Refine
Has Fulltext
- yes (13) (remove)
Year of publication
- 2009 (13) (remove)
Document Type
- Master's Thesis (13) (remove)
Keywords
- 20. Jahrhundert (1)
- 20th century (1)
- Affectivity (1)
- Affektivität (1)
- African Religion (1)
- African Union (1)
- Altersstrukturen (1)
- Anderson (1)
- Arabidopsis thaliana (1)
- Argentina (1)
- Argentinien (1)
- August Stramm (1)
- Ausbreitung (1)
- Buchform (1)
- Bühnenform (1)
- Casimir effect (1)
- Casimir-Effekt (1)
- Casimir-Polder Wechselwirkung (1)
- Casimir-Polder interaction (1)
- Chaos (1)
- Complex networks (1)
- Conversation Analysis (1)
- Cuba (1)
- DDR-Literatur (1)
- Datenanalyse (1)
- Disorder (1)
- Dokumentarliteratur (1)
- Drama (1)
- ECOWAS (1)
- Emotion (1)
- Erzählung (1)
- European Union (1)
- European-African relations (1)
- Europäisch-Afrikanische Beziehungen (1)
- Europäische Union (1)
- Expressionismus (1)
- Frauenliteratur (1)
- Frequenz (1)
- Graphentheorie (1)
- Interactional Linguistics (1)
- Interaktionale Linguistik (1)
- Klimadaten (1)
- Klimanetzwerke (1)
- Komplexe Netzwerke (1)
- Konversationsanalyse (1)
- Kuba (1)
- Localization (1)
- Lokalisierung (1)
- Maxie Wander (1)
- Metal (1)
- Metall (1)
- Militärgeschichte (1)
- Natürlichkeit (1)
- New Public Management (1)
- Orisha (1)
- Personalmanagement (1)
- Protokoll-Literatur (1)
- Santeria (1)
- Schnittstelle Phonologie/Morphologie (1)
- Spiritismus (1)
- Spracherwerb (1)
- Spreading (1)
- Statistikprogramm R (1)
- Storytelling (1)
- Supraleiter (1)
- Unordnung (1)
- Vacuum interaction (1)
- Vakuumwechselwirkung (1)
- Verwaltung (1)
- Yoruba (1)
- age structure (1)
- animated PCA (1)
- animierte PCA (1)
- artificial language (1)
- civil service (1)
- climate data (1)
- climate networks (1)
- cultural identity (1)
- data analysis (1)
- frequency (1)
- graph theory (1)
- human resources management (1)
- international relations (1)
- internationale Beziehungen (1)
- irregular Migration (1)
- irreguläre Migration (1)
- kulturelle Identität (1)
- künstliche Sprache (1)
- language acquisition (1)
- military history (1)
- national identity (1)
- nationale Identität (1)
- naturalness (1)
- new public management (1)
- phonology-morphology interface (1)
- statistics program R (1)
- strategic management (1)
- superconductor (1)
- Öffentlicher Dienst (1)
Diese Arbeit umfasst die Archivierung, Visualisierung anhand bioinformatischer Methoden und Interpretation eines vorhandenen Messdatensatz (Element [ICP-MS]-, Ionen [IC]- und Metabolitdaten [RP-HPLC und GC/TOF-MS]) der Pflanze Arabidopsis thaliana getrennt in Blätter und Wurzeln. Die Pflanzen wurden den sechs Mangelsituationen der Nährstoffe Eisen, Kalium, Magnesium, Stickstoff, Phosphor und Schwefel ausgesetzt und zu neun Messzeitpunkten [0.5-, 1-, 2-, 3-, 4-, 5-, 6-, 7-in Tagen und „resupply“ (vier Stunden nach dem vierten Tag)] analysiert. Es erfolgte die Integration der Messdaten in eine SQlite-Datenbank. Die Veranschaulichung erfolgte mit Hilfe der Programmiersprache R. Anhand einiger Pakete zur Erweiterung des Funktionsumfangs von R wurde erstens eine Schnittstelle zur SQLite- Datenbank hergestellt, was ein Abfragen an diese ermöglichte und zweitens verhalfen sie zu der Erstellung einer Reihe zusätzlicher Darstellungsformen (Heatmap, Wireframe, PCA). Selbstgeschriebene Skripte erlaubten den Datenzugriff und die grafische Ausgabe als z. B. Heatmaps. In der Entstehung dieser Arbeit sind weiterhin zwei weitere Visualisierungsformen von PCA-Daten entwickelt worden: Das Abstandsdiagramm und die animierte PCA. Beides sind hilfreiche Werkzeuge zur Interpretation von PCA-Plots eines zeitlichen Verlaufes. Anhand der Darstellungen der Element- und Ionendaten ließen sich die Nährstoffmangelsituationen durch Abnahme der entsprechenden Totalelemente und Ionen nachweisen. Weiterhin sind starke Ähnlichkeiten der durch RP-HPLC bestimmten Metaboliten unter Eisen-, Kalium und Magnesiummangel erkannt worden. Allerdings gibt es nur eine geringe Anzahl an Interkationen der Metabolitgehalte, da der Großteil der Metabolitlevel im Vergleich zur Kontrolle unverändert blieb. Der Literaturvergleich mit zwei Publikationen, die den Phosphat- und Schwefelmangel in Arabidopsis thaliana untersuchten, zeigte ein durchwachsenes Ergebnis. Einerseits gab es eine gleiche Tendenz der verglichenen Aminosäuren zu verzeichen, aber andererseits wiesen die Visualisierungen auch Gegensätzlichkeiten auf. Der Vergleich der mit RP-HPLC und GC/TOF-MS gemessenen Metaboliten erbrachte ein sehr kontroverses Ergebnis. Zum einen wurden Übereinstimmungen der gleichen Metaboliten durch gemeinsame Cluster in den Heatmaps beobachtet, zum anderen auch Widersprüche, exemplarisch in den Abstandsdiagrammen der Blätterdaten jedes Verfahrens, in welchen unterschiedliche Abstandshöhepunkte erkennbar sind.
