Numerical investigations on atmosphere-biosphere interactions

Der Austausch von Spurengasen und Aerosolpartikeln zwischenAtmosphäre und Biosphäre spielt eine wichtige Rolle in derAtmosphärenphysik und -chemie. Wälder repräsentieren sowohleine signifikante Senke als auch Quelle für Spurengase undPartikel und tragen somit maßgeblich zu derenatmosphärischem Budget bei. Strahlungsnebel beeinflußt durchAufnahme, Entfernen und Prozessieren von Aerosolpartikelnund löslichen Spurengasen deren Konzentrationen in derGasphase. In dieser Arbeit wird erstmalig ein Modell präsentiert,welches die Simulation des Austausches zwischen Atmosphäreund Biosphäre unter Berücksichtigung der dynamischenWechselwirkung zwischen Strahlungsnebel, Blattflächenwasserund Mehrphasenchemie ermöglicht. Numerische Fallstudien mitfolgenden Schwerpunkten werden präsentiert: - Einfluß von Vegetation und Blattflächenwasser auf diezeitlichen und räumlichen Schwankungen derGrößenabhängigkeit der Flüssigphasenkonzentrationen inNebeltropfen, - Einfluß von Blattflächenwasser auf dieTrockendepositionsflüsse von Ammoniak im Wald - Simulationenwurden mit einem neuen dynamischen Depositionsmodelldurchgeführt und mit dem Widerstandsansatz verglichen -, - Einfluß von physikalischen und chemischen Prozessen aufdie Reduktion von NO- und Isoprenemissionen aus demWaldbestand verglichen mit den primären Emissionen.

The role of Interleukin-12 in liver inflammation

Chronic liver inflammation during viral hepatitis is a major health problem worldwide. The role of proinflammatory cytokines, like IL-12, in breaking hepatic immune tolerance, and inducing acute liver inflammation and virus clearance is not clear. Nor is clear its role in uncontrolled severe inflammatory response, leading to fulminant hepatitis and hepatic failure. This work, focused in the study of the role of endogenous produced IL-12 in inducing hepatic inflammatory responses, demonstrates: In vitro, using adenovirus coding for IL-12, that hepatocytes stimulate CD4+ T cells in a tolerogenic manner, and that endogenous IL-12 is able to switch the immune response into Th1; and in vivo, that endogenous IL-12 induces hepatocyte damage and virus elimination in mice infected with adenovirus. In addition, and in order to study in vivo the relevance of IL-12 in acute inflammation, conditional IL-12 transgenic mice expressing IL-12 in the liver after cre-recombinase mediated induction were generated. For this purpose, an IL-12 fusion protein was created, which demonstrated high levels of bioactivity. Induction of IL-12 expression during embryonic development was achieved by crossbreeding with Act-Cre transgenic mice; induction of IL-12 expression in adult mice was achieved by a plasmid coding for the cre-recombinase. This study demonstrates that after induction, IL-12 is expressed in the liver of the transgenic mice. It also demonstrates that hepatic expression of IL-12 induces splenomegaly and liver inflammation, characterized by large infiltrations in portal tracts and veins, associated with hepatic damage, necrosis areas and lethality. Furthermore, constitutive hepatic IL-12 expression does not lead to abortion, but to total lethality, short after delivery. In conclusion, in this study, a transgenic mouse model has been generated, in which the expression of active IL-12 in the liver can be induced at any time; this model will be very helpful for studying hepatic pathologies. This study has also demonstrated that hepatic produced IL-12 is able of breaking liver tolerance inducing inflammation, virus elimination, severe hepatocyte damage, and lethality. These findings suggest IL-12 as a key cytokine in acute liver inflammation and fulminant hepatic failure. 5.1 Future studies Once the importance of IL-12 in inducing hepatic inflammation and virus elimination was demonstrated in this study, understanding the mechanisms of the IL-12 induced liver damage, and more important, how to avoid it will be the main focus in the future. It is very important to achieve hepatic inflammation for a more effective and faster viral elimination, but avoiding the toxicity of IL-12, which leads to massive liver injury and lethality is obviously necessary to allow IL-12 as therapy. For that purpose, future studies will be mainly base on three different points: 1. The determination of different cell populations present in the hepatic infiltration, which of them are responsible for liver injury, and as well their state of activation. 2. The measure of other pro- and anti-inflammatory cytokines and chemokines, which can play a role in IL-12-induced liver inflammation and hepatocyte damage. For these purposes, specific blocking antibodies (anti TNF-alpha, anti IL-12, anti IFN-g) will be used. The study with different transgenic mice: TNF-alpha Receptor knockout, TGF-b, will also help in determining the role of those cytokines during IL-12-induced liver damage and lethality. 3. The establishing of liver pathology models (viral infection, tumours, auto-antigens) in mice. Induction of IL-12 at any time of the pathology development will help in clarifying the role of IL-12 in those models. Finally, the transgenic mice expressing IL-23 in the liver will be generated.

