Pair approximation for a model of vertical and horizontal transmission of parasites.

We apply Stochastic Dynamics method for a differential equations model, proposed by Marc Lipsitch and collaborators (Proc. R. Soc. Lond. B 260, 321, 1995), for which the transmission dynamics of parasites occurs from a parent to its offspring (vertical transmission), and by contact with infected host (horizontal transmission). Herpes, Hepatitis and AIDS are examples of diseases for which both horizontal and vertical transmission occur simultaneously during the virus spreading. Understanding the role of each type of transmission in the infection prevalence on a susceptible host population may provide some information about the factors that contribute for the eradication and/or control of those diseases. We present a pair mean-field approximation obtained from the master equation of the model. The pair approximation is formed by the differential equations of the susceptible and infected population densities and the differential equations of pairs that contribute to the former ones. In terms of the model parameters, we obtain the conditions that lead to the disease eradication, and set up the phase diagram based on the local stability analysis of fixed points. We also perform Monte Carlo simulations of the model on complete graphs and Erdös-Rényi graphs in order to investigate the influence of population size and neighborhood on the previous mean-field results; by this way, we also expect to evaluate the contribution of vertical and horizontal transmission on the elimination of parasite. Pair Approximation for a Model of Vertical and Horizontal Transmission of Parasites.

Study of surface free energy on a lattice-gas model applied to Liquid bridge

The pulmonary crackling and the formation of liquid bridges are problems that for centuries have been attracting the attention of scientists. In order to study these phenomena, it was developed a canonical cubic lattice-gas­ like model to explain the rupture of liquid bridges in lung airways [A. Alencar et al., 2006, PRE]. Here, we further develop this model and add entropy analysis to study thermodynamic properties, such as free energy and force. The simulations were performed using the Monte Carlo method with Metropolis algorithm. The exchange between gas and liquid particles were performed randomly according to the Kawasaki dynamics and weighted by the Boltzmann factor. Each particle, which can be solid (s), liquid (l) or gas (g), has 26 neighbors: 6 + 12 + 8, with distances 1, √2 and √3, respectively. The energy of a lattice's site m is calculated by the following expression: Em = ∑k=126 Ji(m)j(k) in witch (i, j) = g, l or s. Specifically, it was studied the surface free energy of the liquid bridge, trapped between two planes, when its height is changed. For that, was considered two methods. First, just the internal energy was calculated. Then was considered the entropy. It was fond no difference in the surface free energy between this two methods. We calculate the liquid bridge force between the two planes using the numerical surface free energy. This force is strong for small height, and decreases as the distance between the two planes, height, is increased. The liquid-gas system was also characterized studying the variation of internal energy and heat capacity with the temperature. For that, was performed simulation with the same proportion of liquid and gas particle, but different lattice size. The scale of the liquid-gas system was also studied, for low temperature, using different values to the interaction Jij.

Transcriptional regulation of human mu-opioid receptor gene: functional characterization of activating and inhibitory transcription factors

