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A phagocyte-specific Irf8 gene enhancer establishes early conventional dendritic cell commitment
(2011)
Haematopoietic development is a complex process that is strictly hierarchically organized. Here, the phagocyte lineages are a very heterogeneous cell compartment with specialized functions in innate immunity and induction of adaptive immune responses. Their generation from a common precursor must be tightly controlled. Interference within lineage formation programs for example by mutation or change in expression levels of transcription factors (TF) is causative to leukaemia. However, the molecular mechanisms driving specification into distinct phagocytes remain poorly understood. In the present study I identify the transcription factor Interferon Regulatory Factor 8 (IRF8) as the specification factor of dendritic cell (DC) commitment in early phagocyte precursors. Employing an IRF8 reporter mouse, I showed the distinct Irf8 expression in haematopoietic lineage diversification and isolated a novel bone marrow resident progenitor which selectively differentiates into CD8α+ conventional dendritic cells (cDCs) in vivo. This progenitor strictly depends on Irf8 expression to properly establish its transcriptional DC program while suppressing a lineage-inappropriate neutrophile program. Moreover, I demonstrated that Irf8 expression during this cDC commitment-step depends on a newly discovered myeloid-specific cis-enhancer which is controlled by the haematopoietic transcription factors PU.1 and RUNX1. Interference with their binding leads to abrogation of Irf8 expression, subsequently to disturbed cell fate decisions, demonstrating the importance of these factors for proper phagocyte cell development. Collectively, these data delineate a transcriptional program establishing cDC fate choice with IRF8 in its center.
A systems biological approach towards the molecular basis of heterosis in Arabidopsis thaliana
(2011)
Heterosis is defined as the superiority in performance of heterozygous genotypes compared to their corresponding genetically different homozygous parents. This phenomenon is already known since the beginning of the last century and it has been widely used in plant breeding, but the underlying genetic and molecular mechanisms are not well understood. In this work, a systems biological approach based on molecular network structures is proposed to contribute to the understanding of heterosis. Hybrids are likely to contain additional regulatory possibilities compared to their homozygous parents and, therefore, they may be able to correctly respond to a higher number of environmental challenges, which leads to a higher adaptability and, thus, the heterosis phenomenon. In the network hypothesis for heterosis, presented in this work, more regulatory interactions are expected in the molecular networks of the hybrids compared to the homozygous parents. Partial correlations were used to assess this difference in the global interaction structure of regulatory networks between the hybrids and the homozygous genotypes. This network hypothesis for heterosis was tested on metabolite profiles as well as gene expression data of the two parental Arabidopsis thaliana accessions C24 and Col-0 and their reciprocal crosses. These plants are known to show a heterosis effect in their biomass phenotype. The hypothesis was confirmed for mid-parent and best-parent heterosis for either hybrid of our experimental metabolite as well as gene expression data. It was shown that this result is influenced by the used cutoffs during the analyses. Too strict filtering resulted in sets of metabolites and genes for which the network hypothesis for heterosis does not hold true for either hybrid regarding mid-parent as well as best-parent heterosis. In an over-representation analysis, the genes that show the largest heterosis effects according to our network hypothesis were compared to genes of heterotic quantitative trait loci (QTL) regions. Separately for either hybrid regarding mid-parent as well as best-parent heterosis, a significantly larger overlap between the resulting gene lists of the two different approaches towards biomass heterosis was detected than expected by chance. This suggests that each heterotic QTL region contains many genes influencing biomass heterosis in the early development of Arabidopsis thaliana. Furthermore, this integrative analysis led to a confinement and an increased confidence in the group of candidate genes for biomass heterosis in Arabidopsis thaliana identified by both approaches.
This Thesis puts its focus on the physics of neutron stars and its description with methods of numerical relativity. In the first step, a new numerical framework the Whisky2D code will be developed, which solves the relativistic equations of hydrodynamics in axisymmetry. Therefore we consider an improved formulation of the conserved form of these equations. The second part will use the new code to investigate the critical behaviour of two colliding neutron stars. Considering the analogy to phase transitions in statistical physics, we will investigate the evolution of the entropy of the neutron stars during the whole process. A better understanding of the evolution of thermodynamical quantities, like the entropy in critical process, should provide deeper understanding of thermodynamics in relativity. More specifically, we have written the Whisky2D code, which solves the general-relativistic hydrodynamics equations in a flux-conservative form and in cylindrical coordinates. This of course brings in 1/r singular terms, where r is the radial cylindrical coordinate, which must be dealt with appropriately. In the above-referenced works, the flux operator is expanded and the 1/r terms, not containing derivatives, are moved to the right-hand-side of the equation (the source term), so that the left hand side assumes a form identical to the one of the three-dimensional (3D) Cartesian formulation. We call this the standard formulation. Another possibility is not to split the flux operator and to redefine the conserved variables, via a multiplication by r. We call this the new formulation. The new equations are solved with the same methods as in the Cartesian case. From a mathematical point of view, one would not expect differences between the two ways of writing the differential operator, but, of course, a difference is present at the numerical level. Our tests show that the new formulation yields results with a global truncation error which is one or more orders of magnitude smaller than those of alternative and commonly used formulations. The second part of the Thesis uses the new code for investigations of critical phenomena in general relativity. In particular, we consider the head-on-collision of two neutron stars in a region of the parameter space where two final states a new stable neutron star or a black hole, lay close to each other. In 1993, Choptuik considered one-parameter families of solutions, S[P], of the Einstein-Klein-Gordon equations for a massless scalar field in spherical symmetry, such that for every P > P⋆, S[P] contains a black hole and for every P < P⋆, S[P] is a solution not containing singularities. He studied numerically the behavior of S[P] as P → P⋆ and found that the critical solution, S[P⋆], is universal, in the sense that it is approached by all nearly-critical solutions regardless of the particular family of initial data considered. All these phenomena have the common property that, as P approaches P⋆, S[P] approaches a universal solution S[P⋆] and that all the physical quantities of S[P] depend only on |P − P⋆|. The first study of critical phenomena concerning the head-on collision of NSs was carried out by Jin and Suen in 2007. In particular, they considered a series of families of equal-mass NSs, modeled with an ideal-gas EOS, boosted towards each other and varied the mass of the stars, their separation, velocity and the polytropic index in the EOS. In this way they could observe a critical phenomenon of type I near the threshold of black-hole formation, with the putative solution being a nonlinearly oscillating star. In a successive work, they performed similar simulations but considering the head-on collision of Gaussian distributions of matter. Also in this case they found the appearance of type-I critical behaviour, but also performed a perturbative analysis of the initial distributions of matter and of the merged object. Because of the considerable difference found in the eigenfrequencies in the two cases, they concluded that the critical solution does not represent a system near equilibrium and in particular not a perturbed Tolmann-Oppenheimer-Volkoff (TOV) solution. In this Thesis we study the dynamics of the head-on collision of two equal-mass NSs using a setup which is as similar as possible to the one considered above. While we confirm that the merged object exhibits a type-I critical behaviour, we also argue against the conclusion that the critical solution cannot be described in terms of equilibrium solution. Indeed, we show that, in analogy with what is found in, the critical solution is effectively a perturbed unstable solution of the TOV equations. Our analysis also considers fine-structure of the scaling relation of type-I critical phenomena and we show that it exhibits oscillations in a similar way to the one studied in the context of scalar-field critical collapse.
In this work new fluorinated and non-fluorinated mono- and bifunctional trithiocarbonates of the structure Z-C(=S)-S-R and Z-C(=S)-S-R-S-C(=S)-Z were synthesized for the use as chain transfer agents (CTAs) in the RAFT-process. All newly synthesized CTAs were tested for their efficiency to moderate the free radical polymerization process by polymerizing styrene (M3). Besides characterization of the homopolymers by GPC measurements, end- group analysis of the synthesized block copolymers via 1H-, 19F-NMR, and in some cases also UV-vis spectroscopy, were performed attaching suitable fluorinated moieties to the Z- and/or R-groups of the CTAs. Symmetric triblock copolymers of type BAB and non-symmetric fluorine end- capped polymers were accessible using the RAFT process in just two or one polymerization step. In particular, the RAFT-process enabled the controlled polymerization of hydrophilic monomers such as N-isopropylacrylamide (NIPAM) (M1) as well as N-acryloylpyrrolidine (NAP) (M2) for the A-blocks and of the hydrophobic monomers styrene (M3), 2-fluorostyrene (M4), 3-fluorostyrene (M5), 4-fluorostyrene (M6) and 2,3,4,5,6-pentafluorostyrene (M7) for the B-blocks. The properties of the BAB-triblock copolymers were investigated in dilute, concentrated and highly concentrated aqueous solutions using DLS, turbidimetry, 1H- and 19F-NMR, rheology, determination of the CMC, foam height- and surface tension measurements and microscopy. Furthermore, their ability to stabilize emulsions and microemulsions and the wetting behaviour of their aqueous solutions on different substrates was investigated. The behaviour of the fluorine end-functionalized polymers to form micelles was studied applying DLS measurements in diluted organic solution. All investigated BAB-triblock copolymers were able to form micelles and show surface activity at room temperature in dilute aqueous solution. The aqueous solutions displayed moderate foam formation. With different types and concentrations of oils, the formation of emulsions could be detected using a light microscope. A boosting effect in microemulsions could not be found adding BAB-triblock copolymers. At elevated polymer concentrations, the formation of hydrogels was proved applying rheology measurements.
The present thesis introduces an iterative expert-based Bayesian approach for assessing greenhouse gas (GHG) emissions from the 2030 German new vehicle fleet and quantifying the impacts of their main drivers. A first set of expert interviews has been carried out in order to identify technologies which may help to lower car GHG emissions and to quantify their emission reduction potentials. Moreover, experts were asked for their probability assessments that the different technologies will be widely adopted, as well as for important prerequisites that could foster or hamper their adoption. Drawing on the results of these expert interviews, a Bayesian Belief Network has been built which explicitly models three vehicle types: Internal Combustion Engine Vehicles (which include mild and full Hybrid Electric Vehicles), Plug-In Hybrid Electric Vehicles, and Battery Electric Vehicles. The conditional dependencies of twelve central variables within the BBN - battery energy, fuel and electricity consumption, relative costs, and sales shares of the vehicle types - have been quantified by experts from German car manufacturers in a second series of interviews. For each of the seven second-round interviews, an expert's individually specified BBN results. The BBN have been run for different hypothetical 2030 scenarios which differ, e.g., in regard to battery development, regulation, and fuel and electricity GHG intensities. The present thesis delivers results both in regard to the subject of the investigation and in regard to its method. On the subject level, it has been found that the different experts expect 2030 German new car fleet emission to be at 50 to 65% of 2008 new fleet emissions under the baseline scenario. They can be further reduced to 40 to 50% of the emissions of the 2008 fleet though a combination of a higher share of renewables in the electricity mix, a larger share of biofuels in the fuel mix, and a stricter regulation of car CO$_2$ emissions in the European Union. Technically, 2030 German new car fleet GHG emissions can be reduced to a minimum of 18 to 44% of 2008 emissions, a development which can not be triggered by any combination of measures modeled in the BBN alone but needs further commitment. Out of a wealth of existing BBN, few have been specified by individual experts through elicitation, and to my knowledge, none of them has been employed for analyzing perspectives for the future. On the level of methods, this work shows that expert-based BBN are a valuable tool for making experts' expectations for the future explicit and amenable to the analysis of different hypothetical scenarios. BBN can also be employed for quantifying the impacts of main drivers. They have been demonstrated to be a valuable tool for iterative stakeholder-based science approaches.
Corvino, Corvino and Schoen, Chruściel and Delay have shown the existence of a large class of asymptotically flat vacuum initial data for Einstein's field equations which are static or stationary in a neighborhood of space-like infinity, yet quite general in the interior. The proof relies on some abstract, non-constructive arguments which makes it difficult to calculate such data numerically by using similar arguments. A quasilinear elliptic system of equations is presented of which we expect that it can be used to construct vacuum initial data which are asymptotically flat, time-reflection symmetric, and asymptotic to static data up to a prescribed order at space-like infinity. A perturbation argument is used to show the existence of solutions. It is valid when the order at which the solutions approach staticity is restricted to a certain range. Difficulties appear when trying to improve this result to show the existence of solutions that are asymptotically static at higher order. The problems arise from the lack of surjectivity of a certain operator. Some tensor decompositions in asymptotically flat manifolds exhibit some of the difficulties encountered above. The Helmholtz decomposition, which plays a role in the preparation of initial data for the Maxwell equations, is discussed as a model problem. A method to circumvent the difficulties that arise when fast decay rates are required is discussed. This is done in a way that opens the possibility to perform numerical computations. The insights from the analysis of the Helmholtz decomposition are applied to the York decomposition, which is related to that part of the quasilinear system which gives rise to the difficulties. For this decomposition analogous results are obtained. It turns out, however, that in this case the presence of symmetries of the underlying metric leads to certain complications. The question, whether the results obtained so far can be used again to show by a perturbation argument the existence of vacuum initial data which approach static solutions at infinity at any given order, thus remains open. The answer requires further analysis and perhaps new methods.
Most of the microelectronic circuits fabricated today are synchronous, i.e. they are driven by one or several clock signals. Synchronous circuit design faces several fundamental challenges such as high-speed clock distribution, integration of multiple cores operating at different clock rates, reduction of power consumption and dealing with voltage, temperature, manufacturing and runtime variations. Asynchronous or clockless design plays a key role in alleviating these challenges, however the design and test of asynchronous circuits is much more difficult in comparison to their synchronous counterparts. A driving force for a widespread use of asynchronous technology is the availability of mature EDA (Electronic Design Automation) tools which provide an entire automated design flow starting from an HDL (Hardware Description Language) specification yielding the final circuit layout. Even though there was much progress in developing such EDA tools for asynchronous circuit design during the last two decades, the maturity level as well as the acceptance of them is still not comparable with tools for synchronous circuit design. In particular, logic synthesis (which implies the application of Boolean minimisation techniques) for the entire system's control path can significantly improve the efficiency of the resulting asynchronous implementation, e.g. in terms of chip area and performance. However, logic synthesis, in particular for asynchronous circuits, suffers from complexity problems. Signal Transitions Graphs (STGs) are labelled Petri nets which are a widely used to specify the interface behaviour of speed independent (SI) circuits - a robust subclass of asynchronous circuits. STG decomposition is a promising approach to tackle complexity problems like state space explosion in logic synthesis of SI circuits. The (structural) decomposition of STGs is guided by a partition of the output signals and generates a usually much smaller component STG for each partition member, i.e. a component STG with a much smaller state space than the initial specification. However, decomposition can result in component STGs that in isolation have so-called irreducible CSC conflicts (i.e. these components are not SI synthesisable anymore) even if the specification has none of them. A new approach is presented to avoid such conflicts by introducing internal communication between the components. So far, STG decompositions are guided by the finest output partitions, i.e. one output per component. However, this might not yield optimal circuit implementations. Efficient heuristics are presented to determine coarser partitions leading to improved circuits in terms of chip area. For the new algorithms correctness proofs are given and their implementations are incorporated into the decomposition tool DESIJ. The presented techniques are successfully applied to some benchmarks - including 'real-life' specifications arising in the context of control resynthesis - which delivered promising results.
Business Process Management (BPM) emerged as a means to control, analyse, and optimise business operations. Conceptual models are of central importance for BPM. Most prominently, process models define the behaviour that is performed to achieve a business value. In essence, a process model is a mapping of properties of the original business process to the model, created for a purpose. Different modelling purposes, therefore, result in different models of a business process. Against this background, the misalignment of process models often observed in the field of BPM is no surprise. Even if the same business scenario is considered, models created for strategic decision making differ in content significantly from models created for process automation. Despite their differences, process models that refer to the same business process should be consistent, i.e., free of contradictions. Apparently, there is a trade-off between strictness of a notion of consistency and appropriateness of process models serving different purposes. Existing work on consistency analysis builds upon behaviour equivalences and hierarchical refinements between process models. Hence, these approaches are computationally hard and do not offer the flexibility to gradually relax consistency requirements towards a certain setting. This thesis presents a framework for the analysis of behaviour consistency that takes a fundamentally different approach. As a first step, an alignment between corresponding elements of related process models is constructed. Then, this thesis conducts behavioural analysis grounded on a relational abstraction of the behaviour of a process model, its behavioural profile. Different variants of these profiles are proposed, along with efficient computation techniques for a broad class of process models. Using behavioural profiles, consistency of an alignment between process models is judged by different notions and measures. The consistency measures are also adjusted to assess conformance of process logs that capture the observed execution of a process. Further, this thesis proposes various complementary techniques to support consistency management. It elaborates on how to implement consistent change propagation between process models, addresses the exploration of behavioural commonalities and differences, and proposes a model synthesis for behavioural profiles.
Business process models are used within a range of organizational initiatives, where every stakeholder has a unique perspective on a process and demands the respective model. As a consequence, multiple process models capturing the very same business process coexist. Keeping such models in sync is a challenge within an ever changing business environment: once a process is changed, all its models have to be updated. Due to a large number of models and their complex relations, model maintenance becomes error-prone and expensive. Against this background, business process model abstraction emerged as an operation reducing the number of stored process models and facilitating model management. Business process model abstraction is an operation preserving essential process properties and leaving out insignificant details in order to retain information relevant for a particular purpose. Process model abstraction has been addressed by several researchers. The focus of their studies has been on particular use cases and model transformations supporting these use cases. This thesis systematically approaches the problem of business process model abstraction shaping the outcome into a framework. We investigate the current industry demand in abstraction summarizing it in a catalog of business process model abstraction use cases. The thesis focuses on one prominent use case where the user demands a model with coarse-grained activities and overall process ordering constraints. We develop model transformations that support this use case starting with the transformations based on process model structure analysis. Further, abstraction methods considering the semantics of process model elements are investigated. First, we suggest how semantically related activities can be discovered in process models-a barely researched challenge. The thesis validates the designed abstraction methods against sets of industrial process models and discusses the method implementation aspects. Second, we develop a novel model transformation, which combined with the related activity discovery allows flexible non-hierarchical abstraction. In this way this thesis advocates novel model transformations that facilitate business process model management and provides the foundations for innovative tool support.
The Casimir-Polder interaction between a single neutral atom and a nearby surface, arising from the (quantum and thermal) fluctuations of the electromagnetic field, is a cornerstone of cavity quantum electrodynamics (cQED), and theoretically well established. Recently, Bose-Einstein condensates (BECs) of ultracold atoms have been used to test the predictions of cQED. The purpose of the present thesis is to upgrade single-atom cQED with the many-body theory needed to describe trapped atomic BECs. Tools and methods are developed in a second-quantized picture that treats atom and photon fields on the same footing. We formulate a diagrammatic expansion using correlation functions for both the electromagnetic field and the atomic system. The formalism is applied to investigate, for BECs trapped near surfaces, dispersion interactions of the van der Waals-Casimir-Polder type, and the Bosonic stimulation in spontaneous decay of excited atomic states. We also discuss a phononic Casimir effect, which arises from the quantum fluctuations in an interacting BEC.
Non-mycorrhizal fungal endophytes are able to colonize internally roots without causing visible disease symptoms establishing neutral or mutualistic associations with plants. These fungi known as non-clavicipitaceous endophytes have a broad host range of monocot and eudicot plants and are highly diverse. Some of them promote plant growth and confer increased abiotic-stress tolerance and disease resistance. According to such possible effects on host plants, it was aimed to isolate and to characterize native fungal root endophytes from tomato (Lycopersicon esculentum Mill.) and to analyze their effects on plant development, plant resistance and fruit yield and quality together with the model endophyte Piriformospora indica. Fifty one new fungal strains were isolated from desinfected tomato roots of four different crop sites in Colombia. These isolates were roughly characterized and fourteen potential endophytes were further analyzed concerning their taxonomy, their root colonization capacity and their impact on plant growth. Sequencing of the ITS region from the ribosomal RNA gene cluster and in-depth morphological characterisation revealed that they correspond to different phylogenetic groups among the phylum Ascomycota. Nine different morphotypes were described including six dark septate endophytes (DSE) that did not correspond to the Phialocephala group. Detailed confocal microscopy analysis showed various colonization patterns of the endophytes inside the roots ranging from epidermal penetration to hyphal growth through the cortex. Tomato pot experiments under glass house conditions showed that they differentially affect plant growth depending on colonization time and inoculum concentration. Three new isolates (two unknown fungal endophyte DSE48, DSE49 and one identified as Leptodontidium orchidicola) with neutral or positiv effects were selected and tested in several experiments for their influence on vegetative growth, fruit yield and quality and their ability to diminish the impact of the pathogen Verticillium dahliae on tomato plants. Although plant growth promotion by all three fungi was observed in young plants, vegetative growth parameters were not affected after 22 weeks of cultivation except a reproducible increase of root diameter by the endophyte DSE49. Additionally, L. orchidicola increased biomass and glucose content of tomato fruits, but only at an early date of harvest and at a certain level of root colonization. Concerning bioprotective effects, the endophytes DSE49 and L. orchidicola decreased significantly disease symptoms caused by the pathogen V. dahliae, but only at a low dosis of the pathogen. In order to analyze, if the model root endophytic fungus Piriformospora indica could be suitable for application in production systems, its impact on tomato was evaluated. Similarly to the new fungal isolates, significant differences for vegetative growth parameters were only observable in young plants and, but protection against V. dahliae could be seen in one experiment also at high dosage of the pathogen. As the DSE L. orchidicola, P. indica increased the number and biomass of marketable tomatoes only at the beginning of fruit setting, but this did not lead to a significant higher total yield. If the effects on growth are due to a better nutrition of the plant with mineral element was analyzed in barley in comparison to the arbuscular mycorrhizal fungus Glomus mosseae. While the mycorrhizal fungus increased nitrogen and phosphate uptake of the plant, no such effect was observed for P. indica. In summary this work shows that many different fungal endophytes can be also isolated from roots of crops and, that these isolates can have positive effects on early plant development. This does, however, not lead to an increase in total yield or in improvement of fruit quality of tomatoes under greenhouse conditions.
The present thesis was born and evolved within the RAdial Velocity Experiment (RAVE) with the goal of measuring chemical abundances from the RAVE spectra and exploit them to investigate the chemical gradients along the plane of the Galaxy to provide constraints on possible Galactic formation scenarios. RAVE is a large spectroscopic survey which aims to observe spectroscopically ~10^6 stars by the end of 2012 and measures their radial velocities, atmospheric parameters and chemical abundances. The project makes use of the UK Schmidt telescope at Australian Astronomical Observatory (AAO) in Siding Spring, Australia, equipped with the multiobject spectrograph 6dF. To date, RAVE collected and measured more than 450,000 spectra. The precision of the chemical abundance estimations depends on the reliability of the atomic and atmosphere parameters adopted (in particular the oscillator strengths of the absorption lines and the effective temperature, gravity, and metallicity of the stars measured). Therefore we first identified 604 absorption lines in the RAVE wavelength range and refined their oscillator strengths with an inverse spectral analysis. Then, we improved the RAVE stellar parameters by modifying the RAVE pipeline and the spectral library the pipeline rely on. The modifications removed some systematic errors in stellar parameters discovered during this work. To obtain chemical abundances, we developed two different processing pipelines. Both of them perform chemical abundances measurements by assuming stellar atmospheres in Local Thermodynamic Equilibrium (LTE). The first one determines elements abundances from equivalent widths of absorption lines. Since this pipeline showed poor sensibility on abundances relative to iron, it has been superseded. The second one exploits the chi^2 minimization technique between observed and model spectra. Thanks to its precision, it has been adopted for the creation of the RAVE chemical catalogue. This pipeline provides abundances with uncertains of about ~0.2dex for spectra with signal-to-noise ratio S/N>40 and ~0.3dex for spectra with 20>S/N>40. For this work, the pipeline measured chemical abundances up to 7 elements for 217,358 RAVE stars. With these data we investigated the chemical gradients along the Galactic radius of the Milky Way. We found that stars with low vertical velocities |W| (which stay close to the Galactic plane) show an iron abundance gradient in agreement with previous works (~-0.07$ dex kpc^-1) whereas stars with larger |W| which are able to reach larger heights above the Galactic plane, show progressively flatter gradients. The gradients of the other elements follow the same trend. This suggests that an efficient radial mixing acts in the Galaxy or that the thick disk formed from homogeneous interstellar matter. In particular, we found hundreds of stars which can be kinetically classified as thick disk stars exhibiting a chemical composition typical of the thin disk. A few stars of this kind have already been detected by other authors, and their origin is still not clear. One possibility is that they are thin disk stars kinematically heated, and then underwent an efficient radial mixing process which blurred (and so flattened) the gradient. Alternatively they may be a transition population" which represents an evolutionary bridge between thin and thick disk. Our analysis shows that the two explanations are not mutually exclusive. Future follow-up high resolution spectroscopic observations will clarify their role in the Galactic disk evolution.
In the living cell, the organization of the complex internal structure relies to a large extent on molecular motors. Molecular motors are proteins that are able to convert chemical energy from the hydrolysis of adenosine triphosphate (ATP) into mechanical work. Being about 10 to 100 nanometers in size, the molecules act on a length scale, for which thermal collisions have a considerable impact onto their motion. In this way, they constitute paradigmatic examples of thermodynamic machines out of equilibrium. This study develops a theoretical description for the energy conversion by the molecular motor myosin V, using many different aspects of theoretical physics. Myosin V has been studied extensively in both bulk and single molecule experiments. Its stepping velocity has been characterized as a function of external control parameters such as nucleotide concentration and applied forces. In addition, numerous kinetic rates involved in the enzymatic reaction of the molecule have been determined. For forces that exceed the stall force of the motor, myosin V exhibits a 'ratcheting' behaviour: For loads in the direction of forward stepping, the velocity depends on the concentration of ATP, while for backward loads there is no such influence. Based on the chemical states of the motor, we construct a general network theory that incorporates experimental observations about the stepping behaviour of myosin V. The motor's motion is captured through the network description supplemented by a Markov process to describe the motor dynamics. This approach has the advantage of directly addressing the chemical kinetics of the molecule, and treating the mechanical and chemical processes on equal grounds. We utilize constraints arising from nonequilibrium thermodynamics to determine motor parameters and demonstrate that the motor behaviour is governed by several chemomechanical motor cycles. In addition, we investigate the functional dependence of stepping rates on force by deducing the motor's response to external loads via an appropriate Fokker-Planck equation. For substall forces, the dominant pathway of the motor network is profoundly different from the one for superstall forces, which leads to a stepping behaviour that is in agreement with the experimental observations. The extension of our analysis to Markov processes with absorbing boundaries allows for the calculation of the motor's dwell time distributions. These reveal aspects of the coordination of the motor's heads and contain direct information about the backsteps of the motor. Our theory provides a unified description for the myosin V motor as studied in single motor experiments.
The complete consumption of the oceanic domain of a tectonic plate by subduction into the upper mantle results in continent subduction, although continental crust is typically of lower density than the upper mantle. Thus, the sites of former oceanic domains (named suture zones) are generally decorated with stratigraphic sequences deposited along continental passive margins that were metamorphosed under low-grade, high-pressure conditions, i.e., low temperature/depth ratios (< 15°C/km) with respect to geothermal gradients in tectonically stable regions. Throughout the Mesozoic and Cenozoic (i.e., since ca. 250 Ma), the Mediterranean realm was shaped by the closure of the Tethyan Ocean, which likely consisted in numerous oceanic domains and microcontinents. However, the exact number and position of Tethyan oceans and continents (i.e., the Tethyan palaeogeography) remains debated. This is particularly the case of Western and Central Anatolia, where a continental fragment was accreted to the southern composite margin of the Eurasia sometime between the Late Cretaceous and the early Cenozoic. The most frontal part of this microcontinent experienced subduction-related metamorphism around 85-80 Ma, and collision-related metamorphism affected more external parts around 35 Ma. This unsually-long period between subduction- and collision-related metamorphisms (ca. 50 Ma) in units ascribed to the same continental edge constitutes a crucial issue to address in order to unravel how Anatolia was assembled. The Afyon Zone is a tectono-sedimentary unit exposed south and structurally below the front high-pressure belt. It is composed of a Mesozoic sedimentary sequence deposited on top of a Precambrian to Palaeozoic continental substratum, which can be traced from Northwestern to southern Central Anatolia, along a possible Tethyan suture. Whereas the Afyon Zone was defined as a low-pressure metamorphic unit, high-pressure minerals (mainly Fe-Mg-carpholite in metasediments) were recently reported from its central part. These findings shattered previous conceptions on the tectono-metamorphic evolution of the Afyon Zone in particular, and of the entire region in general, and shed light on the necessity to revise the regional extent of subduction-related metamorphism by re-inspecting the petrology of poorly-studied metasediments. In this purpose, I re-evaluated the metamorphic evolution of the entire Afyon Zone starting from field observations. Low-grade, high-pressure mineral assemblages (Fe-Mg-carpholite and glaucophane) are reported throughout the unit. Well-preserved carpholite-chloritoid assemblages are useful to improve our understanding of mineral relations and transitions in the FeO-MgO-Al2O3-SiO2-H2O system during rocks’ travel down to depth (prograde metamorphism). Inspection of petrographic textures, minute variations in mineral composition and Mg-Fe distribution among carpholite-chloritoid assemblages documents multistage mineral growth, accompanied by a progressive enrichment in Mg, and strong element partitioning. Using an updated database of mineral thermodynamic properties, I modelled the pressure and temperature conditions that are consistent with textural and chemical observations. Carpholite-bearing assemblages in the Afyon Zone account for a temperature increase from 280 to 380°C between 0.9 and 1.1 GPa (equivalent to a depth of 30-35 km). In order to further constrain regional geodynamics, first radiometric ages were determined in close association with pressure-temperature estimates for the Afyon Zone, as well as two other tectono-sedimentary units from the same continental passive margin (the Ören and Kurudere-Nebiler Units from SW Anatolia). For age determination, I employed 40Ar-39Ar geochronology on white mica in carpholite-bearing rocks. For thermobarometry, a multi-equilibrium approach was used based on quartz-chlorite-mica and quartz-chlorite-chloritoid associations formed at the expense of carpholite-bearing assemblages, i.e., during the exhumation from the subduction zone. This combination allows deciphering the significance of the calculated radiometric ages in terms of metamorphic conditions. Results show that the Afyon Zone and the Ören Unit represent a latest Cretaceous high-pressure metamorphic belt, and the Kurudere-Nebiler Unit was affected by subduction-related metamorphism around 45 Ma and cooled down after collision-related metamorphism around 26 Ma. The results provided in the present thesis and from the literature allow better understanding continental amalgamation in Western Anatolia. It is shown that at least two distinct oceanic branches, whereas only one was previously considered, have closed during continuous north-dipping subduction between 92 and 45 Ma. Between 85-80 and 70-65 Ma, a narrow continental domain (including the Afyon Zone) was buried into a subduction zone within the northern oceanic strand. Parts of the subducted continent crust were exhumed while the upper oceanic plate was transported southwards. Subduction of underlying lithosphere persisted, leading to the closure of the southern oceanic branch and to subduct the front of a second continental domain (including the Kurudere-Nebiler Unit). This followed by a continental collisional stage characterized by the cease of subduction, crustal thicknening and the detachment of the subducting oceanic slab from the accreted continent lithosphere. The present study supports that in the late Mesozoic the East Mediterranean realm had a complex tectonic configuration similar to present Southeast Asia or the Caribbean, with multiple, coexisting oceanic basins, microcontinents and subduction zones.
Complete protection against flood risks by structural measures is impossible. Therefore flood prediction is important for flood risk management. Good explanatory power of flood models requires a meaningful representation of bio-physical processes. Therefore great interest exists to improve the process representation. Progress in hydrological process understanding is achieved through a learning cycle including critical assessment of an existing model for a given catchment as a first step. The assessment will highlight deficiencies of the model, from which useful additional data requirements are derived, giving a guideline for new measurements. These new measurements may in turn lead to improved process concepts. The improved process concepts are finally summarized in an updated hydrological model. In this thesis I demonstrate such a learning cycle, focusing on the advancement of model evaluation methods and more cost effective measurements. For a successful model evaluation, I propose that three questions should be answered: 1) when is a model reproducing observations in a satisfactory way? 2) If model results deviate, of what nature is the difference? And 3) what are most likely the relevant model components affecting these differences? To answer the first two questions, I developed a new method to assess the temporal dynamics of model performance (or TIGER - TIme series of Grouped Errors). This method is powerful in highlighting recurrent patterns of insufficient model behaviour for long simulation periods. I answered the third question with the analysis of the temporal dynamics of parameter sensitivity (TEDPAS). For calculating TEDPAS, an efficient method for sensitivity analysis is necessary. I used such an efficient method called Fourier Amplitude Sensitivity Test, which has a smart sampling scheme. Combining the two methods TIGER and TEDPAS provided a powerful tool for model assessment. With WaSiM-ETH applied to the Weisseritz catchment as a case study, I found insufficient process descriptions for the snow dynamics and for the recession during dry periods in late summer and fall. Focusing on snow dynamics, reasons for poor model performance can either be a poor representation of snow processes in the model, or poor data on snow cover, or both. To obtain an improved data set on snow cover, time series of snow height and temperatures were collected with a cost efficient method based on temperature measurements on multiple levels at each location. An algorithm was developed to simultaneously estimate snow height and cold content from these measurements. Both, snow height and cold content are relevant quantities for spring flood forecasting. Spatial variability was observed at the local and the catchment scale with an adjusted sampling design. At the local scale, samples were collected on two perpendicular transects of 60 m length and analysed with geostatistical methods. The range determined from fitted theoretical variograms was within the range of the sampling design for 80% of the plots. No patterns were found, that would explain the random variability and spatial correlation at the local scale. At the watershed scale, locations of the extensive field campaign were selected according to a stratified sample design to capture the combined effects of elevation, aspect and land use. The snow height is mainly affected by the plot elevation. The expected influence of aspect and land use was not observed. To better understand the deficiencies of the snow module in WaSiM-ETH, the same approach, a simple degree day model was checked for its capability to reproduce the data. The degree day model was capable to explain the temporal variability for plots with a continuous snow pack over the entire snow season, if parameters were estimated for single plots. However, processes described in the simple model are not sufficient to represent multiple accumulation-melt-cycles, as observed for the lower catchment. Thus, the combined spatio-temporal variability at the watershed scale is not captured by the model. Further tests on improved concepts for the representation of snow dynamics at the Weißeritz are required. From the data I suggest to include at least rain on snow and redistribution by wind as additional processes to better describe spatio-temporal variability. Alternatively an energy balance snow model could be tested. Overall, the proposed learning cycle is a useful framework for targeted model improvement. The advanced model diagnostics is valuable to identify model deficiencies and to guide field measurements. The additional data collected throughout this work helps to get a deepened understanding of the processes in the Weisseritz catchment.
The Arctic is a particularly sensitive area with respect to climate change due to the high surface albedo of snow and ice and the extreme radiative conditions. Clouds and aerosols as parts of the Arctic atmosphere play an important role in the radiation budget, which is, as yet, poorly quantified and understood. The LIDAR (Light Detection And Ranging) measurements presented in this PhD thesis contribute with continuous altitude resolved aerosol profiles to the understanding of occurrence and characteristics of aerosol layers above Ny-Ålesund, Spitsbergen. The attention was turned to the analysis of periods with high aerosol load. As the Arctic spring troposphere exhibits maximum aerosol optical depths (AODs) each year, March and April of both the years 2007 and 2009 were analyzed. Furthermore, stratospheric aerosol layers of volcanic origin were analyzed for several months, subsequently to the eruptions of the Kasatochi and Sarychev volcanoes in summer 2008 and 2009, respectively. The Koldewey Aerosol Raman LIDAR (KARL) is an instrument for the active remote sensing of atmospheric parameters using pulsed laser radiation. It is operated at the AWIPEV research base and was fundamentally upgraded within the framework of this PhD project. It is now equipped with a new telescope mirror and new detection optics, which facilitate atmospheric profiling from 450m above sea level up to the mid-stratosphere. KARL provides highly resolved profiles of the scattering characteristics of aerosol and cloud particles (backscattering, extinction and depolarization) as well as water vapor profiles within the lower troposphere. Combination of KARL data with data from other instruments on site, namely radiosondes, sun photometer, Micro Pulse LIDAR, and tethersonde system, resulted in a comprehensive data set of scattering phenomena in the Arctic atmosphere. The two spring periods March and April 2007 and 2009 were at first analyzed based on meteorological parameters, like local temperature and relative humidity profiles as well as large scale pressure patterns and air mass origin regions. Here, it was not possible to find a clear correlation between enhanced AOD and air mass origin. However, in a comparison of two cloud free periods in March 2007 and April 2009, large AOD values in 2009 coincided with air mass transport through the central Arctic. This suggests the occurrence of aerosol transformation processes during the aerosol transport to Ny-Ålesund. Measurements on 4 April 2009 revealed maximum AOD values of up to 0.12 and aerosol size distributions changing with altitude. This and other performed case studies suggest the differentiation between three aerosol event types and their origin: Vertically limited aerosol layers in dry air, highly variable hygroscopic boundary layer aerosols and enhanced aerosol load across wide portions of the troposphere. For the spring period 2007, the available KARL data were statistically analyzed using a characterization scheme, which is based on optical characteristics of the scattering particles. The scheme was validated using several case studies. Volcanic eruptions in the northern hemisphere in August 2008 and June 2009 arose the opportunity to analyze volcanic aerosol layers within the stratosphere. The rate of stratospheric AOD change was similar within both years with maximum values above 0.1 about three to five weeks after the respective eruption. In both years, the stratospheric AOD persisted at higher rates than usual until the measurements were stopped in late September due to technical reasons. In 2008, up to three aerosol layers were detected, the layer structure in 2009 was characterized by up to six distinct and thin layers which smeared out to one broad layer after about two months. The lowermost aerosol layer was continuously detected at the tropopause altitude. Three case studies were performed, all revealed rather large indices of refraction of m = (1.53–1.55) - 0.02i, suggesting the presence of an absorbing carbonaceous component. The particle radius, derived with inversion calculations, was also similar in both years with values ranging from 0.16 to 0.19 μm. However, in 2009, a second mode in the size distribution was detected at about 0.5 μm. The long term measurements with the Koldewey Aerosol Raman LIDAR in Ny-Ålesund provide the opportunity to study Arctic aerosols in the troposphere and the stratosphere not only in case studies but on longer time scales. In this PhD thesis, both, tropospheric aerosols in the Arctic spring and stratospheric aerosols following volcanic eruptions have been described qualitatively and quantitatively. Case studies and comparative studies with data of other instruments on site allowed for the analysis of microphysical aerosol characteristics and their temporal evolution.
Supermassive black holes are a fundamental component of the universe in general and of galaxies in particular. Almost every massive galaxy harbours a supermassive black hole (SMBH) in its center. Furthermore, there is a close connection between the growth of the SMBH and the evolution of its host galaxy, manifested in the relationship between the mass of the black hole and various properties of the galaxy's spheroid component, like its stellar velocity dispersion, luminosity or mass. Understanding this relationship and the growth of SMBHs is essential for our picture of galaxy formation and evolution. In this thesis, I make several contributions to improve our knowledge on the census of SMBHs and on the coevolution of black holes and galaxies. The first route I follow on this road is to obtain a complete census of the black hole population and its properties. Here, I focus particularly on active black holes, observable as Active Galactic Nuclei (AGN) or quasars. These are found in large surveys of the sky. In this thesis, I use one of these surveys, the Hamburg/ESO survey (HES), to study the AGN population in the local volume (z~0). The demographics of AGN are traditionally represented by the AGN luminosity function, the distribution function of AGN at a given luminosity. I determined the local (z<0.3) optical luminosity function of so-called type 1 AGN, based on the broad band B_J magnitudes and AGN broad Halpha emission line luminosities, free of contamination from the host galaxy. I combined this result with fainter data from the Sloan Digital Sky Survey (SDSS) and constructed the best current optical AGN luminosity function at z~0. The comparison of the luminosity function with higher redshifts supports the current notion of 'AGN downsizing', i.e. the space density of the most luminous AGN peaks at higher redshifts and the space density of less luminous AGN peaks at lower redshifts. However, the AGN luminosity function does not reveal the full picture of active black hole demographics. This requires knowledge of the physical quantities, foremost the black hole mass and the accretion rate of the black hole, and the respective distribution functions, the active black hole mass function and the Eddington ratio distribution function. I developed a method for an unbiased estimate of these two distribution functions, employing a maximum likelihood technique and fully account for the selection function. I used this method to determine the active black hole mass function and the Eddington ratio distribution function for the local universe from the HES. I found a wide intrinsic distribution of black hole accretion rates and black hole masses. The comparison of the local active black hole mass function with the local total black hole mass function reveals evidence for 'AGN downsizing', in the sense that in the local universe the most massive black holes are in a less active stage then lower mass black holes. The second route I follow is a study of redshift evolution in the black hole-galaxy relations. While theoretical models can in general explain the existence of these relations, their redshift evolution puts strong constraints on these models. Observational studies on the black hole-galaxy relations naturally suffer from selection effects. These can potentially bias the conclusions inferred from the observations, if they are not taken into account. I investigated the issue of selection effects on type 1 AGN samples in detail and discuss various sources of bias, e.g. an AGN luminosity bias, an active fraction bias and an AGN evolution bias. If the selection function of the observational sample and the underlying distribution functions are known, it is possible to correct for this bias. I present a fitting method to obtain an unbiased estimate of the intrinsic black hole-galaxy relations from samples that are affected by selection effects. Third, I try to improve our census of dormant black holes and the determination of their masses. One of the most important techniques to determine the black hole mass in quiescent galaxies is via stellar dynamical modeling. This method employs photometric and kinematic observations of the galaxy and infers the gravitational potential from the stellar orbits. This method can reveal the presence of the black hole and give its mass, if the sphere of the black hole's gravitational influence is spatially resolved. However, usually the presence of a dark matter halo is ignored in the dynamical modeling, potentially causing a bias on the determined black hole mass. I ran dynamical models for a sample of 12 galaxies, including a dark matter halo. For galaxies for which the black hole's sphere of influence is not well resolved, I found that the black hole mass is systematically underestimated when the dark matter halo is ignored, while there is almost no effect for galaxies with well resolved sphere of influence.
Does it have to be trees? : Data-driven dependency parsing with incomplete and noisy training data
(2011)
We present a novel approach to training data-driven dependency parsers on incomplete annotations. Our parsers are simple modifications of two well-known dependency parsers, the transition-based Malt parser and the graph-based MST parser. While previous work on parsing with incomplete data has typically couched the task in frameworks of unsupervised or semi-supervised machine learning, we essentially treat it as a supervised problem. In particular, we propose what we call agnostic parsers which hide all fragmentation in the training data from their supervised components. We present experimental results with training data that was obtained by means of annotation projection. Annotation projection is a resource-lean technique which allows us to transfer annotations from one language to another within a parallel corpus. However, the output tends to be noisy and incomplete due to cross-lingual non-parallelism and error-prone word alignments. This makes the projected annotations a suitable test bed for our fragment parsers. Our results show that (i) dependency parsers trained on large amounts of projected annotations achieve higher accuracy than the direct projections, and that (ii) our agnostic fragment parsers perform roughly on a par with the original parsers which are trained only on strictly filtered, complete trees. Finally, (iii) when our fragment parsers are trained on artificially fragmented but otherwise gold standard dependencies, the performance loss is moderate even with up to 50% of all edges removed.
Dryland vulnerability : typical patterns and dynamics in support of vulnerability reduction efforts
(2011)
The pronounced constraints on ecosystem functioning and human livelihoods in drylands are frequently exacerbated by natural and socio-economic stresses, including weather extremes and inequitable trade conditions. Therefore, a better understanding of the relation between these stresses and the socio-ecological systems is important for advancing dryland development. The concept of vulnerability as applied in this dissertation describes this relation as encompassing the exposure to climate, market and other stresses as well as the sensitivity of the systems to these stresses and their capacity to adapt. With regard to the interest in improving environmental and living conditions in drylands, this dissertation aims at a meaningful generalisation of heterogeneous vulnerability situations. A pattern recognition approach based on clustering revealed typical vulnerability-creating mechanisms at global and local scales. One study presents the first analysis of dryland vulnerability with global coverage at a sub-national resolution. The cluster analysis resulted in seven typical patterns of vulnerability according to quantitative indication of poverty, water stress, soil degradation, natural agro-constraints and isolation. Independent case studies served to validate the identified patterns and to prove the transferability of vulnerability-reducing approaches. Due to their worldwide coverage, the global results allow the evaluation of a specific system’s vulnerability in its wider context, even in poorly-documented areas. Moreover, climate vulnerability of smallholders was investigated with regard to their food security in the Peruvian Altiplano. Four typical groups of households were identified in this local dryland context using indicators for harvest failure risk, agricultural resources, education and non-agricultural income. An elaborate validation relying on independently acquired information demonstrated the clear correlation between weather-related damages and the identified clusters. It also showed that household-specific causes of vulnerability were consistent with the mechanisms implied by the corresponding patterns. The synthesis of the local study provides valuable insights into the tailoring of interventions that reflect the heterogeneity within the social group of smallholders. The conditions necessary to identify typical vulnerability patterns were summarised in five methodological steps. They aim to motivate and to facilitate the application of the selected pattern recognition approach in future vulnerability analyses. The five steps outline the elicitation of relevant cause-effect hypotheses and the quantitative indication of mechanisms as well as an evaluation of robustness, a validation and a ranking of the identified patterns. The precise definition of the hypotheses is essential to appropriately quantify the basic processes as well as to consistently interpret, validate and rank the clusters. In particular, the five steps reflect scale-dependent opportunities, such as the outcome-oriented aspect of validation in the local study. Furthermore, the clusters identified in Northeast Brazil were assessed in the light of important endogenous processes in the smallholder systems which dominate this region. In order to capture these processes, a qualitative dynamic model was developed using generalised rules of labour allocation, yield extraction, budget constitution and the dynamics of natural and technological resources. The model resulted in a cyclic trajectory encompassing four states with differing degree of criticality. The joint assessment revealed aggravating conditions in major parts of the study region due to the overuse of natural resources and the potential for impoverishment. The changes in vulnerability-creating mechanisms identified in Northeast Brazil are well-suited to informing local adjustments to large-scale intervention programmes, such as “Avança Brasil”. Overall, the categorisation of a limited number of typical patterns and dynamics presents an efficient approach to improving our understanding of dryland vulnerability. Appropriate decision-making for sustainable dryland development through vulnerability reduction can be significantly enhanced by pattern-specific entry points combined with insights into changing hotspots of vulnerability and the transferability of successful adaptation strategies.
Motivation | Societal and economic needs of East Africa rely entirely on the availability of water, which is governed by the regular onset and retreat of the rainy seasons. Fluctuations in the amounts of rainfall has tremendous impact causing widespread famine, disease outbreaks and human migrations. Efforts towards high resolution forecasting of seasonal precipitation and hydrological systems are therefore needed, which requires high frequency short to long-term analyses of available climate data that I am going to present in this doctoral thesis by three different studies. 15,000 years - Suguta Valley | The main study of this thesis concentrated on the understanding of humidity changes within the last African Humid Period (AHP, 14.8-5.5 ka BP). The nature and causes of intensity variations of the West-African (WAM) and Indian Summer monsoons (ISM) during the AHP, especially their exact influence on regional climate relative to each other, is currently intensely debated. Here, I present a high-resolution multiproxy lake-level record spanning the AHP from the remote Suguta Valley in the northern Kenya Rift, located between the WAM and ISM domains. The presently desiccated valley was during the AHP filled by a 300 m deep and 2200 km2 large palaeo-lake due to an increase in precipitation of only 26%. The record explains the synchronous onset of large lakes in the East African Rift System (EARS) with the longitudinal shift of the Congo Air Boundary (CAB) over the East African and Ethiopian Plateaus, as the direct consequence of an enhanced atmospheric pressure gradient between East-Africa and India due to a precessional-forced northern hemisphere insolation maximum. Pronounced, and abrupt lake level fluctuations during the generally wet AHP are explained by small-scale solar irradiation changes weakening this pressure gradient atmospheric moisture availability preventing the CAB from reaching the study area. Instead, the termination of the AHP occurred, in a non-linear manner due to a change towards an equatorial insolation maximum ca. 6.5 ka ago extending the AHP over Ethiopia and West-Africa. 200 years - Lake Naivasha | The second part of the thesis focused on the analysis of a 200 year-old sediment core from Lake Naivasha in the Central Kenya Rift, one of the very few present freshwater lakes in East Africa. The results revealed and confirmed, that the appliance of proxy records for palaeo-climate reconstruction for the last 100 years within a time of increasing industrialisation and therefore human impact to the proxy-record containing sites are broadly limited. Since the middle of the 20th century, intense anthropogenic activity around Lake Naivasha has led to cultural eutrophication, which has overprinted the influence of natural climate variation to the lake usually inferred from proxy records such as diatoms, transfer-functions, geochemical and sedimentological analysis as used in this study. The results clarify the need for proxy records from remote unsettled areas to contribute with pristine data sets to current debates about anthropologic induced global warming since the past 100 years. 14 years - East African Rift | In order to avoid human influenced data sets and validate spatial and temporal heterogeneities of proxy-records from East Africa, the third part of the thesis therefore concentrated on the most recent past 14 years (1996-2010) detecting climate variability by using remotely sensed rainfall data. The advancement in the spatial coverage and temporal resolutions of rainfall data allow a better understanding of influencing climate mechanisms and help to better interpret proxy-records from the EARS in order to reconstruct past climate conditions. The study focuses on the dynamics of intraseasonal rainfall distribution within catchments of eleven lake basins in the EARS that are often used for palaeo-climate studies. We discovered that rainfall in adjacent basins exhibits high complexities in the magnitudes of intraseasonal variability, biennial to triennial precipitation patterns and even are not necessarily correlated often showing opposite trends. The variability among the watersheds is driven by the complex interaction of topography, in particular the shape, length and elevation of the catchment and its relative location to the East African Rift System and predominant influence of the ITCZ or CAB, whose locations and intensities are dependent on the strength of low pressure cells over India, SST variations in the Atlantic, Pacific or Indian Ocean, QBO phases and the 11-year solar cycle. Among all seasons we observed, January-September is the season of highest and most complex rainfall variability, especially for the East African Plateau basins, most likely due to the irregular penetration and sensitivity of the CAB.
The impact of global warming on human water resources is attracting increasing attention. No other region in this world is so strongly affected by changes in water supply than the tropics. Especially in Africa, the availability and access to water is more crucial to existence (basic livelihoods and economic growth) than anywhere else on Earth. In East Africa, rainfall is mainly influenced by the migration of the Inter-Tropical Convergence Zone (ITCZ) and by the El Niño Southern Oscillation (ENSO) with more rain and floods during El Niño and severe droughts during La Niña. The forecasting of East African rainfall in a warming world requires a better understanding of the response of ENSO-driven variability to mean climate. Unfortunately, existing meteorological data sets are too short or incomplete to establish a precise evaluation of future climate. From Lake Challa near Mount Kilimanjaro, we report records from a laminated lake sediment core spanning the last 25,000 years. Analyzing a monthly cleared sediment trap confirms the annual origin of the laminations and demonstrates that the varve-thicknesses are strongly linked to the duration and strength of the windy season. Given the modern control of seasonal ITCZ location on wind and rain in this region and the inverse relation between the two, thicker varves represent windier and thus drier years. El Niño (La Niña) events are associated with wetter (drier) conditions in east Africa and decreased (increased) surface wind speeds. Based on this fact, the thickness of the varves can be used as a tool to reconstruct a) annual rainfall b) wind season strength, and c) ENSO variability. Within this thesis, I found evidence for centennialscale changes in ENSO-related rainfall variability during the last three millennia, abrupt changes in variability during the Medieval Climate Anomaly and the Little Ice Age, and an overall reduction in East African rainfall and its variability during the Last Glacial period. Climate model simulations support forward extrapolation from these lake-sediment data, indicating that a future Indian Ocean warming will enhance East Africa’s hydrological cycle and its interannual variability in rainfall. Furthermore, I compared geochemical analyses from the sediment trap samples with a broad range of limnological, meteorological, and geological parameters to characterize the impact of sedimentation processes from the in-situ rocks to the deposited sediments. As a result an excellent calibration for existing μXRF data from Lake Challa over the entire 25,000 year long profile was provided. The climate development during the last 25,000 years as reconstructed from the Lake Challa sediments is in good agreement with other studies and highlights the complex interactions between long-term orbital forcing, atmosphere, ocean and land surface conditions. My findings help to understand how abrupt climate changes occur and how these changes correlate with climate changes elsewhere on Earth.
Salty taste has evolved to maintain electrolyte homeostasis, serving as a detector for salt containing food. In rodents, salty taste involves at least two transduction mechanisms. One is sensitive to the drug amiloride and specific for Na+, involving epithelial sodium channel (ENaC). A second rodent transduction pathway, which is triggered by various cations, is amiloride insensitive and not almost understood to date. Studies in primates showed amiloride-sensitive as well as amiloride-insensitive gustatory responses to NaCl, implying a role of both salt taste transduction pathways in humans. However, sensory studies in humans point to largely amiloride-insensitive sodium taste perception. An involvement of ENaC in human sodium taste perception was not shown, so far. In this study, ENaC subunit protein and mRNA could be localized to human taste bud cells (TBC). Thus, basolateral αβγ-ENaC ion channels are likely in TBC of circumvallate papillae, possibly mediating basolateral sodium entry. Similarly, basolateral βγ-ENaC might play a role in fungiform TBC. Strikingly, δ-ENaC subunit was confined to taste bud pores of both papillae, likely mediating gustatory sodium entry in TBC, either apical or paracellular via tight junctions. However, regional separation of δ-ENaC and βγ-ENaC in fungiform and circumvallate TBC indicate the presence of unknown interaction partner necessary to assemble into functional ion channels. However, screening of a macaque taste tissue cDNA library did neither reveal polypeptides assembling into a functional cation channel by interaction with δ-ENaC or βγ-ENaC nor ENaC independent salt taste receptor candidates. Thus, ENaC subunits are likely involved in human taste transduction, while exact composition and identity of an amiloride (in)sensitive salt taste receptors remain unclear. Localization of δ-ENaC in human taste pores strongly suggests a role in human taste transduction. In contrast, δ-ENaC is classified as pseudogene Scnn1d in mouse. However, no experimental detected sequences are annotated, while evidences for parts of Scnn1d derived mRNAs exist. In order to elucidate if Scnn1d is possibly involved in rodent salt taste perception, Scnn1d was evaluated in this study to clarify if Scnn1d is a gene or a transcribed pseudogene in mice. Comparative mapping of human SCNN1D to mouse chromosome 4 revealed complete Scnn1d sequence as well as its pseudogenization by Mus specific endogenous retroviruses. Moreover, tissue specific transcription of unitary Scnn1d pseudogene was found in mouse vallate papillae, kidney and testis and led to identification of nine Scnn1d transcripts. In vitro translation experiments showed that Scnn1d transcripts are coding competent for short polypeptides, possibly present in vivo. However, no sodium channel like function or sodium channel modulating activity was evident for Scnn1d transcripts and/or derived polypeptides. Thus, an involvement of mouse δ-ENaC in sodium taste transduction is unlikely and points to species specific differences in salt taste transduction mechanisms.
Public debate about energy relations between the EU and Russia is distorted. These distortions present considerable obstacles to the development of true partnership. At the core of the conflict is a struggle for resource rents between energy producing, energy consuming and transit countries. Supposed secondary aspects, however, are also of great importance. They comprise of geopolitics, market access, economic development and state sovereignty. The European Union, having engaged in energy market liberalisation, faces a widening gap between declining domestic resources and continuously growing energy demand. Diverse interests inside the EU prevent the definition of a coherent and respected energy policy. Russia, for its part, is no longer willing to subsidise its neighbouring economies by cheap energy exports. The Russian government engages in assertive policies pursuing Russian interests. In so far, it opts for a different globalisation approach, refusing the role of mere energy exporter. In view of the intensifying struggle for global resources, Russia, with its large energy potential, appears to be a very favourable option for European energy supplies, if not the best one. However, several outcomes of the strategic game between the two partners can be imagined. Engaging in non-cooperative strategies will in the end leave all stakeholders worse-off. The European Union should therefore concentrate on securing its partnership with Russia instead of damaging it. Stable cooperation would need the acceptance that the partner may pursue his own goals, which might be different from one’s own interests. The question is, how can a sustainable compromise be found? This thesis finds that a mix of continued dialogue, a tit for tat approach bolstered by an international institutional framework and increased integration efforts appears as a preferable solution.
Mathematical modeling of biological phenomena has experienced increasing interest since new high-throughput technologies give access to growing amounts of molecular data. These modeling approaches are especially able to test hypotheses which are not yet experimentally accessible or guide an experimental setup. One particular attempt investigates the evolutionary dynamics responsible for today's composition of organisms. Computer simulations either propose an evolutionary mechanism and thus reproduce a recent finding or rebuild an evolutionary process in order to learn about its mechanism. The quest for evolutionary fingerprints in metabolic and gene-coexpression networks is the central topic of this cumulative thesis based on four published articles. An understanding of the actual origin of life will probably remain an insoluble problem. However, one can argue that after a first simple metabolism has evolved, the further evolution of metabolism occurred in parallel with the evolution of the sequences of the catalyzing enzymes. Indications of such a coevolution can be found when correlating the change in sequence between two enzymes with their distance on the metabolic network which is obtained from the KEGG database. We observe that there exists a small but significant correlation primarily on nearest neighbors. This indicates that enzymes catalyzing subsequent reactions tend to be descended from the same precursor. Since this correlation is relatively small one can at least assume that, if new enzymes are no "genetic children" of the previous enzymes, they certainly be descended from any of the already existing ones. Following this hypothesis, we introduce a model of enzyme-pathway coevolution. By iteratively adding enzymes, this model explores the metabolic network in a manner similar to diffusion. With implementation of an Gillespie-like algorithm we are able to introduce a tunable parameter that controls the weight of sequence similarity when choosing a new enzyme. Furthermore, this method also defines a time difference between successive evolutionary innovations in terms of a new enzyme. Overall, these simulations generate putative time-courses of the evolutionary walk on the metabolic network. By a time-series analysis, we find that the acquisition of new enzymes appears in bursts which are pronounced when the influence of the sequence similarity is higher. This behavior strongly resembles punctuated equilibrium which denotes the observation that new species tend to appear in bursts as well rather than in a gradual manner. Thus, our model helps to establish a better understanding of punctuated equilibrium giving a potential description at molecular level. From the time-courses we also extract a tentative order of new enzymes, metabolites, and even organisms. The consistence of this order with previous findings provides evidence for the validity of our approach. While the sequence of a gene is actually subject to mutations, its expression profile might also indirectly change through the evolutionary events in the cellular interplay. Gene coexpression data is simply accessible by microarray experiments and commonly illustrated using coexpression networks where genes are nodes and get linked once they show a significant coexpression. Since the large number of genes makes an illustration of the entire coexpression network difficult, clustering helps to show the network on a metalevel. Various clustering techniques already exist. However, we introduce a novel one which maintains control of the cluster sizes and thus assures proper visual inspection. An application of the method on Arabidopsis thaliana reveals that genes causing a severe phenotype often show a functional uniqueness in their network vicinity. This leads to 20 genes of so far unknown phenotype which are however suggested to be essential for plant growth. Of these, six indeed provoke such a severe phenotype, shown by mutant analysis. By an inspection of the degree distribution of the A.thaliana coexpression network, we identified two characteristics. The distribution deviates from the frequently observed power-law by a sharp truncation which follows after an over-representation of highly connected nodes. For a better understanding, we developed an evolutionary model which mimics the growth of a coexpression network by gene duplication which underlies a strong selection criterion, and slight mutational changes in the expression profile. Despite the simplicity of our assumption, we can reproduce the observed properties in A.thaliana as well as in E.coli and S.cerevisiae. The over-representation of high-degree nodes could be identified with mutually well connected genes of similar functional families: zinc fingers (PF00096), flagella, and ribosomes respectively. In conclusion, these four manuscripts demonstrate the usefulness of mathematical models and statistical tools as a source of new biological insight. While the clustering approach of gene coexpression data leads to the phenotypic characterization of so far unknown genes and thus supports genome annotation, our model approaches offer explanations for observed properties of the coexpression network and furthermore substantiate punctuated equilibrium as an evolutionary process by a deeper understanding of an underlying molecular mechanism.
In this thesis chemical reactions under hydrothermal conditions were explored, whereby emphasis was put on green chemistry. Water at high temperature and pressure acts as a benign solvent. Motivation to work under hydrothermal conditions was well-founded in the tunability of physicochemical properties with temperature, e.g. of dielectric constant, density or ion product, which often resulted in surprising reactivity. Another cornerstone was the implementation of the principles of green chemistry. Besides the use of water as solvent, this included the employment of a sustainable feedstock and the sensible use of resources by minimizing waste and harmful intermediates and additives. To evaluate the feasibility of hydrothermal conditions for chemical synthesis, exemplary reactions were performed. These were carried out in a continuous flow reactor, allowing for precise control of reaction conditions and kinetics measurements. In most experiments a temperature of 200 °C in combination with a pressure of 100 bar was chosen. In some cases the temperature was even raised to 300 °C. Water in this subcritical range can also be found in nature at hydrothermal vents on the ocean floor. On the primitive earth, environments with such conditions were however present in larger numbers. Therefore we tested whether biologically important carbohydrates could be formed at high temperature from the simple, probably prebiotic precursor formaldehyde. Indeed, this formose reaction could be carried out successfully, although the yield was lower compared to the counterpart reaction under ambient conditions. However, striking differences regarding selectivity and necessary catalysts were observed. At moderate temperatures bases and catalytically active cations like Ca2+ are necessary and the main products are hexoses and pentoses, which accumulate due to their higher stability. In contrast, in high-temperature water no catalyst was necessary but a slightly alkaline solution was sufficient. Hexoses were only formed in negligible amounts, whereas pentoses and the shorter carbohydrates accounted for the major fraction. Amongst the pentoses there was some preference for the formation of ribose. Even deoxy sugars could be detected in traces. The observation that catalysts can be avoided was successfully transferred to another reaction. In a green chemistry approach platform chemicals must be produced from sustainable resources. Carbohydrates can for instance be employed as a basis. They can be transformed to levulinic acid and formic acid, which can both react via a transfer hydrogenation to the green solvent and biofuel gamma-valerolactone. This second reaction usually requires catalysis by Ru or Pd, which are neither sustainable nor low-priced. Under hydrothermal conditions these heavy metals could be avoided and replaced by cheap salts, taking advantage of the temperature dependence of the acid dissociation constant. Simple sulfate was recognized as a temperature switchable base. With this additive high yield could be achieved by simultaneous prevention of waste. In contrast to conventional bases, which create salt upon neutralization, a temperature switchable base becomes neutral again when cooled down and thus can be reused. This adds another sustainable feature to the high atom economy of the presented hydrothermal synthesis. In a last study complex decomposition pathways of biomass were investigated. Gas chromatography in conjunction with mass spectroscopy has proven to be a powerful tool for the identification of unknowns. It was observed that several acids were formed when carbohydrates were treated with bases at high temperature. This procedure was also applied to digest wood. Afterwards it was possible to fermentate the solution and a good yield of methane was obtained. This has to be regarded in the light of the fact that wood practically cannot be used as a feedstock in a biogas factory. Thus the hydrothermal pretreatment is an efficient means to employ such materials as well. Also the reaction network of the hydrothermal decomposition of glycine was investigated using isotope-labeled compounds as comparison for the unambiguous identification of unknowns. This refined analysis allowed the identification of several new molecules and pathways, not yet described in literature. In summary several advantages could be taken from synthesis in high-temperature water. Many catalysts, absolutely necessary under ambient conditions, could either be completely avoided or replaced by cheap, sustainable alternatives. In this respect water is not only a green solvent, but helps to prevent waste and preserves resources.
Regulation of gene transcription plays a major role in mediating cellular responses and physiological behavior in all known organisms. The finding that similar genes are often regulated in a similar manner (co-regulated or "co-expressed") has directed several "guilt-by-association" approaches in order to reverse-engineer the cellular transcriptional networks using gene expression data as a compass. This kind of studies has been considerably assisted in the recent years by the development of high-throughput transcript measurement platforms, specifically gene microarrays and next-generation sequencing. In this thesis, I describe several approaches for improving the extraction and interpretation of the information contained in microarray based gene expression data, through four steps: (1) microarray platform design, (2) microarray data normalization, (3) gene network reverse engineering based on expression data and (4) experimental validation of expression-based guilt-by-association inferences. In the first part test case is shown aimed at the generation of a microarray for Thellungiella salsuginea, a salt and drought resistant close relative to the model plant Arabidopsis thaliana; the transcripts of this organism are generated on the combination of publicly available ESTs and newly generated ad-hoc next-generation sequencing data. Since the design of a microarray platform requires the availability of highly reliable and non-redundant transcript models, these issues are addressed consecutively, proposing several different technical solutions. In the second part I describe how inter-array correlation artifacts are generated by the common microarray normalization methods RMA and GCRMA, together with the technical and mathematical characteristics underlying the problem. A solution is proposed in the form of a novel normalization method, called tRMA. The third part of the thesis deals with the field of expression-based gene network reverse engineering. It is shown how different centrality measures in reverse engineered gene networks can be used to distinguish specific classes of genes, in particular essential genes in Arabidopsis thaliana, and how the use of conditional correlation can add a layer of understanding over the information flow processes underlying transcript regulation. Furthermore, several network reverse engineering approaches are compared, with a particular focus on the LASSO, a linear regression derivative rarely applied before in global gene network reconstruction, despite its theoretical advantages in robustness and interpretability over more standard methods. The performance of LASSO is assessed through several in silico analyses dealing with the reliability of the inferred gene networks. In the final part, LASSO and other reverse engineering methods are used to experimentally identify novel genes involved in two independent scenarios: the seed coat mucilage pathway in Arabidopsis thaliana and the hypoxic tuber development in Solanum tuberosum. In both cases an interesting method complementarity is shown, which strongly suggests a general use of hybrid approaches for transcript expression-based inferences. In conclusion, this work has helped to improve our understanding of gene transcription regulation through a better interpretation of high-throughput expression data. Part of the network reverse engineering methods described in this thesis have been included in a tool (CorTo) for gene network reverse engineering and annotated visualization from custom transcription datasets.
