Refine
Has Fulltext
- yes (26)
Is part of the Bibliography
- yes (26)
Year of publication
Document Type
- Doctoral Thesis (24)
- Journal article (2)
Language
- English (26) (remove)
Keywords
- Simulation (26) (remove)
Institute
- Institut für Theoretische Physik und Astrophysik (5)
- Institut für Informatik (4)
- Physikalisches Institut (4)
- Institut für Mathematik (2)
- Betriebswirtschaftliches Institut (1)
- Center for Computational and Theoretical Biology (1)
- Fakultät für Biologie (1)
- Fakultät für Mathematik und Informatik (1)
- Graduate School of Life Sciences (1)
- Graduate School of Science and Technology (1)
Sonstige beteiligte Institutionen
ResearcherID
- D-1250-2010 (1)
Staphylococcus aureus (SA) causes nosocomial infections including life threatening sepsis by multi-resistant strains (MRSA). It has the ability to form biofilms to protect it from the host immune system and from anti staphylococcal drugs. Biofilm and planctonic life style is regulated by a complex Quorum-Sensing (QS) system with agr as a central regulator. To study biofilm formation and QS mechanisms in SA a Boolean network was build (94 nodes, 184 edges) including two different component systems such as agr, sae and arl. Important proteins such as Sar, Rot and SigB were included as further nodes in the model. System analysis showed there are only two stable states biofilm forming versus planctonic with clearly different subnetworks turned on. Validation according to gene expression data confirmed this. Network consistency was tested first according to previous knowledge and literature. Furthermore, the predicted node activity of different in silico knock-out strains agreed well with corresponding micro array experiments and data sets. Additional validation included the expression of further nodes (Northern blots) and biofilm production compared in different knock-out strains in biofilm adherence assays. The model faithfully reproduces the behaviour of QS signalling mutants. The integrated model allows also prediction of various other network mutations and is supported by experimental data from different strains. Furthermore, the well connected hub proteins elucidate how integration of different inputs is achieved by the QS network. For in silico as well as in vitro experiments it was found that the sae-locus is also a central modulator of biofilm production. Sae knock-out strains showed stronger biofilms. Wild type phenotype was rescued by sae complementation. To elucidate the way in which sae takes influence on biofilm formation the network was used and Venn-diagrams were made, revealing nodes regulated by sae and changed in biofilms. In these Venn-diagrams nucleases and extracellular proteins were found to be promising nodes. The network revealed DNAse to be of great importance. Therefore qualitatively the DNAse amount, produced by different SA mutants was measured, it was tried to dissolve biofilms with according amounts of DNAse and the concentration of nucleic acids, proteins and polysaccharides were measured in biofilms of different SA mutants.
With its thorough validation the network model provides a powerful tool to study QS and biofilm formation in SA, including successful predictions for different knock-out mutant behaviour, QS signalling and biofilm formation. This includes implications for the behaviour of MRSA strains and mutants. Key regulatory mutation combinations (agr–, sae–, sae–/agr–, sigB+, sigB+/sae–) were directly tested in the model but also in experiments. High connectivity was a good guide to identify master regulators, whose detailed behaviour was studied both in vitro and in the model. Together, both lines of evidence support in particular a refined regulatory role for sae and agr with involvement in biofilm repression and/or SA dissemination. With examination of the composition of different mutant biofilms as well as with the examination of the reaction cascade that connects sae to the biofilm forming ability of SA and also by postulating that nucleases might play an important role in that, first steps were taken in proving and explaining regulatory links leading from sae to biofilms. Furthermore differences in biofilms of different mutant SA strains were found leading us in perspective towards a new understanding of biofilms including knowledge how to better regulate, fight and use its different properties.
