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562 results for “Fault”
Numerical modeling results for Compression at strike-slip fault is a favorable condition for subduction initiation
<p>Each compressed file contains the visualization data of one model with vtk files. </p> <p>Opensource software Paraview is required to open the vtk files. </p> <p>Put the 'pvsm' file into folds with time.pvd for visulization.</p>
Datasets related to paper "Crustal structure and fault geometries of the Garhwal Himalaya, India: Insight from new high-resolution gravity data modeling and PSO inversion"
<p>The files include Satellite gravity data, topography and earthquake data used in the paper "Crustal structure and fault geometries of the Garhwal Himalaya, India: Insight from new high-resolution gravity data modeling and PSO inversion" by Chamoli A., Rana S., Dwivedi D., Pandey A.K.. This has been submitted to Journal of Geophysical Research: Solid Earth. Restrictions applied to the availability of the land gravity data set.</p>
M180 Data for "Laboratory Earthquakes Simulations – Typical Events, Fault Damage, and Gouge Production"
<p>M180 Data for "Laboratory Earthquakes Simulations – Typical Events, Fault Damage, and Gouge Production"</p>
Behavior of amagmatic orogenic geothermal systems: insights from the Agua Blanca Fault, Baja California, Mexico
<p>This dataset includes all the data used for the paper submitted to the Journal of Geophysical Research: Solid Earth, entitled: <strong>Behavior of amagmatic orogenic geothermal systems: insights from the Agua Blanca Fault, Baja California, Mexico. </strong></p> <p>One word and excel file are provided with the following information:</p> <p><strong>Word file: Geological and geochemical data</strong></p> <p>Table 1: Chemical and isotopic compositions of thermal waters.</p> <p>Table 1: Chemical and isotopic compositions of gases dissolved in thermal waters.</p> <p>Table S1: Major oxides and Th and U concentrations in host rocks.</p> <p>Table S2: Thermal waters corrected by the seawater fraction.</p> <p>Table S3: Classical geothermometric temperatures, brittle–ductile transition depth, geothermal gradient, and the minimum depth of equilibration.</p> <p>Table S4: Pameters to estimate the hydraulic head gradient</p> <p><strong>Excel file: geophysical data</strong></p> <p>Seismic events</p>
Characteristically repeating earthquake catalog for Hayward and Rodgers Creek Faults
<p>Characteristically repeating earthquake catalog for Hayward and Rodgers Creek Faults</p>
Data from: Role of backbone fault system on earthquake spawning and geohazards in the Seoul metropolitan area
<p class="MsoNormal"><span>Major earthquakes in continental regions may cause significant damages. Preexisting fault system across megacity receives high attention for possible seismic damages. Earthquake occurrence mechanism is important to assess the geohazard potentials. Continental-scale Quaternary fault system is developed across the Seoul metropolitan area where the population is the largest in the Korean Peninsula. Historical seismic-damage records suggest potential seismic hazards in the Seoul metropolitan area. We investigate the fault motions and spatial distribution of earthquakes in the Seoul metropolitan area using a matched-filter technique that is based on stacked waveform crosscorrelation functions among densely-deployed seismic stations. The analysis detects 1,103 earthquakes that include 360 events with magnitudes (M<sub>L</sub>) of -0.6 to 2.0 around the Chugaryeong fault and 34 events with magnitudes of -0.5 to 2.7 around Wangsukcheon, Pocheon, and Yeseonggang faults. The seismicity suggests a set of near-vertical subparallel (or orthogonal) faults that develop from the major faults. The Major fault system behaves as a backbone structure that makes branch faults develop, producing seismicity including major earthquakes. The backbone structure may control the fault development that conforms to the ambient stress field. The backbone faults may play a role in increasing geohazard potentials.</span></p>
Dataset for manuscript "Asymmetric ring-fault activity and alternating radial and circumferential eruptions at Wolf volcano, Galápagos Islands"
<p>The datasets are the processed interferograms presented in our manuscript, which is under review at Geophysical Research Letter (one of the journals of the American Geophysical Union, AGU).</p>
SOUND-BASED DRONE FAULT CLASSIFICATION USING MULTI-TASK LEARNING
