Spatial seismic hazard variation and adaptive sampling of portfolio location uncertainty in probabilistic seismic risk analysis

Probabilistic seismic risk analysis is widely used in the insurance industry to model the likelihood and severity of losses to insured portfolios by earthquake events. The available ground motion data - especially for strong and infrequent earthquakes - are often limited to a few decades, resulting in incomplete earthquake catalogues and related uncertainties and assumptions. The situation is further aggravated by the sometimes poor data quality with regard to insured portfolios. For example, due to geocoding issues of address information, risk items are often only known to be located within an administrative geographical zone, but precise coordinates remain unknown to the modeler. We analyze spatial seismic hazard and loss rate variation inside administrative geographical zones in western Indonesia. We find that the variation in hazard can vary strongly between different zones. The spatial variation in loss rate displays a similar pattern as the variation in hazard, without depending on the return period. In a recent work, we introduced a framework for stochastic treatment of portfolio location uncertainty. This results in the necessity to simulate ground motion on a high number of sampled geographical coordinates, which typically dominates the computational effort in probabilistic seismic risk analysis. We therefore propose a novel sampling scheme to improve the efficiency of stochastic portfolio location uncertainty treatment. Depending on risk item properties and measures of spatial loss rate variation, the scheme dynamically adapts the location sample size individually for insured risk items. We analyze the convergence and variance reduction of the scheme empirically. The results show that the scheme can improve the efficiency of the estimation of loss frequency curves and may thereby help to spread the treatment and communication of uncertainty in probabilistic seismic risk analysis

Three-dimensional dynamic rupture simulation with a high-order discontinuous Galerkin method on unstructured tetrahedral meshes

Accurate and efficient numerical methods to simulate dynamic earthquake rupture and wave propagation in complex media and complex fault geometries are needed to address fundamental questions in earthquake dynamics, to integrate seismic and geodetic data into emerging approaches for dynamic source inversion, and to generate realistic physics-based earthquake scenarios for hazard assessment. Modeling of spontaneous earthquake rupture and seismic wave propagation by a high-order discontinuous Galerkin (DG) method combined with an arbitrarily high-order derivatives (ADER) time integration method was introduced in two dimensions by de la Puente et al. (2009). The ADER-DG method enables high accuracy in space and time and discretization by unstructured meshes. Here we extend this method to three-dimensional dynamic rupture problems. The high geometrical flexibility provided by the usage of tetrahedral elements and the lack of spurious mesh reflections in the ADER-DG method allows the refinement of the mesh close to the fault to model the rupture dynamics adequately while concentrating computational resources only where needed. Moreover, ADER-DG does not generate spurious high-frequency perturbations on the fault and hence does not require artificial Kelvin-Voigt damping. We verify our three-dimensional implementation by comparing results of the SCEC TPV3 test problem with two well-established numerical methods, finite differences, and spectral boundary integral. Furthermore, a convergence study is presented to demonstrate the systematic consistency of the method. To illustrate the capabilities of the high-order accurate ADER-DG scheme on unstructured meshes, we simulate an earthquake scenario, inspired by the 1992 Landers earthquake, that includes curved faults, fault branches, and surface topography

Effects of the representation of the crustal structure on seismic wave propagation modeling on the continental scal

The representation of crustal structure in 3D numerical models often poses particular problems that are difficult to overcome. Practical implementations of an improved crustal model into efficient tools for seismic wave propagation modeling often fail to honor the strongly varying depth of the Moho discontinuity. The widely used Spectral Element Method (SEM) using hexahedral elements follows the compromise to approximate this undulating discontinuity with polynomials inside the elements. This solution is satisfactory when modeling seismic wave propagation on the global scale and limitedly to rather low frequencies, but may induce inaccuracies or artifacts when working at the continental scale, where propagation distances are in the order of a few hundred or thousand kilometers and frequencies of interest are up to 0.1 Hz. An alternative modeling tool for seismic wave propagation simulations is the Discontinuous Galerkin Finite Element Method (ADER-DG) that achieves high-order accuracy in space and time using fully unstructured tetrahedral meshes. With this approach strong and undulating discontinuities can be considered more easily by the mesh and modifications of the geometrical properties can be carried out rapidly due to an external mesh generation process. Therefore, we implement more realistic models for the European crust -- based on a new, comprehensive compilation of currently available information from diverse sources, ranging from seismic prospection to receiver functions studies -- in both, the SEM and ADER-DG codes, to study the effects of the numerical representation of crustal structures on seismic wave propagation modeling. We compare the results of the different methods and implementation strategies with respect to accuracy and performance. Clearly, an improved knowledge and detailed representation of the structure of the Earth's crust is a key requisite for better imaging of the mantle structure