The fact that photovoltaics is a key technology for climate-neutral energy production can be taken as a given. The question to what extent perovskite will be used for photovoltaic technologies has not yet been fully answered. From a photophysical point of view, however, it has the potential to make a useful contribution to the energy sector. However, it remains to be seen whether perovskite-based modules will be able to compete with established technologies in terms of durability and cost efficiency. The additional aspect of ionic migration poses an additional challenge. In the present work, primarily the interaction between ionic redistribution, capacitive properties and recombination dynamics was investigated. This was done using impedance spectroscopy, OCVD and IV characteristics as well as extensive numerical drift-diffusion simulations. The combination of experimental and numerical methods proved to be very fruitful. A suitable model for the description of solar cells with respect to mobile ions was introduced in chapter 4.4. The formal mathematical description of the model was transferred by a non-dimensionalization and suitable numerically solvable form. The implementation took place in the Julia language. By intelligent use of structural properties of the sparse systems of equations, automatic differentiation and the use of efficient integration methods, the simulation tool is not only remarkably fast in finding the solution, but also scales quasi-linearly with the grid resolution. The software package was released under an open source license. In conventional semiconductor diodes, capacitance measurements are often used to determine the space charge density. In the first experimental chapter 5, it is shown that although this is also possible for the ionic migration present in perovskites, it cannot be directly understood as doping related, since the space charge distribution strongly depends on the preconditions and can be manipulated by an externally applied voltage. The exact form of this behavior depends on the perovskite composition. This shows, among other things, that experimental results can only be interpreted within the framework of conventional semiconductors to a very limited extent. Nevertheless, the built-in 99 potential of the solar cell can be determined if the experiments are carried out properly. A statement concerning the type and charge of the mobile ions is not possible without further effort, while their number can be determined. The simulations were applied to experimental data in chapter 6. Thus, it could be shown that mobile ions make a significant contribution to the OCVD of perovskite solar cells. j-V characteristics and OCVD transients measured as a function of temperature and illumination intensities could be quantitatively modeled simultaneously using a single global set of parameters. By the simulations it was further possible to derive a simple experimental procedure to determine the concentration and the diffusivity of the mobile ions. The possibility of describing different experiments in a uniform temperaturedependent manner strongly supports the model of mobile ions in perovskites. In summary, this work has made an important contribution to the elucidation of ionic contributions to the (photo)electrical properties of perovskite solar cells. Established experimental techniques for conventional semiconductors have been reinterpreted with respect to ionic mass transport and new methods have been proposed to draw conclusions on the properties for ionic transport. As a result, the published simulation tools can be used for a number of further studies.
In this doctoral thesis we cover the performance evaluation of next generation data plane architectures, comprised of complex software as well as programmable hardware components that allow fine granular configuration. In the scope of the thesis we propose mechanisms to monitor the performance of singular components and model key performance indicators of software based packet processing solutions. We present novel approaches towards network abstraction that allow the integration of heterogeneous data plane technologies into a singular network while maintaining total transparency between control and data plane. Finally, we investigate a full, complex system consisting of multiple software-based solutions and perform a detailed performance analysis. We employ simulative approaches to investigate overload control mechanisms that allow efficient operation under adversary conditions. The contributions of this work build the foundation for future research in the areas of network softwarization and network function virtualization.
This thesis deals with the chaotic dynamics of nonlinear networks consisting of semiconductor lasers which have time-delayed self-feedbacks or mutual couplings. These semiconductor lasers are simulated numerically by the Lang-Kobayashi equations. The central issue is how the chaoticity of the lasers, measured by the maximal Lyapunov exponent, changes when the delay time is changed. It is analysed how this change of chaoticity with increasing delay time depends on the reflectivity of the mirror for the self-feedback or the strength of the mutal coupling, respectively. The consequences of the different types of chaos for the effect of chaos synchronization of mutually coupled semiconductor lasers are deduced and discussed. At the beginning of this thesis, the master stability formalism for the stability analysis of nonlinear networks with delay is explained. After the description of the Lang-Kobayashi equations and their linearizations as a model for the numerical simulation of semiconductor lasers with time-delayed couplings, the artificial sub-Lyapunov exponent $\lambda_{0}$ is introduced. It is explained how the sign of the sub-Lyapunov exponent can be determined by experiments. The notions of "strong chaos" and "weak chaos" are introduced and distinguished by their different scaling properties of the maximal Lyapunov exponent with the delay time. The sign of the sub-Lyapunov exponent $\lambda_{0}$ is shown to determine the occurence of strong or weak chaos. The transition sequence "weak to strong chaos and back to weak chaos" upon monotonically increasing the coupling strength $\sigma$ of a single laser's self-feedback is shown for numerical calculations of the Lang-Kobayashi equations. At the transition between strong and weak chaos, the sub-Lyapunov exponent vanishes, $\lambda_{0}=0$, resulting in a special scaling behaviour of the maximal Lyapunov exponent with the delay time. Transitions between strong and weak chaos by changing $\sigma$ can also be found for the Rössler and