Techn. University, Diss., 2004--München.

No description available.

A Markov chain is introduced to the major steps of the process of learning a subject matter by a group of students in the classroom, in order to obtain a mathematical representation of the above process. A classroom experiment for learning mathematics is also presented illustrating the applicability of our results in practice.

No description available.

Cancer as a disease causes about 8.8 million deaths worldwide per year, a number that will largely increase in the next decades. Although the cellular processes involved in tumor emergence are more and more understood, the implications of specific changes at the cellular scale on tumor emergence at the tissue scale remain elusive. Main reasons for this lack of understanding are that the cellular processes are often hardly observable especially in the early phase of tumor development and that the interplay between cellular and tissue scale is difficult to deduce. Cell-based mathematical models provide a valuable tool to investigate in which way observable phenomena on the tissue scale develop by cellular processes. The implications of these models can elucidate underlying mechanisms and generate quantitative predictions that can be experimentally validated. In this thesis, we infer the role of genetic and phenotypic cell changes on tumor development with the help of cell-based Markov chain models which are calibrated by tissue-scale data. In the first part, we utilize data on the diagnosed fractions of benign and malignant tumor subtypes to unravel the consequences of genetic cell changes on tumor development. We introduce extensions of Moran models to investigate two specific biological questions. First, we evaluate the tumor regression behavior of pilocytic astrocytoma which represents the most common brain tumor in children and young adults. We formulate a Moran model with two absorbing states representing different subtypes of this tumor, derive the absorption probabilities in these states and calculate the tumor regression probability within the model. This analysis allows to predict the chance for tumor regression in dependency of the remaining tumor size and implies a different clinical resection strategy for pilocytic astrocytoma compared to other brain tumors. Second, we shed light on the hardly observable early cellular dynamics of tumor development and its consequences on the emergence of different tumor subtypes on the tissue scale. For this purpose, we utilize spatial and non-spatial Moran models with two absorbing states which describe both benign and malignant tumor subtypes and estimate lower and upper bounds for the range of cellular competition in different tissues. Our results suggest the existence of small and tissue-specific tumor-originating niches in which the fate of tumor development is decided long before a tumor manifests. These findings might help to identify the tumor-originating cell types for different cancer types. From a theoretical point of view, the novel analytical results regarding the absorption behavior of our extended Moran models contribute to a better understanding of this model class and have several applications also beyond the scope of this thesis. The second part is devoted to the investigation of the role of phenotypic plasticity of cancer cells in tumor development. In order to understand how phenotypic heterogeneity in tumors arises we describe cell state changes by a Markov chain model. This model allows to quantify the cell state transitions leading to the observed heterogeneity from experimental tissue-scale data on the evolution of cell state proportions. In order to bridge the gap between mathematical modeling and the analysis of such data, we developed an R package called CellTrans which is freely available. This package automatizes the whole process of mathematical modeling and can be utilized to (i) infer the transition probabilities between different cell states, (ii) predict cell line compositions at a certain time, (iii) predict equilibrium cell state compositions and (iv) estimate the time needed to reach this equilibrium. We utilize publicly available data on the evolution of cell compositions to demonstrate the applicability of CellTrans. Moreover, we apply CellTrans to investigate the observed cellular phenotypic heterogeneity in glioblastoma. For this purpose, we use data on the evolution of glioblastoma cell line compositions to infer to which extent the heterogeneity in these tumors can be explained by hierarchical phenotypic transitions. We also demonstrate in which way our newly developed R package can be utilized to analyze the influence of different micro-environmental conditions on cell state proportions. Summarized, this thesis contributes to gain a better understanding of the consequences of both genetic and phenotypic cell changes on tumor development with the help of Markov chain models which are motivated by the specific underlying biological questions. Moreover, the analysis of the novel Moran models provides new theoretical results, in particular regarding the absorption behavior of the underlying stochastic processes.

