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562 results for “faulting”
Data for "Fault-tolerant quantum architectures based on erasure qubits"
<p>Example Stim circuits used to simulate Floquet codes implemented with erasure qubits. Each circuit is the converted stabilizer circuit for a given pattern of erasure check detection events. To view the circuit diagram, please download the file and change the extension to html.</p>
Seismic reflection data of profile across the Central Basin Fault and the Kyushu-Palau Ridge
<p>Seismic reflection profiles were acquired in 2020 by the R/V "Dayanghao" (Second Institute of Oceanology, Ministry of Natural Resources, China) using a 6040 cubic inch air gun array, discharged at 37.5 m intervals, and a 6-km-long, 480-channel streamer. Data were recorded for 14 s at 2 ms sampling intervals. Seismic data processing involved noise reduction, signal enhancement via filtering and deconvolution, velocity analysis, time migration, and depth migration. </p>
Data from the manuscript "Is the 2010 Maule Earthquake a repeating earthquake? Rupture heterogeneities and their impact on ground motion, landslides and cortical faults in Subduction Zones. "
<p>MATLAB data and codes used for the manuscript are provided. These calculate ground motion from a heterogeneous rupture, similar to the approach used in Venegas-Aravena (2024). The rupture simulation can be performed using the 'HE_B rupture.mat' code, which implements the Heterogeneous Energy-Based method (Venegas-Aravena, 2023) to model the 2010 Mw 8.8 Maule earthquake. The code for generating ground motion, 'Displacement_field.mat', calculates near-, intermediate-, and far-field displacement fields following equations 4.32 in Aki and Richards (2002) as a summation of point sources from the earthquake rupture. The subduction geometry is included in this dataset. The code can compute displacements in rho, theta, phi, direction and in east-west, north-south, and dip directions after following code instructions. Additionally, it includes a feature to add Rayleigh waves, although this was not utilized in the 2010 Maule earthquake manuscript.<br><br>A video showing the data can be seen here: <strong>https://youtu.be/6Zf3fgb6AGc.</strong><br><br><br>References</p> <p>Aki and Richards (2002): QUANTITATIVE SEISMOLOGY, SECOND EDITION.</p> <p>Venegas-Aravena (2023): https://doi.org/10.1515/geo-2022-0522.</p> <p>Venegas-Aravena (2024): https://doi.org/10.1007/s11069-024-06651-9.<br><br></p>
Computational modeling and analytical validation of singular geometric effects in fault data using a combinatorial approach - Input and processed data
<p>The archive contains the input and processed data for the companion manuscript.</p> <p>The input data contains XYZ coordinates of points documenting the investigated interfaces. The output datasets contain directional data from applying the combinatorial algorithm to point data sets.</p> <p>We have also included .VTU and .PVSM files for visualization of the geological settings in ParaView.</p>
Important role of intra-transform spreading centers in shaping thermal structure along the Blanco transform fault
<p>The input files for the six models presented in the paper are included in the accompanying compressed file.</p>
Measurement-free, scalable and fault-tolerant universal quantum computing
<p>The repository is supporting the publication "Measurement-free, scalable and fault-tolerant universal quantum computing". </p> <p>It includes the data shown in the manuscript as well as the simulation code and circuits that were used to obtain this data. </p>
This repository serves as a replication package for the research paper titled "Typestate-based Fault Localization of API Usage Violations in a Deep Learning Program"
