Sea Level Changes Affect Seismicity Rates in a Hydrothermal System Near Istanbul

Small stress changes such as those from sea level fluctuations can be large enough to trigger earthquakes. If small and large earthquakes initiate similarly, high-resolution catalogs with low detection thresholds are best suited to illuminate such processes. Below the Sea of Marmara section of the North Anatolian Fault, a segment of urn:x-wiley:00948276:media:grl65397:grl65397-math-0001150 km is late in its seismic cycle. We generated high-resolution seismicity catalogs for a hydrothermal region in the eastern Sea of Marmara employing AI-based and template matching techniques to investigate the link between sea level fluctuations and seismicity over 6 months. All high resolution catalogs show that local seismicity rates are larger during time periods shortly after local minima of sea level, when it is already rising. Local strainmeters indicate that seismicity is promoted when the ratio of differential to areal strain is the largest. The strain changes from sea level variations, on the order of 30–300 nstrain, are sufficient to promote seismicity

On the Use of High‐Resolution and Deep‐Learning Seismic Catalogs for Short‐Term Earthquake Forecasts: Potential Benefits and Current Limitations

Enhanced earthquake catalogs provide detailed images of evolving seismic sequences. Currently, these data sets take some time to be released but will soon become available in real time. Here, we explore whether and how enhanced seismic catalogs feeding into established short-term earthquake forecasting protocols may result in higher predictive skill. We consider three enhanced catalogs for the 2016–2017 Central Italy sequence, featuring a bulk completeness lower by at least two magnitude units compared to the real-time catalog and an improved hypocentral resolution. We use them to inform a set of physical Coulomb Rate-and-State (CRS) and statistical Epidemic-Type Aftershock Sequence (ETAS) models to forecast the space-time occurrence of M3+ events during the first 6 months of the sequence. We track model performance using standard likelihood-based metrics and compare their skill against the best-performing CRS and ETAS models among those developed with the real-time catalog. We find that while the incorporation of the triggering contributions from new small magnitude detections of the enhanced catalogs is beneficial for both types of forecasts, these models do not significantly outperform their respective near real-time benchmarks. To explore the reasons behind this result, we perform targeted sensitivity tests that show how (a) the typical spatial discretizations of forecast experiments (urn:x-wiley:21699313:media:jgrb55931:jgrb55931-math-00012 km) hamper the ability of models to capture highly localized secondary triggering patterns and (b) differences in earthquake parameters (i.e., magnitude and hypocenters) reported in different catalogs can affect forecast evaluation. These findings will contribute toward improving forecast model design and evaluation strategies for next-generation seismic catalogs. Key Points We compare retrospective forecast models informed by enhanced versus real-time earthquake catalogs for the 2016–2017 Central Italy sequence To realize the benefits of high-resolution catalogs, models should integrate advanced experimental setups, like finer spatial grids Results stimulate further testing on the optimal design of next-generation forecast models based on enhanced seismic catalog

Laboratory earthquake forecasting. A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance

Dynamic Evolution of Microscopic Wet Cracking Noises

Characterizing the interaction between water and microscopic defects is one of the long-standing challenges in understanding a broad range of cracking processes. Different physical aspects of microscopic events, driven or influenced by water, have been extensively discussed in atomistic calculations but have not been accessible in microscale experiments. Through the analysis of the emitted noises during the evolution of individual, dynamic microcracking events, we show that the onset of a secondary instability known as hybrid events occurs during the fast healing phase of microcracking, which leads to (local) sudden increase of pore water pressure in the process zone, inducing a secondary instability, which is followed by a fast-locking phase on the microscopic faults (pulse-like rupture)

Three-dimensional studies of pathogenic peptides from the c-terminal of Trypanosoma cruzi ribosomal P proteins and their interaction with a monoclonal antibody structural model

