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It is desirable to reduce the potential threats that result from the variability of nature, such as droughts or heat waves that lead to food shortage, or the other extreme, floods that lead to severe damage. To prevent such catastrophic events, it is necessary to understand, and to be capable of characterising, nature's variability. Typically one aims to describe the underlying dynamics of geophysical records with differential equations. There are, however, situations where this does not support the objectives, or is not feasible, e.g., when little is known about the system, or it is too complex for the model parameters to be identified. In such situations it is beneficial to regard certain influences as random, and describe them with stochastic processes. In this thesis I focus on such a description with linear stochastic processes of the FARIMA type and concentrate on the detection of long-range dependence. Long-range dependent processes show an algebraic (i.e. slow) decay of the autocorrelation function. Detection of the latter is important with respect to, e.g. trend tests and uncertainty analysis. Aiming to provide a reliable and powerful strategy for the detection of long-range dependence, I suggest a way of addressing the problem which is somewhat different from standard approaches. Commonly used methods are based either on investigating the asymptotic behaviour (e.g., log-periodogram regression), or on finding a suitable potentially long-range dependent model (e.g., FARIMA[p,d,q]) and test the fractional difference parameter d for compatibility with zero. Here, I suggest to rephrase the problem as a model selection task, i.e.comparing the most suitable long-range dependent and the most suitable short-range dependent model. Approaching the task this way requires a) a suitable class of long-range and short-range dependent models along with suitable means for parameter estimation and b) a reliable model selection strategy, capable of discriminating also non-nested models. With the flexible FARIMA model class together with the Whittle estimator the first requirement is fulfilled. Standard model selection strategies, e.g., the likelihood-ratio test, is for a comparison of non-nested models frequently not powerful enough. Thus, I suggest to extend this strategy with a simulation based model selection approach suitable for such a direct comparison. The approach follows the procedure of a statistical test, with the likelihood-ratio as the test statistic. Its distribution is obtained via simulations using the two models under consideration. For two simple models and different parameter values, I investigate the reliability of p-value and power estimates obtained from the simulated distributions. The result turned out to be dependent on the model parameters. However, in many cases the estimates allow an adequate model selection to be established. An important feature of this approach is that it immediately reveals the ability or inability to discriminate between the two models under consideration. Two applications, a trend detection problem in temperature records and an uncertainty analysis for flood return level estimation, accentuate the importance of having reliable methods at hand for the detection of long-range dependence. In the case of trend detection, falsely concluding long-range dependence implies an underestimation of a trend and possibly leads to a delay of measures needed to take in order to counteract the trend. Ignoring long-range dependence, although present, leads to an underestimation of confidence intervals and thus to an unjustified belief in safety, as it is the case for the return level uncertainty analysis. A reliable detection of long-range dependence is thus highly relevant in practical applications. Examples related to extreme value analysis are not limited to hydrological applications. The increased uncertainty of return level estimates is a potentially problem for all records from autocorrelated processes, an interesting examples in this respect is the assessment of the maximum strength of wind gusts, which is important for designing wind turbines. The detection of long-range dependence is also a relevant problem in the exploration of financial market volatility. With rephrasing the detection problem as a model selection task and suggesting refined methods for model comparison, this thesis contributes to the discussion on and development of methods for the detection of long-range dependence.
In the modern industrialized countries every year several hundred thousands of people die due to the sudden cardiac death. The individual risk for this sudden cardiac death cannot be defined precisely by common available, non-invasive diagnostic tools like Holter-monitoring, highly amplified ECG and traditional linear analysis of heart rate variability (HRV). Therefore, we apply some rather unconventional methods of nonlinear dynamics to analyse the HRV. Especially, some complexity measures that are basing on symbolic dynamics as well as a new measure, the renormalized entropy, detect some abnormalities in the HRV of several patients who have been classified in the low risk group by traditional methods. A combination of these complexity measures with the parameters in the frequency domain seems to be a promising way to get a more precise definition of the individual risk. These findings have to be validated by a representative number of patients.
We have used techniques of nonlinear dynamics to compare a special model for the reversals of the Earth's magnetic field with the observational data. Although this model is rather simple, there is no essential difference to the data by means of well-known characteristics, such as correlation function and probability distribution. Applying methods of symbolic dynamics we have found that the considered model is not able to describe the dynamical properties of the observed process. These significant differences are expressed by algorithmic complexity and Renyi information.