Lorenz dynamics. The connection between the sub-Lyapunov exponent and the time-dependent eigenvalues of the Jacobian for the internal laser dynamics is analysed. Counterintuitively, the difference between strong and weak chaos is not directly visible from the trajectory although the difference of the trajectories induces the transitions between the two types of chaos. In addition, it is shown that a linear measure like the auto-correlation function cannot unambiguously reveal the difference between strong and weak chaos either. Although the auto-correlations after one delay time are significantly higher for weak chaos than for strong chaos, it is not possible to detect a qualitative difference. If two time-scale separated self-feedbacks are present, the shorter feedback has to be taken into account for the definition of a new sub-Lyapunov exponent $\lambda_{0,s}$, which in this case determines the occurence of strong or weak chaos. If the two self-feedbacks have comparable delay times, the sub-Lyapunov exponent $\lambda_{0}$ remains the criterion for strong or weak chaos. It is shown that the sub-Lyapunov exponent scales with the square root of the effective pump current $\sqrt{p-1}$, both in its magnitude and in the position of the critical coupling strengths. For networks with several distinct sub-Lyapunov exponents, it is shown that the maximal sub-Lyapunov exponent of the network determines whether the network's maximal Lyapunov exponent scales strongly or weakly with increasing delay time. As a consequence, complete synchronization of a network is excluded for arbitrary networks which contain at least one strongly chaotic laser. Furthermore, it is demonstrated that the sub-Lyapunov exponent of a driven laser depends on the number of the incoherently superimposed inputs from unsynchronized input lasers. For networks of delay-coupled lasers operating in weak chaos, the condition $|\gamma_{2}|<\mathrm{e}^{-\lambda_{\mathrm{m}}\,\tau}$ for stable chaos synchronization is deduced using the master stability formalism. Hence, synchronization of any network depends only on the properties of a single laser with self-feedback and the eigenvalue gap of the coupling matrix. The characteristics of the master stability function for the Lang-Kobayashi dynamics is described, and consequently, the master stability function is refined to allow for precise practical prediction of synchronization. The prediction of synchronization with the master stability function is demonstrated for bidirectional and unidirectional networks. Furthermore, the master stability function is extended for two distinct delay times. Finally, symmetries and resonances for certain values of the ratio of the delay times are shown for the master stability function of the Lang-Kobyashi equations.
This work aims at elucidating chemical processes involving homogeneous catalysis and photo–physical relaxation of excited molecules in the solid state. Furthermore, compounds with supposedly small singlet–triplet gaps and therefore biradicaloid character are investigated with respect to their electro–chemical behavior. The work on hydroboration catalysis via a reduced 9,10–diboraanthracene (DBA) was preformed in collaboration with the Wagner group in Frankfurt, more specifically Dr. Sven Prey, who performed all laboratory experiments. The investigation of delayed luminescence properties in arylboronic esters in their solid state was conducted in collaboration with the Marder group in Würzburg. The author of this work took part in the synthesis of the investigated compounds while being supervised by Dr. Zhu Wu. The final project was a collaboration with the group of Anukul Jana from Hyderabad, India who provided the experimental data.
This thesis contains two major parts: The first part introduces the reader into three independent concepts of treating strongly correlated many body physics. These are, on the analytical side the SO(5)-theory (Chap.3), which poses the general frame. On the numerical side these are the Stochastic Series Expansion (SSE) (Chap.1) and the Contractor Renormalization Group (CORE) approach (Chap. 2}). The central idea of this thesis was to combine these above concepts, in order to achieve a better understanding of the high-T_c superconductors (HTSC). The results obtained by this combination can be found in the second major part of this thesis (chapters 4 and 5). The main idea of this thesis, i.e., to combine the SO(5)-theory with the capabilities of bosonic Quantum-Monte Carlo simulations and those of the CORE approach, has been proven to be a very successful Ansatz. Two different approaches, one based on symmetry and one on renormalization-group arguments, motivate an effective bosonic Hamiltonian. In a subsequent step the effective Hamiltonian has been simulated efficiently using the SSE. The results reproduce salient experiments on high-T_c superconductors. In addition, it has been shown that the model can be extended to capture also charge ordering. These results also form a profound basis for further studies, for example one could address the open question of SO(5)-symmetry restoration at a multicritical point in the extended pSO(5) model, where longer ranged interactions are included.
Understanding the emergence of species' ranges is one of the most fundamental challenges in ecology. Early on, geographical barriers were identified as obvious natural constraints to the spread of species. However, many range borders occur along gradually changing landscapes, where no sharp barriers are obvious. Mechanistic explanations for this seeming contradiction incorporate environmental gradients that either affect the spatio-temporal variability of conditions or the increasing fragmentation of habitat. Additionally, biological mechanisms like Allee effects (i.e. decreased growth rates at low population sizes or densities), condition-dependent dispersal, and biological interactions with other species have been shown to severely affect the location of range margins. The role of dispersal has been in the focus of many studies dealing with range border formation. Dispersal is known to be highly plastic and evolvable, even over short ecological time-scales. However, only few studies concentrated on the impact of evolving dispersal on range dynamics. This thesis aims at filling this gap. I study the influence of evolving dispersal rates on the persistence of spatially structured populations in environmental gradients and its consequences for the establishment of range borders. More specially I investigate scenarios of range formation in equilibrium, periods of range expansion, and range shifts under global climate change ...
