Global ETD Search

21	Simulating ultracold matter : horizons and slow light Farrell, Conor January 2008 (has links) This thesis explores the links between different ways of modelling the physical world. Finite difference numerical simulations may be used to encode the behaviour of physical systems, allowing us to gain insight into their workings and even to predict their behaviour. Similarly, one can investigate the properties of gravitational black holes through the use of analogue black holes, physical systems which share at least some part of the physics of the astronomical objects. Concentrating on black hole analogues using Bose-Einstein condensates, I show how simulations of these systems may be greatly assisted through the use of a proper absorbing boundary condition, the Perfectly Matched Layer. Such a boundary condition allows the effcient truncation of the computational domain, both saving computational time and increasing accuracy. I then apply this technique to the simulation of the supersonic flow of a Bose-Einstein condensate through a Laval nozzle, a black hole analogue, showing that such a flow should be stable and observable in the laboratory. Moving to a related system, I investigate the optical analogue of the Iordanskii force - the friction resulting from interaction between excitations in a superfluid's normal component and a superfluid vortex - through the simulation of such a vortex in a Bose-Einstein condensate illuminated by slow light, which is light whose group velocity is on the order of metres per second. The interaction of the slow light with the vortex should produce a momentum transfer due to the optical Aharonov-Bohm effect, exerting a force on the vortex. The coupled system of equations describing the condensate-slow light system is simulated, giving some surprising results. 530.1
22	Multi-scale modelling of the microvasculature in the human cerebral cortex El-Bouri, Wahbi K. January 2017 (has links) Cerebrovascular diseases are by far the largest causes of death in the UK, as well as one of the leading causes of adult disability. The brain's healthy function depends on a steady supply of oxygen, delivered through the microvasculature. Cerebrovascular diseases, such as stroke and dementia, can interrupt the transport of blood (and hence oxygen) rapidly, or over a prolonged period of time. An interruption in flow can lead to ischaemia, with prolonged interruptions leading to tissue death and eventual brain damage. The microvasculature plays a key role in the transport of oxygen and nutrients to brain tissue; however, its role in diseases such as dementia is poorly understood, primarily due to the inability of current clinical imaging techniques to resolve microvessels, and due to the complexity of the underlying microvasculature. Therefore, in order to understand cerebrovascular diseases, it is necessary to be able to resolve and understand the microvasculature. In particular, generating large-scale models of the human microvasculature that can be linked back to contemporary clinical imaging is important in helping plug the current imaging gap that exists. A novel statistical model is proposed here that generates such large-scale models efficiently. Homogenization theory is used to generate a porous continuum capillary bed (characterised by its permeability) that allows for the efficient scaling up of the microvasculature. A novel order-based density-filling algorithm is then developed which generates morphologically accurate penetrating arterioles and venules, also demonstrating that the topology of the vessels only has a minor influence on CBF compared to diameter. Finally, the capillary bed and penetrating vessels are coupled into a large voxel-sized model of the microvasculature from which pressure and flux variations through the voxel can be analysed. A decoupling of the pressure and flux, as well as a layering of flow, was observed within the voxel, driven by the topology of the penetrating vessels. Micro-infarctions were also simulated, demonstrating the large local effects they have on the pressure and flux, whilst only causing a minor drop in CBF within the voxel. 610.28
23	A mathematical exploration of principles of collective cell migration and self-organisation Schumacher, Linus J. January 2015 (has links) This thesis explores the role of collective cell migration and self-organisation in the development of the embryo and in vitro tissue formation through mathematical and computational approaches. We consider how population heterogeneity, microenvironmental signals and cell-cell interactions facilitate cells to collectively organise and navigate, with the aim to work towards uncovering general rules and principles, rather than delving into the microscopic molecular details. To ensure the biological relevance of our results, we collaborate closely with experimental biologists working on two model systems. First, to understand how neural crest cells obtain directionality, maintain persistence and specialise during their migration, we use computational simulations in parallel with imaging of chick embryos under genetic and surgical perturbations. We show how only a few cells adopting a leader state that enables them to read out chemical signals can lead a population of cells in a follower state over long distances in the embryo. Furthermore, we devise and test an improved mechanism of