Aus Punkt 1: "Warum lohnt sich Semiotik gerade im Bereich Usability und Design? Mehr noch, die Semiotik als übergreifende Perspektive ist hier gar nicht zu vermeiden. (Vermeidbar ist allenfalls der Soziolekt bzw. Technolekt der akademischen Semiotik, nicht aber ein semiotisches Arbeiten selbst.) Das Denken vieler Designer ist eher visuell geprägt. Diese Ausrichtung auf non-verbale Formen und Handlungen scheint der Semiotik entgegen zu stehen. Die Semiotik hat zwar eine starke Tradition in der Linguistik, aber diese stellt nur eine von mehreren gleichwertigen Zugängen dar: Man denke etwa an die Medizin (wo visuelle und sonstige Symptome als Zeichen gedeutet werden), an die Malerei (wo es Repräsentationen für ästhetische, soziale und politische Entsprechungen gibt), an die Gestik (wo jede kleinere oder größere Bewegung eines Muskels mit Bedeutungen verknüpft ist) oder an die Musik (wo sehr abstrakte Tonfolgen mit emotionaler Dynamik verbunden sind) – dazu etwa Eco (2002), Nöth (2000), Hucklenbroich (2003), Mazzola (2003) sowie Grammer (2004). ..."

The presented work wants to contribute a new solution based on the analysis of stochastic signals. On the basis of the Dresden Live-Camera-System which is providing real-time information about the traffic state on 31 focal points (March 2005) one is able to use a wide range of image types under different and severe conditions. The method is based on the analysis of stochastic signals derived from the live-camra images. These signals are analyzed with cross-correlation, amplitude- and frequency filters. The resulting data enable the distinction of stable and non-stable traffic flow and the automated identification of traffic congestion. Moreover fundamental diagrams are calculated. / Die vorgelegte Arbeit beinhaltet ein neuartiges Verfahren zur automatischen Ermittlung des Verkehrszustandes aus Live-Kamera-Bildern. Die Datengrundlage dafür liefert das im Rahmen des BMBF-Leitprojektes intermobil Region Dresden geschaffenen Live-Kamerasystem mit 31 Standorten (Stand März 2005). Das entwickelte Verfahren basiert auf der Analyse stochastischer Signale, die aus den Kamerabildern ermittelt werden. Die methodischen Grundlagen des Verfahrens sind Korrelationsanalyse sowie Amplituden- und Frequenzfilterung. Die Rahmenbedingungen für den praktischen Einsatz sind durch die Variabilität von Auflösung und Blickwinkel an den unterschiedlichen Kamerastandorten geprägt. Die ermittelten Messwerte ermöglichen eine Unterscheidung der Verkehrszustände "flüssiger Verkehr", "zähflüssiger Verkehr" und "Stop&Go" und werden am Fundamentaldiagramm interpretiert.

The human sense of hearing is characterized by its exquisite sensitivity, sharp frequency selectivity, and wide dynamic range. These features depend on an active process that in the inner ear boosts vibrations evoked by auditory stimuli. Spontaneous otoacoustic emissions constitute a demonstrative manifestation of this physiologically vulnerable mechanism. In the cochlea, sensory hair bundles transduce sound-induced vibrations into neural signals. Hair bundles can power mechanical movements of their tip, oscillate spontaneously, and operate as tuned nonlinear amplifiers of weak periodic stimuli. Active hair-bundle motility constitutes a promising candidate with respect to the biophysical implementation of the active process underlying human hearing. The responsiveness of isolated hair bundles, however, is seriously hampered by intrinsic fluctuations. In this thesis, we present theoretical and experimental results concerning the noise-imposed limitations of nonlinear amplification by active sensory hair bundles. We analyze the effect of noise within the framework of a stochastic description of hair-bundle dynamics and relate our findings to generic aspects of the stochastic dynamics of oscillatory systems. Hair bundles in vivo are often elastically coupled by overlying gelatinous membranes. In addition to theoretical results concerning the dynamics of elastically coupled hair bundles, we report on an experimental study. We have interfaced dynamic force clamp performed on a hair bundle from the sacculus of the bullfrog with real-time stochastic simulations of hair-bundle dynamics. By means of this setup, we could couple a hair bundle to two virtual neighbors, called cyber clones. Our theoretical and experimental work shows that elastic coupling leads to an effective noise reduction. Coupled hair bundles exhibit an increased coherence of spontaneous oscillations and an enhanced amplification gain. We therefore argue that elastic coupling by overlying membranes constitutes a morphological specialization for reducing the detrimental effect of intrinsic fluctuations.

