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Dataset results
12 results for “wave groups”
Accuracy of the Group Velocity of Love Waves Extracted from Ambient Seismic Noise
<p>Love wave waveforms derived from the empirical Green's functions and Ground Truth earthquake in my manuscript submitted to Journal of Geophysical Research: Solid Earth.</p>
Fundamental mode Rayleigh wave group velocity dispersion data
<p>Fundamental-mode Rayleigh-wave group-velocity dispersion curves have been computed from 14706 regional waveforms (ray-paths) sampling India, Himalaya, Tibet and surrounding regions. These have been combined through ray-based travel-time tomography to compute 2D group-velocity maps at periods between 10 and 120~s. These ray-paths sample the region with unprecedented density and uniformity. The 2D maps have a lateral resolution of 3\deg x3\deg, comparable to the regional geology. The dispersion curves, at each 1\deg\ spaced node-points, are inverted to obtain a 3D isotropic shear-wave velocity structure.</p>
Bichromatic wave groups with DIFFerent REPetition periods over a 1:100 sloping bed (DIFFREP-ICL).
<p><strong>DATASET DESCRIPTION</strong></p> <p>DIFFREP-ICL is the dataset that gathers the measurements described in <em>Padilla and Alsina, 2018</em>: <em>Long Wave Generation Induced by Differences in the Wave-Group Structure</em>.</p> <p>For wave cases from MR-01 to MR-10, the provided variables are:</p> <p><strong>i.</strong> Spatial domain measured from the wave paddle (<em>X</em>)</p> <p><strong>ii.</strong> Spatial domain measured from the shoreline at still water conditions (<em>x</em>)</p> <p><strong>iii.</strong> Water depth (<em>d</em>)</p> <p><strong>iv.</strong> Temporal domain (<em>time</em>)</p> <p><strong>v.</strong> Surface elevation series (<em>eta</em>) </p> <p><strong>vi.</strong> Run-up series measured according to the x-coordinate (<em>runup</em>) </p>
Velocity models from "Investigation of Martian regional crustal structure near the dichotomy using S1222a surface-wave group velocities"
<p>The isotropic velocity models from joint inversion of Rayleigh- and Love-wave group-velocity measurements of S1222a. The details about these models and the joint inversion are in "Investigation of Martian regional crustal structure near the dichotomy using S1222a surface-wave group velocities" which is submitted to GRL.</p>
Fundamental mode Rayleigh wave group velocity dispersion data
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Identical BIchromatic wave groups over a Mild Slope (IBIMS-ICL).
<p>IBIMS-ICL is the data set that gathers the measurements described in the article: Padilla, E. M., & Alsina, J. M. (2017). Transfer and dissipation of energy during wave group propagation on a gentle beach slope. <em>Journal of Geophysical Research: Oceans</em>, <em>122</em>(8), 6773-6794.</p> <p>For series A(1-5), B(1-4) and C(1-3), the provided variables are:</p> <p><strong>i.</strong> Spatial domain (<em>X</em>)</p> <p><strong>ii.</strong> Water depth (<em>d</em>)</p> <p><strong>iii.</strong> Temporal domain (<em>time</em><strong>)</strong></p> <p><strong>iv.</strong> Surface elevation series (<em>eta</em>) </p> <p> </p>
CSRM Level 2 dataset: Rayleigh wave phase and group velocity maps in continental China
<p>This dataset contains the Rayleigh wave phase/group velocity maps at the period range from 8 to 70 s. These maps are obtained by travel time tomography using the <strong>639,171</strong> inter-station and <strong>54,792 </strong>event-station Rayleigh wave phase/group velicity dispersion curves (<a href="../records/8103561">data link</a>). The spatial resolution of these maps is ~60 km in the north-south seismic belt and thans-North China Orogen regions, and ~120 km in the rest of the continental China. This dataset results from a project of constructing the high-resolution China Seismological Reference Model (<strong>CSRM-1.0</strong>) in the top 100 km of the crust and uppermost mantle in continental China (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">model link</a>).</p> <p>本数据库包含了利用 <strong>8 - 70 s </strong>的中国大陆区域瑞利波相/群速度结构。反演该相/群速度结构用到了 <strong>639,171 </strong>条台站间瑞利波相/群速度频散曲线和 <strong>54,792 </strong>事件-台站间频散曲线(数据链接)。相/群速度图在南北地震带和华北造山带的分辨率约为 <strong>60</strong> km, 在中国大陆其他区域的分辨率约为 <strong>120</strong> km。该数据库源于构建中国大陆区域高精度地壳和上地幔顶部 100 公里三维地震学模型(<strong>CSRM-1.0</strong>)的工作 (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">模型链接</a>) 。</p> <p>If you face any problem or issue in the usage of this dataset, please feel free to communicate with the corresponding author Xiao Xiao (<strong>xiaox.seis@gmail.com</strong>). </p>