Untersuchung zur Bestimmung quantitativer Parameter der Lungenventilation mittels CT und MRT

Die zuverlässige Berechnung von quantitativen Parametern der Lungenventilation ist für ein Verständnis des Verhaltens der Lunge und insbesondere für die Diagnostik von Lungenerkrankungen von großer Bedeutung. Nur durch quantitative Parameter sind verlässliche und reproduzierbare diagnostische Aussagen über den Gesundheitszustand der Lunge möglich. Im Rahmen dieser Arbeit wurden neue quantitative Verfahren zur Erfassung der Lungenventilation basierend auf der dynamischen Computer- (CT) und Magnetresonanztomographie (MRT) entwickelt. Im ersten Teil dieser Arbeit wurde die Frage untersucht, ob das Aufblähen der Lunge in gesunden Schweinelungen und Lungen mit Akutem Lungenversagen (ARDS) durch einzelne, diskrete Zeitkonstanten beschrieben werden kann, oder ob kontinuierliche Verteilungen von Zeitkonstanten die Realität besser beschreiben. Hierzu wurden Serien dynamischer CT-Aufnahmen während definierter Beatmungsmanöver (Drucksprünge) aufgenommen und anschließend aus den Messdaten mittels inverser Laplace-Transformation die zugehörigen Verteilungen der Zeitkonstanten berechnet. Um die Qualität der Ergebnisse zu analysieren, wurde der Algorithmus im Rahmen von Simulationsrechnungen systematisch untersucht und anschließend in-vivo an gesunden und ARDS-Schweinelungen eingesetzt. Während in den gesunden Lungen mono- und biexponentielle Verteilungen bestimmt wurden, waren in den ARDS-Lungen Verteilungen um zwei dominante Zeitkonstanten notwendig, um die gemessenen Daten auf der Basis des verwendeten Modells verlässlich zu beschreiben. Es wurden sowohl diskrete als auch kontinuierliche Verteilungen gefunden. Die CT liefert Informationen über das solide Lungengewebe, während die MRT von hyperpolarisiertem 3He in der Lage ist, direkt das eingeatmete Gas abzubilden. Im zweiten Teil der Arbeit wurde zeitlich hochaufgelöst das Einströmen eines 3He-Bolus in die Lunge erfasst. Über eine Entfaltungsanalyse wurde anschließend das Einströmverhalten unter Idealbedingungen (unendlich kurzer 3He-Bolus), also die Gewebeantwortfunktion, berechnet und so eine Messtechnik-unabhängige Erfassung des Einströmens von 3He in die Lunge ermöglicht. Zentrale Fragestellung war hier, wie schnell das Gas in die Lunge einströmt. Im Rahmen von Simulationsrechnungen wurde das Verhalten eines Entfaltungsalgorithmus (basierend auf B-Spline Repräsentationen) systematisch analysiert. Zusätzlich wurde ein iteratives Entfaltungsverfahren eingesetzt. Aus zeitlich hochaufgelösten Messungen (7ms) an einer gesunden und einer ARDS-Schweinelunge konnte erstmals nachgewiesen werden, dass das Einströmen in-vivo in weniger als 0,1s geschieht. Die Ergebnisse zeigen Zeitkonstanten im Bereich von 4ms–50ms, wobei zwischen der gesunden Lungen und der ARDS-Lunge deutliche Unterschiede beobachtet wurden. Zusammenfassend ermöglichen daher die in dieser Arbeit vorgestellten Algorithmen eine objektivere Bestimmung quantitativer Parameter der Lungenventilation. Dies ist für die eindeutige Beschreibung ventilatorischer Vorgänge in der Lunge und somit für die Lungendiagnostik unerlässlich. Damit stehen quantitative Methoden für die Lungenfunktionsdiagnostik zur Verfügung, deren diagnostische Relevanz im Rahmen wissenschaftlicher und klinischer Studien untersucht werden kann.