<h2>Overview</h2> <p>This repository serves as a replication package for the research paper titled "An Approach to Detecting Usage Protocol Violations in Deep Learning Programs."</p> <h2>Benchmarks</h2> <p>Two benchmarks were utilized in the research:</p> <ol> <li> <p>Benchmark1 from NeuraLint:</p> <ul> <li>Location: <code>NLBench/SOSamples</code></li> </ul> </li> <li> <p>Benchmark2 from Humbatova et al.:</p> <ul> <li>Location: <code>HumbatovaBench/SOSamples</code></li> </ul> </li> </ol> <h2>Reproducing Results</h2> <p>To replicate the results presented in the paper, follow these steps:</p> <ol> <li>Download the NeuralStateAnalysis Zip file.</li> <li>Extract the file and navigate to the NeuralStateAnlaysis directory.</li> <li>(Optional) Install the necessary requirements by executing <code>pip install requirements.txt</code>. Note: The requirements.txt file is already available in this repository.</li> </ol> <h3>Running NeuralState on <code>NLBench</code>:</h3> <ol> <li>Navigate to the <code>NLBench</code><code>/SOSamples</code> directory.</li> <li>Open any of the programs you wish to execute.</li> <li>Set the path to the NeuralStateAnalysis directory: <code>Path-to-folder/NeuralStateAnalysis/</code></li> <li>Run the program using the command <code>python program_id</code>. Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you will be able to reproduce the results.</li> </ol> <h3>Running NeuralState on <code>HumbatovaBench</code>:</h3> <ol> <li>Navigate to the <code>HumbatovaBench</code><code>/SOSamples</code> directory.</li> <li>Open any of the programs you wish to execute.</li> <li>Set the path to the NeuralStateAnalysis directory: <code>Path-to-folder/NeuralStateAnalysis/</code></li> <li>Run the program using the command <code>python program_id</code>. Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you will be able to reproduce the results.</li> </ol>
High-resolution lithospheric shear velocity structure of the Suqian segment of the Tanlu fault zone from ambient noise tomography
<p>This file is the phase velocity dispersion curve manually picked up of Rayleigh wave in Suqian segment of the Tanlu Fault Zone. Only these Rayleigh wave dispersion curve are used for tomographic inversion.</p> <p>Rayleigh Wave Phase Dispersion Data (TL_SQ_Dispersion.zip):<br>Format:<br> Lon (station A) Lat (station A)<br> Lon (station B) Lat (station B)<br> Period (s) Vs (km/s)</p>
High-resolution lithospheric shear velocity structure of the Suqian segment of the Tanlu fault zone from ambient noise tomography
<p>Cross-correlation Functions Data(TL_SQ_CCFs.zip):<br>Format:<br> Lon (station A) Lat (station A) Elevation (A)<br> Lon (station B) Lat (station B) Elevation (B)<br> Time (t=0) GAB(t) GBA(t)<br> Time (t=dt) GAB(t) GBA(t) <br> Time (t=2dt) GAB(t) GBA(t)</p>
Artifact for "Modular criticality analysis for dynamic fault trees"
<p>This artifact contains the fault trees and log files of the experimental evaluation from the paper <em>"Modular criticality analysis for dynamic fault trees"</em>. The implementation is available in the <a href="https://www.safest.dgbtek.com/">SAFEST tool</a>.</p>
Rupture Process of the 2020 Mw7.0 Samos earthquake and its effect on surrounding active faults
<p>Here we have archived available geodetic and strong motion data that accompany the article 'Rupture Process of the 2020 Mw7.0 Samos earthquake and its effect on surrounding active faults'.</p>
Supplementary Materials for paper Evaluating the Rate of Consistency Violation Faults for Self-Stabilizing Programs
<p>Source code and data for the paper Evaluating the Rate of Consistency Violation Faults for Self-Stabilizing Programs</p> <p>Content:</p> <p>+ directory src: source code</p> <p>+ directory lib: libaries used by source code</p> <p>+ directory graphs: input graphs (topology) for programs</p> <p>+ directory results-2021: analysis and simulation data</p> <p>+ run_analyze_cvf_script.sh: script for running analysis</p> <p>+ run_simulation_script.sh: script for running simulation</p>
Fine seismic imaging of the Lianhuashan fault zone, South China, and tectonic implications – Constrained by ambient noise adjoint tomography
<p>The Rayleigh wave group velocity dispersion and the cross-correlation functions used in the study "Fine seismic imaging of the Lianhuashan fault zone, South China, and tectonic implications – Constrained by ambient noise adjoint tomography".</p>
Injecting Software Faults in Python Applications: The OpenStack Case Study - Supplemental Material (https://rdcu.be/cAPUh)
<p>Injecting Software Faults in Python Applications: The OpenStack Case Study - Supplemental Material<br> Link to the paper: <a href="https://rdcu.be/cAPUh">https://rdcu.be/cAPUh</a></p>
Malawi Active Fault Database
<p>First release of the Malawi Active Fault Database (MAFD) associated with a publication in review with the journal Geochemistry, Geophysics and Geosystems.</p> <p>To reference this database please refer to the latest release of the dataset on Github and Zenodo and please also cite: Williams, J. N., Wedmore, L. N. J., Scholz, C. A., Kolawole, F., Wright, L. J. M., Shillington, D., Fagereng, Å., Biggs, J., Mdala, H., Dulanya, Z., Mphepo, F., Chindandali, P. R. N., Werner, M. J. (2022), The Malawi Active Fault Database: an onshore-offshore database for regional assessment of seismic hazard and tectonic evoultion. _Geochemistry, Geophysics, Geosystems_, 23(5), e2022GC010425. <a href="https://doi.org/10.1029/2022GC010425">https://doi.org/10.1029/2022GC010425</a></p> <p>For full details of the database, please refer to the journal article above.</p>
RSQSim Simulated Earthquake Catalog 4983, California, UCERF3 Fault System, 715kyr
<p>Simulated earthquake catalog, generated with the Rate-State Earthquake Simulator (RSQSim), described in and used by the following publication:</p> <p>Kevin R. Milner, Bruce E. Shaw, Christine A. Goulet, Keith B. Richards‐Dinger, Scott Callaghan, Thomas H. Jordan, James H. Dieterich, Edward H. Field; Toward Physics‐Based Nonergodic PSHA: A Prototype Fully Deterministic Seismic Hazard Model for Southern California. <em><em>Bulletin of the Seismological Society of America</em></em> 2021;; 111 (2): 898–915. doi: <a href="https://doi.org/10.1785/0120200216">https://doi.org/10.1785/0120200216</a></p> <p>The catalog is simulated on the UCERF3 fault system for California (<a href="https://doi.org/10.1785/0120130164">https://doi.org/10.1785/0120130164</a>), following the hybrid loading technique described in Shaw (2019) (<a href="https://doi.org/10.1785/0120180128">https://doi.org/10.1785/0120180128</a>).</p> <p><strong>File Descriptions:</strong></p> <p><strong>Catalog CSV Files:</strong><em> catalog.csv, catalog_m6.5.csv</em></p> <p>These are human-readable summary files listing each event (after skipping the first 65kyrs of model spin-up time). The "catalog_m6.5.csv" file is filtered for only M>6.5 events (those used Milner et al., 2021). Each line corresponds to an event in the catalog, and contains the following information:</p> <ul> <li>Event ID and occurrence time</li> <li>Magnitude, Moment, and Area</li> <li>Participating element information (count, average slip, long-term average slip rate)</li> <li>Hypocenter and scalar-moment centroid locations</li> <li>Rupture surface minimum and maximum depths</li> </ul> <p><strong>Geometry File (ASCII):</strong><em> geometry.flt</em></p> <p>ASCII file listing patch (triangular) geometry for the simulated faults in a UTM coordinate system (zone 11S). The primary columns are:</p> <ul> <li><em>x1, y1, z1</em> - UTM coordinates of the first vertex</li> <li><em>x2, y2, z2</em> - UTM coordinates of the second vertex</li> <li><em>x3, y3, z3</em> - UTM coordinates of the third vertex</li> <li><em>rake</em> - Direction of the motion of the hanging wall relative to the footwall (in degrees, following the convention of Aki & Richards, 2002)</li> <li><em>slip_rate</em> - Long-term average slip rate (in m/s)</li> </ul> <p>The first line in the file (excluding comment lines that start with '#') is the patch with ID=1, the second ID=2, etc. Additional metadata columns may exist in each line beyond those listed and can be ignored.</p> <p><strong>Catalog List Files (binary):<em> </em></strong><em>catalog.eList, catalog.pList, catalog.tList, catalog.dList</em></p> <p>The raw output of RSQSim includes 4 binary "list" files that define the simulated event IDs, times, and total slip in each participating patch. All 4 list files should be processed together, as the <em>N</em>-th item in one list file corresponds to the <em>N</em>-th item in each other file.