Solving three major biases of the ETAS model to improve forecasts of the 2019 Ridgecrest sequence

Strong earthquakes cause aftershock sequences that are clustered in time according to a power decay law, and in space along their extended rupture, shaping a typically elongate pattern of aftershock locations. A widely used approach to model earthquake clustering, the Epidemic Type Aftershock Sequence (ETAS) model, shows three major biases. First, the conventional ETAS approach assumes isotropic spatial triggering, which stands in conflict with observations and geophysical arguments for strong earthquakes. Second, the spatial kernel has unlimited extent, allowing smaller events to exert disproportionate trigger potential over an unrealistically large area. Third, the ETAS model assumes complete event records and neglects inevitable short-term aftershock incompleteness as a consequence of overlapping coda waves. These three aspects can substantially bias the parameter estimation and lead to underestimated cluster sizes. In this article, we combine the approach of Grimm et al. (Bulletin of the Seismological Society of America, 2021), who introduced a generalized anisotropic and locally restricted spatial kernel, with the ETAS-Incomplete (ETASI) time model of Hainzl (Bulletin of the Seismological Society of America, 2021), to define an ETASI space-time model with flexible spatial kernel that solves the abovementioned shortcomings. We apply different model versions to a triad of forecasting experiments of the 2019 Ridgecrest sequence, and evaluate the prediction quality with respect to cluster size, largest aftershock magnitude and spatial distribution. The new model provides the potential of more realistic simulations of on-going aftershock activity, e.g. allowing better predictions of the probability and location of a strong, damaging aftershock, which might be beneficial for short term risk assessment and disaster response

An arbitrary high-order Discontinuous Galerkin method for elastic waves on unstructured meshes - V. Local time stepping and p-adaptivity

SUMMARY This article describes the extension of the arbitrary high-order Discontinuous Galerkin (ADER-DG) method to treat locally varying polynomial degress of the basis functions, so-called p-adaptivity, as well as locally varying time steps that may be different from one element to another. The p-adaptive version of the scheme is useful in complex 3-D models with small-scale features which have to be meshed with reasonably small elements to capture the necessary geometrical details of interest. Using a constant high polynomial degree of the basis functions in the whole computational domain can lead to an unreasonably high CPU effort since good spatial resolution at the surface may be already obtained by the fine mesh. Therefore, it can be more adequate in some cases to use a lower order method in the small elements to reduce the CPU effort without loosing much accuracy. To further increase computational efficiency, we present a new local time stepping (LTS) algorithm. For usual explicit time stepping schemes the element with the smallest time step resulting from the stability criterion of the method will dictate its time step to all the other elements of the computational domain. In contrast, by using local time stepping, each element can use its optimal time step given by the local stability condition. Our proposed LTS algorithm for ADER-DG is very general and does not need any temporal synchronization between the elements. Due to the ADER approach, accurate time interpolation is automatically provided at the element interfaces such that the computational overhead is very small and such that the method maintains the uniform high order of accuracy in space and time as in the usual ADER-DG schemes with a globally constant time step. However, the LTS ADER-DG method is computationally much more efficient for problems with strongly varying element size or material parameters since it allows to reduce the total number of element updates considerably. This holds especially for unstructured tetrahedral meshes that contain strongly degenerate elements, so-called slivers. We show numerical convergence results and CPU times for LTS ADER-DG schemes up to sixth order in space and time on irregular tetrahedral meshes containing elements of very different size and also on tetrahedral meshes containing slivers. Further validation of the algorithm is provided by results obtained for the layer over half-space (LOH.1) benchmark problem proposed by the Pacific Earthquake Engineering Research Center. Finally, we present a realistic application on earthquake modelling and ground motion prediction for the alpine valley of Grenoble

Asynchronous wake-up scheme for wireless light curtains

It is desired to wirelessly control light curtains in an industrial environment. Yet, batteries should last for a long time. Compromise is needed between reaction speed and energy saving. We use LF-RFID wake-up techniques to achieve fast on-demand use of the wireless link and at the same time achieve very low power consumption

Evolution of two distinct phylogenetic lineages of the emerging human pathogen Mycobacterium ulcerans