The acquisition of phonological alternations consists of many aspects as discussions in the relevant literature show. There are contrary findings about the role of naturalness. A natural process is grounded in phonetics; they are easy to learn, even in second language acquisition when adults have to learn certain processes that do not occur in their native language. There is also evidence that unnatural – arbitrary – rules can be learned. Current work on the acquisition of morphophonemic alternations suggests that their probability of occurrence is a crucial factor in acquisition. I have conducted an experiment to investigate the effects of naturalness as well as of probability of occurrence with 80 adult native speakers of German. It uses the Artificial Grammar paradigm: Two artificial languages were constructed, each with a particular alternation. In one language the alternation is natural (vowel harmony); in the other language the alternation is arbitrary (a vowel alternation depends on the sonorancy of the first consonant of the stem). The participants were divided in two groups, one group listened to the natural alternation and the other group listened to the unnatural alternation. Each group was divided into two subgroups. One subgroup then was presented with material in which the alternation occurred frequently and the other subgroup was presented with material in which the alternation occurred infrequently. After this exposure phase every participant was asked to produce new words during the test phase. Knowledge about the language-specific alternation pattern was needed to produce the forms correctly as the phonological contexts demanded certain alternants. The group performances have been compared with respect to the effects of naturalness and probability of occurrence. The natural rule was learned more easily than the unnatural one. Frequently presented rules were not learned more easily than the ones that were presented less frequently. Moreover, participants did not learn the unnatural rule at all, whether this rule was presented frequently or infrequently did not matter. There was a tendency that the natural rule was learned more easily if presented frequently than if presented infrequently, but it was not significant due to variability across participants.
Complex network theory provides an elegant and powerful framework to statistically investigate the topology of local and long range dynamical interrelationships, i.e., teleconnections, in the climate system. Employing a refined methodology relying on linear and nonlinear measures of time series analysis, the intricate correlation structure within a multivariate climatological data set is cast into network form. Within this graph theoretical framework, vertices are identified with grid points taken from the data set representing a region on the the Earth's surface, and edges correspond to strong statistical interrelationships between the dynamics on pairs of grid points. The resulting climate networks are neither perfectly regular nor completely random, but display the intriguing and nontrivial characteristics of complexity commonly found in real world networks such as the internet, citation and acquaintance networks, food webs and cortical networks in the mammalian brain. Among other interesting properties, climate networks exhibit the "small-world" effect and possess a broad degree distribution with dominating super-nodes as well as a pronounced community structure. We have performed an extensive and detailed graph theoretical analysis of climate networks on the global topological scale focussing on the flow and centrality measure betweenness which is locally defined at each vertex, but includes global topological information by relying on the distribution of shortest paths between all pairs of vertices in the network. The betweenness centrality field reveals a rich internal structure in complex climate networks constructed from reanalysis and atmosphere-ocean coupled general circulation model (AOGCM) surface air temperature data. Our novel approach uncovers an elaborately woven meta-network of highly localized channels of strong dynamical information flow, that we relate to global surface ocean currents and dub the backbone of the climate network in analogy to the homonymous data highways of the internet. This finding points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). Carefully comparing the backbone structures detected in climate networks constructed using linear Pearson correlation and nonlinear mutual information, we argue that the high sensitivity of betweenness with respect to small changes in network structure may allow to detect the footprints of strongly nonlinear physical interactions in the climate system. The results presented in this thesis are thoroughly founded and substantiated using a hierarchy of statistical significance tests on the level of time series and networks, i.e., by tests based on time series surrogates as well as network surrogates. This is particularly relevant when working with real world data. Specifically, we developed new types of network surrogates to include the additional constraints imposed by the spatial embedding of vertices in a climate network. Our methodology is of potential interest for a broad audience within the physics community and various applied fields, because it is universal in the sense of being valid for any spatially extended dynamical system. It can help to understand the localized flow of dynamical information in any such system by combining multivariate time series analysis, a complex network approach and the information flow measure betweenness centrality. Possible fields of application include fluid dynamics (turbulence), plasma physics and biological physics (population models, neural networks, cell models). Furthermore, the climate network approach is equally relevant for experimental data as well as model simulations and hence introduces a novel perspective on model evaluation and data driven model building. Our work is timely in the context of the current debate on climate change within the scientific community, since it allows to assess from a new perspective the regional vulnerability and stability of the climate system while relying on global and not only on regional knowledge. The methodology developed in this thesis hence has the potential to substantially contribute to the understanding of the local effect of extreme events and tipping points in the earth system within a holistic global framework.