The organization of the nervous and immune systems is characterized by obvious differences and striking parallels. Both systems need to relay information across very short and very long distances. The nervous system communicates over both long and short ranges primarily by means of more or less hardwired intercellular connections, consisting of axons, dendrites, and synapses. Longrange communication in the immune system occurs mainly via the ordered and guided migration of immune cells and systemically acting soluble factors such as antibodies, cytokines, and chemokines. Its short-range communication either is mediated by locally acting soluble factors or transpires during direct cell–cell contact across specialized areas called “immunological synapses” (Kirschensteiner et al., 2003). These parallels in intercellular communication are complemented by a complex array of factors that induce cell growth and differentiation: these factors in the immune system are called cytokines; in the nervous system, they are called neurotrophic factors. Neither the cytokines nor the neurotrophic factors appear to be completely exclusive to either system (Neumann et al., 2002). In particular, mounting evidence indicates that some of the most potent members of the neurotrophin family, for example, nerve growth factor (NGF) and brainderived neurotrophic factor (BDNF), act on or are produced by immune cells (Kerschensteiner et al., 1999) There are, however, other neurotrophic factors, for example the insulin-like growth factor-1 (IGF-1), that can behave similarly (Kermer et al., 2000). These factors may allow the two systems to “cross-talk” and eventually may provide a molecular explanation for the reports that inflammation after central nervous system (CNS) injury has beneficial effects (Moalem et al., 1999). In order to shed some more light on such a cross-talk, therefore, transcription factors modulating mu-opioid receptor (MOPr) expression in neurons and immune cells are here investigated. More precisely, I focused my attention on IGF-I modulation of MOPr in neurons and T-cell receptor induction of MOPr expression in T-lymphocytes. Three different opioid receptors [mu (MOPr), delta (DOPr), and kappa (KOPr)] belonging to the G-protein coupled receptor super-family have been cloned. They are activated by structurallyrelated exogenous opioids or endogenous opioid peptides, and contribute to the regulation of several functions including pain transmission, respiration, cardiac and gastrointestinal functions, and immune response (Zollner and Stein 2007). MOPr is expressed mainly in the central nervous system where it regulates morphine-induced analgesia, tolerance and dependence (Mayer and Hollt 2006). Recently, induction of MOPr expression in different immune cells induced by cytokines has been reported (Kraus et al., 2001; Kraus et al., 2003). The human mu-opioid receptor gene (OPRM1) promoter is of the TATA-less type and has clusters of potential binding sites for different transcription factors (Law et al. 2004). Several studies, primarily focused on the upstream region of the OPRM1 promoter, have investigated transcriptional regulation of MOPr expression. Presently, however, it is still not completely clear how positive and negative transcription regulators cooperatively coordinate cellor tissue-specific transcription of the OPRM1 gene, and how specific growth factors influence its expression. IGF-I and its receptors are widely distributed throughout the nervous system during development, and their involvement in neurogenesis has been extensively investigated (Arsenijevic et al. 1998; van Golen and Feldman 2000). As previously mentioned, such neurotrophic factors can be also produced and/or act on immune cells (Kerschenseteiner et al., 2003). Most of the physiologic effects of IGF-I are mediated by the type I IGF surface receptor which, after ligand binding-induced autophosphorylation, associates with specific adaptor proteins and activates different second messengers (Bondy and Cheng 2004). These include: phosphatidylinositol 3-kinase, mitogen-activated protein kinase (Vincent and Feldman 2002; Di Toro et al. 2005) and members of the Janus kinase (JAK)/STAT3 signalling pathway (Zong et al. 2000; Yadav et al. 2005). REST plays a complex role in neuronal cells by differentially repressing target gene expression (Lunyak et al. 2004; Coulson 2005; Ballas and Mandel 2005). REST expression decreases during neurogenesis, but has been detected in the adult rat brain (Palm et al. 1998) and is up-regulated in response to global ischemia (Calderone et al. 2003) and induction of epilepsy (Spencer et al. 2006). Thus, the REST concentration seems to influence its function and the expression of neuronal genes, and may have different effects in embryonic and differentiated neurons (Su et al. 2004; Sun et al. 2005). In a previous study, REST was elevated during the early stages of neural induction by IGF-I in neuroblastoma cells. REST may contribute to the down-regulation of genes not yet required by the differentiation program, but its expression decreases after five days of treatment to allow for the acquisition of neural phenotypes. Di Toro et al. proposed a model in which the extent of neurite outgrowth in differentiating neuroblastoma cells was affected by the disappearance of REST (Di Toro et al. 2005). The human mu-opioid receptor gene (OPRM1) promoter contains a DNA sequence binding the repressor element 1 silencing transcription factor (REST) that is implicated in transcriptional repression. Therefore, in the fist part of this thesis, I investigated whether insulin-like growth factor I (IGF-I), which affects various aspects of neuronal induction and maturation, regulates OPRM1 transcription in neuronal cells in the context of the potential influence of REST. A series of OPRM1-luciferase promoter/reporter constructs were transfected into two neuronal cell models, neuroblastoma-derived SH-SY5Y cells and PC12 cells. In the former, endogenous levels of human mu-opioid receptor (hMOPr) mRNA were evaluated by real-time PCR. IGF-I upregulated OPRM1 transcription in: PC12 cells lacking REST, in SH-SY5Y cells transfected with constructs deficient in the REST DNA binding element, or when REST was down-regulated in retinoic acid-differentiated cells. IGF-I activates the signal transducer and activator of transcription-3 (STAT3) signaling pathway and this transcription factor, binding to the STAT1/3 DNA element located in the promoter, increases OPRM1 transcription. T-cell receptor (TCR) recognizes peptide antigens displayed in the context of the major histocompatibility complex (MHC) and gives rise to a potent as well as branched intracellular signalling that convert naïve T-cells in mature effectors, thus significantly contributing to the genesis of a specific immune response. In the second part of my work I exposed wild type Jurkat CD4+ T-cells to a mixture of CD3 and CD28 antigens in order to fully activate TCR and study whether its signalling influence OPRM1 expression. Results were that TCR engagement determined a significant induction of OPRM1 expression through the activation of transcription factors AP-1, NF-kB and NFAT. Eventually, I investigated MOPr turnover once it has been expressed on T-cells outer membrane. It turned out that DAMGO induced MOPr internalisation and recycling, whereas morphine did not. Overall, from the data collected in this thesis we can conclude that that a reduction in REST is a critical switch enabling IGF-I to up-regulate human MOPr, helping these findings clarify how human MOPr expression is regulated in neuronal cells, and that TCR engagement up-regulates OPRM1 transcription in T-cells. My results that neurotrophic factors a and TCR engagement, as well as it is reported for cytokines, seem to up-regulate OPRM1 in both neurons and immune cells suggest an important role for MOPr as a molecular bridge between neurons and immune cells; therefore, MOPr could play a key role in the cross-talk between immune system and nervous system and in particular in the balance between pro-inflammatory and pro-nociceptive stimuli and analgesic and neuroprotective effects.

