Reconstructing the Pleistocene depositional environments at Schöningen (northern Germany) : insights from 3D subsurface modelling and numerical simulation

[no abstract

Deformation of salt structures by ice-sheet loading: insights into the controlling parameters from numerical modelling

Subsurface salt flow is driven by differential loading, which is typically caused by tectonics or sedimentation. During glaciations, the weight of an ice sheet represents another source of differential loading. In salt-bearing basins affected by Pleistocene glaciations, such as the Central European Basin System, ice loading has been postulated as a trigger of young deformation at salt structures. Here, we present finite-element simulations (ABAQUS) with models based on a simplified 50-km long and 10-km-deep two-dimensional geological cross-section of a salt diapir subject to the load of a 300-m-thick ice sheet. The focus of our study is to evaluate the sensitivity of the model to material parameters, including linear and non-linear viscosity of the salt rocks and different elasticities. A spatially and temporarily variable pressure was applied to simulate ice loading. An ice advance towards the diapir causes lateral salt flow into the diapir and diapiric rise. Complete ice coverage leads to downward displacement of the diapir. After unloading, displacements are largely restored. The modelled displacements do not exceed few metres and are always larger in models with linear viscosity than in those with non-linear viscosity. Considering the low stresses caused by ice-sheet loading and the long time-scale, the application of linear viscosity seems appropriate. The elastic parameters also have a strong impact, with lower Young's moduli leading to larger deformation. The impact of both the viscosity and the elasticity highlights the importance of a careful parameter choice in numerical modelling, especially when aiming to replicate any real-world observations

Modular parameter identification of biomolecular networks

The increasing complexity of dynamic models in systems and synthetic biology poses computational challenges especially for the identification of model parameters. While modularization of the corresponding optimization problems could help reduce the “curse of dimensionality,” abundant feedback and crosstalk mechanisms prohibit a simple decomposition of most biomolecular networks into subnetworks, or modules. Drawing on ideas from network modularization and multiple-shooting optimization, we present here a modular parameter identification approach that explicitly allows for such interdependencies. Interfaces between our modules are given by the experimentally measured molecular species. This definition allows deriving good (initial) estimates for the inter-module communication directly from the experimental data. Given these estimates, the states and parameter sensitivities of different modules can be integrated independently. To achieve consistency between modules, we iteratively adjust the estimates for inter-module communication while optimizing the parameters. After convergence to an optimal parameter set---but not during earlier iterations---the intermodule communication as well as the individual modules\' state dynamics agree with the dynamics of the nonmodularized network. Our modular parameter identification approach allows for easy parallelization; it can reduce the computational complexity for larger networks and decrease the probability to converge to suboptimal local minima. We demonstrate the algorithm\'s performance in parameter estimation for two biomolecular networks, a synthetic genetic oscillator and a mammalian signaling pathway

Pairing and superconductivity driven by strong quasiparticle renormalization in two-dimensional organic charge transfer salts

We introduce and analyze a variational wave function for quasi two-dimensional kappa-ET organic salts containing strong local and nonlocal correlation effects. We find an unconventional superconducting ground state for intermediate charge carrier interaction, sandwiched between a conventional metal at weak coupling and a spin liquid at larger coupling. Most remarkably, the excitation spectrum is dramatically renormalized and is found to be the driving force for the formation of the unusual superconducting state.Comment: 4 pages, 4 figure

Position-Based Multicast Routing for Mobile Ad-Hoc Networks

In this paper we present Position-Based Multicast (PBM), a multicast routing algorithm for mobile ad-hoc networks which does neither require the maintenance of a distribution structure (e.g., a tree or a mesh) nor resorts to flooding of data packets. Instead a forwarding node uses information about the positions of the destinations and its own neighbors to determine the next hops that the packet should be forwarded to and is thus very well suited for highly dynamic networks. PBM is a generalization of existing position-based unicast routing protocols such as face-2 or GPSR. The key contributions of PBM are rules for the splitting of multicast packets and a repair strategy for situations where there exists no direct neighbor that makes progress toward one or more destinations. The characteristics of PBM are evaluated in detail by means of simulation