Harmonic deformation of Delaunay triangulations

We construct harmonic functions on random graphs given by Delaunay triangulations of ergodic point processes as the limit of the zero-temperature harness process. (C) 2012 Elsevier B.V All rights reserved.

A quantitative approach to evolution of music and philosophy

The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic.

A Robust Structural PGN Model for Control of Cell-Cycle Progression Stabilized by Negative Feedbacks

The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a probabilistic genetic network (PGN) to construct a hypothetical model with a dynamical behavior displaying the degree of robustness typical of the biological cell cycle. The structure of our PGN model was inspired in well-established biological facts such as the existence of integrator subsystems, negative and positive feedback loops, and redundant signaling pathways. Our model represents genes interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model does not perform as well as our PGN model, even upon moderate noise conditions. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle.

Consequences of plant population size for pollinator visitation and plant reproductive success

Habitat loss and fragmentation have a prominent role in determining the size of plant populations, and can affect plant-pollinator interactions. It is hypothesized that in small plant populations the ability to set seeds can be reduced due to limited pollination services, since individuals in small populations can receive less quantity or quality of visits. In this study, I investigated the effect of population size on plant reproductive success and insect visitation in 8 populations of two common species in the island of Lesvos, Greece (Mediterranean Sea), Echium plantagineum and Ballota acetabulosa, and of a rare perennial shrub endemic to north-central Italy, Ononis masquillierii. All the three species depended on insect pollinators for sexual reproduction. For each species, pollen limitation was present in all or nearly all populations, but the relationship between pollen limitation and population size was only present in Ononis masquillierii. However, in Echium plantagineum, significant relationships between both open-pollinated and handcrossed-pollinated seed sets and population size were found, being small populations comparatively less productive than large ones. Additionally, for this species, livestock grazing intensity was greater for small populations and for sparse patches, and had a negative influence on productivity of the remnant plants. Both Echium plantagineum and Ballota acetabulosa attracted a great number of insects, representing a wide spectrum of pollinators, thereby can be considered as generalist species. For Ballota acetabulosa, the most important pollinators were megachilid female bees, and insect diversity didn’t decrease with decreasing plant population size. By contrast, Ononis masquillierii plants generally received few visits, with flowers specialized on small bees (Lasioglossum spp.), representing the most important insect guild. In Echium plantagineum and Ballota acetabulosa, plants in small and large populations received the same amount of visits per flower, and no differences in the number of intraplant visited flowers were detected. On the contrary, large Ononis populations supported higher amounts of pollinators than small ones. At patch level, high Echium flower density was associated with more and higher quality pollinators. My results indicate that small populations were not subject to reduced pollination services than large ones in Echium plantagineum and Ballota acetabulosa, and suggest that grazing and resource limitation could have a major impact on population fitness in Echium plantagineum. The absence of any size effects in these two species can be explained in the light of their high local abundance, wide habitat specificity, and ability to compete with other co-flowering species for pollinators. By contrast, size represents a key characteristic for both pollination and reproduction in Ononis masquillierii populations, as an increase in size could mitigate the negative effects coming from the disadvantageous reproductive traits of the species. Finally, the widespread occurrence of pollen limitation in the three species may be the result of 1) an ongoing weakening or disruption of plantpollinator interactions derived from ecological perturbations, 2) an adaptive equilibrium in response to stochastic processes, and 3) the presence of unfavourable reproductive traits (for Ononis masquillierii).

Charakterisierung und Konvergenz mehrdimensionaler kontinuierlicher Verzweigungsprozesse

