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During reading oculomotor processes guide the eyes over the text. The visual information recorded is accessed, evaluated and processed. Only by retrieving the meaning of a word from the long-term memory, as well as through the connection and storage of the information about each individual word, is it possible to access the semantic meaning of a sentence. Therefore memory, and here in particular working memory, plays a pivotal role in the basic processes of reading. The following dissertation investigates to what extent different demands on memory and memory capacity have an effect on eye movement behavior while reading. The frequently used paradigm of the reading span task, in which test subjects read and evaluate individual sentences, was used for the experimental review of the research questions. The results speak for the fact that working memory processes have a direct effect on various eye movement measurements. Thus a high working memory load, for example, reduced the perceptual span while reading. The lower the individual working memory capacity of the reader was, the stronger was the influence of the working memory load on the processing of the sentence.
The past climate in central Asia, and especially on the Tibetan Plateau (TP), is of great importance for an understanding of global climate processes and for predicting the future climate. As a major influence on the climate in this region, the Asian Summer Monsoon (ASM) and its evolutionary history are of vital importance for accurate predictions. However, neither the evolutionary pattern of the summer monsoon nor the driving mechanisms behind it are yet clearly understood. For this research, I first synthesized previously published Late Glacial to Holocene climatic records from monsoonal central Asia in order to extract the general climate signals and the associated summer monsoon intensities. New climate and vegetation sequences were then established using improved quantitative methods, focusing on fossil pollen records recovered from Tibetan lakes and also incorporating new modern datasets. The pollen-vegetation and vegetation-climate relationships on the TP were also evaluated in order to achieve a better understanding of fossil pollen records. The synthesis of previously published moisture-related palaeoclimate records in monsoonal central Asia revealed generally different temporal patterns for the two monsoonal subsystems, i.e. the Indian Summer Monsoon (ISM) and East Asian Summer Monsoon (EASM). The ISM appears to have experienced maximum wet conditions during the early Holocene, while many records from the area affected by the EASM indicate relatively dry conditions at that time, particularly in north-central China where the maximum moisture levels occurred during the middle Holocene. A detailed consideration of possible driving factors affecting the summer monsoon, including summer solar insolation and sea surface temperatures, revealed that the ISM was primarily driven by variations in northern hemisphere solar insolation, and that the EASM may have been constrained by the ISM resulting in asynchronous patterns of evolution for these two subsystems. This hypothesis is further supported by modern monsoon indices estimated using the NCEP/NCAR Reanalysis data from the last 50 years, which indicate a significant negative correlation between the two summer monsoon subsystems. By analogy with the early Holocene, intensification of the ISM during coming decades could lead to increased aridification elsewhere as a result of the asynchronous nature of the monsoon subsystems, as can already be observed in the meteorological data from the last 15 years. A quantitative climate reconstruction using fossil pollen records was achieved through analysis of sediment core recovered from Lake Donggi Cona (in the north-eastern part of the TP) which has been dated back to the Last Glacial Maximum (LGM). A new data-set of modern pollen collected from large lakes in arid to semi-arid regions of central Asia is also presented herein. The concept of "pollen source area" was introduced to modern climate calibration based on pollen from large lakes, and was applied to the fossil pollen sequence from Lake Donggi Cona. Extremely dry conditions were found to have dominated the LGM, and a subsequent gradually increasing trend in moisture during the Late Glacial period was terminated by an abrupt reversion to a dry phase that lasted for about 1000 years and coincided with the first Heinrich Event of the northern Atlantic region. Subsequent periods corresponding to the warm Bølling-Allerød period and the Younger Dryas cold event were followed by moist conditions during the early Holocene, with annual precipitation of up to about 400 mm. A slightly drier trend after 9 cal ka BP was then followed by a second wet phase during the middle Holocene that lasted until 4.5 cal ka BP. Relatively steady conditions with only slight fluctuations then dominated the late Holocene, resulting in the present climatic conditions. In order to investigate the relationship between vegetation and climate, temporal variations in the possible driving factors for vegetation change on the northern TP were examined using a high resolution late Holocene pollen record from Lake Kusai. Moving-window Redundancy Analyses (RDAs) were used to evaluate the correlations between pollen assemblages and individual sedimentary proxies. These analyses have revealed frequent fluctuations in the relative abundances of alpine steppe and alpine desert components, and in particular a decrease in the total vegetation cover at around 1500 cal a BP. The climate was found to have had an important influence on vegetation changes when conditions were relatively wet and stable. However, after the 1500 cal a BP threshold in vegetation cover was crossed the vegetation appears to have been affected more by extreme events such as dust storms or fluvial erosion than by the general climatic trends. In addition, pollen spectra over the last 600 years have been revealed by Procrustes analysis to be significantly different from those recovered from older samples, which is attributed to an increased human impact that resulted in unprecedented changes to the composition of the vegetation. Theoretical models that have been developed and widely applied to the European area (i.e. the Extended R-Value (ERV) model and the Regional Estimates of Vegetation Abundance from Large Sites (REVEALS) model) have been applied to the high alpine TP ecosystems in order to investigate the pollen-vegetation relationships, as well as for quantitative reconstructions of vegetation abundance. The modern pollen–vegetation relationships for four common pollen species on the TP have been investigated using Poaceae as the reference taxa. The ERV Submodel 2 yielded relatively high PPEs for the steppe and desert taxa (Artemisia Chenopodiaceae), and low PPEs for the Cyperaceae that are characteristic of the alpine Kobresia meadows. The plant abundances on the central and north-eastern TP were quantified by applying these PPEs to four post-Late Glacial fossil pollen sequences. The reconstructed vegetation assemblages for the four pollen sequences always yielded smaller compositional species turnovers than suggested by the pollen spectra, indicating that the strength of the previously-reported vegetation changes may therefore have been overestimated. In summary, the key findings of this thesis are that (a) the two ASM subsystems show asynchronous patterns during both the Holocene and modern time periods, (b) fossil pollen records from large lakes reflect regional signals for which the pollen source areas need to be taken into account, (c) climate is not always the main driver for vegetation change, and (d) previously reported vegetation changes on the TP may have been overestimated because they ignored inter-species variations in pollen productivity.
