Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Robustness of the non-Markovian Alzheimer walk under stochastic perturbation

The elephant walk model originally proposed by Schutz and Trimper to investigate non-Markovian processes led to the investigation of a series of other random-walk models. Of these, the best known is the Alzheimer walk model, because it was the first model shown to have amnestically induced persistence-i.e. superdiffusion caused by loss of memory. Here we study the robustness of the Alzheimer walk by adding a memoryless stochastic perturbation. Surprisingly, the solution of the perturbed model can be formally reduced to the solutions of the unperturbed model. Specifically, we give an exact solution of the perturbed model by finding a surjective mapping to the unperturbed model. Copyright (C) EPLA, 2012

Dynamics of epithelial monolayers assessed by acoustic and impedimetric whole cell biosensors

Mit der Zielsetzung der vorliegenden Arbeit wurde die detailierten Analyse von Migrationsdynamiken epithelilaler Monolayer anhand zweier neuartiger in vitro Biosensoren verfolgt, der elektrischen Zell-Substrat Impedanz Spektroskopie (electrical cell-substrate impedance sensing, ECIS) sowie der Quarz Kristall Mikrowaage (quartz crystal microbalance, QCM). Beide Methoden erwiesen sich als sensitiv gegenüber der Zellmotilität und der Nanozytotoxizität.rnInnerhalb des ersten Projektes wurde ein Fingerprinting von Krebszellen anhand ihrer Motilitätsdynamiken und der daraus generierten elektrischen oder akkustischen Fluktuationen auf ECIS oder QCM Basis vorgenommen; diese Echtzeitsensoren wurdene mit Hilfe klassicher in vitro Boyden-Kammer Migrations- und Invasions-assays validiert. Fluktuationssignaturen, also Langzeitkorrelationen oder fraktale Selbstähnlichkeit aufgrund der kollektiven Zellbewegung, wurden über Varianz-, Fourier- sowie trendbereinigende Fluktuationsanalyse quantifiziert. Stochastische Langzeitgedächtnisphänomene erwiesen sich als maßgebliche Beiträge zur Antwort adhärenter Zellen auf den QCM und ECIS-Sensoren. Des weiteren wurde der Einfluss niedermolekularer Toxine auf die Zytoslelettdynamiken verfolgt: die Auswirkungen von Cytochalasin D, Phalloidin und Blebbistatin sowie Taxol, Nocodazol und Colchicin wurden dabei über die QCM und ECIS Fluktuationsanalyse erfasst.rnIn einem zweiten Projektschwerpunkt wurden Adhäsionsprozesse sowie Zell-Zell und Zell-Substrat Degradationsprozesse bei Nanopartikelgabe charackterisiert, um ein Maß für Nanozytotoxizität in Abhangigkeit der Form, Funktionalisierung Stabilität oder Ladung der Partikel zu erhalten.rnAls Schlussfolgerung ist zu nennen, dass die neuartigen Echtzeit-Biosensoren QCM und ECIS eine hohe Zellspezifität besitzen, auf Zytoskelettdynamiken reagieren sowie als sensitive Detektoren für die Zellvitalität fungieren können.

Stochastic foundations of dynamic trade and labor market models

This dissertation consists of three self-contained papers that are related to two main topics. In particular, the first and third studies focus on labor market modeling, whereas the second essay presents a dynamic international trade setup.rnrnIn Chapter "Expenses on Labor Market Reforms during Transitional Dynamics", we investigate the arising costs of a potential labor market reform from a government point of view. To analyze various effects of unemployment benefits system changes, this chapter develops a dynamic model with heterogeneous employed and unemployed workers.rn rnIn Chapter "Endogenous Markup Distributions", we study how markup distributions adjust when a closed economy opens up. In order to perform this analysis, we first present a closed-economy general-equilibrium industry dynamics model, where firms enter and exit markets, and then extend our analysis to the open-economy case.rn rnIn Chapter "Unemployment in the OECD - Pure Chance or Institutions?", we examine effects of aggregate shocks on the distribution of the unemployment rates in OECD member countries.rn rnIn all three chapters we model systems that behave randomly and operate on stochastic processes. We therefore exploit stochastic calculus that establishes clear methodological links between the chapters.

