Dynamic Rupture Models, Fault Interaction and Ground Motion Simulations for the Segmented Húsavík‐Flatey Fault Zone, Northern Iceland

The Húsavík-Flatey Fault Zone (HFFZ) is the largest strike-slip fault in Iceland and poses a high seismic risk to coastal communities. To investigate physics-based constraints on earthquake hazards, we construct three fault system models of varying geometric complexity and model 79 3-D multi-fault dynamic rupture scenarios in the HFFZ. By assuming a simple regional prestress and varying hypocenter locations, we analyze the rupture dynamics, fault interactions, and the associated ground motions up to 2.5 Hz. All models account for regional seismotectonics, topo-bathymetry, 3-D subsurface velocity, viscoelastic attenuation, and off-fault plasticity, and we explore the effect of fault roughness. The rupture scenarios obey earthquake scaling relations and predict magnitudes comparable to those of historical events. We show how fault system geometry and segmentation, hypocenter location, and prestress can affect the potential for rupture cascading, leading to varying slip distributions across different portions of the fault system. Our earthquake scenarios yield spatially heterogeneous near-field ground motions modulated by geometric complexities, topography, and rupture directivity, particularly in the near-field. The average ground motion attenuation characteristics of dynamic rupture scenarios of comparable magnitudes and mean stress drop are independent of variations in source complexity, magnitude-consistent and in good agreement with the latest regional empirical ground motion models. However, physics-based ground motion variability changes considerably with fault-distance and increases for unilateral compared to bilateral ruptures. Systematic variations in physics-based near-fault ground motions provide important insights into the mechanics and potential earthquake hazard of large strike-slip fault systems, such as the HFFZ

Calibration of a Bayesian spatio-temporal ETAS model to the June 2000 South Iceland seismic sequence

SUMMARY The reliable forecasting of seismic sequences following a main shock has practical implications because effective post-event response is crucial in earthquake-stricken regions, aftershocks can progressively cause increased damage and compound economic losses. In the South Iceland Seismic Zone (SISZ), one of two large transform zones in Iceland where earthquake hazard is the highest, an intense seismic sequence took place during 17–24 June 2000, starting with a ${M}_{\rm{w}}$ 6.4 main shock on 17 June 2000, followed by another ${M}_{\rm{w}}$ 6.5 main shock four days later and on a different fault. Both earthquakes caused considerable damage and incurred heavy economic losses. They were immediately followed by intense aftershock activity on the causative faults and triggered earthquakes as far as 80 km away along the transform zone. To investigate the feasibility of forecasting the progression of such complex sequences, we calibrated a spatio-temporal epidemic-type aftershock sequence (ETAS) clustering model to the June 2000 seismic sequence in the framework of Bayesian statistics. Short-term seismicity forecasts were carried out for various forecasting intervals and compared with the observations, the first generated a few hours after the first main shock and followed by daily forecasts. The reliability of the early forecasts was seen to depend on the initial model parameters. By using an adaptive parameter inference approach where the posteriors from each preceding forecasting interval served as informative priors for the next, the fast convergence of the parametric values was ensured. As a result, the 16–84 percentile range of the forecasted number of events captured the actual number of observed events in all daily forecasts, and the model exhibited a strong spatial forecasting ability, even only a few hours after the main shock, and over all subsequent daily forecasts. We present the spatio-temporal ETAS parameters for the June 2000 sequence as ideal candidates of prior estimates for future operational earthquake forecasting of other Icelandic aftershock sequences. Past seismic sequences need to be analysed retrospectively to confirm the stability of the parameters of this study, effectively enable the application of the Bayesian ETAS model as an operational earthquake forecasting system for aftershocks in Iceland

High spatial-resolution loss estimation using dense array strong-motion near-fault records. Case study for Hveragerði and the Mw 6.3 Ölfus earthquake, South Iceland