In dieser Arbeit wird eine Klasse von stochastischen Prozessen untersucht, die eine abstrakte Verzweigungseigenschaft besitzen. Die betrachteten Prozesse sind homogene Markov-Prozesse in stetiger Zeit mit Zuständen im mehrdimensionalen reellen Raum und dessen Ein-Punkt-Kompaktifizierung. Ausgehend von Minimalforderungen an die zugehörige Übergangsfunktion wird eine vollständige Charakterisierung der endlichdimensionalen Verteilungen mehrdimensionaler kontinuierlicher Verzweigungsprozesse vorgenommen. Mit Hilfe eines erweiterten Laplace-Kalküls wird gezeigt, dass jeder solche Prozess durch eine bestimmte spektral positive unendlich teilbare Verteilung eindeutig bestimmt ist. Umgekehrt wird nachgewiesen, dass zu jeder solchen unendlich teilbaren Verteilung ein zugehöriger Verzweigungsprozess konstruiert werden kann. Mit Hilfe der allgemeinen Theorie Markovscher Operatorhalbgruppen wird sichergestellt, dass jeder mehrdimensionale kontinuierliche Verzweigungsprozess eine Version mit Pfaden im Raum der cadlag-Funktionen besitzt. Ferner kann die (funktionale) schwache Konvergenz der Prozesse auf die vage Konvergenz der zugehörigen Charakterisierungen zurückgeführt werden. Hieraus folgen allgemeine Approximations- und Konvergenzsätze für die betrachtete Klasse von Prozessen. Diese allgemeinen Resultate werden auf die Unterklasse der sich verzweigenden Diffusionen angewendet. Es wird gezeigt, dass für diese Prozesse stets eine Version mit stetigen Pfaden existiert. Schließlich wird die allgemeinste Form der Fellerschen Diffusionsapproximation für mehrtypige Galton-Watson-Prozesse bewiesen.

Sea-Level climate variability in the Mediterranean Sea

Sea-level variability is characterized by multiple interacting factors described in the Fourth Assessment Report (Bindoff et al., 2007) of the Intergovernmental Panel on Climate Change (IPCC) that act over wide spectra of temporal and spatial scales. In Church et al. (2010) sea-level variability and changes are defined as manifestations of climate variability and change. The European Environmental Agency (EEA) defines sea level as one of most important indicators for monitoring climate change, as it integrates the response of different components of the Earths system and is also affected by anthropogenic contributions (EEA, 2011). The balance between the different sea-level contributions represents an important source of uncertainty, involving stochastic processes that are very difficult to describe and understand in detail, to the point that they are defined as an enigma in Munk (2002). Sea-level rate estimates are affected by all these uncertainties, in particular if we look at possible responses to sea-level contributions to future climate. At the regional scale, lateral fluxes also contribute to sea-level variability, adding complexity to sea-level dynamics. The research strategy adopted in this work to approach such an interesting and challenging topic has been to develop an objective methodology to study sea-level variability at different temporal and spatial scales, applicable in each part of the Mediterranean basin in particular, and in the global ocean in general, using all the best calibrated sources of data (for the Mediterranean): in-situ, remote-sensig and numerical models data. The global objective of this work was to achieve a deep understanding of all of the components of the sea-level signal contributing to sea-level variability, tendency and trend and to quantify them.

Statistical problems related to excitation threshold and reset value of membrane potentials

Die vorliegende Arbeit ist motiviert durch biologische Fragestellungen bezüglich des Verhaltens von Membranpotentialen in Neuronen. Ein vielfach betrachtetes Modell für spikende Neuronen ist das Folgende. Zwischen den Spikes verhält sich das Membranpotential wie ein Diffusionsprozess X der durch die SDGL dX_t= beta(X_t) dt+ sigma(X_t) dB_t gegeben ist, wobei (B_t) eine Standard-Brown'sche Bewegung bezeichnet. Spikes erklärt man wie folgt. Sobald das Potential X eine gewisse Exzitationsschwelle S überschreitet entsteht ein Spike. Danach wird das Potential wieder auf einen bestimmten Wert x_0 zurückgesetzt. In Anwendungen ist es manchmal möglich, einen Diffusionsprozess X zwischen den Spikes zu beobachten und die Koeffizienten der SDGL beta() und sigma() zu schätzen. Dennoch ist es nötig, die Schwellen x_0 und S zu bestimmen um das Modell festzulegen. Eine Möglichkeit, dieses Problem anzugehen, ist x_0 und S als Parameter eines statistischen Modells aufzufassen und diese zu schätzen. In der vorliegenden Arbeit werden vier verschiedene Fälle diskutiert, in denen wir jeweils annehmen, dass das Membranpotential X zwischen den Spikes eine Brown'sche Bewegung mit Drift, eine geometrische Brown'sche Bewegung, ein Ornstein-Uhlenbeck Prozess oder ein Cox-Ingersoll-Ross Prozess ist. Darüber hinaus beobachten wir die Zeiten zwischen aufeinander folgenden Spikes, die wir als iid Treffzeiten der Schwelle S von X gestartet in x_0 auffassen. Die ersten beiden Fälle ähneln sich sehr und man kann jeweils den Maximum-Likelihood-Schätzer explizit angeben. Darüber hinaus wird, unter Verwendung der LAN-Theorie, die Optimalität dieser Schätzer gezeigt. In den Fällen OU- und CIR-Prozess wählen wir eine Minimum-Distanz-Methode, die auf dem Vergleich von empirischer und wahrer Laplace-Transformation bezüglich einer Hilbertraumnorm beruht. Wir werden beweisen, dass alle Schätzer stark konsistent und asymptotisch normalverteilt sind. Im letzten Kapitel werden wir die Effizienz der Minimum-Distanz-Schätzer anhand simulierter Daten überprüfen. Ferner, werden Anwendungen auf reale Datensätze und deren Resultate ausführlich diskutiert.

