Warped extra dimensions: flavor, precision tests and Higgs physics

In this thesis, the phenomenology of the Randall-Sundrum setup is investigated. In this context models with and without an enlarged SU(2)_L x SU(2)_R x U(1)_X x P_{LR} gauge symmetry, which removes corrections to the T parameter and to the Z b_L \bar b_L coupling, are compared with each other. The Kaluza-Klein decomposition is formulated within the mass basis, which allows for a clear understanding of various model-specific features. A complete discussion of tree-level flavor-changing effects is presented. Exact expressions for five dimensional propagators are derived, including Yukawa interactions that mediate flavor-off-diagonal transitions. The symmetry that reduces the corrections to the left-handed Z b \bar b coupling is analyzed in detail. In the literature, Randall-Sundrum models have been used to address the measured anomaly in the t \bar t forward-backward asymmetry. However, it will be shown that this is not possible within a natural approach to flavor. The rare decays t \to cZ and t \to ch are investigated, where in particular the latter could be observed at the LHC. A calculation of \Gamma_{12}^{B_s} in the presence of new physics is presented. It is shown that the Randall-Sundrum setup allows for an improved agreement with measurements of A_{SL}^s, S_{\psi\phi}, and \Delta\Gamma_s. For the first time, a complete one-loop calculation of all relevant Higgs-boson production and decay channels in the custodial Randall-Sundrum setup is performed, revealing a sensitivity to large new-physics scales at the LHC.

Zoomed simulations of Halo segregation in cosmological models with two species of coupled dark matter

La materia ordinaria copre soli pochi punti percentuali della massa-energia totale dell'Universo, che è invece largamente dominata da componenti “oscure”. Il modello standard usato per descriverle è il modello LambdaCDM. Nonostante esso sembri consistente con la maggior parte dei dati attualmente disponibili, presenta alcuni problemi fondamentali che ad oggi restano irrisolti, lasciando spazio per lo studio di modelli cosmologici alternativi. Questa Tesi mira a studiare un modello proposto recentemente, chiamato “Multi-coupled Dark Energy” (McDE), che presenta interazioni modificate rispetto al modello LambdaCDM. In particolare, la Materia Oscura è composta da due diversi tipi di particelle con accoppiamento opposto rispetto ad un campo scalare responsabile dell'Energia Oscura. L'evoluzione del background e delle perturbazioni lineari risultano essere indistinguibili da quelle del modello LambdaCDM. In questa Tesi viene presentata per la prima volta una serie di simulazioni numeriche “zoomed”. Esse presentano diverse regioni con risoluzione differente, centrate su un singolo ammasso di interesse, che permettono di studiare in dettaglio una singola struttura senza aumentare eccessivamente il tempo di calcolo necessario. Un codice chiamato ZInCo, da me appositamente sviluppato per questa Tesi, viene anch'esso presentato per la prima volta. Il codice produce condizioni iniziali adatte a simulazioni cosmologiche, con differenti regioni di risoluzione, indipendenti dal modello cosmologico scelto e che preservano tutte le caratteristiche dello spettro di potenza imposto su di esse. Il codice ZInCo è stato usato per produrre condizioni iniziali per una serie di simulazioni numeriche del modello McDE, le quali per la prima volta mostrano, grazie all'alta risoluzione raggiunta, che l'effetto di segregazione degli ammassi avviene significativamente prima di quanto stimato in precedenza. Inoltre, i profili radiale di densità ottenuti mostrano un appiattimento centrale nelle fasi iniziali della segregazione. Quest'ultimo effetto potrebbe aiutare a risolvere il problema “cusp-core” del modello LambdaCDM e porre limiti ai valori dell'accoppiamento possibili.

Suche nach dem Higgs-Boson im Zerfallskanal H WW eny e myny my mit dem D0-Detektor

Diese Arbeit beschäftigt sich mit der Suche nach dem Higgs-Boson.rn Dazu wurden die Daten des D0-Experimentes am Fermi National rn Accelerator Laboratory analysiert. Diese stammen ausrn Proton-Antiproton-Kollisionen, welche vom Tevatron-Beschleuniger beirn einer Schwerpunktsenergie von sqrt(s)=1.96 TeV erzeugtrn wurden. Der Datensatz umfasst mit einer integrierten Luminosität vonrn 9.7 fb^-1 den vollen RunII, welcher von April 2002 bisrn September 2011 aufgezeichnet wurde. Die Suche wurde für dreirn unterschiedliche Modelle durchgeführt: Das Standardmodell, einrn fermiophobes Higgs-Modell und ein Modell mit einer viertenrn Fermiongeneration. Zusätzlich wurde der Wirkungsquerschnitt derrn nicht resonanten WW-Produktion gemessen.rnrn Dazu wurden Daten mit einem Elektron, einem Myon und fehlenderrn Transversalenergie im Endzustand untersucht. Dieser Endzustand wirdrn beim Zerfall eines Higgs-Bosons in zwei W-Bosonen mit anschließendemrn Zerfall in ein Elektron, ein Myon und zwei Neutrinos erwartet undrn weist die größte Sensitivität für die Suche am Tevatron auf.rnrn Weder für das Standardmodell noch für die erweiterten Modelle konntern ein Hinweis auf ein Higgs-Signal gefunden werden. Deshalb wurdenrn obere Grenzen auf den Produktionswirkungsquerschnitt für diern einzelnen Modelle bestimmt. Die oberen Grenzen für Higgs-Bosonen imrn Rahmen des Standardmodells reichen von 28*sigma_SM für einrn Higgs-Boson mit einer Masse von 100 GeV bis zu einemrn Ausschluss des Standardmodell-Higgs-Bosons im Bereich zwischen 160rn und 167 GeV mit 95% Vertrauensniveau. Damit ist der inrn dieser Arbeit beschriebene Kanal der einzige Kanal amrn D0-Experiment, welcher eine ausreichend hohe Sensitivität erreicht,rn um allein ein Higgs-Boson im hohen Massenbereich auszuschließen. Fürrn ein Higgs-Boson mit 125 GeV Masse sind die Ergebnisse sowohlrn mit der Signal+Untergrund- als auch mit der Untergrund-Hypothesern kompatibel. rn Im Rahmen des fermiophoben Higgs-Modells wurden oberen Grenzenrn zwischen 2*sigma_FHM und 4*sigma_FHM imrn Massenbereich zwischen 100 und 170 GeV bestimmt. Für diern betrachteten Modelle mit einer vierten Fermiongeneration konnte einrn Higgs-Boson in einem weiten Massenbereich zwischen 135 undrn 220 GeV mit 95% Vertrauensniveau ausgeschlossen werden.rnrn Die Messung des Wirkungsquerschnitts der nicht-resonantenrn WW-Produktion ist die genaueste Messung fürrn sqrt(s)=1.96 TeV. Der gemessene Wirkungsquerschnitt beträgtrn sigma_ppbar->WW^em=11.1 +- 0.6 (stat.) +- 0.6 (syst.) pbrn und bestätigt damit die theoretische NLO-Vorhersage im Rahmen ihrerrn Unsicherheiten.rn

Hunting for warped extra dimensions via loop-induced processes

This thesis is on loop-induced processes in theories with warped extra dimensions where the fermions and gauge bosons are allowed to propagate in the bulk, while the Higgs sector is localized on or near the infra-red brane. These so-called Randall-Sundrum (RS) models have the potential to simultaneously explain the hierarchy problem and address the question of what causes the large hierarchies in the fermion sector of the Standard Model (SM). The Kaluza-Klein (KK) excitations of the bulk fields can significantly affect the loop-level processes considered in this thesis and, hence, could indirectly indicate the existence of warped extra dimensions. The analytical part of this thesis deals with the detailed calculation of three loop-induced processes in the RS models in question: the Higgs production process via gluon fusion, the Higgs decay into two photons, and the flavor-changing neutral current b → sγ. A comprehensive, five-dimensional (5D) analysis will show that the amplitudes of the Higgs processes can be expressed in terms of integrals over 5D propagators with the Higgs-boson profile along the extra dimension, which can be used for arbitrary models with a compact extra dimension. To this end, both the boson and fermion propagators in a warped 5D background are derived. It will be shown that the seemingly contradictory results for the gluon fusion amplitude in the literature can be traced back to two distinguishable, not smoothly-connected incarnations of the RS model. The investigation of the b → sγ transition is performed in the KK decomposed theory. It will be argued that summing up the entire KK tower leads to a finite result, which can be well approximated by a closed, analytical expression.rnIn the phenomenological part of this thesis, the analytic results of all relevant Higgs couplings in the RS models in question are compared with current and in particular future sensitivities of the Large Hadron Collider (LHC) and the planned International Linear Collider. The latest LHC Higgs data is then used to exclude significant portions of the parameter space of each RS scenario. The analysis will demonstrate that especially the loop-induced Higgs couplings are sensitive to KK particles of the custodial RS model with masses in the multi tera-electronvolt range. Finally, the effect of the RS model on three flavor observables associated with the b → sγ transition are examined. In particular, we study the branching ratio of the inclusive decay B → X_s γ