The Libor Market Model: from theory to calibration

This thesis is focused on the financial model for interest rates called the LIBOR Market Model. In the appendixes, we provide the necessary mathematical theory. In the inner chapters, firstly, we define the main interest rates and financial instruments concerning with the interest rate models, then, we set the LIBOR market model, demonstrate its existence, derive the dynamics of forward LIBOR rates and justify the pricing of caps according to the Black’s formula. Then, we also present the Swap Market Model, which models the forward swap rates instead of the LIBOR ones. Even this model is justified by a theoretical demonstration and the resulting formula to price the swaptions coincides with the Black’s one. However, the two models are not compatible from a theoretical point. Therefore, we derive various analytical approximating formulae to price the swaptions in the LIBOR market model and we explain how to perform a Monte Carlo simulation. Finally, we present the calibration of the LIBOR market model to the markets of both caps and swaptions, together with various examples of application to the historical correlation matrix and the cascade calibration of the forward volatilities to the matrix of implied swaption volatilities provided by the market.

Jarrow-Yildirim model for inflation: theory and applications

This thesis deals with inflation theory, focussing on the model of Jarrow & Yildirim, which is nowadays used when pricing inflation derivatives. After recalling main results about short and forward interest rate models, the dynamics of the main components of the market are derived. Then the most important inflation-indexed derivatives are explained (zero coupon swap, year-on-year, cap and floor), and their pricing proceeding is shown step by step. Calibration is explained and performed with a common method and an heuristic and non standard one. The model is enriched with credit risk, too, which allows to take into account the possibility of bankrupt of the counterparty of a contract. In this context, the general method of pricing is derived, with the introduction of defaultable zero-coupon bonds, and the Monte Carlo method is treated in detailed and used to price a concrete example of contract. Appendixes: A: martingale measures, Girsanov's theorem and the change of numeraire. B: some aspects of the theory of Stochastic Differential Equations; in particular, the solution for linear EDSs, and the Feynman-Kac Theorem, which shows the connection between EDSs and Partial Differential Equations. C: some useful results about normal distribution.

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins

The goal of this thesis work is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of cysteine residues in proteins, which is a sub-problem of a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction of disulfide bonding states of cysteine residues will help in putting a constraint in the three dimensional (3D) space of the respective protein structure, and thus will eventually help in the prediction of 3D structure of proteins. Results of this work will have direct implications in site-directed mutational studies of proteins, proteins engineering and the problem of protein folding. We have used a combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM), the so-called Hidden Neural Network (HNN) as a machine learning technique to develop our prediction method. By using different global and local features of proteins (specifically profiles, parity of cysteine residues, average cysteine conservation, correlated mutation, sub-cellular localization, and signal peptide) as inputs and considering Eukaryotes and Prokaryotes separately we have reached to a remarkable accuracy of 94% on cysteine basis for both Eukaryotic and Prokaryotic datasets, and an accuracy of 90% and 93% on protein basis for Eukaryotic dataset and Prokaryotic dataset respectively. These accuracies are best so far ever reached by any existing prediction methods, and thus our prediction method has outperformed all the previously developed approaches and therefore is more reliable. Most interesting part of this thesis work is the differences in the prediction performances of Eukaryotes and Prokaryotes at the basic level of input coding when ‘profile’ information was given as input to our prediction method. And one of the reasons for this we discover is the difference in the amino acid composition of the local environment of bonded and free cysteine residues in Eukaryotes and Prokaryotes. Eukaryotic bonded cysteine examples have a ‘symmetric-cysteine-rich’ environment, where as Prokaryotic bonded examples lack it.

