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Both horizontal-to-vertical (H/V) spectral ratios and the spatial autocorrelation method (SPAC) have proven to be valuable tools to gain insight into local site effects by ambient noise measurements. Here, the two methods are employed to assess the subsurface velocity structure at the Piano delle Concazze area on Mt Etna. Volcanic tremor records from an array of 26 broadband seismometers is processed and a strong variability of H/V ratios during periods of increased volcanic activity is found. From the spatial distribution of H/V peak frequencies, a geologic structure in the north-east of Piano delle Concazze is imaged which is interpreted as the Ellittico caldera rim. The method is extended to include both velocity data from the broadband stations and distributed acoustic sensing data from a co-located 1.5 km long fibre optic cable. High maximum amplitude values of the resulting ratios along the trajectory of the cable coincide with known faults. The outcome also indicates previously unmapped parts of a fault. The geologic interpretation is in good agreement with inversion results from magnetic survey data. Using the neighborhood algorithm, spatial autocorrelation curves obtained from the modified SPAC are inverted alone and jointly with the H/V peak frequencies for 1D shear wave velocity profiles. The obtained models are largely consistent with published models and were able to validate the results from the fibre optic cable.
Die vorliegende Masterarbeit hat in einer Einstellungsstudie untersucht, welchen Einfluss Einstellungen gegenüber sprachlichen Varietäten und gegenüber der wahrgenommenen ethnischen Herkunft von Sprecher*innen auf die Leistungsbewertung von Schulaufsätzen haben. In Anlehnung an die Debatte um Sprachideologien wurden Einstellungen gegenüber den sprachlichen Varietäten Kiezdeutsch und dominantes Deutsch sowie, aufbauend auf Studien zur Wahrnehmung von sozialer Information über Sprecher*innen, Einstellungen gegenüber türkisch und deutsch markierten Vornamen miteinander verglichen. 157 Lehramtsstudierenden der Universität Potsdam wurde je ein fiktiver Schulaufsatz vorgelegt, der die jeweiligen Einstellungsobjekte sprachliche Varietät und ethnisch markierter Vorname enthielt. Durch einen Vergleich der individuellen Leistungsbewertung der Aufsätze wurde untersucht, welche Unterschiede sich im schulischen Kontext in der Bewertung und damit der Einstellung gegenüber bestimmten Sprecher*innen und ihrem Sprachgebrauch feststellen ließen. Die Studie ergab, dass in den fiktiven Schulaufsätzen Kiezdeutsch stärker sanktioniert wurde als dominantes Deutsch. Dieses Ergebnis konnte verstärkt beobachtet werden, wenn der Schulaufsatz vermeintlich von einer*m Sprecher*in mit türkisch markiertem Vornamen stammte. Die Ergebnisse der Studie lassen vermuten, dass eine Bewertung von Schüler*innen von einer Vorstellung darüber abhängt, wie weit oder nah entfernt der oder die betreffende Schüler*in zur sprachlichen und sozialen Norm steht.
Der internationale Standard CityGML ist zu einer zentralen Schnittstelle für die geometrische wie semantische Beschreibung von 3D-Stadtmodellen geworden. Das Institut für Geodäsie und Geoinformationstechnik (IGG) der Technischen Universität Berlin leistet mit ihren Entwicklung der 3D City Database und der Importer/Exporter Software einen entscheidenden Beitrag die Komplexität von CityGML-Daten in einer Geodatenbank intuitiv und effizient nutzen zu können. Die Software des IGG ist Open Source, unterstützte mit Oracle Spatial (ab Version 10g) aber bisher nur ein proprietäres Datenbank Management System (DBMS). Im Rahmen dieser Masterarbeit wurde eine Portierung auf die freie Datenbank-Software PostgreSQL/PostGIS vorgenommen und mit der Performanz der Oracle-Version verglichen. PostGIS gilt als eine der ausgereiftesten Geodatenbanken und wurde in diesem Jahr mit dem Release der Version 2.0 nochmals um zahlreiche Funktionen und Features (u.a. auch 3D-Unterstützung) erweitert. Die Ergebnisse des Vergleiches sowie die umfangreiche Gegenüberstellung aller verwendeten Konzepte (SQL, PL, Java) geben Aufschluss auf die Charakteristika beider räumlicher DBMS und ermöglichen einen Erkenntnisgewinn über die Projektgrenzen hinaus.
