Coarse-Grained Simulation of Myosin-V Movement

We describe the development of a hierarchic modelling method applied to simulating the processive movement of the myosin-V molecular motor protein along an actin filament track. In the hierarchic model, three different levels of protein structure resolution are represented: secondary structure, domain, and protein, with the level of detail changing according to the degree of interaction among the molecules. The integrity of the system is maintained using a tree of spatially organised bounding volumes and distance constraints. Although applied to an actin-myosin system, the hierarchic framework is general enough so that it may easily be adapted to a number of other large biomolecular systems containing in the order of 100 proteins. We compared the simulation results with biophysical data, and despite the lack of atomic detail in our model, we find good agreement and can even suggest some refinements to the current model of myosin-V motion

Fractal Analysis and Chaos in Geosciences

The fractal analysis is becoming a very useful tool to process obtained data from chaotic systems in geosciences. It can be used to resolve many ambiguities in this domain. This book contains eight chapters showing the recent applications of the fractal/mutifractal analysis in geosciences. Two chapters are devoted to applications of the fractal analysis in climatology, two of them to data of cosmic and solar geomagnetic data from observatories. Four chapters of the book contain some applications of the (multi-) fractal analysis in exploration geophysics. I believe that the current book is an important source for researchers and students from universities

Analysis of the traffic conflict situation for speed probability distributions

The increasingly widespread application of drones and the emergence of urban air mobility leads to a challenging question in airspace modernisation: how to create a safe and scalable air traffic management system that can handle the expected density of operations. Increasing the number of vehicles in a given airspace volume and enabling routine operations are essential for these services to be economically viable. However, a higher density of operations increases risks, poses a great challenge for coordination and necessitates the development of a novel solution for traffic management. This paper contributes to the research towards such a strategy and the field of airspace management by calculating and analysing the conflict probability in an en-route, free-flight scenario for autonomous vehicles. Analytical methods are used to determine the directional dependence of conflict probabilities for exponential and normal prescribed speed probability distributions. The notions of geometric and speed conflict are introduced and distinguished throughout the calculations of the paper. The effect of truncating the set of available flight speeds is also investigated. The sensitivity of the calculated results to speed and heading perturbations is studied within the analytical framework and verified by numerical simulations. Results enable a fresh approach to conflict detection and resolution through distribution shaping and are intended to be used in an integrated, stochastic coordination framework

Spatial Stochastic Modeling of the ErbB Receptor Family

ErbB transmembrane receptors are a family of 4 receptor tyrosine kinases that interact with one another through homo and heterodimer interactions. When these dimers form, the kinase domains on the receptor tails interact with one another, transphosphorylating one another, initiating a signal cascade. The signaling pathways these receptors participate in are responsible for many different cell functions including apoptosis, growth, and proliferation. The overexpression of these receptors has been linked to various forms of cancer, emphasizing the importance of understanding how these receptors interact with one another to trigger these cascades. Single Particle Tracking experiments have provided more precise and detailed measures of dimer lifetimes and diffusion. A major observation from the experiments is the anomalous diffusion of the receptors. One suggested contributor to this anomalous diffusion is confinement zones on the membrane. In this work, we develop, validate, and implement a spatial stochastic model to study these receptors and uncover how their kinetics and dynamics as well as the membrane landscape come together to impact erbB activation. We start by focusing on erbB1. Single particle tracking experiments show that receptor pairs interact repeatedly over a period of time. One possible explanation for these repeated interactions is to facilitate phosphorylation. An asymmetric phosphorylation model is proposed, where one receptor in the dimer pair is responsible for activating the other receptor, the receiver, which then in turn phosphorylates the original activator. The model shows that the confinement zones on the membrane play a critical role in causing repeated receptor interactions and reveals that receptors dynamically switch between different activation states over time. Our work continues by delving deeper into the membrane landscape. Single particle tracking data is analyzed to investigate the characteristics of the observed anomalous diffusion. The analysis gives an estimate for the size range of the confinement zones and shows that they are a series of domains, not corrals. Taking the single particle tracking analysis one step further, we develop a Domain Reconstruction Algorithm that reconstructs confinement zone shapes and sizes from single particle tracking trajectories. In the final study, we move on to erbB2 and erbB3 interactions. ErbB3, which is traditionally believed to be kinase dead, has recently been shown to have weak kinase activity. Through kinase assay experiments, we show in the presence of erbB2 and heregulin, erbB3 has measurable kinase activity. Using the reconstructed domains from erbB2 and erbB3 data to create a simulation space, and experimental data from the kinase assay and single particle tracking, we extend the erbB1 spatial stochastic model for this study. We show that erbB2 and erbB3 have significantly different interactions with the cellular membrane confinement zones, erbB3 is dependent on erbB2 activation, and erbB3 homodimer stability inhibits erbB3 activation. Extension of the model to investigate mutation behaviors in erbB3 receptors reveals insights into how a gain of function mutation in the erbB3 kinase domain impacts erbB2 and erbB3 interactions. Finally, discovery of a gain of function mutation in the kinase domain of erbB3 is connected to an uptick in erbB3 kinase activity. As a path forward from this work, we suggest using the spatial stochastic model to investigate more possible mutations in erbB3 receptors to give better insight into which mutations would be promising to explore

Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstracts

Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstract

Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstracts

Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstract

ComplexWorld Position Paper

The Complex ATM Position Paper is the common research vehicle that defines the high-level, strategic scientific vision for the ComplexWorld Network. The purpose of this document is to provide an orderly and consistent scientific framework for the WP-E complexity theme. The specific objectives of the position paper are to: - analyse the state of the art within the different research areas relevant to the network, identifying the major accomplishments and providing a comprehensive set of references, including the main publications and research projects; - include a complete list of , a list of application topics, and an analysis of which techniques are best suited to each one of those applications; - identify and perform an in-depth analysis of the most promising research avenues and the major research challenges lying at the junction of ATM and complex systems domains, with particular attention to their impact and potential benefits for the ATM community; - identify areas of common interest and synergies with other SESAR activities, with special attention to the research topics covered by other WP-E networks. An additional goal for future versions of this position paper is to develop an indicative roadmap on how these research challenges should be accomplished, providing a guide on how to leverage on different aspects of the complexity research in Air Transport

Exploring the role of biota and biogenic components for the formation and function of (micro-)aggregates in soil

The here presented cumulative dissertation deals with the initial processes/mechanisms of aggregate formation in soil with a special focus on soil biota. Generally, aggregates are formed by the interaction between (in-)organic soil constituents (e.g., minerals and soil organic matter) and their response to changing environmental conditions. The interactions of these potentially (micro-)aggregate forming materials are influenced by their inherent properties (e.g., surface charge and roughness, particle shape and size, biopolymer composition, molecular weight and size), the prevailing environmental conditions (e.g., pH and electrical conductivity) and external forces (e.g., bioturbation, gravity, water menisci, swelling and shrinking processes). In soil, a three dimensional natural porous medium, aggregation-forming processes are ubiquitous, occurring sequentially as well as simultaneously. Consequently, the identification and investigation of specific aspects of aggregate formation is essential to place them in a high-level context and thus derive consequences on the pedon-scale (e.g., pollutant/nutrient accumulation, evolution of habitat, structure formation and stabilization). This cumulative work includes five publications dealing with the influence of biogenically excreted organic matter on aggregation revealed by lab based in-vitro studies (P2 and P3), numerical simulations dealing with the impact of the balance between particle size and concentration on aggregate morphology and aggregation dynamics (P4 and P5) as well as one comprehensive review article of biogenically triggered aggregation processes in soil (P1)