Structural and elastic properties of DNA and chromatin

We investigate a chain consisting of two coupled worm-like chains withconstant distance between the strands. The effects due todouble-strandedness of the chain are studied. In a previous analyticalstudy of this system an intrinsic twist-stretch coupling and atendency of kinking is predicted. Even though a local twist structureis observed the predicted features are not recovered. A new model for DNA at the base-pair level is presented. Thebase-pairs are treated as flat rigid ellipsoids and thesugar-phosphate backbones are represented as stiff harmonic springs.The base-pair stacking interaction is modeled by a variant of theGay-Berne potential. It is shown by systematic coarse-graininghow the elastic constants of a worm-like chain are related to thelocal fluctuations of the base-pair step parameters. Even though a lotof microscopic details of the base-pair geometry is neglected themodel can be optimized to obtain a B-DNA conformation as ground stateand reasonable elastic properties. Moreover the model allows tosimulate much larger length scales than it is possible with atomisticsimulations due to the simplification of the force-field and inparticular due to the possibility of non-local Monte-Carlo moves. Asa first application the behavior under stretching is investigated. Inagreement with micromanipulation experiments on single DNA moleculesone observes a force-plateau in the force-extension curvescorresponding to an overstretching transition from B-DNA to aso-called S-DNA state. The model suggests a structure for S-DNA withhighly inclined base-pairs in order to enable at least partialbase-pair stacking. Finally a simple model for chromatin is introduced to study itsstructural and elastic properties. The underlying geometry of themodeled fiber is based on a crossed-linker model. The chromatosomesare treated as disk-like objects. Excluded volume and short rangenucleosomal interaction are taken into account by a variant of theGay-Berne potential. It is found that the bending rigidity and thestretching modulus of the fiber increase with more compact fibers. Fora reasonable parameterization of the fiber for physiologicalconditions and sufficiently high attraction between the nucleosomes aforce-extension curve is found similar to stretching experiments onsingle chromatin fibers. For very small stretching forces a kinkedfiber forming a loop is observed. If larger forces are applied theloop formation is stretched out and a decondensation of the fibertakes place.