The most recent and costliest damaging earthquake in Iceland is the w6.3 29-May-2008 Ölfus earthquake to date. In particular, Hveragerði town located in the extreme near-fault region, suffered intense horizontal peak ground accelerations (PGA) of ∼40–90%g and large amplitude and long-period near-fault pulses, recorded on a dense urban strong-motion array in the town. In this study we collated a high-spatial resolution exposure database (building-by-building) complete with actual reported losses and classified the buildings by building materials and construction year according to the code design requirements in place at the time. We took advantage of the array data and evaluated a set of well-known ground motion intensity measures (IM), including PGA, pseudo-acceleration response spectra at short-to-long periods, Arias Intensity and Cumulative Absolute Velocity. We applied empirical Bayesian kriging geostatistical analyses to generate high-resolution shakemaps and provide IM estimates for each building. The shakemaps showed significant and systematic variation of the IMs across the small study area, with the lowest ground motions observed centrally and highest values in the outskirts. Furthermore, correlation analysis was carried out for the damage ratio and the exposure data IMs, but only low-to-moderate correlations were observed. A key reason is the incurred losses were primarily due to damage to non-structural components, to which the code design requirements do not apply. We carried out a seismic loss assessment in Hveragerði for the earthquake scenario of the Ölfus earthquake both on building-by-building, and municipality levels of spatial resolution. We applied both local and global fragility models for associated with detail building typologies identified based on the SERA taxonomy scheme. The results show that the global fragility functions severely underestimate the seismic performance of the building stock, except for one-story reinforced concrete buildings, while overall the masonry buildings were associated with the most predicted and observed losses. On the other hand, the local models predicted losses that conformed well with the observed damages to timber and concrete buildings. The high-spatial resolution predictions of losses gave results that better correlated with the observed losses in most typologies.This study was funded by the TURNkey H2020 European project (Towards more Earthquake-Resilient Urban Societies through a Multi-Sensor-Based Information System enabling Earthquake Forecasting, Early Warning and Rapid Response Actions) [www.earthquake-turnkey.eu] under grant agreement No 821046. This work was facilitated by an Erasmus+ staff mobility grant No. IS-TS2020-87850 for the lead author to the University of Alicante, Spain. This work was also partly supported by a Postdoctoral fellowship (No. 218255-051), grant of excellence (No. 218149-051) from the Icelandic Research Fund of the Icelandic Centre for Research, and the University of Iceland Research Fund

The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase

publishedVersio

A New Therapy for Relapsed/Refractory Hodgkin’s Lymphoma

Hodgkin's lymphoma is a tumor originating in white blood cells. Treatment with modern chemo- and radiotherapy has an excellent prognosis. Despite this fact, 15-20% of patients go into relapse. Brentuximb Vedotin is a monoclonal antibody against CD30. It is now being used in the treatment of refractory/relapsed Hodgkin's lymphoma.egységes, osztatlanáltalános orvosango

Ranking of ground-motion models (Gmms) for use in probabilistic seismic hazard analysis for iran based on an independent data set

We apply three data-driven selection methods, log-likelihood (LLH), Euclidean distance-based ranking (EDR), and deviance information criterion (DIC), to objectively evaluate the predictive capability of 10 ground-motion models (GMMs) developed from Iranian and worldwide data sets against a new and independent Iranian strong-motion data set. The data set includes, for example, the 12 November 2017 Mw 7.3 Ezgaleh earthquake and the 25 November 2018 Mw 6.3 Sarpol-e Zahab earthquake and includes a total of 201 records from 29 recent events with moment magnitudes 4:5 ≤ Mw ≤ 7:3 with distances up to 275 km. The results of this study show that the prior sigma of the GMMs acts as the key measure used by the LLH and EDR methods in the ranking against the data set. In some cases, this leads to the resulting model bias being ignored. In contrast, the DIC method is free from such ambiguity as it uses the posterior sigma as the basis for the ranking. Thus, the DIC method offers a clear advantage of partially removing the ergodic assumption from the GMM selection process and allows a more objective representation of the expected ground motion at a specific site when the ground-motion recordings are homogeneously distributed in terms of magnitudes and distances. The ranking results thus show that the local models that were exclusively developed from Iranian strong motions perform better than GMMs from other regions for use in probabilistic seismic hazard analysis in Iran. Among the Next Generation Attenuation-West2 models, the GMMs by Boore et al. (2014) and Abrahamson et al. (2014) perform better. The GMMs proposed by Darzi et al. (2019) and Farajpour et al. (2019) fit the recorded data well at short periods (peak ground acceleration and pseudoacceleration spectra at T 0:2 s). However, at long periods, the models developed by Zafarani et al. (2018), Sedaghati and Pezeshk (2017), and Kale et al. (2015) are preferable

Dynamic Rupture Models, Fault Interaction and Ground Motion Simulations for the Segmented Husavik-Flatey Fault Zone, Northern Iceland