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.

Impact of anthropogenic stressors on the population genetics of the common bioindicator Dreissena polymorpha (Pallas, 1771)

Toxicant inputs from agriculture, industry and human settlements have been shown to severely affect freshwater ecosystems. Pollution can lead to changes in population genetic patterns through various genetic and stochastic processes. In my thesis, I investigated the impact of anthropogenic stressors on the population genetics of the zebra mussel Dreissena polymorpha. In order to analyze the genetics of zebra mussel populations, I isolated five new highly polymorphic microsatellite loci. Out of those and other already existing microsatellite markers for this species, I established a robust marker set of six microsatellite loci for D. polymorpha. rnMonitoring the biogeographical background is an important requirement when integrating population genetic measures into ecotoxicological studies. I analyzed the biogeographical background of eleven populations in a section of the River Danube (in Hungary and Croatia) and some of its tributaries, and another population in the River Rhine as genetic outgroup. Moreover, I measured abiotic water parameters at the sampling sites and analyzed if they were correlated with the genetic parameters of the populations. The genetic differentiation was basically consistent with the overall biogeographical history of the populations in the study region. However, the genetic diversity of the populations was not influenced by the geographical distance between the populations, but by the environmental factors oxygen and temperature and also by other unidentified factors. I found strong evidence that genetic adaptation of zebra mussel populations to local habitat conditions had influenced the genetic constitution of the populations. Moreover, by establishing the biogeographical baseline of molecular variance in the study area, I laid the foundation for interpreting population genetic results in ecotoxicological experiments in this region.rnIn a cooperation project with the Department of Zoology of the University of Zagreb, I elaborated an integrated approach in biomonitoring with D. polymorpha by combining the analysis techniques of microsatellite analysis, Comet assay and micronucleus test (MNT). This approach was applied in a case study on freshwater contamination by an effluent of a wastewater treatment plant (WWTP) in the River Drava (Croatia) and a complementary laboratory experiment. I assessed and compared the genetic status of two zebra mussel populations from a contaminated and a reference site. Microsatellite analysis suggested that the contaminated population had undergone a genetic bottleneck, caused by random genetic drift and selection, whereas a bottleneck was not detected in the reference population. The Comet assay did not indicate any difference in DNA damage between the two populations, but MNT revealed that the contaminated population had an increased percentage of micronuclei in hemocytes in comparison to the reference population. The laboratory experiment with mussels exposed to municipal wastewater revealed that mussels from the contaminated site had a lower percentage of tail DNA and a higher percentage of micronuclei than the reference population. These differences between populations were probably caused by an overall decreased fitness of mussels from the contaminated site due to genetic drift and by an enhanced DNA repair mechanism due to adaptation to pollution in the source habitat. Overall, the combination of the three biomarkers provided sufficient information on the impact of both treated and non-treated municipal wastewater on the genetics of zebra mussels at different levels of biological organization.rnIn my thesis, I could show that the newly established marker set of six microsatellite loci provided reliable and informative data for population genetic analyses of D. polymorpha. The adaptation of the analyzed zebra mussel populations to the local conditions of their habitat had a strong influence on their genetic constitution. We found evidence that the different genetic constitutions of two populations had influenced the outcome of our ecotoxicological experiment. Overall, the integrated approach in biomonitoring gave comprehensive information about the impact of both treated and non-treated municipal wastewater on the genetics of zebra mussels at different levels of biological organization and was well practicable in a first case study.