Advanced CMOS Interfaces for Bio-Nanosensors

The improvement of devices provided by Nanotechnology has put forward new classes of sensors, called bio-nanosensors, which are very promising for the detection of biochemical molecules in a large variety of applications. Their use in lab-on-a-chip could gives rise to new opportunities in many fields, from health-care and bio-warfare to environmental and high-throughput screening for pharmaceutical industry. Bio-nanosensors have great advantages in terms of cost, performance, and parallelization. Indeed, they require very low quantities of reagents and improve the overall signal-to-noise-ratio due to increase of binding signal variations vs. area and reduction of stray capacitances. Additionally, they give rise to new challenges, such as the need to design high-performance low-noise integrated electronic interfaces. This thesis is related to the design of high-performance advanced CMOS interfaces for electrochemical bio-nanosensors. The main focus of the thesis is: 1) critical analysis of noise in sensing interfaces, 2) devising new techniques for noise reduction in discrete-time approaches, 3) developing new architectures for low-noise, low-power sensing interfaces. The manuscript reports a multi-project activity focusing on low-noise design and presents two developed integrated circuits (ICs) as examples of advanced CMOS interfaces for bio-nanosensors. The first project concerns low-noise current-sensing interface for DC and transient measurements of electrophysiological signals. The focus of this research activity is on the noise optimization of the electronic interface. A new noise reduction technique has been developed so as to realize an integrated CMOS interfaces with performance comparable with state-of-the-art instrumentations. The second project intends to realize a stand-alone, high-accuracy electrochemical impedance spectroscopy interface. The system is tailored for conductivity-temperature-depth sensors in environmental applications, as well as for bio-nanosensors. It is based on a band-pass delta-sigma technique and combines low-noise performance with low-power requirements.

The Dynamics of Passive Torsional Fatigue Test Rigs: Innovative Applications of Universal Joints

The dynamics of a passive back-to-back test rig have been characterised, leading to a multi-coordinate approach for the analysis of arbitrary test configurations. Universal joints have been introduced into a typical pre-loaded back-to-back system in order to produce an oscillating torsional moment in a test specimen. Two different arrangements have been investigated using a frequency-based sub-structuring approach: the receptance method. A numerical model has been developed in accordance with this theory, allowing interconnection of systems with two-coordinates and closed multi-loop schemes. The model calculates the receptance functions and modal and deflected shapes of a general system. Closed form expressions of the following individual elements have been developed: a servomotor, damped continuous shaft and a universal joint. Numerical results for specific cases have been compared with published data in literature and experimental measurements undertaken in the present work. Due to the complexity of the universal joint and its oscillating dynamic effects, a more detailed analysis of this component has been developed. Two models have been presented. The first represents the joint as two inertias connected by a massless cross-piece. The second, derived by the dynamic analysis of a spherical four-link mechanism, considers the contribution of the floating element and its gyroscopic effects. An investigation into non-linear behaviour has led to a time domain model that utilises the Runge-Kutta fourth order method for resolution of the dynamic equations. It has been demonstrated that the torsional receptances of a universal joint, derived using the simple model, result in representation of the joint as an equivalent variable inertia. In order to verify the model, a test rig has been built and experimental validation undertaken. The variable inertia of a universal joint has lead to a novel application of the component as a passive device for the balancing of inertia variations in slider-crank mechanisms.

Von der geographischen Analyse über die Bestandsaufnahme der anzutreffenden Krankheiten und der Anwendung traditioneller Medizin zu einem geomedizinischen Informationssystem am Beispiel einer Bergregion im Kabupaten Sikka (Insel Flores, Indonesien)

