Refine
Year of publication
- 2014 (202) (remove)
Document Type
- Doctoral Thesis (202) (remove)
Is part of the Bibliography
- yes (202) (remove)
Keywords
- Gammastrahlungsastronomie (4)
- data analysis (4)
- gamma-ray astronomy (4)
- Crab Nebula (3)
- Datenanalyse (3)
- Krebsnebel (3)
- Synchronisation (3)
- Systembiologie (3)
- synchronization (3)
- systems biology (3)
Institute
- Institut für Biochemie und Biologie (32)
- Institut für Physik und Astronomie (23)
- Institut für Geowissenschaften (17)
- Wirtschaftswissenschaften (14)
- Institut für Chemie (13)
- Historisches Institut (12)
- Institut für Informatik und Computational Science (9)
- Institut für Ernährungswissenschaft (8)
- Department Psychologie (7)
- Hasso-Plattner-Institut für Digital Engineering gGmbH (6)
In processing and data storage mainly ferromagnetic (FM) materials are being used. Approaching physical limits, new concepts have to be found for faster, smaller switches, for higher data densities and more energy efficiency. Some of the discussed new concepts involve the material classes of correlated oxides and materials with antiferromagnetic coupling. Their applicability depends critically on their switching behavior, i.e., how fast and how energy efficient material properties can be manipulated. This thesis presents investigations of ultrafast non-equilibrium phase transitions on such new materials. In transition metal oxides (TMOs) the coupling of different degrees of freedom and resulting low energy excitation spectrum often result in spectacular changes of macroscopic properties (colossal magneto resistance, superconductivity, metal-to-insulator transitions) often accompanied by nanoscale order of spins, charges, orbital occupation and by lattice distortions, which make these material attractive. Magnetite served as a prototype for functional TMOs showing a metal-to-insulator-transition (MIT) at T = 123 K. By probing the charge and orbital order as well as the structure after an optical excitation we found that the electronic order and the structural distortion, characteristics of the insulating phase in thermal equilibrium, are destroyed within the experimental resolution of 300 fs. The MIT itself occurs on a 1.5 ps timescale. It shows that MITs in functional materials are several thousand times faster than switching processes in semiconductors. Recently ferrimagnetic and antiferromagnetic (AFM) materials have become interesting. It was shown in ferrimagnetic GdFeCo, that the transfer of angular momentum between two opposed FM subsystems with different time constants leads to a switching of the magnetization after laser pulse excitation. In addition it was theoretically predicted that demagnetization dynamics in AFM should occur faster than in FM materials as no net angular momentum has to be transferred out of the spin system. We investigated two different AFM materials in order to learn more about their ultrafast dynamics. In Ho, a metallic AFM below T ≈ 130 K, we found that the AFM Ho can not only be faster but also ten times more energy efficiently destroyed as order in FM comparable metals. In EuTe, an AFM semiconductor below T ≈ 10 K, we compared the loss of magnetization and laser-induced structural distortion in one and the same experiment. Our experiment shows that they are effectively disentangled. An exception is an ultrafast release of lattice dynamics, which we assign to the release of magnetostriction. The results presented here were obtained with time-resolved resonant soft x-ray diffraction at the Femtoslicing source of the Helmholtz-Zentrum Berlin and at the free-electron laser in Stanford (LCLS). In addition the development and setup of a new UHV-diffractometer for these experiments will be reported.
Software maintenance encompasses any changes made to a software system after its initial deployment and is thereby one of the key phases in the typical software-engineering lifecycle. In software maintenance, we primarily need to understand structural and behavioral aspects, which are difficult to obtain, e.g., by code reading. Software analysis is therefore a vital tool for maintaining these systems: It provides - the preferably automated - means to extract and evaluate information from their artifacts such as software structure, runtime behavior, and related processes. However, such analysis typically results in massive raw data, so that even experienced engineers face difficulties directly examining, assessing, and understanding these data. Among other things, they require tools with which to explore the data if no clear question can be formulated beforehand. For this, software analysis and visualization provide its users with powerful interactive means. These enable the automation of tasks and, particularly, the acquisition of valuable and actionable insights into the raw data. For instance, one means for exploring runtime behavior is trace visualization. This thesis aims at extending and improving the tool set for visual software analysis by concentrating on several open challenges in the fields of dynamic and static analysis of software systems. This work develops a series of concepts and tools for the exploratory visualization of the respective data to support users in finding and retrieving information on the system artifacts concerned. This is a difficult task, due to the lack of appropriate visualization metaphors; in particular, the visualization of complex runtime behavior poses various questions and challenges of both a technical and conceptual nature. This work focuses on a set of visualization techniques for visually representing control-flow related aspects of software traces from shared-memory software systems: A trace-visualization concept based on icicle plots aids in understanding both single-threaded as well as multi-threaded runtime behavior on the function level. The concept’s extensibility further allows the visualization and analysis of specific aspects of multi-threading such as synchronization, the correlation of such traces with data from static software analysis, and a comparison between traces. Moreover, complementary techniques for simultaneously analyzing system structures and the evolution of related attributes are proposed. These aim at facilitating long-term planning of software architecture and supporting management decisions in software projects by extensions to the circular-bundle-view technique: An extension to 3-dimensional space allows for the use of additional variables simultaneously; interaction techniques allow for the modification of structures in a visual manner. The concepts and techniques presented here are generic and, as such, can be applied beyond software analysis for the visualization of similarly structured data. The techniques' practicability is demonstrated by several qualitative studies using subject data from industry-scale software systems. The studies provide initial evidence that the techniques' application yields useful insights into the subject data and its interrelationships in several scenarios.
Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks.
The International Project for the Evaluation of Educational Achievement (IEA) was formed in the 1950s (Postlethwaite, 1967). Since that time, the IEA has conducted many studies in the area of mathematics, such as the First International Mathematics Study (FIMS) in 1964, the Second International Mathematics Study (SIMS) in 1980-1982, and a series of studies beginning with the Third International Mathematics and Science Study (TIMSS) which has been conducted every 4 years since 1995. According to Stigler et al. (1999), in the FIMS and the SIMS, U.S. students achieved low scores in comparison with students in other countries (p. 1). The TIMSS 1995 “Videotape Classroom Study” was therefore a complement to the earlier studies conducted to learn “more about the instructional and cultural processes that are associated with achievement” (Stigler et al., 1999, p. 1). The TIMSS Videotape Classroom Study is known today as the TIMSS Video Study. From the findings of the TIMSS 1995 Video Study, Stigler and Hiebert (1999) likened teaching to “mountain ranges poking above the surface of the water,” whereby they implied that we might see the mountaintops, but we do not see the hidden parts underneath these mountain ranges (pp. 73-78). By watching the videotaped lessons from Germany, Japan, and the United States again and again, they discovered that “the systems of teaching within each country look similar from lesson to lesson. At least, there are certain recurring features [or patterns] that typify many of the lessons within a country and distinguish the lessons among countries” (pp. 77-78). They also discovered that “teaching is a cultural activity,” so the systems of teaching “must be understood in relation to the cultural beliefs and assumptions that surround them” (pp. 85, 88). From this viewpoint, one of the purposes of this dissertation was to study some cultural aspects of mathematics teaching and relate the results to mathematics teaching and learning in Vietnam. Another research purpose was to carry out a video study in Vietnam to find out the characteristics of Vietnamese mathematics teaching and compare these characteristics with those of other countries. In particular, this dissertation carried out the following research tasks: - Studying the characteristics of teaching and learning in different cultures and relating the results to mathematics teaching and learning in Vietnam - Introducing the TIMSS, the TIMSS Video Study and the advantages of using video study in investigating mathematics teaching and learning - Carrying out the video study in Vietnam to identify the image, scripts and patterns, and the lesson signature of eighth-grade mathematics teaching in Vietnam - Comparing some aspects of mathematics teaching in Vietnam and other countries and identifying the similarities and differences across countries - Studying the demands and challenges of innovating mathematics teaching methods in Vietnam – lessons from the video studies Hopefully, this dissertation will be a useful reference material for pre-service teachers at education universities to understand the nature of teaching and develop their teaching career.
Magnetite is an iron oxide, which is ubiquitous in rocks and is usually deposited as small nanoparticulate matter among other rock material. It differs from most other iron oxides because it contains divalent and trivalent iron. Consequently, it has a special crystal structure and unique magnetic properties. These properties are used for paleoclimatic reconstructions where naturally occurring magnetite helps understanding former geological ages. Further on, magnetic properties are used in bio- and nanotechnological applications –synthetic magnetite serves as a contrast agent in MRI, is exploited in biosensing, hyperthermia or is used in storage media.
Magnetic properties are strongly size-dependent and achieving size control under preferably mild synthesis conditions is of interest in order to obtain particles with required properties. By using a custom-made setup, it was possible to synthesize stable single domain magnetite nanoparticles with the co-precipitation method. Furthermore, it was shown that magnetite formation is temperature-dependent, resulting in larger particles at higher temperatures. However, mechanistic approaches about the details are incomplete.
Formation of magnetite from solution was shown to occur from nanoparticulate matter rather than solvated ions. The theoretical framework of such processes has only started to be described, partly due to the lack of kinetic or thermodynamic data. Synthesis of magnetite nanoparticles at different temperatures was performed and the Arrhenius plot was used determine an activation energy for crystal growth of 28.4 kJ mol-1, which led to the conclusion that nanoparticle diffusion is the rate-determining step.
Furthermore, a study of the alteration of magnetite particles of different sizes as a function of their storage conditions is presented. The magnetic properties depend not only on particle size but also depend on the structure of the oxide, because magnetite oxidizes to maghemite under environmental conditions. The dynamics of this process have not been well described. Smaller nanoparticles are shown to oxidize more rapidly than larger ones and the lower the storage temperature, the lower the measured oxidation. In addition, the magnetic properties of the altered particles are not decreased dramatically, thus suggesting that this alteration will not impact the use of such nanoparticles as medical carriers.
Finally, the effect of biological additives on magnetite formation was investigated. Magnetotactic bacteria¬¬ are able to synthesize and align magnetite nanoparticles of well-defined size and morphology due to the involvement of special proteins with specific binding properties. Based on this model of morphology control, phage display experiments were performed to determine peptide sequences that preferably bind to (111)-magnetite faces. The aim was to control the shape of magnetite nanoparticles during the formation. Magnetotactic bacteria are also able to control the intracellular redox potential with proteins called magnetochromes. MamP is such a protein and its oxidizing nature was studied in vitro via biomimetic magnetite formation experiments based on ferrous ions. Magnetite and further trivalent oxides were found.
This work helps understanding basic mechanisms of magnetite formation and gives insight into non-classical crystal growth. In addition, it is shown that alteration of magnetite nanoparticles is mainly based on oxidation to maghemite and does not significantly influence the magnetic properties. Finally, biomimetic experiments help understanding the role of MamP within the bacteria and furthermore, a first step was performed to achieve morphology control in magnetite formation via co-precipitation.