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Spatio-temporal data denotes a category of data that contains spatial as well as temporal components. For example, time-series of geo-data, thematic maps that change over time, or tracking data of moving entities can be interpreted as spatio-temporal data.
In today's automated world, an increasing number of data sources exist, which constantly generate spatio-temporal data. This includes for example traffic surveillance systems, which gather movement data about human or vehicle movements, remote-sensing systems, which frequently scan our surroundings and produce digital representations of cities and landscapes, as well as sensor networks in different domains, such as logistics, animal behavior study, or climate research.
For the analysis of spatio-temporal data, in addition to automatic statistical and data mining methods, exploratory analysis methods are employed, which are based on interactive visualization. These analysis methods let users explore a data set by interactively manipulating a visualization, thereby employing the human cognitive system and knowledge of the users to find patterns and gain insight into the data.
This thesis describes a software framework for the visualization of spatio-temporal data, which consists of GPU-based techniques to enable the interactive visualization and exploration of large spatio-temporal data sets. The developed techniques include data management, processing, and rendering, facilitating real-time processing and visualization of large geo-temporal data sets. It includes three main contributions:
- Concept and Implementation of a GPU-Based Visualization Pipeline.
The developed visualization methods are based on the concept of a GPU-based visualization pipeline, in which all steps -- processing, mapping, and rendering -- are implemented on the GPU. With this concept, spatio-temporal data is represented directly in GPU memory, using shader programs to process and filter the data, apply mappings to visual properties, and finally generate the geometric representations for a visualization during the rendering process. Data processing, filtering, and mapping are thereby executed in real-time, enabling dynamic control over the mapping and a visualization process which can be controlled interactively by a user.
- Attributed 3D Trajectory Visualization.
A visualization method has been developed for the interactive exploration of large numbers of 3D movement trajectories. The trajectories are visualized in a virtual geographic environment, supporting basic geometries such as lines, ribbons, spheres, or tubes. Interactive mapping can be applied to visualize the values of per-node or per-trajectory attributes, supporting shape, height, size, color, texturing, and animation as visual properties. Using the dynamic mapping system, several kind of visualization methods have been implemented, such as focus+context visualization of trajectories using interactive density maps, and space-time cube visualization to focus on the temporal aspects of individual movements.
- Geographic Network Visualization.
A method for the interactive exploration of geo-referenced networks has been developed, which enables the visualization of large numbers of nodes and edges in a geographic context. Several geographic environments are supported, such as a 3D globe, as well as 2D maps using different map projections, to enable the analysis of networks in different contexts and scales. Interactive filtering, mapping, and selection can be applied to analyze these geographic networks, and visualization methods for specific types of networks, such as coupled 3D networks or temporal networks have been implemented.
As a demonstration of the developed visualization concepts, interactive visualization tools for two distinct use cases have been developed. The first contains the visualization of attributed 3D movement trajectories of airplanes around an airport. It allows users to explore and analyze the trajectories of approaching and departing aircrafts, which have been recorded over the period of a month. By applying the interactive visualization methods for trajectory visualization and interactive density maps, analysts can derive insight from the data, such as common flight paths, regular and irregular patterns, or uncommon incidents such as missed approaches on the airport.
The second use case involves the visualization of climate networks, which are geographic networks in the climate research domain. They represent the dynamics of the climate system using a network structure that expresses statistical interrelationships between different regions. The interactive tool allows climate analysts to explore these large networks, analyzing the network's structure and relating it to the geographic background. Interactive filtering and selection enables them to find patterns in the climate data and identify e.g. clusters in the networks or flow patterns.
