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Proteins are molecules that are essential for life and carry out an enormous number of functions in organisms. To this end, they change their conformation and bind to other molecules. However, the interplay between conformational change and binding is not fully understood. In this work, this interplay is investigated with molecular dynamics (MD) simulations of the protein-peptide system Mdm2-PMI and by analysis of data from relaxation experiments.
The central task it to uncover the binding mechanism, which is described by the sequence of (partial) binding events and conformational change events including their probabilities. In the simplest case, the binding mechanism is described by a two-step model: binding followed by conformational change or conformational change followed by binding. In the general case, longer sequences with multiple conformational changes and partial binding events are possible as well as parallel pathways that differ in their sequences of events. The theory of Markov state models (MSMs) provides the theoretical framework in which all these cases can be modeled. For this purpose, MSMs are estimated in this work from MD data, and rate equation models, which are related to MSMs, are inferred from experimental relaxation data.
The MD simulation and Markov modeling of the PMI-Mdm2 system shows that PMI and Mdm2 can bind via multiple pathways. A main result of this work is a dissociation rate on the order of one event per second, which was calculated using Markov modeling and is in agreement with experiment. So far, dissociation rates and transition rates of this magnitude have only been calculated with methods that speed up transitions by acting with time-dependent, external forces on the binding partners. The simulation technique developed in this work, in contrast, allows the estimation of dissociation rates from the combination of free energy calculation and direct MD simulation of the fast binding process. Two new statistical estimators TRAM and TRAMMBAR are developed to estimate a MSM from the joint data of both simulation types.
In addition, a new analysis technique for time-series data from chemical relaxation experiments is developed in this work. It allows to identify one of the above-mentioned two-step mechanisms as the mechanism that underlays the data. The new method is valid for a broader range of concentrations than previous methods and therefore allows to choose the concentrations such that the mechanism can be uniquely identified. It is successfully tested with data for the binding of recoverin to a rhodopsin kinase peptide.
Start-up incentives targeted at unemployed individuals have become an important tool of the Active Labor Market Policy (ALMP) to fight unemployment in many countries in recent years. In contrast to traditional ALMP instruments like training measures, wage subsidies, or job creation schemes, which are aimed at reintegrating unemployed individuals into dependent employment, start-up incentives are a fundamentally different approach to ALMP, in that they intend to encourage and help unemployed individuals to exit unemployment by entering self-employment and, thus, by creating their own jobs. In this sense, start-up incentives for unemployed individuals serve not only as employment and social policy to activate job seekers and combat unemployment but also as business policy to promote entrepreneurship. The corresponding empirical literature on this topic so far has been mainly focused on the individual labor market perspective, however. The main part of the thesis at hand examines the new start-up subsidy (“Gründungszuschuss”) in Germany and consists of four empirical analyses that extend the existing evidence on start-up incentives for unemployed individuals from multiple perspectives and in the following directions:
First, it provides the first impact evaluation of the new start-up subsidy in Germany. The results indicate that participation in the new start-up subsidy has significant positive and persistent effects on both reintegration into the labor market as well as the income profiles of participants, in line with previous evidence on comparable German and international programs, which emphasizes the general potential of start-up incentives as part of the broader ALMP toolset. Furthermore, a new innovative sensitivity analysis of the applied propensity score matching approach integrates findings from entrepreneurship and labor market research about the key role of an individual’s personality on start-up decision, business performance, as well as general labor market outcomes, into the impact evaluation of start-up incentives. The sensitivity analysis with regard to the inclusion and exclusion of usually unobserved personality variables reveals that differences in the estimated treatment effects are small in magnitude and mostly insignificant. Consequently, concerns about potential overestimation of treatment effects in previous evaluation studies of similar start-up incentives due to usually unobservable personality variables are less justified, as long as the set of observed control variables is sufficiently informative (Chapter 2).