Im Rahmen der interdisziplinären Zusammenarbeit zur Durchsetzung des »Menschenrecht Gesundheit« wurde ein geomedizinisches Informationssystem erstellt, das auf die nordexponierten Bergdörfer zwischen 350 m ü. NN und 450 m ü. NN des Kabupaten Sikka auf der Insel Flores in Indonesien anwendbar ist. Es wurde eine Analyse der Zeit-Raum-Dimension der Gesundheitssituation in Wololuma und Napun Lawan - exemplarisch für die nordexponierten Bergdörfer - durchgeführt. Im Untersuchungsraum wurden Gesundheitsgefahren und Gesundheitsrisiken analysiert, Zonen der Gefahren herausgearbeitet und Risikoräume bewertet. Trotz eines El Niño-Jahres waren prinzipielle Bezüge der Krankheiten zum jahreszeitlichen Rhythmus der wechselfeuchten Tropen zu erkennen. Ausgehend von der Vermutung, dass Krankheiten mit spezifischen Klimaelementen korrelieren, wurden Zusammenhänge gesucht. Für jede Krankheit wurden Makro-, Meso- und Mikrorisikoräume ermittelt. Somit wurden Krankheitsherde lokalisiert. Die Generalisierung des geomedizinischen Informationssystems lässt sich auf der Makroebene auf die nordexponierten Bergdörfer zwischen 350 m ü. NN und 450 m ü. NN des Kabupaten Sikka übertragen. Aus einer Vielzahl von angetroffenen Krankheiten wurden sechs Krankheiten selektiert. Aufgrund der Häufigkeitszahlen ergibt sich für das Gesundheitsrisiko der Bevölkerung eine Prioritätenliste:rn- Dermatomykosen (ganzjährig)rn- Typhus (ganzjährig)rn- Infektionen der unteren Atemwege (Übergangszeit)rn- Infektionen der oberen Atemwege (Übergangszeit)rn- Malaria (Regenzeit)rn- Struma (ganzjährig)rnDie Hauptrisikogruppe der Makroebene ist die feminine Bevölkerung. Betroffen sind weibliche Kleinkinder von null bis sechs Jahren und Frauen ab 41 Jahren. Die erstellten Karten des zeitlichen und räumlichen Verbreitungsmusters der Krankheiten und des Zugangs zu Gesundheitsdienstleistungen dienen Entscheidungsträgern als Entscheidungshilfe für den Einsatz der Mittel zur Primärprävention. Die Geographie als Wissenschaft mit ihren Methoden und dem Zeit-Raum-Modell hat gezeigt, dass sie die Basis für die interdisziplinäre Forschung darstellt. Die interdisziplinäre Zusammenarbeit zur Gesundheitsforschung im Untersuchungszeitraum 2009 hat sich bewährt und muss weiter ausgebaut werden. Die vorgeschlagenen Lösungsmöglichkeiten dienen der Minimierung des Gesundheitsrisikos und der Gesundheitsvorsorge. Da die Systemzusammenhänge der Ätiologie der einzelnen Krankheiten sehr komplex sind, besteht noch immer sehr großer Forschungsbedarf. rnDas Ergebnis der vorliegenden Untersuchung zeigt, dass Wasser in jeder Form die primäre Ursache für das Gesundheitsrisiko der Bergdörfer im Kabupaten Sikka auf der Insel Flores in Indonesien ist.rnDer Zugang zu Wasser ist unerlässlich für die Verwirklichung des »Menschenrecht Gesundheit«. Das Recht auf Wasser besagt, dass jeder Mensch Zugang zu nicht gesundheitsgefährdendem, ausreichendem und bezahlbarem Wasser haben soll. Alle Staaten dieser Erde sollten sich dieser Forderung verpflichtet fühlen.rn

Wavelet estimation in diffusions with periodicity

Wir betrachten einen zeitlich inhomogenen Diffusionsprozess, der durch eine stochastische Differentialgleichung gegeben wird, deren Driftterm ein deterministisches T-periodisches Signal beinhaltet, dessen Periodizität bekannt ist. Dieses Signal sei in einem Besovraum enthalten. Wir schätzen es mit Hilfe eines nichtparametrischen Waveletschätzers. Unser Schätzer ist von einem Wavelet-Dichteschätzer mit Thresholding inspiriert, der 1996 in einem klassischen iid-Modell von Donoho, Johnstone, Kerkyacharian und Picard konstruiert wurde. Unter gewissen Ergodizitätsvoraussetzungen an den Prozess können wir nichtparametrische Konvergenzraten angegeben, die bis auf einen logarithmischen Term den Raten im klassischen iid-Fall entsprechen. Diese Raten werden mit Hilfe von Orakel-Ungleichungen gezeigt, die auf Ergebnissen über Markovketten in diskreter Zeit von Clémencon, 2001, beruhen. Außerdem betrachten wir einen technisch einfacheren Spezialfall und zeigen einige Computersimulationen dieses Schätzers.

Stationary states in random walks on networks

In this thesis we dealt with the problem of describing a transportation network in which the objects in movement were subject to both finite transportation capacity and finite accomodation capacity. The movements across such a system are realistically of a simultaneous nature which poses some challenges when formulating a mathematical description. We tried to derive such a general modellization from one posed on a simplified problem based on asyncronicity in particle transitions. We did so considering one-step processes based on the assumption that the system could be describable through discrete time Markov processes with finite state space. After describing the pre-established dynamics in terms of master equations we determined stationary states for the considered processes. Numerical simulations then led to the conclusion that a general system naturally evolves toward a congestion state when its particle transition simultaneously and we consider one single constraint in the form of network node capacity. Moreover the congested nodes of a system tend to be located in adjacent spots in the network, thus forming local clusters of congested nodes.