I perform and analyse the first ever calculations of rotating stellar iron core collapse in {3+1} general relativity that start out with presupernova models from stellar evolutionary calculations and include a microphysical finite-temperature nuclear equation of state, an approximate scheme for electron capture during collapse and neutrino pressure effects. Based on the results of these calculations, I obtain the to-date most realistic estimates for the gravitational wave signal from collapse, bounce and the early postbounce phase of core collapse supernovae. I supplement my {3+1} GR hydrodynamic simulations with 2D Newtonian neutrino radiation-hydrodynamic supernova calculations focussing on (1) the late postbounce gravitational wave emission owing to convective overturn, anisotropic neutrino emission and protoneutron star pulsations, and (2) on the gravitational wave signature of accretion-induced collapse of white dwarfs to neutron stars.
The layer-by-layer assembly (LBL) of polyelectrolytes has been extensively studied for the preparation of ultrathin films due to the versatility of the build-up process. The control of the permeability of these layers is particularly important as there are potential drug delivery applications. Multilayered polyelectrolyte microcapsules are also of great interest due to their possible use as microcontainers. This work will present two methods that can be used as employable drug delivery systems, both of which can encapsulate an active molecule and tune the release properties of the active species. Poly-(N-isopropyl acrylamide), (PNIPAM) is known to be a thermo-sensitive polymer that has a Lower Critical Solution Temperature (LCST) around 32oC; above this temperature PNIPAM is insoluble in water and collapses. It is also known that with the addition of salt, the LCST decreases. This work shows Differential Scanning Calorimetry (DSC) and Confocal Laser Scanning Microscopy (CLSM) evidence that the LCST of the PNIPAM can be tuned with salt type and concentration. Microcapsules were used to encapsulate this thermo-sensitive polymer, resulting in a reversible and tunable stimuli- responsive system. The encapsulation of the PNIPAM inside of the capsule was proven with Raman spectroscopy, DSC (bulk LCST measurements), AFM (thickness change), SEM (morphology change) and CLSM (in situ LCST measurement inside of the capsules). The exploitation of the capsules as a microcontainer is advantageous not only because of the protection the capsules give to the active molecules, but also because it facilitates easier transport. The second system investigated demonstrates the ability to reduce the permeability of polyelectrolyte multilayer films by the addition of charged wax particles. The incorporation of this hydrophobic coating leads to a reduced water sensitivity particularly after heating, which melts the wax, forming a barrier layer. This conclusion was proven with Neutron Reflectivity by showing the decreased presence of D2O in planar polyelectrolyte films after annealing creating a barrier layer. The permeability of capsules could also be decreased by the addition of a wax layer. This was proved by the increase in recovery time measured by Florescence Recovery After Photobleaching, (FRAP) measurements. In general two advanced methods, potentially suitable for drug delivery systems, have been proposed. In both cases, if biocompatible elements are used to fabricate the capsule wall, these systems provide a stable method of encapsulating active molecules. Stable encapsulation coupled with the ability to tune the wall thickness gives the ability to control the release profile of the molecule of interest.
Collisions of black holes and neutron stars, named mixed binaries in the following, are interesting because of at least two reasons. Firstly, it is expected that they emit a large amount of energy as gravitational waves, which could be measured by new detectors. The form of those waves is expected to carry information about the internal structure of such systems. Secondly, collisions of such objects are the prime suspects of short gamma ray bursts. The exact mechanism for the energy emission is unknown so far. In the past, Newtonian theory of gravitation and modifications to it were often used for numerical simulations of collisions of mixed binary systems. However, near to such objects, the gravitational forces are so strong, that the use of General Relativity is necessary for accurate predictions. There are a lot of problems in general relativistic simulations. However, systems of two neutron stars and systems of two black holes have been studies extensively in the past and a lot of those problems have been solved. One of the remaining problems so far has been the use of hydrodynamic on excision boundaries. Inside excision regions, no evolution is carried out. Such regions are often used inside black holes to circumvent instabilities of the numerical methods near the singularity. Methods to handle hydrodynamics at such boundaries have been described and tests are shown in this work. One important test and the first application of those methods has been the simulation of a collapsing neutron star to a black hole. The success of these simulations and in particular the performance of the excision methods was an important step towards simulations of mixed binaries. Initial data are necessary for every numerical simulation. However, the creation of such initial data for general relativistic situations is in general very complicated. In this work it is shown how to obtain initial data for mixed binary systems using an already existing method for initial data of two black holes. These initial data have been used for evolutions of such systems and problems encountered are discussed in this work. One of the problems are instabilities due to different methods, which could be solved by dissipation of appropriate strength. Another problem is the expected drift of the black hole towards the neutron star. It is shown, that this can be solved by using special gauge conditions, which prevent the black hole from moving on the computational grid. The methods and simulations shown in this work are only the starting step for a much more detailed study of mixed binary system. Better methods, models and simulations with higher resolution and even better gauge conditions will be focus of future work. It is expected that such detailed studies can give information about the emitted gravitational waves, which is important in view of the newly built gravitational wave detectors. In addition, these simulations could give insight into the processes responsible for short gamma ray bursts.