The Husavik-Flatey Fault Zone (HFFZ) is the largest strike-slip fault in Iceland and poses a high seismic risk to coastal communities. To investigate physics-based constraints on earthquake hazards, we construct three fault system models of varying geometric complexity and model 79 3-D multi-fault dynamic rupture scenarios in the HFFZ. By assuming a simple regional prestress and varying hypocenter locations, we analyze the rupture dynamics, fault interactions, and the associated ground motions up to 2.5 Hz. All models account for regional seismotectonics, topo-bathymetry, 3-D subsurface velocity, viscoelastic attenuation, and off-fault plasticity, and we explore the effect of fault roughness. The rupture scenarios obey earthquake scaling relations and predict magnitudes comparable to those of historical events. We show how fault system geometry and segmentation, hypocenter location, and prestress can affect the potential for rupture cascading, leading to varying slip distributions across different portions of the fault system. Our earthquake scenarios yield spatially heterogeneous near-field ground motions modulated by geometric complexities, topography, and rupture directivity, particularly in the near-field. The average ground motion attenuation characteristics of dynamic rupture scenarios of comparable magnitudes and mean stress drop are independent of variations in source complexity, magnitude-consistent and in good agreement with the latest regional empirical ground motion models. However, physics-based ground motion variability changes considerably with fault-distance and increases for unilateral compared to bilateral ruptures. Systematic variations in physics-based near-fault ground motions provide important insights into the mechanics and potential earthquake hazard of large strike-slip fault systems, such as the HFFZ. Plain Language Summary The Husavik-Flatey Fault Zone (HFFZ) is the largest strike-slip fault in Iceland, located in the Tjornes Fracture Zone in Northern Iceland where the largest earthquakes in Iceland have occurred. At present the seismogenic potential of HFFZ suggests that an earthquake of magnitude similar to 7 is possible, which poses a high earthquake hazard in the region. In this study, we generate a set of plausible earthquake rupture scenarios on the HFFZ that account for multi-physics, regional geology and topo-bathymetry. We simulate the corresponding seismic ground motions by exploring various assumptions, for example, in terms of slipping fault geometry and hypocenter locations. Our simulated scenarios have comparable magnitudes with historic events. The physics-based ground motion scaling conforms to new empirical ground motion models, but shows varying ground motion variability with distance. Our study provides an overview of multiple rupture scenarios on the HFFZ and suggests that an ensemble of physics-based dynamic rupture scenarios can complement classical seismic hazard assessment methods to better characterize the hazard in tectonically and seismically complex regions, especially in data-scarce regions

A provisional seismic source zonation of Iceland for the ESHM20 based on new physics-based bookshelf fault system models and a new revised earthquake catalogue

The earthquake hazard in Iceland is highest in its two transform zones, the South Iceland Seismic Zone in the South and the Tjörnes Fracture Zone in the North and the reliable probabilistic seismic hazard assessment (PSHA) is the prerequisite for the codified aseismic design of structures and mitigation of seismic risk. The three fundamental aspects of a reliable PSHA, the proper specification of the seismic sources, in particular in the transform zones, their activity rates, and the use of acceptable forms of ground motion models that characterize the rapid attenuation of Icelandic strong-motion, need to be based on the latest state-of-the-art information and methods. In this study, we present a new and provisional subdivision of Iceland into seismic area-source zones on the basis of new physics-based fault system models as well as parameter set for each zone based on new revised and harmonised earthquake catalogue for Iceland. The zonation is guided by the systematic spatial distribution of the predominant types of earthquake faulting mechanisms in Iceland, consistent with the volcanic and transform zones in the country. Moreover, the new physics-based estimates of activity rates in the transform zones effectively explain the historical seismicity and allow the specification of subzone activity rates. On the basis of this new zonation finite-fault earthquake catalogues can be simulated for long-time intervals that are consistent with the time-independent estimates of seismicity. The provisional seismic zonation model can therefore both serve as the basis for the revision of the PSHA of Iceland using conventional engineering approaches and lays the foundation for physics-based earthquake rupture simulation approaches to the time-independent PSHA. For the time being however, this provisional model has been provided to the harmonized efforts of PSHA in Europe (ESHM20).The Iceandic Centre for Research (Grant no. 196089).Peer Reviewe

Automatic fundus image quality assessment on a continuous scale.

To access publisher's full text version of this article click on the hyperlink belowFundus photography is commonly used for screening, diagnosis, and monitoring of various diseases affecting the eye. In addition, it has shown promise in the diagnosis of brain diseases and evaluation of cardiovascular risk factors. Good image quality is important if diagnosis is to be accurate and timely. Here, we propose a method that automatically grades image quality on a continuous scale which is more flexible than binary quality classification. The method utilizes random forest regression models trained on image features discovered automatically by combining basic image filters using simulated annealing as well as features extracted with the discrete Fourier transform. The method was developed and tested on images from two different fundus camera models. The quality of those images was rated on a continuous scale from 0.0 to 1.0 by five experts. In addition, the method was tested on DRIMDB, a publicly available dataset with binary quality ratings. On the DRIMDB dataset the method achieves an accuracy of 0.981, sensitivity of 0.993 and specificity of 0.958 which is consistent with the state of the art. When evaluating image quality on a continuous scale the method outperforms human raters. Keywords: Fundus image quality assessment; Fundus imaging; Machine learning; Simulated annealing