The Feynman-Kac formula and applications to PDEs

The thesis presents a probabilistic approach to the theory of semigroups of operators, with particular attention to the Markov and Feller semigroups. The first goal of this work is the proof of the fundamental Feynman-Kac formula, which gives the solution of certain parabolic Cauchy problems, in terms of the expected value of the initial condition computed at the associated stochastic diffusion processes. The second target is the characterization of the principal eigenvalue of the generator of a semigroup with Markov transition probability function and of second order elliptic operators with real coefficients not necessarily self-adjoint. The thesis is divided into three chapters. In the first chapter we study the Brownian motion and some of its main properties, the stochastic processes, the stochastic integral and the Itô formula in order to finally arrive, in the last section, at the proof of the Feynman-Kac formula. The second chapter is devoted to the probabilistic approach to the semigroups theory and it is here that we introduce Markov and Feller semigroups. Special emphasis is given to the Feller semigroup associated with the Brownian motion. The third and last chapter is divided into two sections. In the first one we present the abstract characterization of the principal eigenvalue of the infinitesimal generator of a semigroup of operators acting on continuous functions over a compact metric space. In the second section this approach is used to study the principal eigenvalue of elliptic partial differential operators with real coefficients. At the end, in the appendix, we gather some of the technical results used in the thesis in more details. Appendix A is devoted to the Sion minimax theorem, while in appendix B we prove the Chernoff product formula for not necessarily self-adjoint operators.

Markers Models in Survival Analysis and Applications to Issues Associated with AIDS

Jewell and Kalbfleisch (1992) consider the use of marker processes for applications related to estimation of the survival distribution of time to failure. Marker processes were assumed to be stochastic processes that, at a given point in time, provide information about the current hazard and consequently on the remaining time to failure. Particular attention was paid to calculations based on a simple additive model for the relationship between the hazard function at time t and the history of the marker process up until time t. Specific applications to the analysis of AIDS data included the use of markers as surrogate responses for onset of AIDS with censored data and as predictors of the time elapsed since infection in prevalent individuals. Here we review recent work on the use of marker data to tackle these kinds of problems with AIDS data. The Poisson marker process with an additive model, introduced in Jewell and Kalbfleisch (1992) may be a useful "test" example for comparison of various procedures.

Generalizations of Current Status Data With Applications

In estimation of a survival function, current status data arises when the only information available on individuals is their survival status at a single monitoring time. Here we briefly review extensions of this form of data structure in two directions: (i) doubly censored current status data, where there is incomplete information on the origin of the failure time random variable, and (ii) current status information on more complicated stochastic processes. Simple examples of these data forms are presented for motivation.

Beherrschung stark korrelierter Logistik- und Produktions-Prozesse

Bei der Simulation von Logistik- und Produktionssystem werden Zufallszahlengeneratoren verwendet, um stochastische Einflüsse zu modellieren. Ein wichtiges Qualitätsmerkmal dieser Generatoren ist die Er-zeugung möglichst unabhängiger Zufallszahlen. Werden jedoch reale Prozesse betrachtet, so sind die Daten im Allgemeinen nicht unabhängig. Diese Arbeit befasst sich mit der Analyse von Praxisdaten bezüglich des Auftretens von Abhängigkeiten. Dazu werden Korrelationsstrukturen gesucht. Außerdem wird gezeigt, dass unabhängige Zufallszahlen in der Regel ungeeignet sind, um stochastische Prozesse mit ausgeprägten Abhängigkeiten zu modellieren.

Stationarity of multivariate particle systems

A particle system is a family of i.i.d. stochastic processes with values translated by Poisson points. We obtain conditions that ensure the stationarity in time of the particle system in RdRd and in some cases provide a full characterisation of the stationarity property. In particular, a full characterisation of stationary multivariate Brown–Resnick processes is given.