Eluding oblivion with smart stochastic selection of synaptic updates

The variables involved in the equations that describe realistic synaptic dynamics always vary in a limited range. Their boundedness makes the synapses forgetful, not for the mere passage of time, but because new experiences overwrite old memories. The forgetting rate depends on how many synapses are modified by each new experience: many changes means fast learning and fast forgetting, whereas few changes means slow learning and long memory retention. Reducing the average number of modified synapses can extend the memory span at the price of a reduced amount of information stored when a new experience is memorized. Every trick which allows to slow down the learning process in a smart way can improve the memory performance. We review some of the tricks that allow to elude fast forgetting (oblivion). They are based on the stochastic selection of the synapses whose modifications are actually consolidated following each new experience. In practice only a randomly selected, small fraction of the synapses eligible for an update are actually modified. This allows to acquire the amount of information necessary to retrieve the memory without compromising the retention of old experiences. The fraction of modified synapses can be further reduced in a smart way by changing synapses only when it is really necessary, i.e. when the post-synaptic neuron does not respond as desired. Finally we show that such a stochastic selection emerges naturally from spike driven synaptic dynamics which read noisy pre and post-synaptic neural activities. These activities can actually be generated by a chaotic system.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

IDENTIFICATION AND ANALYSIS OF A NOVEL ROLE FOR THE TOUSLED-LIKE KINASE IN REGULATING MITOTIC SPINDLE DYNAMICS

Deregulation of kinase activity is one example of how cells become cancerous by evading evolutionary constraints. The Tousled kinase (Tsl) was initially identified in Arabidopsis thaliana as a developmentally important kinase. There are two mammalian orthologues of Tsl and one orthologue in C. elegans, TLK-1, which is essential for embryonic viability and germ cell development. Depletion of TLK-1 leads to embryonic arrest large, distended nuclei, and ultimately embryonic lethality. Prior to terminal arrest, TLK-1-depleted embryos undergo aberrant mitoses characterized by poor metaphase chromosome alignment, delayed mitotic progression, lagging chromosomes, and supernumerary centrosomes. I discovered an unanticipated requirement for TLK-1 in mitotic spindle assembly and positioning. Normally, in the newly-fertilized zygote (P0) the maternal pronucleus migrates toward the paternal pronucleus at the posterior end of the embryo. After pronuclear meeting, the pronuclear-centrosome complex rotates 90° during centration to align on the anteroposterior axis followed by nuclear envelope breakdown (NEBD). However, in TLK-1-depleted P0 embryos, the centrosome-pronuclear complex rotation is significantly delayed with respect to NEBD and chromosome congression, Additionally, centrosome positions over time in tlk-1(RNAi) early embryos revealed a defect in posterior centrosome positioning during spindle-pronuclear centration, and 4D analysis of centrosome positions and movement in newly fertilized embryos showed aberrant centrosome dynamics in TLK-1-depleted embryos. Several mechanisms contribute to spindle rotation, one of which is the anchoring of astral microtubules to the cell cortex. Attachment of these microtubules to the cortices is thought to confer the necessary stability and forces in order to rotate the centrosome-pronuclear complex in a timely fashion. Analysis of a microtubule end-binding protein revealed that TLK-1-depleted embryos exhibit a more stochastic distribution of microtubule growth toward the cell cortices, and the types of microtubule attachments appear to differ from wild-type embryos. Additionally, fewer astral microtubules are in the vicinity of the cell cortex, thus suggesting that the delayed spindle rotation could be in part due to a lack of appropriate microtubule attachments to the cell cortex. Together with recently published biochemical data revealing the Tousled-like kinases associate with components of the dynein microtubule motor complex in humans, these data suggest that Tousled-like kinases play an important role in mitotic spindle assembly and positioning.

