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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.
Bolivia is one of the poorest countries in Latin America. This study analyzes whether rural poverty increases the incidence of food insecurity and whether food insecurity perpetuates the condition of poverty among the rural poor in Bolivia. In order to achieve this aim, the risks that households face and the capacity of households to implement coping strategies in order to mitigate vulnerability shocks are identified. We suggest that efforts by households to become food secure may be difficult in rural areas because of poverty and the vulnerability associated with a lack of physical assets, low levels of human capital, poor infrastructure, and poor health; as well as the precarious regional environment aggravating the severity of vulnerability to food insecurity.
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.
The complementary advantages of high-rate Global Positioning System (GPS) and accelerometer observations for measuring seismic ground motion have been recognised in previous research. Here we propose an approach of tight integration of GPS and accelerometer measurements. The baseline shifts of the accelerometer are introduced as unknown parameters and estimated by a random walk process in the Precise Point Positioning (PPP) solution. To demonstrate the performance of the new strategy, we carried out several experiments using collocated GPS and accelerometer. The experimental results show that the baseline shifts of the accelerometer are automatically corrected, and high precision coseismic information of strong ground motion can be obtained in real-time. Additionally, the convergence and precision of the PPP is improved by the combined solution.
This study aims to further mechanistically understand toxic modes of action after chronic inorganic arsenic exposure. Therefore long-term incubation studies in cultured cells were carried out, to display chronically attained changes, which cannot be observed in the generally applied in vitro short-term incubation studies. Particularly, the cytotoxic, genotoxic and epigenetic effects of an up to 21 days incubation of human urothelial (UROtsa) cells with pico- to nanomolar concentrations of iAsIII and its metabolite thio-DMAV were compared. After 21 days of incubation, cytotoxic effects were strongly enhanced in the case of iAsIII and might partly be due to glutathione depletion and genotoxic effects on the chromosomal level. These results are in strong contrast to cells exposed to thio-DMAV. Thus, cells seemed to be able to adapt to this arsenical, as indicated among others by an increase in the cellular glutathione level. Most interestingly, picomolar concentrations of both iAsIII and thio-DMAV caused global DNA hypomethylation in UROtsa cells, which was quantified in parallel by 5-medC immunostaining and a newly established, reliable, high resolution mass spectrometry (HRMS)-based test system. This is the first time that epigenetic effects are reported for thio-DMAV; iAsIII induced epigenetic effects occur in at least 8000 fold lower concentrations as reported in vitro before. The fact that both arsenicals cause DNA hypomethylation at really low, exposure-relevant concentrations in human urothelial cells suggests that this epigenetic effect might contribute to inorganic arsenic induced carcinogenicity, which for sure has to be further investigated in future studies.
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.
Dieser Artikel adressiert zwei bisher nur wenig untersuchte Aspekte der Führungsforschung: Führungsverhalten im öffentlichen Sektor und Faktoren die Führungsverhalten beeinflussen. Mittels einer Fallstudie in der Bundesagentur für Arbeit werden explorativ Hypothesen über Einflussfaktoren des Führungsverhaltens aufgestellt. Die Studie kommt zu der Erkenntnis, dass eine oftmals angenommene Führungslücke im öffentlichen Sektor nicht bestätigt werden kann. Für das ausgeprägte Führungsverhalten, das in der Fallstudie beobachtet wurde, wird als Determinante die besondere Ausgestaltung des Managementsystems der Bundesagentur für Arbeit verantwortlich gemacht. Dazu gehört unter anderem das Performance Management System sowie die Führungskräfteauswahl und -entwicklung. Die Arbeit schließt mit Empfehlungen für weitere Forschungsansätze auf dem Gebiet der Führungsforschung im öffentlichen Sektor.