</p> <p>For each patch the ruptures during an event, a value is written to each of these files giving 1) the patch number, 2) the event number, 3) the distance slipped during the event, and 4) the time of first rupture for that patch during that event.</p> <p>The format is as follows:</p> <ul> <li>catalog.eList: list of event IDs (1-based), stored as little-endian 4-byte integers</li> <li>catalog.pList: list of patch IDs (1-based), stored as little-endian 4-byte integers</li> <li>catalog.tList: list of time of first slip on each patch in each event (in seconds, relative to simulation origin time), stored as little-endian 8-byte double precision floating-point numbers</li> <li>catalog.dList: list of total slip on each patch in each event (in meters), stored as little-endian 8-byte double precision floating-point numbers</li> </ul> <p><strong>RSQSim Input File (ASCII):</strong><em> params.in</em></p> <p>Key-value pairs of RSQSim model parameters, used to originally run the simulation.</p> <p><strong>M>6.5 Rupture Slip-Time Histories (Standard Rupture Format):</strong> <em>srfs_m6.5.zip</em></p> <p>Rupture slip-time histories in the Standard Rupture Format, version 1.0 (see <a href="http://equake-rc.info/static/paper/SRF-Description-Graves_2.0.pdf">http://equake-rc.info/static/paper/SRF-Description-Graves_2.0.pdf</a>), used in Milner et al. (2021). Slip-time histories are discretized at 0.1s intervals, and represented in the WGS84 coordinate system.</p>
Data for "Constraints on absolute chamber volume from geodetic measurements: Trapdoor faulting in the Galapagos"
<p>SNdif.mat: InSAR data covering the April 2005 trapdoor faulting event.</p> <p>SN_GPS.mat: GPS data of the April 2005 trapdoor faulting event.</p> <p>Both datasets were prepared and provided by Jonsson [2009]</p>
Data of Thermal Insulation and Shock Absorption Effect for Cross-fault Tunnel in High Geothermal Area
<p>Data of manuscript "Thermal Insulation and Shock Absorption Effect for Cross-fault Tunnel in High Geothermal Area"</p>
Dataset used for paper "Issues-Driven Features for Software Fault Prediction"
<p> </p> <div>Dataset used for paper "Issues-Driven Features for Software Fault Prediction".</div> <div> </div> <div> </div> <div> </div> <div>The dataset contains 86 projects from the open source organizations Apache and Spring were written in Java that managed their source code using the Git version control system and an issue tracking system (JIRA or BUGZILLA). </div> <div> </div> <div>For each project, we extracted data for software fault prediction (SFL) task as follows:</div> <div> </div> <div>First, we filtered out projects without reported resolved bugs or less than 5 released versions.<br> Then we iterated the resolved bugs and mapped them to the commits that fixed them.<br> Next, for each version, we labeled the faulty files in the version. A faulty file is a file that was modified in a commit in the version that resolved a bug. <br> The methodology for labeling the files is a variant of the very known approach implemented in the {\it SZZ} algorithm, which accounts for its vulnerabilities.</div> <div>Finally, for each project, we filtered out versions with faulty files' ratios lower than 5\% and higher than 30\%. The remaining set includes a good representation of bugs and reduces the class imbalance produced by the low number of defects. In addition, filtering versions with a low number of bugs helps to prune outliers, such as a version created to fix specific issues.</div> <div> </div> <div>Extracted using Beirut repository mining tool:</div> <p>https://github.com/beirut-repository-mining/repository_mining</p> <p> </p>
Structural data for "Structural and rheological evolution of brittle fault zones in mafic crust: Implications for the strength of oceanic transform faults"
<p>Structural data for "Structural and rheological evolution of brittle fault zones in mafic crust: Implications for the strength of oceanic transform faults"</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.