<p>arxiv : https://arxiv.org/abs/2304.11708</p> <p>Accepted at 29th International Congress on Sound and Vibration (ICSV29). </p> <p>The drone has been used for various purposes including military applications, aerial photography, and pesticide spraying. However, the drone is vulnerable to external disturbances, and malfunction in propellers and motors can easily occur. To improve the safety of drone operations, early detection of mechanical faults should be made in real-time. In this paper, we propose a sound-based deep neural network (DNN) fault classifier and drone sound dataset. The dataset was constructed by collecting the operating sounds of drones from microphones mounted on three different drones in an anechoic chamber. The dataset includes various operating conditions of drones, such as flight directions (front, back, right, left, clockwise, counter clockwise) and faults on propellers and motors. The drone sounds were then mixed with noises recorded in five different spots on the university campus, with a signal-to-noise ratio (SNR) varying from 10 dB to 15 dB. Using the acquired dataset, we train a DNN classifier, 1DCNN-ResNet, that classifies the types of mechanical faults and their locations from short-time input waveforms. We employ multitask learning (MTL) and incorporate the direction classification task as an auxiliary task to make the classifier learn more general audio features. The test over unseen data reveals that the proposed multitask model can successfully classify faults in drones and outperforms single-task models even with less training data. </p> <p> </p> <p>please reorganize the file directory like below</p> <p>drone</p> <p>ㄴA</p> <p>ㄴB</p> <p>ㄴC</p> <p> </p> <p>For each drone type A, B, and C have 54000*2 files. (Here, *2 means stereo channel, you can find mic1 and mic2 in subdirectory) They are divided into train, valid, and test by a 6:2:2 ratio. For each file, recording information is labeled below.</p> <p>{model_type}_{maneuvering_direction}_{fault}_{drone_file_index}_{background}_{background_file_index}_{SNR}</p> <p>model_type: A, B, C</p> <p>maneuvering_direction: F(Front), B(Back), R(Right), L(Left), C(Clockwise), CC(Counter-clockwise)</p> <p>fault: N (Normal), MF1~4 (Moter Failure), PC1~4 (Propeller Cut) -> 1~4 means each motor/propeller of the quadcopter.</p> <p> </p>
Hypocenter-based 3D Imaging of Active Faults: Method and Applications in the Southwestern Swiss Alps [Dataset]
<p>Data repository to the JGR publication of Truttmann et al. (2023), including following datasets for the two analyzed earthquake sequences (St. Léonard and Anzère)</p> <p>- Interactive 3D fault-network models</p> <p>- Focal mechanisms</p> <p>- Relocated hypocenter locations (hypoDD)</p> <p>- Station networks</p> <p>- hypoDD parameters</p>
Data and code for 'Transient knickpoint migrating modulated by fault activities on the Northeastern Tibetan Plateau margin: A case from the Yellow River '
<p> </p> <p>Kindly feel free to reach out to me (<a href="mailto:lizhch@smail.nju.edu.cn">lizhch@smail.nju.edu.cn</a>) if you have any queries or encounter issues with the 'codes'.</p>
Slip distribution of the February 6, 2023 Mw 7.8 and Mw 7.6, Kahramanmaras, Turkey earthquake sequence in the East Anatolian Fault Zone
<p>On February 6, 2023, two large earthquakes occurred near the Turkish town of Kahramanmaras. The moment magnitude (Mw) 7.8 mainshock ruptured a 310 km-long segment of the left-lateral East Anatolian Fault, propagating through multiple releasing step-overs. The Mw 7.6 aftershock involved nearby left-lateral strike-slip faults of the East Anatolian Fault Zone, causing a 150 km-long rupture. We use remote-sensing observations to constrain the spatial distribution of coseismic slip for these two events and the February 20 Mw 6.4 aftershock near Antakya. Pixel tracking of optical and synthetic aperture radar data of the Sentinel-2 and Sentinel-1 satellites, respectively, provide near-field surface displacements. High-rate Global Navigation Satellite System data constrain each event separately. Coseismic slip extends from the surface to about 15 km depth with a shallow slip deficit. For the mainshock, rupture propagation stopped southward at the diffuse termination of the East Anatolian fault and tapered off northward into the Pütürrge segment, some 20 km south of the 2020 Mw 6.8 Elazığ earthquake, highlighting a potential seismic gap. This repository contains the finite slip distribution of the February 6, 2023 Mw 7.8 Kahramanmaras mainshock and Mw 7.6 Elbinstan aftershock, as well as the slip distribution of the second largest aftershock, the February 20, 2023 Mw 6.4 Antakya earthquake. The repository also provides the slip distribution of the 2020 Mw 6.8 Elazığ earthquake. </p>
GNSS time series from "Subdaily slow fault slip dynamics captured by low-frequency earthquakes" (Mouchon et al., 2023)