Second, the thesis expands our knowledge about the longer-term business performance and potential of subsidized businesses arising from the start-up subsidy program. In absolute terms, the analysis shows that a relatively high share of subsidized founders successfully survives in the market with their original businesses in the medium to long run. The subsidy also yields a “double dividend” to a certain extent in terms of additional job creation. Compared to “regular”, i.e., non-subsidized new businesses founded by non-unemployed individuals in the same quarter, however, the economic and growth-related impulses set by participants of the subsidy program are only limited with regard to employment growth, innovation activity, or investment. Further investigations of possible reasons for these differences show that differential business growth paths of subsidized founders in the longer run seem to be mainly limited by higher restrictions to access capital and by unobserved factors, such as less growth-oriented business strategies and intentions, as well as lower (subjective) entrepreneurial persistence. Taken together, the program has only limited potential as a business and entrepreneurship policy intended to induce innovation and economic growth (Chapters 3 and 4).
And third, an empirical analysis on the level of German regional labor markets yields that there is a high regional variation in subsidized start-up activity relative to overall new business formation. The positive correlation between regular start-up intensity and the share among all unemployed individuals who participate in the start-up subsidy program suggests that (nascent) unemployed founders also profit from the beneficial effects of regional entrepreneurship capital. Moreover, the analysis of potential deadweight and displacement effects from an aggregated regional perspective emphasizes that the start-up subsidy for unemployed individuals represents a market intervention into existing markets, which affects incumbents and potentially produces inefficiencies and market distortions. This macro perspective deserves more attention and research in the future (Chapter 5).
The Cauchy problem for the linearised Einstein equation and the Goursat problem for wave equations
(2017)
In this thesis, we study two initial value problems arising in general relativity. The first is the Cauchy problem for the linearised Einstein equation on general globally hyperbolic spacetimes, with smooth and distributional initial data. We extend well-known results by showing that given a solution to the linearised constraint equations of arbitrary real Sobolev regularity, there is a globally defined solution, which is unique up to addition of gauge solutions. Two solutions are considered equivalent if they differ by a gauge solution. Our main result is that the equivalence class of solutions depends continuously on the corre- sponding equivalence class of initial data. We also solve the linearised constraint equations in certain cases and show that there exist arbitrarily irregular (non-gauge) solutions to the linearised Einstein equation on Minkowski spacetime and Kasner spacetime.
In the second part, we study the Goursat problem (the characteristic Cauchy problem) for wave equations. We specify initial data on a smooth compact Cauchy horizon, which is a lightlike hypersurface. This problem has not been studied much, since it is an initial value problem on a non-globally hyperbolic spacetime. Our main result is that given a smooth function on a non-empty, smooth, compact, totally geodesic and non-degenerate Cauchy horizon and a so called admissible linear wave equation, there exists a unique solution that is defined on the globally hyperbolic region and restricts to the given function on the Cauchy horizon. Moreover, the solution depends continuously on the initial data. A linear wave equation is called admissible if the first order part satisfies a certain condition on the Cauchy horizon, for example if it vanishes. Interestingly, both existence of solution and uniqueness are false for general wave equations, as examples show. If we drop the non-degeneracy assumption, examples show that existence of solution fails even for the simplest wave equation. The proof requires precise energy estimates for the wave equation close to the Cauchy horizon. In case the Ricci curvature vanishes on the Cauchy horizon, we show that the energy estimates are strong enough to prove local existence and uniqueness for a class of non-linear wave equations. Our results apply in particular to the Taub-NUT spacetime and the Misner spacetime. It has recently been shown that compact Cauchy horizons in spacetimes satisfying the null energy condition are necessarily smooth and totally geodesic. Our results therefore apply if the spacetime satisfies the null energy condition and the Cauchy horizon is compact and non-degenerate.
Self-adaptive data quality
(2017)
Carrying out business processes successfully is closely linked to the quality of the data inventory in an organization. Lacks in data quality lead to problems: Incorrect address data prevents (timely) shipments to customers. Erroneous orders lead to returns and thus to unnecessary effort. Wrong pricing forces companies to miss out on revenues or to impair customer satisfaction. If orders or customer records cannot be retrieved, complaint management takes longer. Due to erroneous inventories, too few or too much supplies might be reordered.
A special problem with data quality and the reason for many of the issues mentioned above are duplicates in databases. Duplicates are different representations of same real-world objects in a dataset. However, these representations differ from each other and are for that reason hard to match by a computer. Moreover, the number of required comparisons to find those duplicates grows with the square of the dataset size. To cleanse the data, these duplicates must be detected and removed. Duplicate detection is a very laborious process. To achieve satisfactory results, appropriate software must be created and configured (similarity measures, partitioning keys, thresholds, etc.). Both requires much manual effort and experience.
This thesis addresses automation of parameter selection for duplicate detection and presents several novel approaches that eliminate the need for human experience in parts of the duplicate detection process.
A pre-processing step is introduced that analyzes the datasets in question and classifies their attributes semantically. Not only do these annotations help understanding the respective datasets, but they also facilitate subsequent steps, for example, by selecting appropriate similarity measures or normalizing the data upfront. This approach works without schema information.
Following that, we show a partitioning technique that strongly reduces the number of pair comparisons for the duplicate detection process. The approach automatically finds particularly suitable partitioning keys that simultaneously allow for effective and efficient duplicate retrieval. By means of a user study, we demonstrate that this technique finds partitioning keys that outperform expert suggestions and additionally does not need manual configuration. Furthermore, this approach can be applied independently of the attribute types.
To measure the success of a duplicate detection process and to execute the described partitioning approach, a gold standard is required that provides information about the actual duplicates in a training dataset. This thesis presents a technique that uses existing duplicate detection results and crowdsourcing to create a near gold standard that can be used for the purposes above. Another part of the thesis describes and evaluates strategies how to reduce these crowdsourcing costs and to achieve a consensus with less effort.
In this work the human AOX1 was characterized and detailed aspects regarding the expression, the enzyme kinetics and the production of reactive oxygen species (ROS) were investigated. The hAOX1 is a cytosolic enzyme belonging to the molybdenum hydroxylase family. Its catalytically active form is a homodimer with a molecular weight of 300 kDa. Each monomer (150 kDa) consists of three domains: a N-terminal domain (20 kDa) containing two [2Fe-2S] clusters, a 40 kDa intermediate domain containing a flavin adenine dinucleotide (FAD), and a C-terminal domain (85 kDa) containing the substrate binding pocket and the molybdenum cofactor (Moco). The hAOX1 has an emerging role in the metabolism and pharmacokinetics of many drugs, especially aldehydes and N- heterocyclic compounds.
In this study, the hAOX1 was hetereogously expressed in E. coli TP1000 cells, using a new codon optimized gene sequence which improved the expressed protein yield of around 10-fold compared to the previous expression systems for this enzyme. To increase the catalytic activity of hAOX1, an in vitro chemical sulfuration was performed to favor the insertion of the equatorial sulfido ligand at the Moco with consequent increased enzymatic activity of around 10-fold. Steady-state kinetics and inhibition studies were performed using several substrates, electron acceptors and inhibitors. The recombinant hAOX1 showed higher catalytic activity when molecular oxygen was used as electron acceptor. The highest turn over values were obtained with phenanthridine as substrate. Inhibition studies using thioridazine (phenothiazine family), in combination with structural studies performed in the group of Prof. M.J. Romão, Nova Universidade de Lisboa, showed a new inhibition site located in proximity of the dimerization site of hAOX1. The inhibition mode of thioridazine resulted in a noncompetitive inhibition type. Further inhibition studies with loxapine, a thioridazine-related molecule, showed the same type of inhibition. Additional inhibition studies using DCPIP and raloxifene were carried out.
Extensive studies on the FAD active site of the hAOX1 were performed. Twenty new hAOX1 variants were produced and characterized. The hAOX1 variants generated in this work were divided in three groups: I) hAOX1 single nucleotide polymorphisms (SNP) variants; II) XOR- FAD loop hAOX1 variants; III) additional single point hAOX1 variants. The hAOX1 SNP variants G46E, G50D, G346R, R433P, A439E, K1231N showed clear alterations in their catalytic activity, indicating a crucial role of these residues into the FAD active site and in relation to the overall reactivity of hAOX1.
Furthermore, residues of the bovine XOR FAD flexible loop (Q423ASRREDDIAK433) were introduced in the hAOX1. FAD loop hAOX1 variants were produced and characterized for their stability and catalytic activity. Especially the variants hAOX1 N436D/A437D/L438I, N436D/A437D/L438I/I440K and Q434R/N436D/A437D/L438I/I440K showed decreased catalytic activity and stability. hAOX1 wild type and variants were tested for reactivity toward NADH but no reaction was observed.
Additionally, the hAOX1 wild type and variants were tested for the generation of reactive oxygen species (ROS). Interestingly, one of the SNP variants, hAOX1 L438V, showed a high ratio of superoxide prodction. This result showed a critical role for the residue Leu438 in the mechanism of oxygen radicals formation by hAOX1. Subsequently, further hAOX1 variants having the mutated Leu438 residue were produced. The variants hAOX1 L438A, L438F and L438K showed superoxide overproduction of around 85%, 65% and 35% of the total reducing equivalent obtained from the substrate oxidation.
The results of this work show for the first time a characterization of the FAD active site of the hAOX1, revealing the importance of specific residues involved in the generation of ROS and effecting the overall enzymatic activity of hAOX1. The hAOX1 SNP variants presented here indicate that those allelic variations in humans might cause alterations ROS balancing and clearance of drugs in humans.
In this thesis, stochastic dynamics modelling collective motions of populations, one of the most mysterious type of biological phenomena, are considered. For a system of N particle-like individuals, two kinds of asymptotic behaviours are studied : ergodicity and flocking properties, in long time, and propagation of chaos, when the number N of agents goes to infinity. Cucker and Smale, deterministic, mean-field kinetic model for a population without a hierarchical structure is the starting point of our journey : the first two chapters are dedicated to the understanding of various stochastic dynamics it inspires, with random noise added in different ways. The third chapter, an attempt to improve those results, is built upon the cluster expansion method, a technique from statistical mechanics. Exponential ergodicity is obtained for a class of non-Markovian process with non-regular drift. In the final part, the focus shifts onto a stochastic system of interacting particles derived from Keller and Segel 2-D parabolicelliptic model for chemotaxis. Existence and weak uniqueness are proven.
The timing and location of the two largest earthquakes of the 21st century (Sumatra, 2004 and Tohoku 2011, events) greatly surprised the scientific community, indicating that the deformation processes that precede and follow great megathrust earthquakes remain enigmatic. During these phases before and after the earthquake a combination of multi-scale complex processes are acting simultaneously: Stresses built up by long-term tectonic motions are modified by sudden jerky deformations during earthquakes, before being restored by multiple ensuing relaxation processes.
This thesis details a cross-scale thermomechanical model developed with the aim of simulating the entire subduction process from earthquake (1 minute) to million years’ time scale, excluding only rupture propagation. The model employs elasticity, non-linear transient viscous rheology, and rate-and-state friction. It generates spontaneous earthquake sequences, and, by using an adaptive time-step algorithm, recreates the deformation process as observed naturally over single and multiple seismic cycles. The model is thoroughly tested by comparing results to those from known high- resolution solutions of generic modeling setups widely used in modeling of rupture propagation. It is demonstrated, that while not modeling rupture propagation explicitly, the modeling procedure correctly recognizes the appearance of instability (earthquake) and correctly simulates the cumulative slip at a fault during great earthquake by means of a quasi-dynamic approximation.
A set of 2D models is used to study the effects of non-linear transient rheology on the postseismic processes following great earthquakes. Our models predict that the viscosity in the mantle wedge drops by 3 to 4 orders of magnitude during a great earthquake with magnitude above 9. This drop in viscosity results in spatial scales and timings of the relaxation processes following the earthquakes that are significantly different to previous estimates. These models replicate centuries long seismic cycles exhibited by the greatest earthquakes (like the Great Chile 1960 Earthquake) and are consistent with the major features of postseismic surface displacements recorded after the Great Tohoku Earthquake.
The 2D models are also applied to study key factors controlling maximum magnitudes of earthquakes in subduction zones. Even though methods of instrumentally observing earthquakes at subduction zones have rapidly improved in recent decades, the characteristic recurrence interval of giant earthquakes (Mw>8.5) is much larger than the currently available observational record and therefore the necessary conditions for giant earthquakes are not clear. Statistical studies have recognized the importance of the slab shape and its surface roughness, state of the strain of the upper plate and thickness of sediments filling the trenches. In this thesis we attempt to explain these observations and to identify key controlling parameters. We test a set of 2D models representing great earthquake seismic cycles at known subduction zones with various known geometries, megathrust friction coefficients, and convergence rates implemented. We found that low-angle subduction (large effect) and thick sediments in the subduction channel (smaller effect) are the fundamental necessary conditions for generating giant earthquakes, while the change of subduction velocity from 10 to 3.5 cm/yr has a lower effect. Modeling results also suggest that having thick sediments in the subduction channel causes low static friction, resulting in neutral or slightly compressive deformation in the overriding plate for low-angle subduction zones. These modeling results agree well with observations for the largest earthquakes. The model predicts the largest possible earthquakes for subduction zones of given dipping angles. The predicted maximum magnitudes exactly threshold magnitudes of all known giant earthquakes of 20th and 21st centuries.