During reading oculomotor processes guide the eyes over the text. The visual information recorded is accessed, evaluated and processed. Only by retrieving the meaning of a word from the long-term memory, as well as through the connection and storage of the information about each individual word, is it possible to access the semantic meaning of a sentence. Therefore memory, and here in particular working memory, plays a pivotal role in the basic processes of reading. The following dissertation investigates to what extent different demands on memory and memory capacity have an effect on eye movement behavior while reading. The frequently used paradigm of the reading span task, in which test subjects read and evaluate individual sentences, was used for the experimental review of the research questions. The results speak for the fact that working memory processes have a direct effect on various eye movement measurements. Thus a high working memory load, for example, reduced the perceptual span while reading. The lower the individual working memory capacity of the reader was, the stronger was the influence of the working memory load on the processing of the sentence.
This work addresses issues in the automatic preprocessing of historical German input text for use by conventional natural language processing techniques. Conventional techniques cannot adequately account for historical input text due to conventional tools' reliance on a fixed application-specific lexicon keyed by contemporary orthographic surface form on the one hand, and the lack of consistent orthographic conventions in historical input text on the other. Historical spelling variation is treated here as an error-correction problem or "canonicalization" task: an attempt to automatically assign each (historical) input word a unique extant canonical cognate, thus allowing direct application-specific processing (tagging, parsing, etc.) of the returned canonical forms without need for any additional application-specific modifications. In the course of the work, various methods for automatic canonicalization are investigated and empirically evaluated, including conflation by phonetic identity, conflation by lemma instantiation heuristics, canonicalization by weighted finite-state rewrite cascade, and token-wise disambiguation by a dynamic Hidden Markov Model.
Human-induced alterations of the environment are causing biotic changes worldwide, including the extinction of species and a mixing of once disparate floras and faunas. One type of biological communities that is expected to be particularly affected by environmental alterations are herb layer plant communities of fragmented forests such as those in the west European lowlands. However, our knowledge about current changes in species diversity and composition in these communities is limited due to a lack of adequate long-term studies. In this thesis, I resurveyed the herb layer communities of ancient forest patches in the Weser-Elbe region (NW Germany) after two decades using 175 semi-permanent plots. The general objectives were (i) to quantify changes in plant species diversity considering also between-community (β) and functional diversity, (ii) to determine shifts in species composition in terms of species’ niche breadth and functional traits and (iii) to find indications on the most likely environmental drivers for the observed changes. These objectives were pursued with four independent research papers (Chapters 1-4) whose results were brought together in a General Discussion. Alpha diversity (species richness) increased by almost four species on average, whereas β diversity tended to decrease (Chapter 1). The latter is interpreted as a beginning floristic homogenization. The observed changes were primarily the result of a spread of native habitat generalists that are able to tolerate broad pH and moisture ranges. The changes in α and β diversity were only significant when species abundances were neglected (Chapters 1 and 2), demonstrating that the diversity changes resulted mainly from gains and losses of low-abundance species. This study is one of the first studies in temperate Europe that demonstrates floristic homogenization of forest plant communities at a larger than local scale. The diversity changes found at the taxonomic level did not result in similar changes at the functional level (Chapter 2). The likely reason is that these communities are functionally “buffered”. Single communities involve most of the functional diversity of the regional pool, i.e., they are already functionally rich, while they are functionally redundant among each other, i.e., they are already homogeneous. Independent of taxonomic homogenization, the abundance of 30 species decreased significantly (Chapter 4). These species included 12 ancient forest species (i.e., species closely tied to forest patches with a habitat continuity > 200 years) and seven species listed on the Red List of endangered plant species in NW Germany. If these decreases continue over the next decades, local extinctions may result. This biotic impoverishment would seriously conflict with regional conservation goals. Community assembly mechanisms changed at the local level particularly at sites that experienced disturbance by forest management activities between the sampling periods (Chapter 3). Disturbance altered community assembly mechanisms in two ways: (i) it relaxed environmental filters and allowed the coexistence of different reproduction strategies, as reflected by a higher diversity of reproductive traits at the time of the resurvey, and (ii) it enhanced light availability and tightened competitive filters. These limited the functional diversity with respect to canopy height and selected for taller species. Thirty-one winner and 30 loser species, which had significantly increased or decreased in abundance, respectively, were characterized by various functional traits and ecological performances to find indications on the most likely environmental drivers for the observed floristic changes (Chapter 4). Winner species had higher seed longevity, flowered later in the season and had more often an oceanic distribution compared to loser species. Loser species tended to have a higher specific leaf area, to be more susceptible to deer browsing and to have a performance optimum at higher soil pH values compared to winner species. Multiple logistic regression analyses indicated that disturbances due to forest management interventions were the primary cause of the species shifts. As one of the first European resurvey studies, this study provides indications that an enhanced browsing pressure due to increased deer densities and increasingly warmer winters are important drivers. The study failed to demonstrate that eutrophication and acidification due to atmospheric deposition substantially drive herb layer changes. The restriction of the sample to the most base-rich sites in the region is discussed as a likely reason. Furthermore, the decline of several ancient forest species is discussed as an indication that the forest patches are still paying off their “extinction debt”, i.e., exhibit a delayed response to forest fragmentation.
Aggregation of the Amyloid β (Aβ) peptide to amyloid fibrils is associated with the outbreak of Alzheimer’s disease. Early aggregation intermediates in form of soluble oligomers are of special interest as they are believed to be the major toxic components in the process. These oligomers are of disordered and transient nature. Therefore, their detailed molecular structure is difficult to access experimentally and often remains unknown. In the present work extensive, fully atomistic replica exchange molecular dynamics simulations were performed to study the preaggregated, monomer states and early aggregation intermediates (dimers, trimers) of Aβ(25-35) and Aβ(10-35)-NH2 in aqueous solution. The folding and aggregation of Aβ(25-35) were studied at neutral pH and 293 K. Aβ(25-35) monomers mainly adopt β-hairpin conformations characterized by a β-turn formed by residues G29 and A30, and a β-sheet between residues N27–K28 and I31–I32 in equilibrium with coiled conformations. The β-hairpin conformations served as initial configurations to model spontaneous aggregation of Aβ(25-35). As expected, within the Aβ(25-35) dimer and trimer ensembles many different poorly populated conformations appear. Nevertheless, we were able to distinguish between disordered and fibril-like oligomers. Whereas disordered oligomers are rather compact with few intermolecular hydrogen bonds (HBs), fibril-like oligomers are characterized by the formation of large intermolecular β-sheets. In most of the fibril-like dimers and trimers individual peptides are fully extended forming in- or out-of-register antiparallel β-sheets. A small amount of fibril-like trimers contained V-shaped peptides forming parallel β-sheets. The dimensions of extended and V-shaped oligomers correspond well to the diameters of two distinct morphologies found for Aβ(25-35) fibrils. The transition from disordered to fibril-like Aβ(25-35) dimers is unfavorable but driven by energy. The lower energy of fibril-like dimers arises from favorable intermolecular HBs and other electrostatic interactions which compete with a loss in entropy. Approximately 25 % of the entropic cost correspond to configurational entropy. The rest relates to solvent entropy, presumably caused by hydrophobic and electrostatic effects. In contrast to the transition towards fibril-like dimers the first step of aggregation is driven by entropy. Here, we compared structural and thermodynamic properties of the individual monomer, dimer and trimer ensembles to gain qualitative information about the aggregation process. The β-hairpin conformation observed for monomers is successively dissolved in dimer and trimer ensembles while instead intermolecular β-sheets are formed. As expected upon aggregation the configurational entropy decreases. Additionally, the solvent accessible surface area (SASA), especially the hydrophobic SASA, decreases yielding a favorable solvation free energy which overcompensates the loss in configurational entropy. In summary, the hydrophobic effect, possibly combined with electrostatic effects, yields an increase in solvent entropy which is believed to be one major driving force towards aggregation. Spontaneous folding of the Aβ(10-35)-NH2 monomer was modeled using two force fields, GROMOS96 43a1 and OPLS/AA, and compared to primary NMR data collected at pH 5.6 and 283 K taken from the literature. Unexpectedly, the two force fields yielded significantly different main conformations. Comparison between experimental and calculated nuclear Overhauser effect (NOE) distances is not sufficient to distinguish between the different force fields. Additionally, the comparison with scalar coupling constants suggest that the chosen protonation in both simulations corresponds to a pH lower than in the experiment. Based on this analysis we were unable to determine which force field yields a better description of this system. Dimerization of Aβ(10-35)-NH2 was studied at neutral pH and 300 K. Dimer conformations arrange in many distinct, poorly populated and rather complex alignments or interlocking patterns which are rather stabilized by side chain interactions than by specific intermolecular hydrogen bonds. Similar to Aβ(25-35) dimers, transition towards β-sheet-rich, fibril-like Aβ(10-35) dimers is driven by energy competing with a loss in entropy. Here, transition is mediated by favorable peptide-solvent and solvent-solvent interactions mainly arising from electrostatic interactions.