<p>GNSS raw time series from "Subdaily slow fault slip dynamics captured by low-frequency earthquakes" (Mouchon et al., 2023)</p> <p>The raw GNSS time series are available for each three GNSS stations we focus on in this study (COYU, IGUA and MECZ), as well as the three distant stations use to correct from common mode (INEG, TAMP and UXAL), at both 24-hour and 6-hour sampling rates.<br> Each file contains the date, East, North and Vertical displacement and associated errors in meters (format: Decimal year, E (m), N (m), U (m), dE (m), dN (m), dU (m)).</p>
The 2022 Har Lake earthquake sequence highlights a complex fault system in the west Qilian Shan, northeastern Tibetan Plateau
<p>The dataset includes the InSAR-derived LOS displacements related to the 2022 Har Lake earthquake sequence in Qinghai province, China. </p>
Dataset Accompanying: Simultaneous single-qubit driving of semiconductor spin qubits at the fault-tolerant threshold
<p> The promise of quantum information technology hinges on the ability to control large numbers of qubits with high fidelity. Quantum dots define a promising platform due to their compatibility with semiconductor manufacturing. Moreover, high-fidelity operations above 99.9\% have been realized with individual qubits \cite{Yoneda2018,Yang2019a,Hendrickx2021}, though their performance has been limited to 98.67\% when driving two qubits simultaneously \cite{Xue2019}. \textcolor{red}{Here we present single-qubit randomized benchmarking in a two-dimensional array of spin qubits, finding native gate fidelities as high as 99.992(1)\%. Furthermore, we benchmark single qubit gate performance while simultaneously driving two and four qubits. To do this, we develop a novel benchmarking technique called $N$-copy randomized benchmarking, designed for simple experimental implementation, while providing a good estimate of the simultaneous qubit gate fidelity. We find two- and four-copy randomized benchmarking fidelities as high as 99.905(8)\% and 99.34(4)\% respectively. We also find that two-copy benchmarking of next-nearest neighbour pairs can return fidelities within the error margin of their single qubit cases, indicating that cross talk can be highly local in the absence of an exchange interaction.} These characterizations of the single-qubit gate quality and the ability to operate simultaneously are crucial aspects for scaling up germanium based quantum information technology. </p>
Input files for Húsavík-Flatey Fault Zone dynamic simulations
<p>This repository contains the input files needed to reproduce the simulations shown in the paper "<a href="https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022JB025886">Dynamic rupture models, fault interaction and ground motion simulations for the segmented Húsavík‐Flatey Fault Zone, Northern Iceland</a>"</p>
Dataset for "Surface physicochemical properties of smectite-rich fault gouge: A case study of the Japan Trench plate-boundary fault"
<p>This deposit contains dataset for the study reported in the paper "Surface physicochemical properties of smectite-rich fault gouge: A case study of the Japan Trench plate-boundary fault".</p>
Supplementary data for "Seismogenic potential and tsunami threat of the strike-slip Carboneras fault in the western Mediterranean from physics-based earthquake simulations"
<p>Supplementary data for the article "Seismogenic potential and tsunami threat of the strike-slip Carboneras fault in the western Mediterranean from physics-based earthquake simulations" published in Natural Hazards and Earth System Science.</p>
Influence of fault system geometry and slip rates on the relative role of coseismic and interseismic stresses on earthquake triggering and recurrence variability
<p>Supporting information for "Influence of fault system geometry and slip rates on the relative role of coseismic and interseismic stresses on earthquake triggering and recurrence variability" </p>
Bathymetric,Magnetic data and code for Coupled detachment faulting and hydrothermal circulation at 49.7°E Southwest Indian Ridge revealed by seafloor magnetism
<p>The dataset contains the Dragon Horn area bathymetric data, near-bottom magnetic survey data, and the SimPEG (V0.15.2) source code used in the forward and inversion of magnetic anomalies.</p>
Grain size and angularity of fault gouges of the Median Tectonic Line in Shikoku, southwestern Japan: Implications for fault-rock evolution
<p>This file is the all measurement data set of grain size and grain angularity for the "Grain size and angularity of fault gouges of the Median Tectonic Line in Shikoku, southwestern Japan: Implications for fault-rock evolution".</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.