Strukturbildung durch Selbstorganisation von Oligonukleotiden

Die DNA-Doppelhelix ist eine relativ dicke (Ø ≈ 2 nm), kompakte und dadurch auf kurzen Längenskalen relativ steife Verbindung (lp[dsDNA] ≈ 50-60 nm), mit einer klar definierten Struktur, die durch biologische Methoden sehr präzise manipuliert werden kann. Die Auswirkungen der primären Sequenz auf die dreidimensionale Strukturbildung ist gut verstanden und exakt vorhersagbar. Des Weiteren kann DNA an verschiedenen Stellen mit anderen Molekülen verknüpft werden, ohne dass ihre Selbsterkennung gestört wird. Durch die helikale Struktur besteht außerdem ein Zusammenhang zwischen der Lage und der räumlichen Orientierung von eingeführten Modifikationen. Durch moderne Syntheseverfahren lassen sich beliebige Oligonukleotidsequenzen im Bereich bis etwa 150-200 Basen relativ preiswert im Milligrammmaßstab herstellen. Diese Eigenschaften machen die DNA zu einem idealen Kandidaten zur Erzeugung komplexer Strukturen, die durch Selbsterkennung der entsprechenden Sequenzen gebildet werden. In der hier vorgelegten Arbeit wurden einzelsträngige DNA-Abschnitte (ssDNA) als adressierbare Verknüpfungsstellen eingesetzt, um verschiedene molekulare Bausteine zu diskreten nicht periodischen Strukturen zu verbinden. Als Bausteine dienten flexible synthetische Polymerblöcke und semiflexible Doppelstrang-DNA-Abschnitte (dsDNA), die an beiden Enden mit unterschiedlichen Oligonukleotidsequenzen „funktionalisiert“ sind. Die zur Verknüpfung genutzten Oligonukleotidabschnitte wurden so gewählt (n > 20 Basen), dass ihre Hybridisierung zu einer bei Raumtemperatur stabilen Doppelstrangbildung führt. Durch Kombination der Phosphoramiditsynthese von DNA mit einer festkörpergestützten Blockkopplungsreaktion konnte am Beispiel von Polyethylenoxiden ein sehr effektiver Syntheseweg zur Herstellung von ssDNA1-PEO-ssDNA2-Triblockcopolymeren entwickelt werden, der sich problemlos auf andere Polymere übertragen lassen sollte. Die Längen und Basenabfolgen der beiden Oligonukleotidsequenzen können dabei unabhängig voneinander frei gewählt werden. Somit wurden die Voraussetzungen geschaffen, um die Selbsterkennung von Oligonukleotiden durch Kombination verschiedener Triblockcopolymere zur Erzeugung von Multiblockcopolymeren zu nutzen, die mit klassischen Synthesetechniken nicht zugänglich sind. Semiflexible Strukturelemente lassen sich durch die Synthese von Doppelstrangfragmenten mit langen überstehenden Enden (sticky-ends) realisieren. Die klassischen Ansätze der molekularen Genetik zur Erzeugung von sticky-ends sind in diesem Fall nicht praktikabel, da sie zu Einschränkungen im Bezug auf Länge und Sequenz der überhängenden Enden führen. Als Methode der Wahl haben sich zwei verschiedene Varianten der Polymerase Kettenreaktion (PCR) erwiesen, die auf der Verwendung von teilkomplementären Primern beruhen. Die eigentlichen Primersequenzen wurden am 5´-Ende entweder über ein 2´-Desoxyuridin oder über einen kurzen Polyethylenoxid-Spacer (n = 6) mit einer frei wählbaren „sticky-end-Sequenz“ verknüpft. Mit diesen Methoden sind sowohl 3´- als auch 5´-Überhänge zugänglich und die Länge der Doppelstrangabschnitte kann über einen breiten Molmassenbereich sehr exakt eingestellt werden. Durch Kombination derartiger Doppelstrangfragmente mit den biosynthetischen Triblockcopolymeren lassen sich Strukturen erzeugen, die als Modellsysteme zur Untersuchung verschiedener Biomoleküle genutzt werden können, die in Form eines mehrfach gebrochenen Stäbchens vorliegen. Im letzten Abschnitt wurde gezeigt, dass durch geeignete Wahl der überstehenden Enden bzw. durch Hybridisierung der Doppelstrangfragmente mit passenden Oligonukleotiden verzweigte DNA-Strukturen mit Armlängen von einigen hundert Nanometern zugänglich sind. Im Vergleich zu den bisher veröffentlichten Methoden bietet diese Herangehensweise zwei entscheidende Vorteile: Zum einen konnte der Syntheseaufwand auf ein Minimum reduziert werden, zum anderen ist es auf diesem Weg möglich die Längen der einzelnen Arme, unabhängig voneinander, über einen breiten Molmassenbereich zu variieren.

A soft-tetramer model for diblock copolymer melts: structure formation and geometric characterization

The ability of block copolymers to spontaneously self-assemble into a variety of ordered nano-structures not only makes them a scientifically interesting system for the investigation of order-disorder phase transitions, but also offers a wide range of nano-technological applications. The architecture of a diblock is the most simple among the block copolymer systems, hence it is often used as a model system in both experiment and theory. We introduce a new soft-tetramer model for efficient computer simulations of diblock copolymer melts. The instantaneous non-spherical shape of polymer chains in molten state is incorporated by modeling each of the two blocks as two soft spheres. The interactions between the spheres are modeled in a way that the diblock melt tends to microphase separate with decreasing temperature. Using Monte Carlo simulations, we determine the equilibrium structures at variable values of the two relevant control parameters, the diblock composition and the incompatibility of unlike components. The simplicity of the model allows us to scan the control parameter space in a completeness that has not been reached in previous molecular simulations.The resulting phase diagram shows clear similarities with the phase diagram found in experiments. Moreover, we show that structural details of block copolymer chains can be reproduced by our simple model.We develop a novel method for the identification of the observed diblock copolymer mesophases that formalizes the usual approach of direct visual observation,using the characteristic geometry of the structures. A cluster analysis algorithm is used to determine clusters of each component of the diblock, and the number and shape of the clusters can be used to determine the mesophase.We also employ methods from integral geometry for the identification of mesophases and compare their usefulness to the cluster analysis approach.To probe the properties of our model in confinement, we perform molecular dynamics simulations of atomistic polyethylene melts confined between graphite surfaces. The results from these simulations are used as an input for an iterative coarse-graining procedure that yields a surface interaction potential for the soft-tetramer model. Using the interaction potential derived in that way, we perform an initial study on the behavior of the soft-tetramer model in confinement. Comparing with experimental studies, we find that our model can reflect basic features of confined diblock copolymer melts.

