Evolution of swelling pressure of cohesive-frictional, rough and elasto-plastic granulates

The subject of this study is the modeling of the evolution of the swell-ing pressure of granulates with cohesive-frictional, rough and elasto-plastic “mi-croscopic” contact properties. The spherical particles are randomly arranged in a periodic cubic space with a fixed volume so that an increase of the particle size – i.e. swelling that can be caused by intake of some fluid – is accompanied by a de-crease of the void space. An analytical function is proposed that properly de-scribes the (macroscopic) void ratio as function of pressure for different micro-scopic contact properties

The look-ahead effect of phenotypic mutations

The evolution of complex molecular traits such as disulphide bridges often requires multiple mutations. The intermediate steps in such evolutionary trajectories are likely to be selectively neutral or deleterious. Therefore, large populations and long times may be required to evolve such traits. We propose that errors in transcription and translation may allow selection for the intermediate mutations if the final trait provides a large enough selective advantage. We test this hypothesis using a population based model of protein evolution. If an individual acquires one of two mutations needed for a novel trait, the second mutation can be introduced into the phenotype due to transcription and translation errors. If the novel trait is advantageous enough, the allele with only one mutation will spread through the population, even though the gene sequence does not yet code for the complete trait. The first mutation then has a higher frequency than expected without phenotypic mutations giving the second mutation a higher probability of fixation. Thus, errors allow protein sequences to ''look-ahead'' for a more direct path to a complex trait.Comment: Submitted to "Genetics

Resilient Learning-Based Control for Synchronization of Passive Multi-Agent Systems under Attack

In this paper, we show synchronization for a group of output passive agents that communicate with each other according to an underlying communication graph to achieve a common goal. We propose a distributed event-triggered control framework that will guarantee synchronization and considerably decrease the required communication load on the band-limited network. We define a general Byzantine attack on the event-triggered multi-agent network system and characterize its negative effects on synchronization. The Byzantine agents are capable of intelligently falsifying their data and manipulating the underlying communication graph by altering their respective control feedback weights. We introduce a decentralized detection framework and analyze its steady-state and transient performances. We propose a way of identifying individual Byzantine neighbors and a learning-based method of estimating the attack parameters. Lastly, we propose learning-based control approaches to mitigate the negative effects of the adversarial attack

Long-Term Behavior of Coarse-Grained Rockfill Material and Their Constitutive Modeling

For the long-term behavior and safety assessment of rockfill dams, not only the shape of the dam body, the loading history, the geological condition of the dam foundation and abutments, the assessment of possible seismic hazards and seepage events caused by defects of the sealing are important, but also the time dependent mechanical behavior of the dam materials used can be of significant influence. In this paper a novel hypoplastic constitutive model for moisture sensitive, coarse-grained rockfill materials is presented. In the constitutive equations, the so-called solid hardness is a key parameter to reflect the influence of the state of weathering on the mechanical response. With respect to the evolution equation for the solid hardness, creep and stress relaxation can be modeled for dry and wet states of the material in a unified manner. The performance of the model is demonstrated by comparing the numerical simulation with experimental data

Influence of the Loading Condition on Single Grain Crushing in DEM Simulation

Grain crushing is of essential importance for understanding the mechanical behavior of granular materials such as sand, gravel or broken rock under higher pressures. In order to investigate the breakage mechanism of a single grain under different loading conditions, numerical simulations are carried out using DEM. Two different types of boundary conditions are considered to apply displacement-controlled load: loading using platens and loading by uncrushable macro-grains. A 2D crushable macro-grain is built up from a large number of micro-grains which are connected with respect to breakable parallel-bond properties. The response of the crushable macro-grain for different coordination numbers and location of the contact points is discussed. The numerical results show that the type of loading condition can influence the loading capacity and fragmentation patterns of the crushable macro-grain

Tribute to Krzysztof Wilmanski

Some 20 years ago, Krzysztof Wilmanski began his research into the theory of porous and granular media, fields that are addressed in this special issue of Acta Mechanica. In contrast to earlier models for such media, Wilmanski introduced the porosity as a material field, and he derived a particular balance equation for this quantity based on thermodynamic arguments. A principal application of the resulting continuum model has been the investigation of linear wave propagation. This was the topic of one minisymposium at the 8th European Solid Mechanics Conference in the Graz University of Technology, Austria, 9–13 July 2012

The Evolution of Protein Interaction Networks in Regulatory Proteins

Interactions between proteins are essential for intracellular communication. They form complex networks which have become an important source for functional analysis of proteins. Combining phylogenies with network analysis, we investigate the evolutionary history of interaction networks from the bHLH, NR and bZIP transcription-factor families. The bHLH and NR networks show a hub-like structure with varying γ values. Mutation and gene duplication play an important role in adding and removing interactions. We conclude that in several of the protein families that we have studied, networks have primarily arisen by the development of heterodimerizing transcription factors, from an ancestral gene which interacts with any of the newly emerging proteins but also homodimerizes

Finding common protein interaction patterns across organisms

Protein interactions are an important resource to obtain an understanding of cell function. Recently, researchers have compared networks of interactions in order to understand network evolution. While current methods first infer homologs and then compare topologies, we here present a method which first searches for interesting topologies and then looks for homologs. PINA (protein interaction network analysis) takes the protein interaction networks of two organisms, scans both networks for subnetworks deemed interesting, and then tries to find orthologs among the interesting subnetworks. The application is very fast because orthology investigations are restricted to subnetworks like hubs and clusters that fulfill certain criteria regarding neighborhood and connectivity. Finally, the hubs or clusters found to be related can be visualized and analyzed according to protein annotation

Evolutionary Dynamics on Protein Bi-stability Landscapes Can Potentially Resolve Adaptive Conflicts

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bistable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed