@phdthesis{Hintsche2018,
  author    = {Hintsche, Marius},
  title     = {Locomotion of a bacterium with a polar bundle of flagella},
  doi       = {10.25932/publishup-42697},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426972},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xi, 108},
  year      = {2018},
  abstract  = {Movement and navigation are essential for many organisms during some parts of their lives. This is also true for bacteria, which can move along surfaces and swim though liquid environments. They are able to sense their environment, and move towards environmental cues in a directed fashion. These abilities enable microbial lifecyles in biofilms, improved food uptake, host infection, and many more. In this thesis we study aspects of the swimming movement - or motility - of the soil bacterium (P. putida). Like most bacteria, P. putida swims by rotating its helical flagella, but their arrangement differs from the main model organism in bacterial motility research: (E. coli). P. putida is known for its intriguing motility strategy, where fast and slow episodes can occur after each other. Up until now, it was not known how these two speeds can be produced, and what advantages they might confer to this bacterium. Normally the flagella, the main component of thrust generation in bacteria, are not observable by ordinary light microscopy. In order to elucidate this behavior, we therefore used a fluorescent staining technique on a mutant strain of this species to specifically label the flagella, while leaving the cell body only faintly stained. This allowed us to image the flagella of the swimming bacteria with high spacial and temporal resolution with a customized high speed fluorescence microscopy setup. Our observations show that P. putida can swim in three different modes. First, It can swim with the flagella pushing the cell body, which is the main mode of swimming motility previously known from other bacteria. Second, it can swim with the flagella pulling the cell body, which was thought not to be possible in situations with multiple flagella. Lastly, it can wrap its flagellar bundle around the cell body, which results in a speed wich is slower by a factor of two. In this mode, the flagella are in a different physical conformation with a larger radius so the cell body can fit inside. These three swimming modes explain the previous observation of two speeds, as well as the non strict alternation of the different speeds. Because most bacterial swimming in nature does not occur in smoothly walled glass enclosures under a microscope, we used an artificial, microfluidic, structured system of obstacles to study the motion of our model organism in a structured environment. Bacteria were observed in microchannels with cylindrical obstacles of different sizes and with different distances with video microscopy and cell tracking. We analyzed turning angles, run times, and run length, which we compared to a minimal model for movement in structured geometries. Our findings show that hydrodynamic interactions with the walls lead to a guiding of the bacteria along obstacles. When comparing the observed behavior with the statics of a particle that is deflected with every obstacle contact, we find that cells run for longer distances than that model. Navigation in chemical gradients is one of the main applications of motility in bacteria. We studied the swimming response of P. putida cells to chemical stimuli (chemotaxis) of the common food preservative sodium benzoate. Using a microfluidic gradient generation device, we created gradients of varying strength, and observed the motion of cells with a video microscope and subsequent cell tracking. Analysis of different motility parameters like run lengths and times, shows that P. putida employs the classical chemotaxis strategy of E. coli: runs up the gradient are biased to be longer than those down the gradient. Using the two different run speeds we observed due to the different swimming modes, we classify runs into `fast' and `slow' modes with a Gaussian mixture model (GMM). We find no evidence that P. putida's uses its swimming modes to perform chemotaxis. In most studies of bacterial motility, cell tracking is used to gather trajectories of individual swimming cells. These trajectories then have to be decomposed into run sections and tumble sections. Several algorithms have been developed to this end, but most require manual tuning of a number of parameters, or extensive measurements with chemotaxis mutant strains. Together with our collaborators, we developed a novel motility analysis scheme, based on generalized Kramers-Moyal-coefficients. From the underlying stochastic model, many parameters like run length etc., can be inferred by an optimization procedure without the need for explicit run and tumble classification. The method can, however, be extended to a fully fledged tumble classifier. Using this method, we analyze E. coli chemotaxis measurements in an aspartate analog, and find evidence for a chemotactic bias in the tumble angles.},
  language  = {en}
}
@phdthesis{Arora2018,
  author    = {Arora, Ashima},
  title     = {Optical and electric field control of magnetism},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-421479},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ii, 126},
  year      = {2018},
  abstract  = {Future magnetic recording industry needs a high-density data storage technology. However, switching the magnetization of small bits requires high magnetic fields that cause excessive heat dissipation. Therefore, controlling magnetism without applying external magnetic field is an important research topic for potential applications in data storage devices with low power consumption. Among the different approaches being investigated, two of them stand out, namely i) all-optical helicity dependent switching (AO-HDS) and ii) ferroelectric control of magnetism. This thesis aims to contribute towards a better understanding of the physical processes behinds these effects as well as reporting new and exciting possibility for the optical and/or electric control of magnetic properties. Hence, the thesis contains two differentiated chapters of results; the first devoted to AO-HDS on TbFe alloys and the second to the electric field control of magnetism in an archetypal Fe/BaTiO3 system. In the first part, the scalability of the AO-HDS to small laser spot-sizes of few microns in the ferrimagnetic TbFe alloy is investigated by spatially resolving the magnetic contrast with photo-emission electron microscopy (PEEM) and X-ray magnetic circular dichroism (XMCD). The results show that the AO-HDS is a local effect within the laser spot size that occurs in the ring-shaped region in the vicinity of thermal demagnetization. Within the ring region, the helicity dependent switching occurs via thermally activated domain wall motion. Further, the thesis reports on a novel effect of thickness dependent inversion of the switching orientation. It addresses some of the important questions like the role of laser heating and the microscopic mechanism driving AO-HDS. The second part of the thesis focuses on the electric field control of magnetism in an artificial multiferroic heterostructure. The sample consists of an Fe wedge with thickness varying between 0:5 nm and 3 nm, deposited on top of a ferroelectric and ferroelastic BaTiO3 [001]-oriented single crystal substrate. Here, the magnetic contrast is imaged via PEEM and XMCD as a function of out-of-plane voltage. The results show the evidence of the electric field control of superparamagnetism mediated by a ferroelastic modification of the magnetic anisotropy. The changes in the magnetoelastic anisotropy drive the transition from the superparamagnetic to superferromagnetic state at localized sample positions.},
  language  = {en}
}
@phdthesis{Kotha2018,
  author    = {Kotha, Sreeram Reddy},
  title     = {Quantification of uncertainties in seismic ground-motion prediction},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-415743},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 101},
  year      = {2018},
  abstract  = {The purpose of Probabilistic Seismic Hazard Assessment (PSHA) at a construction site is to provide the engineers with a probabilistic estimate of ground-motion level that could be equaled or exceeded at least once in the structure's design lifetime. A certainty on the predicted ground-motion allows the engineers to confidently optimize structural design and mitigate the risk of extensive damage, or in worst case, a collapse. It is therefore in interest of engineering, insurance, disaster mitigation, and security of society at large, to reduce uncertainties in prediction of design ground-motion levels. In this study, I am concerned with quantifying and reducing the prediction uncertainty of regression-based Ground-Motion Prediction Equations (GMPEs). Essentially, GMPEs are regressed best-fit formulae relating event, path, and site parameters (predictor variables) to observed ground-motion values at the site (prediction variable). GMPEs are characterized by a parametric median (μ) and a non-parametric variance (σ) of prediction. μ captures the known ground-motion physics i.e., scaling with earthquake rupture properties (event), attenuation with distance from source (region/path), and amplification due to local soil conditions (site); while σ quantifies the natural variability of data that eludes μ. In a broad sense, the GMPE prediction uncertainty is cumulative of 1) uncertainty on estimated regression coefficients (uncertainty on μ,σ_μ), and 2) the inherent natural randomness of data (σ). The extent of μ parametrization, the quantity, and quality of ground-motion data used in a regression, govern the size of its prediction uncertainty: σ_μ and σ. In the first step, I present the impact of μ parametrization on the size of σ_μ and σ. Over-parametrization appears to increase the σ_μ, because of the large number of regression coefficients (in μ) to be estimated with insufficient data. Under-parametrization mitigates σ_μ, but the reduced explanatory strength of μ is reflected in inflated σ. For an optimally parametrized GMPE, a ~10\% reduction in σ is attained by discarding the low-quality data from pan-European events with incorrect parametric values (of predictor variables). In case of regions with scarce ground-motion recordings, without under-parametrization, the only way to mitigate σ_μ is to substitute long-term earthquake data at a location with short-term samples of data across several locations - the Ergodic Assumption. However, the price of ergodic assumption is an increased σ, due to the region-to-region and site-to-site differences in ground-motion physics. σ of an ergodic GMPE developed from generic ergodic dataset is much larger than that of non-ergodic GMPEs developed from region- and site-specific non-ergodic subsets - which were too sparse to produce their specific GMPEs. Fortunately, with the dramatic increase in recorded ground-motion data at several sites across Europe and Middle-East, I could quantify the region- and site-specific differences in ground-motion scaling and upgrade the GMPEs with 1) substantially more accurate region- and site-specific μ for sites in Italy and Turkey, and 2) significantly smaller prediction variance σ. The benefit of such enhancements to GMPEs is quite evident in my comparison of PSHA estimates from ergodic versus region- and site-specific GMPEs; where the differences in predicted design ground-motion levels, at several sites in Europe and Middle-Eastern regions, are as large as ~50\%. Resolving the ergodic assumption with mixed-effects regressions is feasible when the quantified region- and site-specific effects are physically meaningful, and the non-ergodic subsets (regions and sites) are defined a priori through expert knowledge. In absence of expert definitions, I demonstrate the potential of machine learning techniques in identifying efficient clusters of site-specific non-ergodic subsets, based on latent similarities in their ground-motion data. Clustered site-specific GMPEs bridge the gap between site-specific and fully ergodic GMPEs, with their partially non-ergodic μ and, σ ~15\% smaller than the ergodic variance. The methodological refinements to GMPE development produced in this study are applicable to new ground-motion datasets, to further enhance certainty of ground-motion prediction and thereby, seismic hazard assessment. Advanced statistical tools show great potential in improving the predictive capabilities of GMPEs, but the fundamental requirement remains: large quantity of high-quality ground-motion data from several sites for an extended time-period.},
  language  = {en}
}
@phdthesis{Hlawenka2018,
  author    = {Hlawenka, Peter},
  title     = {Samarium hexaboride},
  school      = {Universit{\"a}t Potsdam},
  pages     = {116, XXI},
  year      = {2018},
  language  = {en}
}
@phdthesis{RodriguezLoureiro2018,
  author    = {Rodriguez Loureiro, Ignacio},
  title     = {Structural characterization of single and interacting soft interfaces displaying brushes of synthetic or biomolecular polymers},
  doi       = {10.25932/publishup-42367},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423675},
  school      = {Universit{\"a}t Potsdam},
  pages     = {132},
  year      = {2018},
  abstract  = {The interaction between surfaces displaying end-grafted hydrophilic polymer brushes plays important roles in biology and in many wet-technological applications. The outer surfaces of Gram-negative bacteria, for example, are composed of lipopolysaccharide (LPS) molecules exposing oligo- and polysaccharides to the aqueous environment. This unique, structurally complex biological interface is of great scientific interest as it mediates the interaction of bacteria with neighboring bacteria in colonies and biofilms. The interaction between polymer-decorated surfaces is generally coupled to the distance-dependent conformation of the polymer chains. Therefore, structural insight into the interacting surfaces is a prerequisite to understand the interaction characteristics as well as the underlying physical mechanisms. This problem has been addressed by theory, but accurate experimental data on polymer conformations under confinement are rare, because obtaining perturbation-free structural insight into buried soft interfaces is inherently difficult. In this thesis, lipid membrane surfaces decorated with hydrophilic polymers of technological and biological relevance are investigated under controlled interaction conditions, i.e., at defined surface separations. For this purpose, dedicated sample architectures and experimental tools are developed. Via ellipsometry and neutron reflectometry pressure-distance curves and distance-dependent polymer conformations in terms of brush compression and reciprocative interpenetration are determined. Additional element-specific structural insight into the end-point distribution of interacting brushes is obtained by standing-wave x-ray fluorescence (SWXF). The methodology is first established for poly[ethylene glycol] (PEG) brushes of defined length and grafting density. For this system, neutron reflectometry revealed pronounced brush interpenetration, which is not captured in common brush theories and therefore motivates rigorous simulation-based treatments. In the second step the same approach is applied to realistic mimics of the outer surfaces of Gram-negative bacteria: monolayers of wild type LPSs extracted from E. Coli O55:B5 displaying strain-specific O-side chains. The neutron reflectometry experiments yield unprecedented structural insight into bacterial interactions, which are of great relevance for the properties of biofilms.},
  language  = {en}
}
@phdthesis{Quade2018,
  author    = {Quade, Markus},
  title     = {Symbolic regression for identification, prediction, and control of dynamical systems},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419790},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiii, 134},
  year      = {2018},
  abstract  = {In the present work, we use symbolic regression for automated modeling of dynamical systems. Symbolic regression is a powerful and general method suitable for data-driven identification of mathematical expressions. In particular, the structure and parameters of those expressions are identified simultaneously. We consider two main variants of symbolic regression: sparse regression-based and genetic programming-based symbolic regression. Both are applied to identification, prediction and control of dynamical systems. We introduce a new methodology for the data-driven identification of nonlinear dynamics for systems undergoing abrupt changes. Building on a sparse regression algorithm derived earlier, the model after the change is defined as a minimum update with respect to a reference model of the system identified prior to the change. The technique is successfully exemplified on the chaotic Lorenz system and the van der Pol oscillator. Issues such as computational complexity, robustness against noise and requirements with respect to data volume are investigated. We show how symbolic