We present a novel approach for resolving modes of rupture directivity in large populations of earthquakes. A seismic spectral decomposition technique is used to first produce relative measurements ...of radiated energy for earthquakes in a spatially-compact cluster. The azimuthal distribution of energy for each earthquake is then assumed to result from one of several distinct modes of rupture propagation. Rather than fitting a kinematic rupture model to determine the most likely mode of rupture propagation, we instead treat the modes as latent variables and learn them with a Gaussian mixture model. The mixture model simultaneously determines the number of events that best identify with each mode. The technique is demonstrated on four datasets in California with several thousand earthquakes. We show that the datasets naturally decompose into distinct rupture propagation modes that correspond to different rupture directions, and the fault plane is unambiguously identified for all cases. We find that these small earthquakes exhibit unilateral ruptures 53-74% of the time on average. The results provide important observational constraints on the physics of earthquakes and faults.
We report the observation of a nonlinear terahertz response of split-ring resonator arrays made of high-temperature superconducting films. Intensity-dependent transmission measurements indicate that ...the resonance strength decreases dramatically (i.e. transient bleaching) and the resonance frequency shifts as the intensity is increased. Pump-probe measurements confirm this behaviour and reveal dynamics on the few-picosecond timescale.
Detecting earthquake arrivals within seismic time series can be a challenging task. Visual, human detection has long been considered the gold standard but requires intensive manual labor that scales ...poorly to large data sets. In recent years, automatic detection methods based on machine learning have been developed to improve the accuracy and efficiency. However, the accuracy of those methods relies on access to a sufficient amount of high‐quality labeled training data, often tens of thousands of records or more. We aim to resolve this dilemma by answering two questions: (1) provided with a limited amount of reliable labeled data, can we use them to generate additional, realistic synthetic waveform data? and (2) can we use those synthetic data to further enrich the training set through data augmentation, thereby enhancing detection algorithms? To address these questions, we use a generative adversarial network (GAN), a type of machine learning model which has shown supreme capability in generating high‐quality synthetic samples in multiple domains. Once trained, our GAN model is capable of producing realistic seismic waveforms of multiple labels (noise and event classes). Applied to real Earth seismic data sets in Oklahoma, we show that data augmentation from our GAN‐generated synthetic waveforms can be used to improve earthquake detection algorithms in instances when only small amounts of labeled training data are available.
Key Points
We develop a generative adversarial neural network model that is capable of synthesizing three‐component waveforms of multiple labels
We validate the synthetic waveforms both visually and quantitatively through use of a machine‐learning based earthquake classifier
We demonstrate that our synthetic waveforms can augment real seismic data to improve machine learning‐based earthquake detection methods
Objective
To evaluate an alternative method of defining acute treatment success in migraine by combining multiple indicators into a single dichotomous measure of success.
Background
Migraine is ...characterized by a symptom complex; combining these features as a single endpoint may improve the measurement of treatment effects and better predict patient satisfaction with treatment.
Methods
We used a confirmatory latent class model (LCM) with two latent classes interpreted as treatment success and treatment failure. Pooled data for placebo and ubrogepant 50 mg from the ACHIEVE I and ACHIEVE II trials and data for ubrogepant 100 mg from ACHIEVE I were used. LCM inputs included pre‐dose and 2‐h post‐dose measures of pain severity (0–3), the presence/absence of associated symptoms (nausea, photophobia, and phonophobia 0 or 1), and functional disability (0–3). All definitions were validated against satisfaction with study medication (SWSM) at 24 h post‐dose; results were compared with 2‐hour pain freedom (2hPF).
Results
This pooled analysis included 2247 participants. At 2 h post‐dose in the ubrogepant 50 and 100 mg dose groups, 53.2% (472/887) and 54.9% (246/448) of participants, respectively, were classified as achieving treatment success using the LCM‐based approach, compared to 39.0% (356/912) of participants in the placebo group. The results for treatment success using the 2hPF endpoint were 20.7% (184/887) and 21.5% (96/447) in the ubrogepant 50 and 100 mg dose groups, respectively, compared to 12.7% (116/912) for placebo. Using 24‐h SWSM as an external validator, the LCM approach sensitivity and correct classification rates were higher than for 2hPF.
Conclusion
The LCM approach led to higher rates of treatment success and greater separation between ubrogepant and placebo and was a more sensitive predictor of treatment satisfaction than the regulatory endpoint of 2hPF.
One of most universal statistical properties of earthquakes is the tendency to cluster in space and time. Yet while clustering is pervasive, individual earthquake sequences can vary markedly in ...duration, spatial extent, and time evolution. In July 2014, a prolific earthquake sequence initiated within the Sheldon Wildlife Refuge in northwest Nevada, USA. The sequence produced 26 M4 earthquakes and several hundred M3s, with no clear mainshock or obvious driving force. Here we combine a suite of seismological analysis techniques to better characterize this unusual earthquake sequence. High-precision relocations reveal a clear, east dipping normal fault as the dominant structure that intersects with a secondary, subvertical cross fault. Seismicity occurs in burst of activity along these two structures before eventually transitioning to shallower structures to the east. Inversion of hundreds of moment tensors constrain the overall normal faulting stress regime. Source spectral analysis suggests that the stress drops and rupture properties of these events are typical for tectonic earthquakes in the western US. While regional station coverage is sparse in this remote study region, the timely installation of a temporary seismometer allows us to detect nearly 70,000 earthquakes over a 40-month time period when the seismic activity is highest. Such immense productivity is difficult to reconcile with current understanding of crustal deformation in the region and may be facilitated by local hydrothermal processes and earthquake triggering at the transitional intersection of subparallel fault systems.
The field of seismology is entering a new era where our understanding of earthquakes and the solid earth is increasingly driven by new Big Data experiments and algorithms.
While the rupture processes of nearby earthquakes are often highly similar, characterizing the differences can provide insight into the complexity of the stress field and fault network in which the ...earthquakes occur. Here we perform a comprehensive analysis of earthquake waveform similarity to characterize rupture processes in the vicinity of Ridgecrest, California. We quantify how similar each earthquake is to neighboring events through cross correlation of full waveforms. The July 2019 Ridgecrest mainshocks impose a step reduction in earthquake similarity, which suggests variability in the residual stress field and activated fault structures on length scales of hundreds of meters or less. Interestingly, among these aftershocks, we observe coherent spatial variations of earthquake similarity along the mainshock rupture trace, and document antisimilar aftershock pairs with waveforms that are nearly identical but with reversed polarity. These observations provide new, high-resolution constraints on stress transfer and faulting complexity throughout the Ridgecrest earthquake sequence.
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