Kollektive Migration und Schwarmverhalten sind Beispiele für Selbstorganisation und können in verschiedenen biologischen Systemen beobachtet werden, beispielsweise in Vogel-und Fischschwärmen oder Bakterienpopulationen. Im Zentrum dieser Arbeit steht ein räumlich diskretes und zeitlich stetiges Model, welches das kollektive Migrieren von Individuen mittels eines stochastischen Vielteilchensystems (VTS) beschreibt und analysierbar macht. Das konstruierte Modell ist in keiner Klasse gut untersuchter Vielteilchensysteme enthalten, sodass der größte Teil der Arbeit der Entwicklung von Methoden zur Untersuchung des Langzeitverhaltens bestimmter VTS gewidmet ist. Eine entscheidende Rolle spielen hier Gibbs-Maße, die zu zeitlich invarianten Maßen in Beziehung gesetzt werden. Durch eine Simulationsstudie und die Analyse des Einflusses der Parameter Migrationsgeschwindigkeit, Sensitivität der Individuen und (räumliche) Dichte der Anfangsverteilung können Eigenschaften kollektiver Migration erklärt und Hypothesen für weitere Analysen aufgestellt werden. / Collective migration and swarming behavior are examples of self-organization and can be observed in various biological systems, such as in flocks of birds, schools of fish or populations of bacteria. In the center of this thesis lies a stochastic interacting particle system (IPS), which is a spatially discrete model with a continuous time scale that describes collective migration and which can be treated using analytical methods. The constructed model is not contained in any class of well-understood IPS’s. The largest part of this work is used to develop methods that can be used to study the long-term behavior of certain IPS’s. Thereby Gibbs-Measures play an important role and are related to temporally invariant measures. One can explain the properties of collective migration and propose a hypothesis for further analyses by a simulation study and by analysing the parameters migration velocity, sensitivity of individuals and (spatial) density of the initial distribution.

No description available.

We consider p independent Brownian motions in ℝd. We assume that p ≥ 2 and p(d- 2) < d. Let ℓt denote the intersection measure of the p paths by time t, i.e., the random measure on ℝd that assigns to any measurable set A ⊂ ℝd the amount of intersection local time of the motions spent in A by time t. Earlier results of Chen derived the logarithmic asymptotics of the upper tails of the total mass ℓt(ℝd) as t →∞. In this paper, we derive a large-deviation principle for the normalised intersection measure t-pℓt on the set of positive measures on some open bounded set B ⊂ ℝd as t →∞ before exiting B. The rate function is explicit and gives some rigorous meaning, in this asymptotic regime, to the understanding that the intersection measure is the pointwise product of the densities of the normalised occupation times measures of the p motions. Our proof makes the classical Donsker-Varadhan principle for the latter applicable to the intersection measure. A second version of our principle is proved for the motions observed until the individual exit times from B, conditional on a large total mass in some compact set U ⊂ B. This extends earlier studies on the intersection measure by König and Mörters.

This study investigates how the structure and activities of states shape societies in different ways during processes of economic development. The analysis explores how the particular institutional configurations of developmental states in South Korea, Taiwan, and Singapore shaped trajectories of social change in ways which impacted processes of political change at later points in time. Using a path dependency approach, the study argues that a critical juncture took place in these three countries at various points in their early post-colonial periods, during which time state elites undertook a comprehensive program of reorganizing the state, society, and the organizational and institutional connections between the two, for the purpose of pursuing a strategy of rapid export-oriented industrialization. Differences in the way this critical juncture took place across these cases shaped important variations in institutional patterns of state-society relations. These differences, in turn, conditioned subsequent variation in the mode and type of political change in these countries.