Modeling the dynamics of human hair cycles by a follicular automaton

The hair follicle cycle successively goes through the anagen, catagen, telogen, and latency phases, which correspond, respectively, to hair growth, arrest, shedding, and absence before a new anagen phase is initiated. Experimental observations collected over a period of 14 years in a group of 10 male volunteers, alopecic and nonalopecic, allowed us to determine the characteristics of scalp hair follicle cycles. On the basis of these observations, we propose a follicular automaton model to simulate the dynamics of human hair cycles. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states anagen, telogen, and latency, and the subsequent return to anagen. The transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a variance. The follicular automaton model accounts both for the dynamical transitions observed in a single follicle and for the behavior of an ensemble of independently cycling follicles. Thus, the model successfully reproduces the evolution of the fractions of follicle populations in each of the three phases, which fluctuate around steady-state or slowly drifting values. We apply the follicular automaton model to the study of spatial patterns of follicular growth that result from a spatially heterogeneous distribution of parameters such as the mean duration of anagen phase. When considering that follicles die or miniaturize after going through a critical number of successive cycles, the model can reproduce the evolution to hair patterns similar to well known types of diffuse or androgenetic alopecia.

Dynamics of Fos-Jun-NFAT1 complexes

Transcription initiation in eukaryotes is controlled by nucleoprotein complexes formed through cooperative interactions among multiple transcription regulatory proteins. These complexes may be assembled via stochastic collisions or defined pathways. We investigated the dynamics of Fos-Jun-NFAT1 complexes by using a multicolor fluorescence resonance energy transfer assay. Fos-Jun heterodimers can bind to AP-1 sites in two opposite orientations, only one of which is populated in mature Fos-Jun-NFAT1 complexes. We studied the reversal of Fos-Jun binding orientation in response to NFAT1 by measuring the efficiencies of energy transfer from donor fluorophores linked to opposite ends of an oligonucleotide to an acceptor fluorophore linked to one subunit of the heterodimer. The reorientation of Fos-Jun by NFAT1 was not inhibited by competitor oligonucleotides or heterodimers. The rate of Fos-Jun reorientation was faster than the rate of heterodimer dissociation at some binding sites. The facilitated reorientation of Fos-Jun heterodimers therefore can enhance the efficiency of Fos-Jun-NFAT1 complex formation. We also examined the influence of the preferred orientation of Fos-Jun binding on the stability and transcriptional activity of Fos-Jun-NFAT1 complexes. Complexes formed at sites where Fos-Jun favored the same binding orientation in the presence and absence of NFAT1 exhibited an 8-fold slower dissociation rate than complexes formed at sites where Fos-Jun favored the opposite binding orientation. Fos-Jun-NFAT1 complexes also exhibited greater transcription activation at promoter elements that favored the same orientation of Fos-Jun binding in the presence and absence of NFAT1. Thus, the orientation of heterodimer binding can influence both the dynamics and promoter selectivity of multiprotein transcription regulatory complexes.

Simple mechanochemistry describes the dynamics of kinesin molecules

Recently, Block and coworkers [Visscher, K., Schnitzer, M. J., & Block, S. M. (1999) Nature (London) 400, 184–189 and Schnitzer, M. J., Visscher, K. & Block, S. M. (2000) Nat. Cell Biol. 2, 718–723] have reported extensive observations of individual kinesin molecules moving along microtubules in vitro under controlled loads, F = 1 to 8 pN, with [ATP] = 1 μM to 2 mM. Their measurements of velocity, V, randomness, r, stalling force, and mean run length, L, reveal a need for improved theoretical understanding. We show, presenting explicit formulae that provide a quantitative basis for comparing distinct molecular motors, that their data are satisfactorily described by simple, discrete-state, sequential stochastic models. The simplest (N = 2)-state model with fixed load-distribution factors and kinetic rate constants concordant with stopped-flow experiments, accounts for the global (V, F, L, [ATP]) interdependence and, further, matches relative acceleration observed under assisting loads. The randomness, r(F,[ATP]), is accounted for by a waiting-time distribution, ψ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}{\mathrm{_{1}^{+}}}\end{equation*}\end{document}(t), [for the transition(s) following ATP binding] with a width parameter ν ≡ 〈t〉2/〈(Δt)2〉≃2.5, indicative of a dispersive stroke of mechanicity ≃0.6 or of a few (≳ν − 1) further, kinetically coupled states: indeed, N = 4 (but not N = 3) models do well. The analysis reveals: (i) a substep of d0 = 1.8–2.1 nm on ATP binding (consistent with structurally based suggestions); (ii) comparable load dependence for ATP binding and unbinding; (iii) a strong load dependence for reverse hydrolysis and subsequent reverse rates; and (iv) a large (≳50-fold) increase in detachment rate, with a marked load dependence, following ATP binding.