The acidic C-terminal peptides from Trypanosoma cruzi ribosomal P proteins are the major target of the antibody response in patients suffering Chagas chronic heart disease. It has been proposed that the disease is triggered by the cross-reaction of these antibodies with the second extra cellular loop of the β1-adrenoreceptor, brought about by the molecular mimicry between the acidic C-terminal peptides and the receptor's loop. To improve the understanding of the structural basis of the autoimmune response against heart receptors, the 3-dimensional structure of the C-terminal peptides of Trypanosoma cruzi ribosomal proteins P0 (EDDDDDFGMGALF) and P2β (EEEDDDMGFGLFD) were solved using the Electrostaticaly Driven MonteCarlo method. Their structures were compared with the second extra-cellular loop of our homology model of human rhodopsin and the existing experimental NMR structures of the C-terminal peptides from human P0 (EESDDDMGFGLFD) and from Leishmania braziliensis P0 (EEADDDMGFGLFD). Docking of Trypanosoma cruzi peptides P0, P2β and human rhodopsin loop into our anti-P2β monoclonal antibody homology model allowed to explore their interactions

Triggering of the 2014 M_w7.3 Papanoa earthquake by a slow slip event in Guerrero, Mexico

Since their discovery two decades ago, slow slip events have been shown to play an important role in accommodating strain in subduction zones. However, the physical mechanisms that generate slow slip and the relationships with earthquakes are unclear. Slow slip events have been recorded in the Guerrero segment of the Cocos–North America subduction zone. Here we use inversion of position time series recorded by a continuous GPS network to reconstruct the evolution of aseismic slip on the subduction interface of the Guerrero segment. We find that a slow slip event began in February 2014, two months before the magnitude (M_w) 7.3 Papanoa earthquake on 18 April. The slow slip event initiated in a region adjacent to the earthquake hypocentre and extended into the vicinity of the seismogenic zone. This spatio-temporal proximity strongly suggests that the Papanoa earthquake was triggered by the ongoing slow slip event. We demonstrate that the triggering mechanism could be either static stress increases in the hypocentral region, as revealed by Coulomb stress modelling, or enhanced weakening of the earthquake hypocentral area by the slow slip. We also show that the plate interface in the Guerrero area is highly coupled between slow slip events, and that most of the accumulated strain is released aseismically during the slow slip episodes

Coupling Constant pH Molecular Dynamics with Accelerated Molecular Dynamics

An extension of the constant pH method originally implemented by Mongan et al. (J. Comput. Chem.2004, 25, 2038−2048) is proposed in this study. This adapted version of the method couples the constant pH methodology with the enhanced sampling technique of accelerated molecular dynamics, in an attempt to overcome the sampling issues encountered with current standard constant pH molecular dynamics methods. Although good results were reported by Mongan et al. on application of the standard method to the hen egg-white lysozyme (HEWL) system, residues which possess strong interactions with neighboring groups tend to converge slowly, resulting in the reported inconsistencies for predicted pKa values, as highlighted by the authors. The application of the coupled method described in this study to the HEWL system displays improvements over the standard version of the method, with the improved sampling leading to faster convergence and producing pKa values in closer agreement to those obtained experimentally for the more slowly converging residues

Evidence for the adaptation of protein pH-dependence to subcellular pH

<p>Abstract</p> <p>Background</p> <p>The availability of genome sequences, and inferred protein coding genes, has led to several proteome-wide studies of isoelectric points. Generally, isoelectric points are distributed following variations on a biomodal theme that originates from the predominant acid and base amino acid sidechain pKas. The relative populations of the peaks in such distributions may correlate with environment, either for a whole organism or for subcellular compartments. There is also a tendency for isoelectric points averaged over a subcellular location to not coincide with the local pH, which could be related to solubility. We now calculate the correlation of other pH-dependent properties, calculated from 3D structure, with subcellular pH.</p> <p>Results</p> <p>For proteins with known structure and subcellular annotation, the predicted pH at which a protein is most stable, averaged over a location, gives a significantly better correlation with subcellular pH than does isoelectric point. This observation relates to the cumulative properties of proteins, since maximal stability for individual proteins follows the bimodal isoelectric point distribution. Histidine residue location underlies the correlation, a conclusion that is tested against a background of proteins randomised with respect to this feature, and for which the observed correlation drops substantially.</p> <p>Conclusion</p> <p>There exists a constraint on protein pH-dependence, in relation to the local pH, that is manifested in the pKa distribution of histidine sub-proteomes. This is discussed in terms of protein stability, pH homeostasis, and fluctuations in proton concentration.</p