If one takes a snapshot of Romanian migration, the first observation might be that the home villages or communities are very different. This is also the conclusion that Massey et al. (1994) first reach when comparing Mexican communities. However, if one compares migrant communities in a longitudinal manner, it can be seen rather that they are converging towards similar migration patterns rather than diverging. To explore this, I conducted fieldwork research in two villages from different socio-cultural regions of Romania, and for the second phase of the research followed the migrants to their destinations in Spain. In total I conducted more than 50 biographical narrative interviews with migrants and fifteen in-depth interviews with representatives from local authorities and other key informants on rural Romanian life. The biographical narrative interviews allowed me to take a longitudinal perspective on the migration from the two villages. The aim in comparing the two villages was to understand the internal logic of migration and examine to what extent two different villages showed any syncretism through cumulative structural effects. Analysing migrants’ projects, the family migration and the general migration from the two villages – each accounting for different levels of analysis – allowed me to specify the stages of migration. In the thesis, firstly I explain the socio-economic, cultural and geographical context in the origin community which shapes migration. Secondly, I compare the migration patterns of two families from the two villages, and thirdly I abstract three migration projects specific to the two communities. All these allow me to show that the two villages are at different stages in the migration process (Massey et al. 1994) and also to explain the mechanism of passing from one stage to the next. So far, the literature on migration policies has looked at the receiving countries. Few references are made to the origin countries, and these refer to Mexico, the Philippines and some of the Northern African countries, countries which have an active policy of promoting migration. Literature with regard to the European cases – for example Serbia, which has a Ministry of the Diaspora, or Poland, a country with a very long history emigration – is absent. Moreover, topics such as grounded migration policy making or the local dimension of policy making are still new in the reflexion of scholars. The thesis fills this gap with respect to migration policies of bonding migrants and involving them in development in the home community. The theory that holds together all these components is Luhmann’s systems theory (1995), in the way it was adapted to migration research by Bommes (2005) and Bommes and Tacke (2006a, 2006b). Using systems theory allows me to perform a critique of concepts like migration networks and transnationalism, which are very often used in the analysis of migration.

Latente Gauß-Prozess-Modelle (latent Gaussian process models) werden von Wissenschaftlern benutzt, um verborgenen Muster in Daten zu er- kennen, Expertenwissen in probabilistische Modelle einfließen zu lassen und um Vorhersagen über die Zukunft zu treffen. Diese Modelle wurden erfolgreich in vielen Gebieten wie Robotik, Geologie, Genetik und Medizin angewendet. Gauß-Prozesse definieren Verteilungen über Funktionen und können als flexible Bausteine verwendet werden, um aussagekräftige probabilistische Modelle zu entwickeln. Dabei ist die größte Herausforderung, eine geeignete Inferenzmethode zu implementieren. Inferenz in probabilistischen Modellen bedeutet die A-Posteriori-Verteilung der latenten Variablen, gegeben der Daten, zu berechnen. Die meisten interessanten latenten Gauß-Prozess-Modelle haben zurzeit nur begrenzte Anwendungsmöglichkeiten auf großen Datensätzen. In dieser Doktorarbeit stellen wir eine neue effiziente Inferenzmethode für latente Gauß-Prozess-Modelle vor. Unser neuer Ansatz, den wir augmented variational inference nennen, basiert auf der Idee, eine erweiterte (augmented) Version des Gauß-Prozess-Modells zu betrachten, welche bedingt konjugiert (conditionally conjugate) ist. Wir zeigen, dass Inferenz in dem erweiterten Modell effektiver ist und dass alle Schritte des variational inference Algorithmus in geschlossener Form berechnet werden können, was mit früheren Ansätzen nicht möglich war. Unser neues Inferenzkonzept ermöglicht es, neue latente Gauß-Prozess- Modelle zu studieren, die zu innovativen Ergebnissen im Bereich der Sprachmodellierung, genetischen Assoziationsstudien und Quantifizierung der Unsicherheit in Klassifikationsproblemen führen. / Latent Gaussian process (GP) models help scientists to uncover hidden structure in data, express domain knowledge and form predictions about the future. These models have been successfully applied in many domains including robotics, geology, genetics and medicine. A GP defines a distribution over functions and can be used as a flexible building block to develop expressive probabilistic models. The main computational challenge of these models is to make inference about the unobserved latent random variables, that is, computing the posterior distribution given the data. Currently, most interesting Gaussian process models have limited applicability to big data. This thesis develops a new efficient inference approach for latent GP models. Our new inference framework, which we call augmented variational inference, is based on the idea of considering an augmented version of the intractable GP model that renders the model conditionally conjugate. We show that inference in the augmented model is more efficient and, unlike in previous approaches, all updates can be computed in closed form. The ideas around our inference framework facilitate novel latent GP models that lead to new results in language modeling, genetic association studies and uncertainty quantification in classification tasks.

Cellular decision-making help cells to infer functionally different phenotypes in response to microenvironmental cues and noise present in the system and the environment, with or without genetic change. In Cellular Biology, there exists a list of open questions such as, how individual cell decisions influence the dynamics at the population level (an organization of indistinguishable cells) and at the tissue level (a group of nearly identical cells and their corresponding extracellular matrix which simultaneously accomplish a set of biological operations)? As collective cell migration originates from local cellular orientation decisions, can one generate a mathematical model for collective cell migration phenomena without elusive undiscovered biophysical/biochemical mechanisms and further predict the pattern formations which originates inside the collective cell migration? how optimal microenvironmental sensing is related to differentiated tissue at the spatial scale ? How cell sensing radius and total entropy production (which precisely helps us to understand the operating regimes where cells can take decisions about their future fate) is correlated, and how can one understand the limits of sensing radius at robust tissue development ? To partially tackle these sets of questions, the LEUP (Least microEnvironmental Uncertainty Principle) hypothesis has been applied to different biological scenaros. At first, the LEUP has been enforced to understand the spatio-temporal behavior of a tissue exhibiting phenotypic plasticity (it is a prototype of cell decision-making). Here, two cases have been rigorously studied i.e., migration/resting and migration/proliferation plasticity which underlie the epithelial-mesenchymal transition (EMT) and the Go-or-Grow dichotomy. On the one hand, for the Go-or-Rest plasticity, a bistable switching mechanism between a diffusive (fluid) and an epithelial (solid) tissue phase has been observed from an analogous mean-field approximation which further depends on the sensitivity of the phenotypes to the microenvironment. However, on the other hand, for the Go-or-Grow plasticity, the possibility of Turing pattern formation is inspected for the “solid” tissue phase and its relation to the parameters of the LEUP-driven cell decisions. Later, LEUP hypothesis has been suggested in the area of collective cell migration such that it can provide a tool for a generative mathematical model of collective migration without precise knowledge about the mechanistic details, where the famous Vicsek model is a special case. In this generative model of collective cell migration, the origin of pattern formation inside collective cell migration has been investigated. Moreover, this hypothesis helps to construct a mathematical model for the collective behavior of spherical \textit{Serratia marcescens} bacteria, where the basic understanding of migration mechanisms remain unknown. Furthermore, LEUP has been applied to understand tissue robustness, which in turn shows the way how progenitor cell fate decisions are associated with environmental sensing. The regulation of environmental sensing drives the robustness of the spatial and temporal order in which cells are generated towards a fully differentiating tissue, which are verified later with the experimental data. LEUP driven stochastic thermodynamic formalism also shows that the thermodynamic robustness of differentiated tissues depends on cell metabolism, cell sensing properties and the limits of the cell sensing radius, which further ensures the robustness of differentiated tissue spatial order. Finally, all important results of the thesis have been encapsulated and the extension of the LEUP has been discussed.:Contents Statement of authorship vii Abstract ix I. Introduction to cell decision-making 1 1. What is cell decision-making ? 