regression can be used for time series prediction. Again, issues such as robustness against noise and convergence rate are investigated us- ing the harmonic oscillator as a toy problem. In combination with embedding, we demonstrate the prediction of a propagating front in coupled FitzHugh-Nagumo oscillators. Additionally, we show how we can enhance numerical weather predictions to commercially forecast power production of green energy power plants. We employ symbolic regression for synchronization control in coupled van der Pol oscillators. Different coupling topologies are investigated. We address issues such as plausibility and stability of the control laws found. The toolkit has been made open source and is used in turbulence control applications. Genetic programming based symbolic regression is very versatile and can be adapted to many optimization problems. The heuristic-based algorithm allows for cost efficient optimization of complex tasks. We emphasize the ability of symbolic regression to yield white-box models. In contrast to black-box models, such models are accessible and interpretable which allows the usage of established tool chains.},
  language  = {en}
}
@phdthesis{Kuehn2018,
  author    = {K{\"u}hn, Danilo},
  title     = {Synchrotron-based angle-resolved time-of-flight electron spectroscopy for dynamics in dichalogenides},
  school      = {Universit{\"a}t Potsdam},
  pages     = {147},
  year      = {2018},
  language  = {en}
}
@phdthesis{Sander2018,
  author    = {Sander, Mathias},
  title     = {Ultrafast tailored strain fields in nanostructures},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-417863},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvii, 119},
  year      = {2018},
  abstract  = {This publication based thesis, which consists of seven published articles, summarizes my contributions to the research field of laser excited ultrafast structural dynamics. The coherent and incoherent lattice dynamics on microscopic length scales are detected by ultrashort optical and X-ray pulses. The understanding of the complex physical processes is essential for future improvements of technological applications. For this purpose, tabletop soruces and large scale facilities, e.g. synchrotrons, are employed to study structural dynamics of longitudinal acoustic strain waves and heat transport. The investigated effects cover timescales from hundreds of femtoseconds up to several microseconds. The main part of this thesis is dedicated to the investigation of tailored phonon wave packets propagating in perovskite nanostructures. Tailoring is achieved either by laser excitation of nanostructured bilayer samples or by a temporal series of laser pulses. Due to the propagation of longitudinal acoustic phonons, the out-of-plane lattice spacing of a thin film insulator-metal bilayer sample is modulated on an ultrafast timescale. This leads to an ultrafast modulation of the X-ray diffraction efficiency which is employed as a phonon Bragg switch to shorten hard X-ray pulses emitted from a 3rd generation synchrotron. In addition, we have observed nonlinear mixing of high amplitude phonon wave packets which originates from an anharmonic interatomic potential. A chirped optical pulse sequence excites a narrow band phonon wave packet with specific momentum and energy. The second harmonic generation of these phonon wave packets is followed by ultrafast X-ray diffraction. Phonon upconversion takes place because the high amplitude phonon wave packet modulates the acoustic properties of the crystal which leads to self steepening and to the successive generation of higher harmonics of the phonon wave packet. Furthermore, we have demonstrated ultrafast strain in direction parallel to the sample surface. Two consecutive so-called transient grating excitations displaced in space and time are used to coherently control thermal gradients and surface acoustic modes. The amplitude of the coherent and incoherent surface excursion is disentangled by time resolved X-ray reflectivity measurements. We calibrate the absolute amplitude of thermal and acoustic surface excursion with measurements of longitudinal phonon propagation. In addition, we develop a diffraction model which allows for measuring the surface excursion on an absolute length scale with sub-{\"A}angstr{\"o}m precision. Finally, I demonstrate full coherent control of an excited surface deformation by amplifying and suppressing thermal and coherent excitations at the surface of a laser-excited Yttrium-manganite sample.},
  language  = {en}
}
@phdthesis{Koc2018,
  author    = {Ko{\c{c}}, Azize},
  title     = {Ultrafast x-ray studies on the non-equilibrium of the magnetic and phononic system in heavy rare-earths},
  doi       = {10.25932/publishup-42328},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423282},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ii, 117},
  year      = {2018},
  abstract  = {In this dissertation the lattice and the magnetic recovery dynamics of the two heavy rare-earth metals Dy and Gd after femtosecond photoexcitation are described. For the investigations, thin films of Dy and Gd were measured at low temperatures in the antiferromagnetic phase of Dy and close to room temperature in the ferromagnetic phase of Gd. Two different optical pump-x-ray probe techniques were employed: Ultrafast x-ray diffraction with hard x-rays (UXRD) yields the structural response of heavy rare-earth metals and resonant soft (elastic) x-ray diffraction (RSXD), which allows measuring directly changes in the helical antiferromagnetic order of Dy. The combination of both techniques enables to study the complex interaction between the magnetic and the phononic subsystems.},
  language  = {en}
}