Modelling and simulating in systems biology: an approach based on multi-agent systems

Systems Biology is an innovative way of doing biology recently raised in bio-informatics contexts, characterised by the study of biological systems as complex systems with a strong focus on the system level and on the interaction dimension. In other words, the objective is to understand biological systems as a whole, putting on the foreground not only the study of the individual parts as standalone parts, but also of their interaction and of the global properties that emerge at the system level by means of the interaction among the parts. This thesis focuses on the adoption of multi-agent systems (MAS) as a suitable paradigm for Systems Biology, for developing models and simulation of complex biological systems. Multi-agent system have been recently introduced in informatics context as a suitabe paradigm for modelling and engineering complex systems. Roughly speaking, a MAS can be conceived as a set of autonomous and interacting entities, called agents, situated in some kind of nvironment, where they fruitfully interact and coordinate so as to obtain a coherent global system behaviour. The claim of this work is that the general properties of MAS make them an effective approach for modelling and building simulations of complex biological systems, following the methodological principles identified by Systems Biology. In particular, the thesis focuses on cell populations as biological systems. In order to support the claim, the thesis introduces and describes (i) a MAS-based model conceived for modelling the dynamics of systems of cells interacting inside cell environment called niches. (ii) a computational tool, developed for implementing the models and executing the simulations. The tool is meant to work as a kind of virtual laboratory, on top of which kinds of virtual experiments can be performed, characterised by the definition and execution of specific models implemented as MASs, so as to support the validation, falsification and improvement of the models through the observation and analysis of the simulations. A hematopoietic stem cell system is taken as reference case study for formulating a specific model and executing virtual experiments.

A multi-regional view on aging societies accounting for the existence of non-tradable goods

This thesis assesses the question, whether accounting for non-tradable goods sectors in a calibrated Auerbach-Kotlikoff multi-regional overlapping-generations-model significantly affects this model’s results when simulating the economic impact of demographic change. Non-tradable goods constitute a major part of up to 80 percent of GDP of modern economies. At the same time, multi-regional overlapping-generations-models presented by literature on demographic change so far ignored their existence and counterfactually assumed perfect tradability between model regions. Moreover, this thesis introduces the assumption of an increasing preference share for non-tradable goods of old generations. This fact-based as-sumption is also not part of models in relevant literature. rnThese obvious simplifications of common models vis-à-vis reality notwithstanding, this thesis concludes that differences in results between a model featuring non-tradable goods and a common model with perfect tradability are very small. In other words, the common simplifi-cation of ignoring non-tradable goods is unlikely to lead to significant distortions in model results. rnIn order to ensure that differences in results between the ‘new’ model, featuring both non-tradable and tradable goods, and the common model solely reflect deviations due to the more realistic structure of the ‘new’ model, both models are calibrated to match exactly the same benchmark data and thus do not show deviations in their respective baseline steady states.rnA variation analysis performed in this thesis suggests that differences between the common model and a model with non-tradable goods can theoretically be large, but only if the bench-mark tradable goods sector is assumed to be unrealistically small.rnFinally, this thesis analyzes potential real exchange rate effects of demographic change, which could occur due to regional price differences of non-tradable goods. However, results show that shifts in real exchange rate based on these price differences are negligible.rn

Projected 21st century decrease in marine productivity: a multi-model analysis

Changes in marine net primary productivity (PP) and export of particulate organic carbon (EP) are projected over the 21st century with four global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All four models show a decrease in global mean PP and EP between 2 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in PP and EP. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in PP and EP as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where three models project an increase in PP while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observation-based estimates compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer net primary production from satellite observations.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings.

Kinetic assessment of persistent halogenated xenobiotics in cell culture models: comparison of mono- and poly-halogenated compounds