Ziel dieser Arbeit ist zunächst die Entwicklung einer Vergleichsgrundlage, auf Basis derer Algorithmen zur Berechnung der Zustandsdichte verglichen werden können. Darauf aufbauend wird ein bestehendes übergangsmatrixbasiertes Verfahren für das großkanonisch Ensemble um ein neues Auswerteverfahren erweitert. Dazu werden numerische Untersuchungen verschiedener Monte-Carlo-Algorithmen zur Berechnung der Zustandsdichte durchgeführt. Das Hauptaugenmerk liegt dabei auf Verfahren, die auf Übergangsmatrizen basieren, sowie auf dem Verfahren von Wang und Landau. Im ersten Teil der Forschungsarbeit wird ein umfassender Überblick über Monte-Carlo-Methoden und Auswerteverfahren zur Bestimmung der Zustandsdichte sowie über verwandte Verfahren gegeben. Außerdem werden verschiedene Methoden zur Berechnung der Zustandsdichte aus Übergangsmatrizen vorgestellt und diskutiert. Im zweiten Teil der Arbeit wird eine neue Vergleichsgrundlage für Algorithmen zur Bestimmung der Zustandsdichte erarbeitet. Dazu wird ein neues Modellsystem entwickelt, an dem verschiedene Parameter frei gewählt werden können und für das die exakte Zustandsdichte sowie die exakte Übergangsmatrix bekannt sind. Anschließend werden zwei weitere Systeme diskutiert für welche zumindest die exakte Zustandsdichte bekannt ist: das Ising Modell und das Lennard-Jones System. Der dritte Teil der Arbeit beschäftigt sich mit numerischen Untersuchungen an einer Auswahl der vorgestellten Verfahren. Auf Basis der entwickelten Vergleichsgrundlage wird der Einfluss verschiedener Parameter auf die Qualität der berechneten Zustandsdichte quantitativ bestimmt. Es wird gezeigt, dass Übergangsmatrizen in Simulationen mit Wang-Landau-Verfahren eine wesentlich bessere Zustandsdichte liefern als das Verfahren selbst. Anschließend werden die gewonnenen Erkenntnisse genutzt um ein neues Verfahren zu entwickeln mit welchem die Zustandsdichte mittels Minimierung der Abweichungen des detaillierten Gleichgewichts aus großen, dünnbesetzten Übergangsmatrizen gewonnen werden kann. Im Anschluss wird ein Lennard-Jones-System im großkanonischen Ensemble untersucht. Es wird gezeigt, dass durch das neue Verfahren Zustandsdichte und Dampfdruckkurve bestimmt werden können, welche qualitativ mit Referenzdaten übereinstimmen.

Self-organization of regular surface pattern under ion beam erosion was described in detail by Navez in 1962. Several years later in 1986 Bradley and Harper (BH) published the first self-consistent theory on this phenomenon based on the competition of surface roughening described by Sigmund's sputter theory and surface smoothing by Mullins-Herring diffusion. Many papers that followed BH theory introduced other processes responsible for the surface patterning e.g. viscous flow, redeposition, phase separation, preferential sputtering, etc. The present understanding is still not sufficient to specify the dominant driving forces responsible for self-organization. 3D atomistic simulations can improve the understanding by reproducing the pattern formation with the detailed microscopic description of the driving forces. 2D simulations published so far can contribute to this understanding only partially. A novel program package for 3D atomistic simulations called TRIDER (TRansport of Ions in matter with DEfect Relaxation), which unifies full collision cascade simulation with atomistic relaxation processes, has been developed. The collision cascades are provided by simulations based on the Binary Collision Approximation, and the relaxation processes are simulated with the 3D lattice kinetic Monte-Carlo method. This allows, without any phenomenological model, a full 3D atomistic description on experimental spatiotemporal scales. Recently discussed new mechanisms of surface patterning like ballistic mass drift or the dependence of the local morphology on sputtering yield are inherently included in our atomistic approach. The atomistic 3D simulations do not depend so much on experimental assumptions like reported 2D simulations or continuum theories. The 3D computer experiments can even be considered as 'cleanest' possible experiments for checking continuum theories. This work aims mainly at the methodology of a novel atomistic approach, showing that: (i) In general, sputtering is not the dominant driving force responsible for the ripple formation. Processes like bulk and surface defect kinetics dominate the surface morphology evolution. Only at grazing incidence the sputtering has been found to be a direct cause of the ripple formation. Bradley and Harper theory fails in explaining the ripple dynamics because it is based on the second-order-effect 'sputtering'. However, taking into account the new mechanisms, a 'Bradley-Harper equation' with redefined parameters can be derived, which describes pattern formation satisfactorily. (ii) Kinetics of (bulk) defects has been revealed as the dominating driving force of pattern formation. Constantly created defects within the collision cascade, are responsible for local surface topography fluctuation and cause surface mass currents. The mass currents smooth the surface at normal and close to normal ion incidence angles, while ripples appear first at incidence angles larger than 40°. The evolution of bimetallic interfaces under ion irradiation is another application of TRIDER described in this thesis. The collisional mixing is in competition with diffusion and phase separation. The irradiation with He ions is studied for two extreme cases of bimetals: (i) Irradiation of interfaces formed by immiscible elements, here Al and Pb. Ballistic interface mixing is accompanied by phase separation. Al and Pb nanoclusters show a self-ordering (banding) parallel to the interface. (ii) Irradiation of interfaces by intermetallics forming species, here Pt and Co. Well-ordered layers of phases of intermetallics appear in the sequence Pt/Pt3Co/PtCo/PtCo3/Co. The TRIDER program package has been proven to be an appropriate technique providing a complete picture of mixing mechanisms.