As a result of CMOS scaling, radiation-induced Single-Event Effects (SEEs) in electronic circuits became a critical reliability issue for modern Integrated Circuits (ICs) operating under harsh radiation conditions. SEEs can be triggered in combinational or sequential logic by the impact of high-energy particles, leading to destructive or non-destructive faults, resulting in data corruption or even system failure. Typically, the SEE mitigation methods are deployed statically in processing architectures based on the worst-case radiation conditions, which is most of the time unnecessary and results in a resource overhead. Moreover, the space radiation conditions are dynamically changing, especially during Solar Particle Events (SPEs). The intensity of space radiation can differ over five orders of magnitude within a few hours or days, resulting in several orders of magnitude fault probability variation in ICs during SPEs. This thesis introduces a comprehensive approach for designing a self-adaptive fault resilient multiprocessing system to overcome the static mitigation overhead issue. This work mainly addresses the following topics: (1) Design of on-chip radiation particle monitor for real-time radiation environment detection, (2) Investigation of space environment predictor, as support for solar particle events forecast, (3) Dynamic mode configuration in the resilient multiprocessing system. Therefore, according to detected and predicted in-flight space radiation conditions, the target system can be configured to use no mitigation or low-overhead mitigation during non-critical periods of time. The redundant resources can be used to improve system performance or save power. On the other hand, during increased radiation activity periods, such as SPEs, the mitigation methods can be dynamically configured appropriately depending on the real-time space radiation environment, resulting in higher system reliability. Thus, a dynamic trade-off in the target system between reliability, performance and power consumption in real-time can be achieved. All results of this work are evaluated in a highly reliable quad-core multiprocessing system that allows the self-adaptive setting of optimal radiation mitigation mechanisms during run-time. Proposed methods can serve as a basis for establishing a comprehensive self-adaptive resilient system design process. Successful implementation of the proposed design in the quad-core multiprocessor shows its application perspective also in the other designs.
Pichia pastoris (syn. Komagataella phaffi) is a distinguished expression system widely used in industrial production processes. Recent molecular research has focused on numerous approaches to increase recombinant protein yield in P. pastoris. For example, the design of expression vectors and synthetic genetic elements, gene copy number optimization, or co-expression of helper proteins
(transcription factors, chaperones, etc.). However, high clonal variability of transformants and low screening throughput have hampered significant success.
To enhance screening capacities, display-based methodologies inherit the potential for efficient isolation of producer clones via fluorescence-activated cell sorting (FACS). Therefore, this study focused on developing a novel clone selection method that is based on the non-covalent attachment of Fab fragments on the P. pastoris cell surface to be applicable for FACS.
Initially, a P. pastoris display system was developed, which is a prerequisite for the surface capture of secreted Fabs. A Design of Experiments approach was applied to analyze the influence of various genetic elements on antibody fragment display. The combined P. pastoris formaldehyde dehydrogenase promoter (PFLD1), Saccharomyces cerevisiae invertase 2 signal peptide (ScSUC2), - agglutinin (ScSAG1) anchor protein, and the ARS of Kluyveromyces lactis (panARS) conferred highest display levels.
Subsequently, eight single-chain variable fragments (scFv) specific for the constant part of the Fab heavy or light chain were individually displayed in P. pastoris. Among the tested scFvs, the anti-human CH1 IgG domain scFv allowed the most efficient Fab capture detected by flow cytometry.
Irrespective of the Fab sequence, exogenously added as well as simultaneously secreted Fabs were successfully captured on the cell surface. Furthermore, Fab secretion capacities were shown to correlate to the level of surface-bound Fabs as demonstrated for characterized producer clones.
Flow-sorted clones presenting high amounts of Fabs showed an increase in median Fab titers (factor of 21 to 49) compared to unsorted clones when screened in deep-well plates. For selected candidates, improved functional Fab yields of sorted cells vs. unsorted cells were confirmed in an upscaled shake flask production. Since the scFv capture matrix was encoded on an episomal plasmid with inherently unstable autonomously replicating sequences (ARS), efficient plasmid curing was observed after removing the selective pressure. Hence, sorted clones could be immediately used for production without the need to modify the expression host or vector. The resulting switchable display/secretion system provides a streamlined approach for the isolation of Fab producers and subsequent Fab production.