Impact of vaccination on the spatial correlation and persistence of measles dynamics.

The onset of measles vaccination in England and Wales in 1968 coincided with a marked drop in the temporal correlation of epidemic patterns between major cities. We analyze a variety of hypotheses for the mechanisms driving this change. Straightforward stochastic models suggest that the interaction between a lowered susceptible population (and hence increased demographic noise) and nonlinear dynamics is sufficient to cause the observed drop in correlation. The decorrelation of epidemics could potentially lessen the chance of global extinction and so inhibit attempts at measles eradication.

Finite temperature dynamics of vortices in the two dimensional anisotropic Heisenberg model

We study the effects of finite temperature on the dynamics of non-planar vortices in the classical, two-dimensional anisotropic Heisenberg model with XY- or easy-plane symmetry. To this end, we analyze a generalized Landau-Lifshitz equation including additive white noise and Gilbert damping. Using a collective variable theory with no adjustable parameters we derive an equation of motion for the vortices with stochastic forces which are shown to represent white noise with an effective diffusion constant linearly dependent on temperature. We solve these stochastic equations of motion by means of a Green's function formalism and obtain the mean vortex trajectory and its variance. We find a non-standard time dependence for the variance of the components perpendicular to the driving force. We compare the analytical results with Langevin dynamics simulations and find a good agreement up to temperatures of the order of 25% of the Kosterlitz-Thouless transition temperature. Finally, we discuss the reasons why our approach is not appropriate for higher temperatures as well as the discreteness effects observed in the numerical simulations.

The stochastic Gross-Pitaevskii equation: II

We provide a derivation of a more accurate version of the stochastic Gross-Pitaevskii equation, as introduced by Gardiner et al (2002 J. Phys. B: At. Mol. Opt. Phys. 35 1555). This derivation does not rely on the concept of local energy and momentum conservation and is based on a quasiclassical Wigner function representation of a 'high temperature' master equation for a Bose gas, which includes only modes below an energy cut-off ER that are sufficiently highly occupied (the condensate band). The modes above this cutoff (the non-condensate band) are treated as being essentially thermalized. The interaction between these two bands, known as growth and scattering processes, provides noise and damping terms in the equation of motion for the condensate band, which we call the stochastic Gross-Pitaevskii equation. This approach is distinguished by the control of the approximations made in its derivation and by the feasibility of its numerical implementation.

Fock-state dynamics in Raman photoassociation of Bose-Einstein condensates

By stochastic modeling of the process of Raman photoassociation of Bose-Einstein condensates, we show that, the farther the initial quantum state is from a coherent state, the farther the one-dimensional predictions are from those of the commonly used zero-dimensional approach. We compare the dynamics of condensates, initially in different quantum states, finding that, even when the quantum prediction for an initial coherent state is relatively close to the Gross-Pitaevskii prediction, an initial Fock state gives qualitatively different predictions. We also show that this difference is not present in a single-mode type of model, but that the quantum statistics assume a more important role as the dimensionality of the model is increased. This contrasting behavior in different dimensions, well known with critical phenomena in statistical mechanics, makes itself plainly visible here in a mesoscopic system and is a strong demonstration of the need to consider physically realistic models of interacting condensates.

Properties of the stochastic Gross-Pitaevskii equation: finite temperature Ehrenfest relations and the optimal plane wave representation

We present Ehrenfest relations for the high temperature stochastic Gross-Pitaevskii equation description of a trapped Bose gas, including the effect of growth noise and the energy cutoff. A condition for neglecting the cutoff terms in the Ehrenfest relations is found which is more stringent than the usual validity condition of the truncated Wigner or classical field method-that all modes are highly occupied. The condition requires a small overlap of the nonlinear interaction term with the lowest energy single particle state of the noncondensate band, and gives a means to constrain dynamical artefacts arising from the energy cutoff in numerical simulations. We apply the formalism to two simple test problems: (i) simulation of the Kohn mode oscillation for a trapped Bose gas at zero temperature, and (ii) computing the equilibrium properties of a finite temperature Bose gas within the classical field method. The examples indicate ways to control the effects of the cutoff, and that there is an optimal choice of plane wave basis for a given cutoff energy. This basis gives the best reproduction of the single particle spectrum, the condensate fraction and the position and momentum densities.