Self-organization of regular surface pattern under ion beam erosion was described in detail by Navez in 1962. Several years later in 1986 Bradley and Harper (BH) published the first self-consistent theory on this phenomenon based on the competition of surface roughening described by Sigmund's sputter theory and surface smoothing by Mullins-Herring diffusion. Many papers that followed BH theory introduced other processes responsible for the surface patterning e.g. viscous flow, redeposition, phase separation, preferential sputtering, etc. The present understanding is still not sufficient to specify the dominant driving forces responsible for self-organization. 3D atomistic simulations can improve the understanding by reproducing the pattern formation with the detailed microscopic description of the driving forces. 2D simulations published so far can contribute to this understanding only partially. A novel program package for 3D atomistic simulations called TRIDER (TRansport of Ions in matter with DEfect Relaxation), which unifies full collision cascade simulation with atomistic relaxation processes, has been developed. The collision cascades are provided by simulations based on the Binary Collision Approximation, and the relaxation processes are simulated with the 3D lattice kinetic Monte-Carlo method. This allows, without any phenomenological model, a full 3D atomistic description on experimental spatiotemporal scales. Recently discussed new mechanisms of surface patterning like ballistic mass drift or the dependence of the local morphology on sputtering yield are inherently included in our atomistic approach. The atomistic 3D simulations do not depend so much on experimental assumptions like reported 2D simulations or continuum theories. The 3D computer experiments can even be considered as 'cleanest' possible experiments for checking continuum theories. This work aims mainly at the methodology of a novel atomistic approach, showing that: (i) In general, sputtering is not the dominant driving force responsible for the ripple formation. Processes like bulk and surface defect kinetics dominate the surface morphology evolution. Only at grazing incidence the sputtering has been found to be a direct cause of the ripple formation. Bradley and Harper theory fails in explaining the ripple dynamics because it is based on the second-order-effect 'sputtering'. However, taking into account the new mechanisms, a 'Bradley-Harper equation' with redefined parameters can be derived, which describes pattern formation satisfactorily. (ii) Kinetics of (bulk) defects has been revealed as the dominating driving force of pattern formation. Constantly created defects within the collision cascade, are responsible for local surface topography fluctuation and cause surface mass currents. The mass currents smooth the surface at normal and close to normal ion incidence angles, while ripples appear first at incidence angles larger than 40°. The evolution of bimetallic interfaces under ion irradiation is another application of TRIDER described in this thesis. The collisional mixing is in competition with diffusion and phase separation. The irradiation with He ions is studied for two extreme cases of bimetals: (i) Irradiation of interfaces formed by immiscible elements, here Al and Pb. Ballistic interface mixing is accompanied by phase separation. Al and Pb nanoclusters show a self-ordering (banding) parallel to the interface. (ii) Irradiation of interfaces by intermetallics forming species, here Pt and Co. Well-ordered layers of phases of intermetallics appear in the sequence Pt/Pt3Co/PtCo/PtCo3/Co. The TRIDER program package has been proven to be an appropriate technique providing a complete picture of mixing mechanisms.

Ziel dieser Arbeit ist zunächst die Entwicklung einer Vergleichsgrundlage, auf Basis derer Algorithmen zur Berechnung der Zustandsdichte verglichen werden können. Darauf aufbauend wird ein bestehendes übergangsmatrixbasiertes Verfahren für das großkanonisch Ensemble um ein neues Auswerteverfahren erweitert. Dazu werden numerische Untersuchungen verschiedener Monte-Carlo-Algorithmen zur Berechnung der Zustandsdichte durchgeführt. Das Hauptaugenmerk liegt dabei auf Verfahren, die auf Übergangsmatrizen basieren, sowie auf dem Verfahren von Wang und Landau. Im ersten Teil der Forschungsarbeit wird ein umfassender Überblick über Monte-Carlo-Methoden und Auswerteverfahren zur Bestimmung der Zustandsdichte sowie über verwandte Verfahren gegeben. Außerdem werden verschiedene Methoden zur Berechnung der Zustandsdichte aus Übergangsmatrizen vorgestellt und diskutiert. Im zweiten Teil der Arbeit wird eine neue Vergleichsgrundlage für Algorithmen zur Bestimmung der Zustandsdichte erarbeitet. Dazu wird ein neues Modellsystem entwickelt, an dem verschiedene Parameter frei gewählt werden können und für das die exakte Zustandsdichte sowie die exakte Übergangsmatrix bekannt sind. Anschließend werden zwei weitere Systeme diskutiert für welche zumindest die exakte Zustandsdichte bekannt ist: das Ising Modell und das Lennard-Jones System. Der dritte Teil der Arbeit beschäftigt sich mit numerischen Untersuchungen an einer Auswahl der vorgestellten Verfahren. Auf Basis der entwickelten Vergleichsgrundlage wird der Einfluss verschiedener Parameter auf die Qualität der berechneten Zustandsdichte quantitativ bestimmt. Es wird gezeigt, dass Übergangsmatrizen in Simulationen mit Wang-Landau-Verfahren eine wesentlich bessere Zustandsdichte liefern als das Verfahren selbst. Anschließend werden die gewonnenen Erkenntnisse genutzt um ein neues Verfahren zu entwickeln mit welchem die Zustandsdichte mittels Minimierung der Abweichungen des detaillierten Gleichgewichts aus großen, dünnbesetzten Übergangsmatrizen gewonnen werden kann. Im Anschluss wird ein Lennard-Jones-System im großkanonischen Ensemble untersucht. Es wird gezeigt, dass durch das neue Verfahren Zustandsdichte und Dampfdruckkurve bestimmt werden können, welche qualitativ mit Referenzdaten übereinstimmen.