The ambient noise cross-correlation function and teleseismic events, the Love-wave phase velocities, Rayleigh-wave phase and group velocities and H/V, Vsv and Vsh model in the study region (CNCC)
<p>The cross-correlation functions form EOBSArray (COR_CNCC), The Love-wave phase velocities (Love_phase), Rayleigh-wave phase (Rayleigh_phase) and group velocities (Rayleigh_group) and H/V (HtoV),and 3-D Vsv and Vsh model and related uncertainties (Vsv_Vsh_model) in the study region (CNCC) are archieved in the file named CNCC_data.7z.</p>
Data from: Initiation and spread of escape waves within animal groups
The exceptional reactivity of animal collectives to predatory attacks is thought to be owing to rapid, but local, transfer of information between group members. These groups turn together in unison and produce escape waves. However, it is not clear how escape waves are created from local interactions, nor is it understood how these patterns are shaped by natural selection. By startling schools of fish with a simulated attack in an experimental arena, we demonstrate that changes in the direction and speed by a small percentage of individuals that detect the danger initiate an escape wave. This escape wave consists of a densely packed band of individuals that causes other school members to change direction. In the majority of cases, this wave passes through the entire group. We use a simulation model to demonstrate that this mechanism can, through local interactions alone, produce arbitrarily large escape waves. In the model, when we set the group density to that seen in real fish schools, we find that the risk to the members at the edge of the group is roughly equal to the risk of those within the group. Our experiments and modelling results provide a plausible explanation for how escape waves propagate in nature without centralized control.
Data from: Initiation and spread of escape waves within animal groups
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CSRM Level 2 dataset: event-station Rayleigh wave phase and group velocity dispersion curves in continental China from regional earthquake data
<p>This dataset contains the <strong>54,792</strong> event-station Rayleigh wave phase and group velocity dispersion curves from vertical-component waveforms of <strong>226 </strong>regional earthquakes recorded by <strong>1463</strong> seismic stations. This dataset results from a project of constructing the high-resolution China Seismological Reference Model (<strong>CSRM-1.0</strong>) in the top 100 km of the crust and uppermost mantle in continental China (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">model link</a>). </p> <p>本数据库包含了利用中国大陆区域 <strong>1463</strong> 个地震台站记录的 <strong>226</strong> 个区域地震的波形数据计算的 <strong>54,792 </strong>条事件-台站间瑞利波相/群速度频散曲线。该数据库源于构建中国大陆区域高精度地壳和上地幔顶部 100 公里三维地震学模型(<strong>CSRM-1.0</strong>)的工作 (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">模型链接</a>) 。</p> <p>If you face any problem or issue in the usage of this dataset, please feel free to communicate with the corresponding author Xiao Xiao (<strong>xiaox.seis@gmail.com</strong>). </p>
Knowledge and Attitude of a Group of Egyptian Parents Toward Dental Treatment of Their Children During the Fourth Wave of COVID-19: A Cross Sectional Study.
ClinicalTrials.gov study NCT05094739. IPD Sharing: Not stated. Countries: 0. Publications: 0.
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Allen Brain Atlas
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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
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