The clear limitation of most of the models developed in the thesis is their 2D nature. Development of 3D models with comparable resolution and complexity will require significant advances in numerical techniques. Nevertheless, we conducted a series of low-resolution 3D models to study the interaction between two large asperities at a subduction interface separated by an aseismic gap of varying width. The novelty of the model is that it considers behavior of the asperities during multiple seismic cycles. As expected, models show that an aseismic gap with a narrow width could not prevent rupture propagation from one asperity to another, and that rupture always crosses the entire model. When the gap becomes too wide, asperities do not interact anymore and rupture independently. However, an interesting mode of interaction was observed in the model with an intermediate width of the aseismic gap: In this model the asperities began to stably rupture in anti-phase following multiple seismic cycles. These 3D modeling results, while insightful, must be considered preliminary because of the limitations in resolution.
The technique developed in this thesis for cross-scale modeling of seismic cycles can be used to study the effects of multiple seismic cycles on the long-term deformation of the upper plate. The technique can be also extended to the case of continental transform faults and for the advanced 3D modeling of specific subduction zones. This will require further development of numerical techniques and adaptation of the existing advanced highly scalable parallel codes like LAMEM and ASPECT.
Magnetotactic bacteria possess an intracellular structure called the magnetosome chain. Magnetosome chains contain nano−particles of iron crystals enclosed by a membrane and aligned on a cytoskeletal filament. Due to the presence of the magnetosome chains, magnetotactic bacteria are able to orient and swim along the magnetic field lines. A detailed study of structural properties of magnetosome chains in magnetotactic bacteria has primary scientific interests. It can provide more insight into the formation of the cytoskeleton in bacteria. In this thesis, we develop a new framework to study the structural properties of magnetosome chains in magnetotactic bacteria.
First, we address the bending stiffness of magnetosome chains resulting from two main contributions: the magnetic interactions of magnetosome particles and the bending stiffness of the cytoskeletal filament to which the magnetosomes are anchored. Our analysis indicates that the linear configuration of magnetosome particles without the stabilisation to the cytoskeleton may close to ring like structures, with no net magnetic moment, which thus can not perform as a compass in cellular navigation. As a result we think that one of the roles of the filament is to stabilize the linear configuration against ring closure.
We then investigate the equilibrium configurations of magnetosome particles including linear chain and closed−ring structures. We notably observe that for the formation of a stable linear structure on the cytoskeletal filament, presence of a binding energy is needed. In the presence of external stimuli the stability of the magnetosome chain is due to the internal dipole−dipole interactions, the stiffness and the binding energy of the protein structure connecting the magnetosome particles to the filament. Our observations, during and after the treatment of the magnetosome chain with the external magnetic field substantiates the stabilisation of magnetosome chains to the cytoskeletal filament by proteinous linkers and the dynamic feature of these structures.
Finally, we employ our model to study the FMR spectra of magnetosome chains in a single cell of magnetotactic bacteria. We explore the effect of magnetocrystalline anisotropy in three-fold symmetry observed in FMR spectra and the peculiarity of different spectra arisen from different mutants of these bacteria.
Detection and Kirchhoff-type migration of seismic events by use of a new characteristic function
(2017)
The classical method of seismic event localization is based on the picking of body wave arrivals, ray tracing and inversion of travel time data. Travel time picks with small uncertainties are required to produce reliable and accurate results with this kind of source localization. Hence recordings, with a low Signal-to-Noise Ratio (SNR) cannot be used in a travel time based inversion. Low SNR can be related with weak signals from distant and/or low magnitude sources as well as with a high level of ambient noise. Diffraction stacking is considered as an alternative seismic event localization method that enables also the processing of low SNR recordings by mean of stacking the amplitudes of seismograms along a travel time function. The location of seismic event and its origin time are determined based on the highest stacked amplitudes (coherency) of the image function. The method promotes an automatic processing since it does not need travel time picks as input data.
However, applying diffraction stacking may require longer computation times if only limited computer resources are used. Furthermore, a simple diffraction stacking of recorded amplitudes could possibly fail to locate the seismic sources if the focal mechanism leads to complex radiation patterns which typically holds for both natural and induced seismicity.
In my PhD project, I have developed a new work flow for the localization of seismic events which is based on a diffraction stacking approach. A parallelized code was implemented for the calculation of travel time tables and for the determination of an image function to reduce computation time. In order to address the effects from complex source radiation patterns, I also suggest to compute diffraction stacking from a characteristic function (CF) instead of stacking the original wave form data. A new CF, which is called in the following mAIC (modified from Akaike Information Criterion) is proposed. I demonstrate that, the performance of the mAIC does not depend on the chosen length of the analyzed time window and that both P- and S-wave onsets can be detected accurately. To avoid cross-talk between P- and S-waves due to inaccurate velocity models, I separate the P- and S-waves from the mAIC function by making use of polarization attributes. Then, eventually the final image function is represented by the largest eigenvalue as a result of the covariance analysis between P- and S-image functions. Before applying diffraction stacking, I also apply seismogram denoising by using Otsu thresholding in the time-frequency domain.
Results from synthetic experiments show that the proposed diffraction stacking provides reliable results even from seismograms with low SNR=1. Tests with different presentations of the synthetic seismograms (displacement, velocity, and acceleration) shown that, acceleration seismograms deliver better results in case of high SNR, whereas displacement seismograms provide more accurate results in case of low SNR recordings. In another test, different measures (maximum amplitude, other statistical parameters) were used to determine the source location in the final image function. I found that the statistical approach is the preferred method particularly for low SNR.
The work flow of my diffraction stacking method was finally applied to local earthquake data from Sumatra, Indonesia. Recordings from a temporary network of 42 stations deployed for 9 months around the Tarutung pull-apart Basin were analyzed. The seismic event locations resulting from the diffraction stacking method align along a segment of the Sumatran Fault. A more complex distribution of seismicity is imaged within and around the Tarutung Basin. Two lineaments striking N-S were found in the middle of the Tarutung Basin which support independent results from structural geology. These features are interpreted as opening fractures due to local extension. A cluster of seismic events repeatedly occurred in short time which might be related to fluid drainage since two hot springs are observed at the surface near to this cluster.
In the present work side-chain polystyrenes were synthesized and characterized, in order to be applied in multilayer OLEDs fabricated by solution process techniques. Manufacture of optoelectronic devices by solution process techniques is meant to decrease significantly fabrication cost and allow large scale production of such devices.
This dissertation focusses in three series, enveloped in two material classes. The two classes differ to each other in the type of charge transport exhibited, either ambipolar transport or electron transport. All materials were applied in all-organic solution processed green Ir-based devices.
In the first part, a series of ambipolar host materials were developed to transport both charge types, holes and electrons, and be applied especially as matrix for green Ir-based emitters. It was possible to increase devices efficacy by modulating the predominant charge transport type. This was achieved by modification of molecules electron transport part with more electron-deficient heterocycles or by extending the delocalization of the LUMO. Efficiencies up to 28.9 cd/A were observed for all-organic solution-process three layer devices.
In the second part, suitability of triarylboranes and tetraphenylsilanes as electron transport materials was studied. High triplet energies were obtained, up to 2.95 eV, by rational combination of both molecular structures. Although the combination of both elements had a low effect in materials electron transport properties, high efficiencies around 24 cd/A were obtained for the series in all-organic solution-processed two layer devices.
In the last part, benzene and pyridine were chosen as the series electron-transport motif. By controlling the relative pyridine content (RPC) solubility into methanol was induced for polystyrenes with bulky side-chains. Materials with RPC ≥ 0.5 could be deposited orthogonally from solution without harming underlying layers. From the best of our knowledge, this is the first time such materials are applied in this architecture showing moderate efficiencies around 10 cd/A in all-organic solution processed OLEDs.
Overall, the outcome of these studies will actively contribute to the current research on materials for all-solution processed OLEDs.