Assuming that liquid iron alloy from the outer core interacts with the solid silicate-rich lower mantle the influence on the core-mantle reflected phase PcP is studied. If the core-mantle boundary is not a sharp discontinuity, this becomes apparent in the waveform and amplitude of PcP. Iron-silicate mixing would lead to regions of partial melting with higher density which in turn reduces the velocity of seismic waves. On the basis of the calculation and interpretation of short-period synthetic seismograms, using the reflectivity and Gauss Beam method, a model space is evaluated for these ultra-low velocity zones (ULVZs). The aim of this thesis is to analyse the behaviour of PcP between 10° and 40° source distance for such models using different velocity and density configurations. Furthermore, the resolution limits of seismic data are discussed. The influence of the assumed layer thickness, dominant source frequency and ULVZ topography are analysed. The Gräfenberg and NORSAR arrays are then used to investigate PcP from deep earthquakes and nuclear explosions. The seismic resolution of an ULVZ is limited both for velocity and density contrasts and layer thicknesses. Even a very thin global core-mantle transition zone (CMTZ), rather than a discrete boundary and also with strong impedance contrasts, seems possible: If no precursor is observable but the PcP_model /PcP_smooth amplitude reduction amounts to more than 10%, a very thin ULVZ of 5 km with a first-order discontinuity may exist. Otherwise, if amplitude reductions of less than 10% are obtained, this could indicate either a moderate, thin ULVZ or a gradient mantle-side CMTZ. Synthetic computations reveal notable amplitude variations as function of the distance and the impedance contrasts. Thereby a primary density effect in the very steep-angle range and a pronounced velocity dependency in the wide-angle region can be predicted. In view of the modelled findings, there is evidence for a 10 to 13.5 km thick ULVZ 600 km south-eastern of Moscow with a NW-SE extension of about 450 km. Here a single specific assumption about the velocity and density anomaly is not possible. This is in agreement with the synthetic results in which several models create similar amplitude-waveform characteristics. For example, a ULVZ model with contrasts of -5% VP , -15% VS and +5% density explain the measured PcP amplitudes. Moreover, below SW Finland and NNW of the Caspian Sea a CMB topography can be assumed. The amplitude measurements indicate a wavelength of 200 km and a height of 1 km topography, previously also shown in the study by Kampfmann and Müller (1989). Better constraints might be provided by a joined analysis of seismological data, mineralogical experiments and geodynamic modelling.
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.
Today about 24 Million people worldwide suffer from dementia, Alzheimer’s Disease accounts for approximately 50-60% of all dementia cases. As the prevalence of dementia grows with increasing age Alzheimer’s Disease becomes more and more of an issue for society as the proportion of elderly people increases from year to year. It is well established, that the amino acid glutamate - quantitatively being the most important neurotransmitter in the central nervous system (CNS) - may reach toxic concentrations if not cleared from the synaptic cleft into which it is released during transmittance of action potentials. In Alzheimer’s Disease there is strong evidence for a generally impaired glutamate uptake system which in turn is thought to result in toxic levels of the amino acid with the potential to kill off neurons. The excitatory amino acid transporter 1 (EAAT1) belongs to the family of Na+-dependent glutamate transporter and accounts together with EAAT2 for most of the glutamate uptake in the CNS. In this project a new splice variant of EAAT1, skipping exon 3 was detected in human brain samples and subsequently called EAAT1Δ3, this being the second splice variant found after the recent detection of EAAT1Δ9. A method was developed to quantify the transcript of EAAT1 wt, EAAT1Δ3 and EAAT1Δ9 by means of real-time PCR. Samples were taken from different brain areas of a set of control and AD cases. The areas chosen for examination are affected differently in Alzheimer’s Disease, this was used an internal control for the experiments done in this project as to determine whether any effect observed is specific for AD, i.e. AD affected areas or is generally seen in all areas examined. The results of this project show that EAAT1Δ3 is transcribed in very low copy numbers making up a proportion of 0.15% of EAAT1 wt whereas EAAT1Δ9 is transcribed in a considerably large proportion of EAAT1 wt of 26.6%. It was moreover found that all EAAT1 variants are transcribed at significantly lower rates (P<0.0001) in AD cases, supporting the theory that EAAT1 protein expression is reduced to a point where glutamate uptake normally mediated by this transporter is impaired. This in turn is thought to result in toxic levels glutamate accounting for neuronal loss in the disease. No area-dependent effects were found, suggesting that the reduction of EAAT1 transcription is rather a result of an underlying general mechanism present in AD. Further research will have to be done to assess the degree of EAAT1 expression in AD and whether those future findings match with the result of this project.