This thesis is focused on the electronic, spin-dependent and dynamical properties of thin magnetic systems. Photoemission-related techniques are combined with synchrotron radiation to study the spin-dependent properties of these systems in the energy and time domains. In the first part of this thesis, the strength of electron correlation effects in the spin-dependent electronic structure of ferromagnetic bcc Fe(110) and hcp Co(0001) is investigated by means of spin- and angle-resolved photoemission spectroscopy. The experimental results are compared to theoretical calculations within the three-body scattering approximation and within the dynamical mean-field theory, together with one-step model calculations of the photoemission process. From this comparison it is demonstrated that the present state of the art many-body calculations, although improving the description of correlation effects in Fe and Co, give too small mass renormalizations and scattering rates thus demanding more refined many-body theories including nonlocal fluctuations. In the second part, it is shown in detail monitoring by photoelectron spectroscopy how graphene can be grown by chemical vapour deposition on the transition-metal surfaces Ni(111) and Co(0001) and intercalated by a monoatomic layer of Au. For both systems, a linear E(k) dispersion of massless Dirac fermions is observed in the graphene pi-band in the vicinity of the Fermi energy. Spin-resolved photoemission from the graphene pi-band shows that the ferromagnetic polarization of graphene/Ni(111) and graphene/Co(0001) is negligible and that graphene on Ni(111) is after intercalation of Au spin-orbit split by the Rashba effect. In the last part, a time-resolved x-ray magnetic circular dichroic-photoelectron emission microscopy study of a permalloy platelet comprising three cross-tie domain walls is presented. It is shown how a fast picosecond magnetic response in the precessional motion of the magnetization can be induced by means of a laser-excited photoswitch. From a comparision to micromagnetic calculations it is demonstrated that the relatively high precessional frequency observed in the experiments is directly linked to the nature of the vortex/antivortex dynamics and its response to the magnetic perturbation. This includes the time-dependent reversal of the vortex core polarization, a process which is beyond the limit of detection in the present experiments.
A phagocyte-specific Irf8 gene enhancer establishes early conventional dendritic cell commitment
(2011)
Haematopoietic development is a complex process that is strictly hierarchically organized. Here, the phagocyte lineages are a very heterogeneous cell compartment with specialized functions in innate immunity and induction of adaptive immune responses. Their generation from a common precursor must be tightly controlled. Interference within lineage formation programs for example by mutation or change in expression levels of transcription factors (TF) is causative to leukaemia. However, the molecular mechanisms driving specification into distinct phagocytes remain poorly understood. In the present study I identify the transcription factor Interferon Regulatory Factor 8 (IRF8) as the specification factor of dendritic cell (DC) commitment in early phagocyte precursors. Employing an IRF8 reporter mouse, I showed the distinct Irf8 expression in haematopoietic lineage diversification and isolated a novel bone marrow resident progenitor which selectively differentiates into CD8α+ conventional dendritic cells (cDCs) in vivo. This progenitor strictly depends on Irf8 expression to properly establish its transcriptional DC program while suppressing a lineage-inappropriate neutrophile program. Moreover, I demonstrated that Irf8 expression during this cDC commitment-step depends on a newly discovered myeloid-specific cis-enhancer which is controlled by the haematopoietic transcription factors PU.1 and RUNX1. Interference with their binding leads to abrogation of Irf8 expression, subsequently to disturbed cell fate decisions, demonstrating the importance of these factors for proper phagocyte cell development. Collectively, these data delineate a transcriptional program establishing cDC fate choice with IRF8 in its center.
The spread of shrubs in Namibian savannas raises questions about the resilience of these ecosystems to global change. This makes it necessary to understand the past dynamics of the vegetation, since there is no consensus on whether shrub encroachment is a new phenomenon, nor on its main drivers. However, a lack of long-term vegetation datasets for the region and the scarcity of suitable palaeoecological archives, makes reconstructing past vegetation and land cover of the savannas a challenge.
