS</div> <div> ------------------------------</div> <div> </div> <div> - scripts.zip Matlab scripts (compressed zip file) used to calculate the magnetic field of </div> <div>lattices of magnetic particles by analytical and semianalytical methods (more information in the associated paper) </div> <div> </div> <div> --------------------------------</div> <div> DATASETS</div> <div> --------------------------------</div> <div> </div> <div> - data.zip: Tabular data required to plot curves (compressed zip file) in csv format,</div> <div>also data used to obtain average values</div> <div> </div> <div> </div> <div>Specific documentation of each file is described in readme files.</div> <div> </div> <div>Refer to the original manuscript (see above) for additional information regarding the collection and generation of these data.</div> <div> </div> <div>------------------------------------------------------------------------------------------------------------</div> <div> </div> <div> ---------------------------------------------------------------------</div> <div> DOCUMENTATION FOR 'scripts.zip'</div> <div> ---------------------------------------------------------------------</div> <div> </div> <div> The zip file contains another readme.txt file (that explains the content of the zip file in detail), </div> <div>and multiple .m files. m files are Matlab scripts, text files that can be read using any text editor. However it has to be executed via Matlab, scripts contain documentation as comments.</div> <div> </div> <div> ---------------------------------------------------------------</div> <div> DOCUMENTATION FOR 'data.zip'</div> <div> ---------------------------------------------------------------</div> <div> </div> <div> The zip file contains another readme.txt file (that explains the content of the zip file in detail), </div> <div>multiple .dat files with data used to obtain averaged valus (see format in the readme.txt </div> <div>contained in the zip), and a folder "curves".</div> <div>The curves folder contains tabular data in .csv files, these files can be used to plot the curves</div> <div>in the manuscript.</div> <p> </p>
IODP Expedition 356 Magnetic remanence (SRM-discrete)
Raw data files for the magnetic remanence measurements of discrete and section-half samples on the superconducting rock magnetometer (SRM-DISC and SRM-SECT) are stored on by hole and by expedition, and are designated as discrete samples, section halves, or, rarely, whole-round sections.
IODP Expedition 356 Magnetic susceptibility (whole round)
Magnetic susceptibility was measured on whole-round sections (and rarely section halves) on the Whole-Round Multisensor Logger (WRMSL) and/or Special Task Multisensor Logger (STMSL) using a Bartington MS2 meter and a 90 mm or 80 mm MS2C loop. As volume of the sample is not controlled for this experiment, susceptibility units are recorded in instrument units and are not volume-corrected.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.