Structure formation of amphiphilic molecules at the air,water interface and after film transfer

One of the basic concepts of molecular self-assembly is that the morphology of the aggregate is directly related to the structure and interaction of the aggregating molecules. This is not only true for the aggregation in bulk solution, but also for the formation of Langmuir films at the air/water interface. Thus, molecules at the interface do not necessarily form flat monomolecular films but can also aggregate into multilayers or surface micelles. In this context, various novel synthetic molecules were investigated in terms of their morphology at the air/water interface and in transferred films. rnFirst, the self-assembly of semifluorinated alkanes and their molecular orientation at the air/water interface and in transferred films was studied employing scanning force microscopy (SFM) and Kelvin potential force microscopy. Here it was found, that the investigated semifluorinated alkanes aggregate to form circular surface micelles with a diameter of 30 nm, which are constituted of smaller muffin-shaped subunits with a diameter of 10 nm. A further result is that the introduction of an aromatic core into the molecular structure leads to the formation of elongated surface micelles and thus implements a directionality to the self-assembly. rnSecond, the self-assembly of two different amphiphilic hybrid materials containing a short single stranded desoxyribonucleic acid (DNA) sequence was investigated at the air/water interface. The first molecule was a single stranded DNA (11mer) molecule with two hydrophobically modified 5-(dodec-1-ynyl)uracil nucleobases at the terminal 5'-end of the oligonucleotide sequence. Isotherm measurements revealed the formation of semi-stable films at the air/water interface. SFM imaging of films transferred via Langmuir-Blodgett technique supported this finding and indicated mono-, bi- and multilayer formation, according to the surface pressure applied upon transfer. Within these films, the hydrophilic DNA sequence was oriented towards air covering 95% of the substrate.rnSimilar results were obtained with a second type of amphiphile, a DNA block copolymer. Furthermore, the potential to perform molecular recognition experiments at the air/water interface with these DNA hybrid materials was evaluated.rnThird, polyglycerol ester molecules (PGE), which are known to form very stable foams, were studies. Aim was to elucidate the molecular structure of PGE molecules at the air/water interface in order to comprehend the foam stabilization mechanism. Several model systems mimicking the air/water interface of a PGE foam and methods for a noninvasive transfer were tested and characterized by SFM. It could be shown, that PGE stabilizes the air/water interface of a foam bubble by formation of multiple surfactant layers. Additionally, a new transfer technique, the bubble film transfer was established and characterized by high speed camera imaging.The results demonstrate the diversity of structures, which can be formed by amphiphilic molecules at the air/water interface and after film transfer, as well as the impact of the chemical structure on the aggregate morphology.

Improvement of photon transport model by including coupled photon-electron transport and kernel refinement

The first part of this work deals with the inverse problem solution in the X-ray spectroscopy field. An original strategy to solve the inverse problem by using the maximum entropy principle is illustrated. It is built the code UMESTRAT, to apply the described strategy in a semiautomatic way. The application of UMESTRAT is shown with a computational example. The second part of this work deals with the improvement of the X-ray Boltzmann model, by studying two radiative interactions neglected in the current photon models. Firstly it is studied the characteristic line emission due to Compton ionization. It is developed a strategy that allows the evaluation of this contribution for the shells K, L and M of all elements with Z from 11 to 92. It is evaluated the single shell Compton/photoelectric ratio as a function of the primary photon energy. It is derived the energy values at which the Compton interaction becomes the prevailing process to produce ionization for the considered shells. Finally it is introduced a new kernel for the XRF from Compton ionization. In a second place it is characterized the bremsstrahlung radiative contribution due the secondary electrons. The bremsstrahlung radiation is characterized in terms of space, angle and energy, for all elements whit Z=1-92 in the energy range 1–150 keV by using the Monte Carlo code PENELOPE. It is demonstrated that bremsstrahlung radiative contribution can be well approximated with an isotropic point photon source. It is created a data library comprising the energetic distributions of bremsstrahlung. It is developed a new bremsstrahlung kernel which allows the introduction of this contribution in the modified Boltzmann equation. An example of application to the simulation of a synchrotron experiment is shown.

