Agent-Based Modeling of Intracellular Transport

We develop an agent-based model of the motion and pattern formation of vesicles. These intracellular particles can be found in four different modes of (undirected and directed) motion and can fuse with other vesicles. While the size of vesicles follows a log-normal distribution that changes over time due to fusion processes, their spatial distribution gives rise to distinct patterns. Their occurrence depends on the concentration of proteins which are synthesized based on the transcriptional activities of some genes. Hence, differences in these spatio-temporal vesicle patterns allow indirect conclusions about the (unknown) impact of these genes. By means of agent-based computer simulations we are able to reproduce such patterns on real temporal and spatial scales. Our modeling approach is based on Brownian agents with an internal degree of freedom, $\theta$, that represents the different modes of motion. Conditions inside the cell are modeled by an effective potential that differs for agents dependent on their value $\theta$. Agent's motion in this effective potential is modeled by an overdampted Langevin equation, changes of $\theta$ are modeled as stochastic transitions with values obtained from experiments, and fusion events are modeled as space-dependent stochastic transitions. Our results for the spatio-temporal vesicle patterns can be used for a statistical comparison with experiments. We also derive hypotheses of how the silencing of some genes may affect the intracellular transport, and point to generalizations of the model

Spatiotemporal chaos and the dynamics of coupled Langmuir and ion-acoustic waves in plasmas

A simulation study is performed to investigate the dynamics of coupled Langmuir waves (LWs) and ion-acoustic waves (IAWs) in an unmagnetized plasma. The effects of dispersion due to charge separation and the density nonlinearity associated with the IAWs, are considered to modify the properties of Langmuir solitons, as well as to model the dynamics of relatively large amplitude wave envelopes. It is found that the Langmuir wave electric field, indeed, increases by the effect of ion-wave nonlinearity (IWN). Use of a low-dimensional model, based on three Fourier modes shows that a transition to temporal chaos is possible, when the length scale of the linearly excited modes is larger than that of the most unstable ones. The chaotic behaviors of the unstable modes are identified by the analysis of Lyapunov exponent spectra. The space-time evolution of the coupled LWs and IAWs shows that the IWN can cause the excitation of many unstable harmonic modes, and can lead to strong IAW emission. This occurs when the initial wave field is relatively large or the length scale of IAWs is larger than the soliton characteristic size. Numerical simulation also reveals that many solitary patterns can be excited and generated through the modulational instability (MI) of unstable harmonic modes. As time goes on, these solitons are seen to appear in the spatially partial coherence (SPC) state due to the free ion-acoustic radiation as well as in the state of spatiotemporal chaos (STC) due to collision and fusion in the stochastic motion. The latter results the redistribution of initial wave energy into a few modes with small length scales, which may lead to the onset of Langmuir turbulence in laboratory as well as space plasmas.Comment: 10 Pages, 14 Figures; to appear in Physical Review

Nonlinear wave-wave interactions in quantum plasmas

Wave-wave interaction in plasmas is a topic of important research since the 16th century. The formation of Langmuir solitons through the coupling of high-frequency (hf) Langmuir and low-frequency (lf) ion-acoustic waves, is one of the most interesting features in the context of turbulence in modern plasma physics. Moreover, quantum plasmas, which are ubiquitous in ultrasmall electronic devices, micromechanical systems as well as in dense astrophysical environments are a topic of current research. In the light of notable interests in such quantum plasmas, we present here a theoretical investigation on the nonlinear interaction of quantum Langmuir waves (QLWs) and quantum ion-acoustic waves (QIAWs), which are governed by the one-dimensional quantum Zakharov equations (QZEs). It is shown that a transition to spatiotemporal chaos (STC) occurs when the length scale of excitation of linear modes is larger than that of the most unstable ones. Such length scale is, however, to be larger (compared to the classical one) in presence of the quantum tunneling effect. The latter induces strong QIAW emission leading to the occurrence of collision and fusion among the patterns at an earlier time than the classical case. Moreover, numerical simulation of the QZEs reveals that many solitary patterns can be excited and saturated through the modulational instability (MI) of unstable harmonic modes. In a longer time, these solitons are seen to appear in the state of STC due to strong QIAW emission as well as by the collision and fusion in stochastic motion. The energy in the system is thus strongly redistributed, which may switch on the onset of Langmuir turbulence in quantum plasmas.Comment: 6 pages, 6 figures (To appear in AIP Conf. Proceedings 2010

Contributions of plasma physics to chaos and nonlinear dynamics

This topical review focusses on the contributions of plasma physics to chaos and nonlinear dynamics bringing new methods which are or can be used in other scientific domains. It starts with the development of the theory of Hamiltonian chaos, and then deals with order or quasi order, for instance adiabatic and soliton theories. It ends with a shorter account of dissipative and high dimensional Hamiltonian dynamics, and of quantum chaos. Most of these contributions are a spin-off of the research on thermonuclear fusion by magnetic confinement, which started in the fifties. Their presentation is both exhaustive and compact. [15 April 2016

Roman roads: The hierarchical endosymbiosis of cognitive modules

Serial endosymbiosis theory provides a unifying paradigm for examining the interaction of cognitive modules at vastly different scales of biological, social, and cultural organization. A trivial but not unimportant model associates a dual information source with a broad class of cognitive processes, and punctuated phenomena akin to phase transitions in physical systems, and associated coevolutionary processes, emerge as consequences of the homology between information source uncertainty and free energy density. The dynamics, including patterns of punctuation similar to ecosystem resilience transitions, are large dominated by the availability of 'Roman roads' constituting channels for the transmission of information between modules

Stochastic Calculus of Wrapped Compartments

The Calculus of Wrapped Compartments (CWC) is a variant of the Calculus of Looping Sequences (CLS). While keeping the same expressiveness, CWC strongly simplifies the development of automatic tools for the analysis of biological systems. The main simplification consists in the removal of the sequencing operator, thus lightening the formal treatment of the patterns to be matched in a term (whose complexity in CLS is strongly affected by the variables matching in the sequences). We define a stochastic semantics for this new calculus. As an application we model the interaction between macrophages and apoptotic neutrophils and a mechanism of gene regulation in E.Coli

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page