We evaluated the suitability of single and multiple cell type cultures as model systems to characterise cellular kinetics of highly lipophilic compounds with potential ecotoxicological impact. Confluent mono-layers of human skin fibroblasts, rat astrocytoma C6 cells, non-differentiated and differentiated mouse 3T3 cells were kept in culture medium supplemented with 10% foetal calf serum. For competitive uptake experiments up to four different cell types, grown on glass sectors, were exposed for 3h to (14)C-labelled model compounds, dissolved either in organic solvents or incorporated into unilamellar lecithin liposomes. Bromo-, or chloro-benzenes, decabromodiphenylether (DBP), and dichlorodiphenyl ethylene (DDE) were tested in rather high concentration of 20 microM. Cellular toxicity was low. Compound levels were related to protein, DNA, and triglyceride contents. Cellular uptake was fast and dependent on physico-chemical properties of the compounds (lipophilicity, molecular size), formulation, and cell type. Mono-halogenated benzenes showed low and similar uptake levels (=low accumulation compounds). DBP and DDE showed much higher cellular accumulations (=high accumulation compounds) except for DBP in 3T3 cells. Uptake from liposomal formulations was mostly higher than if compounds were dissolved in organic solvents. The extent of uptake correlated with the cellular content of triglycerides, except for DBP. Uptake competition between different cell types was studied in a sectorial multi-cell culture model. For low accumulation compounds negligible differences were found among C6 cells and fibroblasts. Uptake of DDE was slightly and that of DBP highly increased in fibroblasts. Well-defined cell culture systems, especially the sectorial model, are appropriate to screen for bioaccumulation and cytotoxicity of (unknown) chemical entities in vitro.

A multi-level decomposition of variance in somatic symptom reporting in families with adolescent children

OBJECTIVES: This paper examines four different levels of possible variation in symptom reporting: occasion, day, person and family. DESIGN: In order to rule out effects of retrospection, concurrent symptom reporting was assessed prospectively using a computer-assisted self-report method. METHODS: A decomposition of variance in symptom reporting was conducted using diary data from families with adolescent children. We used palmtop computers to assess concurrent somatic complaints from parents and children six times a day for seven consecutive days. In two separate studies, 314 and 254 participants from 96 and 77 families, respectively, participated. A generalized multilevel linear models approach was used to analyze the data. Symptom reports were modelled using a logistic response function, and random effects were allowed at the family, person and day level, with extra-binomial variation allowed for on the occasion level. RESULTS: Substantial variability was observed at the person, day and occasion level but not at the family level. CONCLUSIONS: To explain symptom reporting in normally healthy individuals, situational as well as person characteristics should be taken into account. Family characteristics, however, would not help to clarify symptom reporting in all family members.

Underestimation of Standard Errors in Multi-Site Time Series Studies

Multi-site time series studies of air pollution and mortality and morbidity have figured prominently in the literature as comprehensive approaches for estimating acute effects of air pollution on health. Hierarchical models are generally used to combine site-specific information and estimate pooled air pollution effects taking into account both within-site statistical uncertainty, and across-site heterogeneity. Within a site, characteristics of time series data of air pollution and health (small pollution effects, missing data, highly correlated predictors, non linear confounding etc.) make modelling all sources of uncertainty challenging. One potential consequence is underestimation of the statistical variance of the site-specific effects to be combined. In this paper we investigate the impact of variance underestimation on the pooled relative rate estimate. We focus on two-stage normal-normal hierarchical models and on under- estimation of the statistical variance at the first stage. By mathematical considerations and simulation studies, we found that variance underestimation does not affect the pooled estimate substantially. However, some sensitivity of the pooled estimate to variance underestimation is observed when the number of sites is small and underestimation is severe. These simulation results are applicable to any two-stage normal-normal hierarchical model for combining information of site-specific results, and they can be easily extended to more general hierarchical formulations. We also examined the impact of variance underestimation on the national average relative rate estimate from the National Morbidity Mortality Air Pollution Study and we found that variance underestimation as much as 40% has little effect on the national average.

Modeling multilevel sleep transitional data via Poisson log-linear multilevel models

This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

Human experimental pain models in drug development: translational pain research

Human experimental pain models require standardized stimulation and quantitative assessment of the evoked responses. This approach can be applied to healthy volunteers and pain patients before and after pharmacological interventions. Standardized stimuli of different modalities (ie, mechanical, chemical, thermal or electrical) can be applied to the skin, muscles and viscera for a differentiated and comprehensive assessment of various pain pathways and mechanisms. Using a multi-modal, multi-tissue approach, new and existing analgesic drugs can be profiled by their modulation of specific biomarkers. It has been shown that biomarkers, for example, those related to the central integration of repetitive nociceptive stimuli, can predict efficacy of a given drug in neuropathic pain conditions. Human experimental pain models can bridge animal and clinical pain research, and act as translational research providing new possibilities for designing successful clinical trials. Proof-of-concept studies provide cheap, fast and reliable information on dose-efficacy relationships and how pain sensed in the skin, muscles and viscera are inhibited.