Theoretical analysis of hidden photon searches in high-precision experiments

Although the Standard Model of particle physics (SM) provides an extremely successful description of the ordinary matter, one knows from astronomical observations that it accounts only for around 5% of the total energy density of the Universe, whereas around 30% are contributed by the dark matter. Motivated by anomalies in cosmic ray observations and by attempts to solve questions of the SM like the (g-2)_mu discrepancy, proposed U(1) extensions of the SM gauge group have raised attention in recent years. In the considered U(1) extensions a new, light messenger particle, the hidden photon, couples to the hidden sector as well as to the electromagnetic current of the SM by kinetic mixing. This allows for a search for this particle in laboratory experiments exploring the electromagnetic interaction. Various experimental programs have been started to search for hidden photons, such as in electron-scattering experiments, which are a versatile tool to explore various physics phenomena. One approach is the dedicated search in fixed-target experiments at modest energies as performed at MAMI or at JLAB. In these experiments the scattering of an electron beam off a hadronic target e+(A,Z)->e+(A,Z)+l^+l^- is investigated and a search for a very narrow resonance in the invariant mass distribution of the lepton pair is performed. This requires an accurate understanding of the theoretical basis of the underlying processes. For this purpose it is demonstrated in the first part of this work, in which way the hidden photon can be motivated from existing puzzles encountered at the precision frontier of the SM. The main part of this thesis deals with the analysis of the theoretical framework for electron scattering fixed-target experiments searching for hidden photons. As a first step, the cross section for the bremsstrahlung emission of hidden photons in such experiments is studied. Based on these results, the applicability of the Weizsäcker-Williams approximation to calculate the signal cross section of the process, which is widely used to design such experimental setups, is investigated. In a next step, the reaction e+(A,Z)->e+(A,Z)+l^+l^- is analyzed as signal and background process in order to describe existing data obtained by the A1 experiment at MAMI with the aim to give accurate predictions of exclusion limits for the hidden photon parameter space. Finally, the derived methods are used to find predictions for future experiments, e.g., at MESA or at JLAB, allowing for a comprehensive study of the discovery potential of the complementary experiments. In the last part, a feasibility study for probing the hidden photon model by rare kaon decays is performed. For this purpose, invisible as well as visible decays of the hidden photon are considered within different classes of models. This allows one to find bounds for the parameter space from existing data and to estimate the reach of future experiments.

Synthese und Charakterisierung biologischer Hybridpolymere zur gentechnologischen Anwendung

KurzfassungrnrnZiel der vorliegenden Arbeit war es eine gezielte, hochspezifische Inhibierung der Proteinbiosynthese zu erreichen. Dies kann durch eine Blockierung des mRNA-Strangs durch komplementäre DNA/RNA-Stränge (ähnlich zur Antisense-Methode) oder durch die Hydrolyse des mRNA-Strangs mit Hilfe spezieller Enzyme (RNasen) realisiert werden. Da jedoch beide Methoden nicht zu zufriedenstellenden Ergebnissen führen, wäre deshalb eine Kombination aus beiden Methoden ideal, welche in einer spezifischen, gezielten und permanenten Ausschaltung der Proteinbiosynthese resultieren würde. Um dieses Ziel zu verwirklichen, ist es nötig, ein Molekül zu synthetisieren, welches in der Lage ist selektiv an einer spezifischen Position an den RNA-Strang zu hybridisieren und anschließend den RNA-Strang an dieser zu hydrolysieren. Der große Vorteil dieses Konzepts liegt darin, dass die DNA-Sequenz für die Hybridisierung an die entsprechende RNA maßgeschneidert hergestellt werden kann und somit jede RNA gezielt angesteuert werden kann, was letztendlich zu einer spezifischen Inhibierung der korrespondierenden Proteinbiosynthese führen soll.rnDurch die Verwendung und Optimierung der Nativen Chemischen Ligation (NCL) als Konjugationsmethode konnten zwei Biomakromoleküle in Form einer 46-basenlangen DNA (komplementär zum RNA-Strang) und einer 31-aminosäurelangen RNase kovalent verknüpft werden. Durch unterschiedliche chemische und molekularbiologische Analysemethoden, wie PAGE, GPC, CE, MALDI-ToF-MS etc., war es zudem möglich, die erfolgreiche Synthese dieses biologischen Hybridpolymers als monodisperses, reines Produkt zu bestätigen. rnDie Synthese des ca. 800-basenlangen RNA-Strangs, der als Modell-Matrize für die selektive und spezifische Degradierung durch das DNA-RNase-Konjugat dienen sollte, konnte unter Zuhilfenahme gentechnologischer Standard-Methoden erfolgreich bewerkstelligt werden. Weiterhin konnte durch die Verwendung der radioaktiven cDNA-Synthese gezeigt werden, dass das DNA-RNase-Konjugat an die gewünschte Stelle des RNA-Strangs hybridisiert. Die Identifizierung einer anschließenden spezifischen Hydrolyse des RNA-Strangs durch die an den DNA-Strang angeknüpfte RNase war aufgrund der geringen katalytischen Aktivität des Enzyms bisher allerdings nicht möglich.rn