To help meet this challenge, this study addresses three main research questions: 1) is pollen analysis a suitable tool to reflect the vegetation change associated with shrub encroachment in savanna environments? 2) Does the current encroached landscape correspond to an alternative stable state of savanna vegetation? 3) To what extent do pollen-based quantitative vegetation reconstructions reflect changes in past land cover?
The research focuses on north-central Namibia, where despite being the region most affected by shrub invasion, particularly since the 21st century, little is known about the dynamics of this phenomenon.
Field-based vegetation data were compared with modern pollen data to assess their correspondence in terms of composition and diversity along precipitation and grazing intensity gradients. In addition, two sediment cores from Lake Otjikoto were analysed to reveal changes in vegetation composition that have occurred in the region over the past 170 years and their possible drivers. For this, a multiproxy approach (fossil pollen, sedimentary ancient DNA (sedaDNA), biomarkers, compound specific carbon (δ13C) and deuterium (δD) isotopes, bulk carbon isotopes (δ13Corg), grain size, geochemical properties) was applied at high taxonomic and temporal resolution. REVEALS modelling of the fossil pollen record from Lake Otjikoto was run to quantitatively reconstruct past vegetation cover. For this, we first made pollen productivity estimates (PPE) of the most relevant savanna taxa in the region using the extended R-value model and two pollen dispersal options (Gaussian plume model and Lagrangian stochastic model). The REVEALS-based vegetation reconstruction was then validated using remote sensing-based regional vegetation data.
The results show that modern pollen reflects the composition of the vegetation well, but diversity less well. Interestingly, precipitation and grazing explain a significant amount of the compositional change in the pollen and vegetation spectra. The multiproxy record shows that a state change from open Combretum woodland to encroached Terminalia shrubland can occur over a century, and that the transition between states spans around 80 years and is characterized by a unique vegetation composition. This transition is supported by gradual environmental changes induced by management (i.e. broad-scale logging for the mining industry, selective grazing and reduced fire activity associated with intensified farming) and related land-use change. Derived environmental changes (i.e. reduced soil moisture, reduced grass cover, changes in species composition and competitiveness, reduced fire intensity) may have affected the resilience of Combretum open woodlands, making them more susceptible to change to an encroached state by stochastic events such as consecutive years of precipitation and drought, and by high concentrations of pCO2. We assume that the resulting encroached state was further stabilized by feedback mechanisms that favour the establishment and competitiveness of woody vegetation.
The REVEALS-based quantitative estimates of plant taxa indicate the predominance of a semi-open landscape throughout the 20th century and a reduction in grass cover below 50% since the 21st century associated with the spread of encroacher woody taxa. Cover estimates show a close match with regional vegetation data, providing support for the vegetation dynamics inferred from multiproxy analyses. Reasonable PPEs were made for all woody taxa, but not for Poaceae.
In conclusion, pollen analysis is a suitable tool to reconstruct past vegetation dynamics in savannas. However, because pollen cannot identify grasses beyond family level, a multiproxy approach, particularly the use of sedaDNA, is required. I was able to separate stable encroached states from mere woodland phases, and could identify drivers and speculate about related feedbacks. In addition, the REVEALS-based quantitative vegetation reconstruction clearly reflects the magnitude of the changes in the vegetation cover that occurred during the last 130 years, despite the limitations of some PPEs.
This research provides new insights into pollen-vegetation relationships in savannas and highlights the importance of multiproxy approaches when reconstructing past vegetation dynamics in semi-arid environments. It also provides the first time series with sufficient taxonomic resolution to show changes in vegetation composition during shrub encroachment, as well as the first quantitative reconstruction of past land cover in the region. These results help to identify the different stages in savanna dynamics and can be used to calibrate predictive models of vegetation change, which are highly relevant to land management.