3 1.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2. Examplesofcelldecision-making. . . . . . . . . . . . . . . . . . . . . . 4 1.2.1. PhenotypicPlasticity . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.2. Cellularmigration:orientationdecisions . . . . . . . . . . . . . 5 1.2.3. Celldifferentiation . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.3. Challengesandopenquestions . . . . . . . . . . . . . . . . . . . . . . 7 1.4. Solutionstrategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.5. Structureofthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 II. Least microEnvironmental Uncertainty Principle (LEUP) 11 2. Least microEnvironmental Uncertainty Principle (LEUP) 13 2.1. HypothesisbehindLEUP . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.2. Mathematicalformulation . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.1. CellasBayesiandecisionmaker . . . . . . . . . . . . . . . . . . 14 2.2.2. VariationalprincipleforLEUP . . . . . . . . . . . . . . . . . . . . 16 III. LEUP in biological problems 17 3. Phenotypic plasticity : dynamics at the level of tissue from individual cell decisions 19 3.1. Mathematicalframework . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.2. Individualbasedmodel(IBM) . . . . . . . . . . . . . . . . . . . . . . . . 22 3.3. Mean-fieldapproximation . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.3.1. Phenotypicswitchingdynamics . . . . . . . . . . . . . . . . . . 26 3.3.2. Cellmigrationdynamics . . . . . . . . . . . . . . . . . . . . . . . 28 3.3.3. Superpositionofphenotypicswitchingdynamicsandcellmi- gration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.4. Spatio-temporaldynamicsofcellmigration/proliferationplasticity . . 28 3.4.1. CaseI:Largeinteractionradius . . . . . . . . . . . . . . . . . . 29 3.4.2. CaseII:Finiteinteractionradius . . . . . . . . . . . . . . . . . . 30 3.4.3. Phenotypicswitchingdynamicsintheabsenceofmicroenvi- ronmentalsensing . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.5. Summaryandoutlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 4. Cellular orientation decisions: origin of pattern formations in collective cell migrations 39 4.1. Mathematicalframework . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.1.1. Self-propelledparticlemodelwithleupbaseddecision-making 41 4.1.2. Orderparametersandobservables . . . . . . . . . . . . . . . . 42 4.1.3. Statisticaltest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.2. ComparisonwithVicsekmodel . . . . . . . . . . . . . . . . . . . . . . . 43 4.2.1. Patternsindifferentparameterregimes . . . . . . . . . . . . . 45 4.3. Application:thesphericalbacteriacase. . . . . . . . . . . . . . . . . . 47 4.4. Summaryandoutlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5. Cell differentiation and sensing: tissue robustness from optimal environ- mental sensing 53 5.1. LEUPbasedmathematicalmodelforcelldifferentiation . . . . . . . . 56 5.1.1. StatisticalresultsfromLEUP . . . . . . . . . . . . . . . . . . . . 59 5.2. RelationbetweenLEUPandcellsensing . . . . . . . . . . . . . . . . . 60 5.3. LEUPdrivenfluctuationtheorem: confirmsthethermodynamicro- bustnessofdifferentiatedtissues . . . . . . . . . . . . . . . . . . . . . 61 5.3.1. Application: differentiated photoreceptor mosaics are ther- modynamicallyrobust . . . . . . . . . . . . . . . . . . . . . . . . 65 5.4. Thelimitforcellsensingradius . . . . . . . . . . . . . . . . . . . . . . . 67 5.4.1. Application:Theaveragesensingradiusoftheavianconecell 69 5.5. Summaryandoutlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 6. Discussions 75 7. Supplementary Material 91 8. Erklärung 115