Computer simulation methods to study interfacial tensions : from the Ising model to colloidal crystals

In condensed matter systems, the interfacial tension plays a central role for a multitude of phenomena. It is the driving force for nucleation processes, determines the shape and structure of crystalline structures and is important for industrial applications. Despite its importance, the interfacial tension is hard to determine in experiments and also in computer simulations. While for liquid-vapor interfacial tensions there exist sophisticated simulation methods to compute the interfacial tension, current methods for solid-liquid interfaces produce unsatisfactory results.rnrnAs a first approach to this topic, the influence of the interfacial tension on nuclei is studied within the three-dimensional Ising model. This model is well suited because despite its simplicity, one can learn much about nucleation of crystalline nuclei. Below the so-called roughening temperature, nuclei in the Ising model are not spherical anymore but become cubic because of the anisotropy of the interfacial tension. This is similar to crystalline nuclei, which are in general not spherical but more like a convex polyhedron with flat facets on the surface. In this context, the problem of distinguishing between the two bulk phases in the vicinity of the diffuse droplet surface is addressed. A new definition is found which correctly determines the volume of a droplet in a given configuration if compared to the volume predicted by simple macroscopic assumptions.rnrnTo compute the interfacial tension of solid-liquid interfaces, a new Monte Carlo method called ensemble switch method'' is presented which allows to compute the interfacial tension of liquid-vapor interfaces as well as solid-liquid interfaces with great accuracy. In the past, the dependence of the interfacial tension on the finite size and shape of the simulation box has often been neglected although there is a nontrivial dependence on the box dimensions. As a consequence, one needs to systematically increase the box size and extrapolate to infinite volume in order to accurately predict the interfacial tension. Therefore, a thorough finite-size scaling analysis is established in this thesis. Logarithmic corrections to the finite-size scaling are motivated and identified, which are of leading order and therefore must not be neglected. The astounding feature of these logarithmic corrections is that they do not depend at all on the model under consideration. Using the ensemble switch method, the validity of a finite-size scaling ansatz containing the aforementioned logarithmic corrections is carefully tested and confirmed. Combining the finite-size scaling theory with the ensemble switch method, the interfacial tension of several model systems, ranging from the Ising model to colloidal systems, is computed with great accuracy.

Evolutionary forces shaping genomic islands of population differentiation in humans

Background Levels of differentiation among populations depend both on demographic and selective factors: genetic drift and local adaptation increase population differentiation, which is eroded by gene flow and balancing selection. We describe here the genomic distribution and the properties of genomic regions with unusually high and low levels of population differentiation in humans to assess the influence of selective and neutral processes on human genetic structure. Methods Individual SNPs of the Human Genome Diversity Panel (HGDP) showing significantly high or low levels of population differentiation were detected under a hierarchical-island model (HIM). A Hidden Markov Model allowed us to detect genomic regions or islands of high or low population differentiation. Results Under the HIM, only 1.5% of all SNPs are significant at the 1% level, but their genomic spatial distribution is significantly non-random. We find evidence that local adaptation shaped high-differentiation islands, as they are enriched for non-synonymous SNPs and overlap with previously identified candidate regions for positive selection. Moreover there is a negative relationship between the size of islands and recombination rate, which is stronger for islands overlapping with genes. Gene ontology analysis supports the role of diet as a major selective pressure in those highly differentiated islands. Low-differentiation islands are also enriched for non-synonymous SNPs, and contain an overly high proportion of genes belonging to the 'Oncogenesis' biological process. Conclusions Even though selection seems to be acting in shaping islands of high population differentiation, neutral demographic processes might have promoted the appearance of some genomic islands since i) as much as 20% of islands are in non-genic regions ii) these non-genic islands are on average two times shorter than genic islands, suggesting a more rapid erosion by recombination, and iii) most loci are strongly differentiated between Africans and non-Africans, a result consistent with known human demographic history.