Following the early experiences in aviation, medical simulation has rapidly
evolved into one of the most novel educational tools of the last three decades. In addition to its
use in training individuals or teams in crisis resource management, simulation has been studied as
a tool to evaluate technical and non-technical skills of individuals as well as, more recently,
entire medical teams.
It is usually fairly difficult to obtain clinical reference data from critical events to refute
claims that the management of actual events fell below what could reasonably be expected and we
demonstrated the use of rank order statistics to calculate quantiles with confidence limits for
management times of critical obstetrical events using data from realistic simulation. This approach
could be used to describe the distribution of treatment times in order to assist in deciding what
performance may constitute an outlier. It can also identify particular challenges of clinical
practice and allow the development of educational curricula. While the information derived from
simulation has to be interpreted with a high degree of caution for a clinical context, it may
represent a further ‘added value’ or important step in establishing simulation as a training tool
and to provide information that could be used in an appropriate clinical context for adverse
events. Large amounts of data (such as from a simulation registry) would allow the calculation of
acceptable confidence intervals for the required
outcome parameters as well as actual tolerance limits.
How genomic and ecological traits shape island biodiversity - insights from individual-based models
(2020)
Life on oceanic islands provides a playground and comparably easy\-/studied basis
for the understanding of biodiversity in general. Island biota feature many
fascinating patterns: endemic species, species radiations and species with
peculiar trait syndromes. However, classic and current island biogeography
theory does not yet consider all the factors necessary to explain many of these
patterns. In response to this, there is currently a shift in island biogeography
research to systematically consider species traits and thus gain a more
functional perspective. Despite this recent development, a set of species
characteristics remains largely ignored in island biogeography, namely genomic
traits. Evidence suggests that genomic factors could explain many of the
speciation and adaptation patterns found in nature and thus may be highly
informative to explain the fascinating and iconic phenomena known for oceanic
islands, including species radiations and susceptibility to biotic invasions.
Unfortunately, the current lack of comprehensive meaningful data makes studying
these factors challenging. Even with paleontological data and space-for-time
rationales, data is bound to be incomplete due to the very environmental
processes taking place on oceanic islands, such as land slides and volcanism,
and lacks causal information due to the focus on correlative approaches. As
promising alternative, integrative mechanistic models can explicitly consider
essential underlying eco\-/evolutionary mechanisms. In fact, these models have
shown to be applicable to a variety of different systems and study questions.
In this thesis, I therefore examined present mechanistic island models to
identify how they might be used to address some of the current open questions in
island biodiversity research. Since none of the models simultaneously considered
speciation and adaptation at a genomic level, I developed a new genome- and
niche-explicit, individual-based model. I used this model to address three
different phenomena of island biodiversity: environmental variation, insular
species radiations and species invasions.
Using only a single model I could show that small-bodied species with flexible
genomes are successful under environmental variation, that a complex combination
of dispersal abilities, reproductive strategies and genomic traits affect the
occurrence of species radiations and that invasions are primarily driven by the
intensity of introductions and the trait characteristics of invasive
species. This highlights how the consideration of functional traits can promote
the understanding of some of the understudied phenomena in island biodiversity.
The results presented in this thesis exemplify the generality of integrative
models which are built on first principles. Thus, by applying such models to
various complex study questions, they are able to unveil multiple biodiversity
dynamics and patterns. The combination of several models such as the one I
developed to an eco\-/evolutionary model ensemble could further help to identify
fundamental eco\-/evolutionary principles. I conclude the thesis with an outlook
on how to use and extend my developed model to investigate geomorphological
dynamics in archipelagos and to allow dynamic genomes, which would further
increase the model's generality.
The ongoing and evolving usage of networks presents two critical challenges for current and future networks that require attention: (1) the task of effectively managing the vast and continually increasing data traffic and (2) the need to address the substantial number of end devices resulting from the rapid adoption of the Internet of Things. Besides these challenges, there is a mandatory need for energy consumption reduction, a more efficient resource usage, and streamlined processes without losing service quality. We comprehensively address these efforts, tackling the monitoring and quality assessment of streaming applications, a leading contributor to the total Internet traffic, as well as conducting an exhaustive analysis of the network performance within a Long Range Wide Area Network (LoRaWAN), one of the rapidly emerging LPWAN solutions.