<p>Abstract</p> <p>Background</p> <p>Comparative genomics has greatly improved our understanding of the evolution of pathogenic mycobacteria such as <it>Mycobacterium tuberculosis</it>. Here we have used data from a genome microarray analysis to explore insertion-deletion (InDel) polymorphism among a diverse strain collection of <it>Mycobacterium ulcerans</it>, the causative agent of the devastating skin disease, Buruli ulcer. Detailed analysis of large sequence polymorphisms in twelve regions of difference (RDs), comprising irreversible genetic markers, enabled us to refine the phylogenetic succession within <it>M. ulcerans</it>, to define features of a hypothetical <it>M. ulcerans </it>most recent common ancestor and to confirm its origin from <it>Mycobacterium marinum</it>.</p> <p>Results</p> <p><it> M. ulcerans </it>has evolved into five InDel haplotypes that separate into two distinct lineages: (i) the "classical" lineage including the most pathogenic genotypes – those that come from Africa, Australia and South East Asia; and (ii) an "ancestral" <it>M. ulcerans </it>lineage comprising strains from Asia (China/Japan), South America and Mexico. The ancestral lineage is genetically closer to the progenitor <it>M. marinum </it>in both RD composition and DNA sequence identity, whereas the classical lineage has undergone major genomic rearrangements.</p> <p>Conclusion</p> <p>Results of the InDel analysis are in complete accord with recent multi-locus sequence analysis and indicate that <it>M. ulcerans </it>has passed through at least two major evolutionary bottlenecks since divergence from <it>M. marinum</it>. The classical lineage shows more pronounced reductive evolution than the ancestral lineage, suggesting that there may be differences in the ecology between the two lineages. These findings improve the understanding of the adaptive evolution and virulence of <it>M. ulcerans </it>and pathogenic mycobacteria in general and will facilitate the development of new tools for improved diagnostics and molecular epidemiology.</p

MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks

Predicting multiple real-world tasks in a single model often requires a particularly diverse feature space. Multimodal (MM) models aim to extract the synergistic predictive potential of multiple data types to create a shared feature space with aligned semantic meaning across inputs of drastically varying sizes (i.e. images, text, sound). Most current MM architectures fuse these representations in parallel, which not only limits their interpretability but also creates a dependency on modality availability. We present MultiModN, a multimodal, modular network that fuses latent representations in a sequence of any number, combination, or type of modality while providing granular real-time predictive feedback on any number or combination of predictive tasks. MultiModN's composable pipeline is interpretable-by-design, as well as innately multi-task and robust to the fundamental issue of biased missingness. We perform four experiments on several benchmark MM datasets across 10 real-world tasks (predicting medical diagnoses, academic performance, and weather), and show that MultiModN's sequential MM fusion does not compromise performance compared with a baseline of parallel fusion. By simulating the challenging bias of missing not-at-random (MNAR), this work shows that, contrary to MultiModN, parallel fusion baselines erroneously learn MNAR and suffer catastrophic failure when faced with different patterns of MNAR at inference. To the best of our knowledge, this is the first inherently MNAR-resistant approach to MM modeling. In conclusion, MultiModN provides granular insights, robustness, and flexibility without compromising performance.Comment: Accepted as a full paper at NeurIPS 2023 in New Orleans, US

Ongoing Genome Reduction in Mycobacterium ulcerans

M. ulcerans is adapting to a more stable environment

Molecular model of the mitochondrial genome segregation machinery in Trypanosoma brucei

In almost all eukaryotes, mitochondria maintain their own genome. Despite the discovery more than 50 y ago, still very little is known about how the genome is correctly segregated during cell division. The protozoan parasite Trypanosoma brucei contains a single mitochondrion with a singular genome, the kinetoplast DNA (kDNA). Electron microscopy studies revealed the tripartite attachment complex (TAC) to physically connect the kDNA to the basal body of the flagellum and to ensure correct segregation of the mitochondrial genome via the basal bodies movement, during the cell cycle. Using superresolution microscopy, we precisely localize each of the currently known TAC components. We demonstrate that the TAC is assembled in a hierarchical order from the base of the flagellum toward the mitochondrial genome and that the assembly is not dependent on the kDNA itself. Based on the biochemical analysis, the TAC consists of several nonoverlapping subcomplexes, suggesting an overall size of the TAC exceeding 2.8 mDa. We furthermore demonstrate that the TAC is required for correct mitochondrial organelle positioning but not for organelle biogenesis or segregation