Heterogeneity in vaccination coverage explains the size and occurrence of measles epidemics in German surveillance data

The objective of this study was to characterize empirically the association between vaccination coverage and the size and occurrence of measles epidemics in Germany. In order to achieve this we analysed data routinely collected by the Robert Koch Institute, which comprise the weekly number of reported measles cases at all ages as well as estimates of vaccination coverage at the average age of entry into the school system. Coverage levels within each federal state of Germany are incorporated into a multivariate time-series model for infectious disease counts, which captures occasional outbreaks by means of an autoregressive component. The observed incidence pattern of measles for all ages is best described by using the log proportion of unvaccinated school starters in the autoregressive component of the model.

Prognostic importance of anaemia in patients with acute pulmonary embolism

Although associated with adverse outcomes in other cardiopulmonary diseases, limited evidence exists on the prognostic value of anaemia in patients with acute pulmonary embolism (PE). We sought to examine the associations between anaemia and mortality and length of hospital stay in patients with PE. We evaluated 14,276 patients with a primary diagnosis of PE from 186 hospitals in Pennsylvania, USA. We used random-intercept logistic regression to assess the association between anaemia at the time of presentation and 30-day mortality and discrete-time logistic hazard models to assess the association between anaemia and time to hospital discharge, adjusting for patient (age, gender, race, insurance type, clinical and laboratory variables) and hospital (region, size, teaching status) factors. Anaemia was present in 38.7% of patients at admission. Patients with anaemia had a higher 30-day mortality (13.7% vs. 6.3%; p <0.001) and a longer length of stay (geometric mean, 6.9 vs. 6.6 days; p <0.001) compared to patients without anaemia. In multivariable analyses, anaemia remained associated with an increased odds of death (OR 1.82, 95% CI: 1.60-2.06) and a decreased odds of discharge (OR 0.85, 95% CI: 0.82-0.89). Anaemia is very common in patients presenting with PE and is independently associated with an increased short-term mortality and length of stay.

Landfill Closure and Housing Values

The United States disposes roughly 60% of the municipal solid waste it generates each year in solid waste disposal facilities, commonly known as landfills. Hedonic pricing studies have estimated the external costs of landfills on neighboring housing markets, but the literature is silent on what happens to property values after the landfill closes. Original housing price data collected both before and after a landfill closure are used to estimate how a landfill closure affects neighboring property values. Results of both a hedonic pricing model and repeat-sales estimator are used in the analysis.

Survival Analysis with Large Dimensional Covariates: An Application in Microarray Studies

Use of microarray technology often leads to high-dimensional and low- sample size data settings. Over the past several years, a variety of novel approaches have been proposed for variable selection in this context. However, only a small number of these have been adapted for time-to-event data where censoring is present. Among standard variable selection methods shown both to have good predictive accuracy and to be computationally efficient is the elastic net penalization approach. In this paper, adaptation of the elastic net approach is presented for variable selection both under the Cox proportional hazards model and under an accelerated failure time (AFT) model. Assessment of the two methods is conducted through simulation studies and through analysis of microarray data obtained from a set of patients with diffuse large B-cell lymphoma where time to survival is of interest. The approaches are shown to match or exceed the predictive performance of a Cox-based and an AFT-based variable selection method. The methods are moreover shown to be much more computationally efficient than their respective Cox- and AFT- based counterparts.

Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

Setting Inventory Levels of CONWIP Flow Lines via Linear Programming

This paper treats the problem of setting the inventory level and optimizing the buffer allocation of closed-loop flow lines operating under the constant-work-in-process (CONWIP) protocol. We solve a very large but simple linear program that models an entire simulation run of a closed-loop flow line in discrete time to determine a production rate estimate of the system. This approach introduced in Helber, Schimmelpfeng, Stolletz, and Lagershausen (2011) for open flow lines with limited buffer capacities is extended to closed-loop CONWIP flow lines. Via this method, both the CONWIP level and the buffer allocation can be optimized simultaneously. The first part of a numerical study deals with the accuracy of the method. In the second part, we focus on the relationship between the CONWIP inventory level and the short-term profit. The accuracy of the method turns out to be best for such configurations that maximize production rate and/or short-term profit.

SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.