how cells dynamically switch between leader and follower states in the presence of a chemoattractant gradient. Our computational work guides the choice of new experiments, aids in their interpretation and probes hypotheses in ways the experiments can not. Secondly, to study the self-organisation of mouse skin cells in vitro, we draw on aggregation processes and scaling theory. Dermal and epidermal cells, after being dissociated and mixed, can reconstitute functional (transplantable and hair-growing) skin in culture. Using kinetic aggregation models and scaling analysis we show that the initial clustering of epidermal cells can be described by Smoluchowski coagulation, consistent with the dynamics of the "clustering clusters" universality class. Then, we investigate a potential mechanism for the size-regulation of cell aggregates during the later stages of the skin reconstitution process. Our analysis shows the extent to which this tissue formation follows a single physical process and when the transition to different dynamics occurs, which may be triggered by cellular biochemical changes. 570.285
24	Exploiting big data in time series forecasting: A cross-sectional approach Lehner, Wolfgang, Hartmann, Claudio, Hahmann, Martin, Rosenthal, Frank 12 January 2023 (has links) Forecasting time series data is an integral component for management, planning and decision making. Following the Big Data trend, large amounts of time series data are available from many heterogeneous data sources in more and more applications domains. The highly dynamic and often fluctuating character of these domains in combination with the logistic problems of collecting such data from a variety of sources, imposes new challenges to forecasting. Traditional approaches heavily rely on extensive and complete historical data to build time series models and are thus no longer applicable if time series are short or, even more important, intermittent. In addition, large numbers of time series have to be forecasted on different aggregation levels with preferably low latency, while forecast accuracy should remain high. This is almost impossible, when keeping the traditional focus on creating one forecast model for each individual time series. In this paper we tackle these challenges by presenting a novel forecasting approach called cross-sectional forecasting. This method is especially designed for Big Data sets with a multitude of time series. Our approach breaks with existing concepts by creating only one model for a whole set of time series and requiring only a fraction of the available data to provide accurate forecasts. By utilizing available data from all time series of a data set, missing values can be compensated and accurate forecasting results can be calculated quickly on arbitrary aggregation levels. info:eu-repo/classification/ddc/005 ddc:005
25	F2DB: The Flash-Forward Database System Lehner, Wolfgang, Fischer, Ulrike, Rosenthal, Frank 29 November 2022 (has links) Forecasts are important to decision-making and risk assessment in many domains. Since current database systems do not provide integrated support for forecasting, it is usually done outside the database system by specially trained experts using forecast models. However, integrating model-based forecasting as a first-class citizen inside a DBMS speeds up the forecasting process by avoiding exporting the data and by applying database-related optimizations like reusing created forecast models. It especially allows subsequent processing of forecast results inside the database. In this demo, we present our prototype F2DB based on PostgreSQL, which allows for transparent processing of forecast queries. Our system automatically takes care of model maintenance when the underlying dataset changes. In addition, we offer optimizations to save maintenance costs and increase accuracy by using derivation schemes for multidimensional data. Our approach reduces the required expert knowledge by enabling arbitrary users to apply forecasting in a declarative way. info:eu-repo/classification/ddc/005 ddc:005
26	Semi-analytische und simulative Kreditrisikomessung synthetischer Collateralized Debt Obligations bei heterogenen Referenzportfolios / Unternehmenswertorientierte Modellentwicklung und transaktionsbezogene Modellanwendungen / Semi-Analytical and Simulative Credit Risk Measurement of Synthetic Collateralized Debt Obligations with Heterogeneous Reference Portfolios / A Modified Asset-Value Model and Transaction-Based Model Applications Jortzik, Stephan 03 March 2006 (has links) No description available. 330 Wirtschaft Economic Sciences Asset-Backed-Securities CDO CBO CLO ABS Zweckgesellschaft Zinsunterbeteiligung PROMISE KfW Banken Replenishment Unternehmenswertmodell Reduziertes Modell Zeittransformation Brownsche Brücke Ausfallschranke Fourier-Transformation Faktormodell Ausfallrisiko Kreditrisiko Risikoprämie Ratingmigration Asset-Backed Securities CDO CBO CLO ABS Special-Purpose Vehicle Interest Subparticipation PROMISE KfW Banks Replenishment Asset-Value Model Reduced-Form Model Time Transformation Brownian Bridge Default Barrier Fourier Transformation Factor Model Default Risk Credit Risk Risk Premium Rating Migration 85.30 EJBB 280: Finance portfolios investment {Mathematical economics} EJBB 300: Risk theory insurance {Mathematical economics} LCC100

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