Interacting multivalent molecules: affinity and valence impact the extent and symmetry of phase separation

Self-assembly by phase separation is emerging as a powerful and ubiquitous mechanism to organize and compartmentalize biomolecules in cells. Most of the proteins involved in phase separation have a fixed number of binding sites, i.e., fixed multivalency. Therefore, extending theories of phase separation to multivalent components with a fixed number of binding sites is an important challenge. In this work, we develop a simple lattice model for a three-component system composed of two multivalent proteins and the solvent. We show that interaction strength as well as valency of the protein components determine the extent of phase separation, whereas valency alone determines the symmetry of the phase diagram. Our theoretical predictions agree with experimental results on a synthetic system of proteins with tunable interaction strength and valency

Projections of global warming-induced impacts on winter storm losses in the German private household sector

We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses

Automatized Optimization of Beam Lines Using Evolutionary Algorithms

Due to the massive parallel operation modes at GSI accelerators, a lot of accelerator setup and re-adjustment has to be made by operators during a beam time. This is typically done manually using potentiometers and is very time-consuming. With the FAIR project the complexity of the accelerator facility increases further and for efficiency reasons it is recommended to establish a high level of automation for future operation. Modern Accelerator Control Systems allow a fast access to both, accelerator settings and beam diagnostics data. This provides the opportunity to implement algorithms for automated adjustment of e.g. magnet settings to maximize transmission and optimize required beam parameters. The fast-switching magnets in GSI-beamlines are an optimal basis for an automatic exploration of the parameter-space. The optimization of the parameters for the SIS18 multi-turn-injection using a genetic algorithm has already been simulated*. The first results of our automatized online parameter optimization at the CRYRING@ESR injector are presented here