Cognitive psychology is traditionally interested in the interaction of perception, cognition, and behavioral control. Investigating eye movements in reading constitutes a field of research in which the processes and interactions of these subsystems can be studied in a well-defined environment. Thereby, the following questions are pursued: How much information is visually perceived during a fixation, how is processing achieved and temporally coordinated from visual letter encoding to final sentence comprehension, and how do such processes reflect on behavior such as the control of the eyes’ movements during reading. Various theoretical models have been proposed to account for the specific eye-movement behavior in reading (for a review see Reichle, Rayner, & Pollatsek, 2003). Some models are based on the idea of shifting attention serially from one word to the next within the sentence whereas others propose distributed attention allocating processing resources to more than one word at a time. As attention is assumed to drive word recognition processes one major difference between these models is that word processing must either occur in strict serial order, or that word processing is achieved in parallel. In spite of this crucial difference in the time course of word processing, both model classes perform well on explaining many of the benchmark effects in reading. In fact, there seems to be not much empirical evidence that challenges the models to a point at which their basic assumptions could be falsified. One issue often perceived as being decisive in the debate on serial and parallel word processing is how not-yet-fixated words to the right of fixation affect eye movements. Specifically, evidence is discussed as to what spatial extent such parafoveal words are previewed and how this influences current and subsequent word processing. Four experiments investigated parafoveal processing close to the spatial limits of the perceptual span. The present work aims to go beyond mere existence proofs of previewing words at such spatial distances. Introducing a manipulation that dissociates the sources of long-range preview effects, benefits and costs of parafoveal processing can be investigated in a single analysis and the differing impact is tracked across a three-word target region. In addition, the same manipulation evaluates the role of oculomotor error as the cause of non-local distributed effects. In this respect, the results contribute to a better understanding of the time course of word processing inside the perceptual span and attention allocation during reading.
In this work new fluorinated and non-fluorinated mono- and bifunctional trithiocarbonates of the structure Z-C(=S)-S-R and Z-C(=S)-S-R-S-C(=S)-Z were synthesized for the use as chain transfer agents (CTAs) in the RAFT-process. All newly synthesized CTAs were tested for their efficiency to moderate the free radical polymerization process by polymerizing styrene (M3). Besides characterization of the homopolymers by GPC measurements, end- group analysis of the synthesized block copolymers via 1H-, 19F-NMR, and in some cases also UV-vis spectroscopy, were performed attaching suitable fluorinated moieties to the Z- and/or R-groups of the CTAs. Symmetric triblock copolymers of type BAB and non-symmetric fluorine end- capped polymers were accessible using the RAFT process in just two or one polymerization step. In particular, the RAFT-process enabled the controlled polymerization of hydrophilic monomers such as N-isopropylacrylamide (NIPAM) (M1) as well as N-acryloylpyrrolidine (NAP) (M2) for the A-blocks and of the hydrophobic monomers styrene (M3), 2-fluorostyrene (M4), 3-fluorostyrene (M5), 4-fluorostyrene (M6) and 2,3,4,5,6-pentafluorostyrene (M7) for the B-blocks. The properties of the BAB-triblock copolymers were investigated in dilute, concentrated and highly concentrated aqueous solutions using DLS, turbidimetry, 1H- and 19F-NMR, rheology, determination of the CMC, foam height- and surface tension measurements and microscopy. Furthermore, their ability to stabilize emulsions and microemulsions and the wetting behaviour of their aqueous solutions on different substrates was investigated. The behaviour of the fluorine end-functionalized polymers to form micelles was studied applying DLS measurements in diluted organic solution. All investigated BAB-triblock copolymers were able to form micelles and show surface activity at room temperature in dilute aqueous solution. The aqueous solutions displayed moderate foam formation. With different types and concentrations of oils, the formation of emulsions could be detected using a light microscope. A boosting effect in microemulsions could not be found adding BAB-triblock copolymers. At elevated polymer concentrations, the formation of hydrogels was proved applying rheology measurements.
Plant growth and survival depend on photosynthesis in the leaves. This involves the uptake of carbon dioxide from the atmosphere and the simultaneous capture of light energy to produce organic molecules, which enter metabolism and are converted to many other compounds which then serve as building blocks for biomass growth. Leaves are organs specialised for photosynthetic carbon dioxide fixation. The function of leaves involves many trade-offs which must be optimised in order to achieve effective use of resources and maximum photosynthesis. It is known that the morphology of leaves adjusts to the growth environment of plants and this is important for optimising their function for photosynthesis. However, it is unclear how this adjustment is regulated. The general aim of the work presented in this thesis is to understand how leaf growth and morphology are regulated in the model species Arabidopsis thaliana. Special attention was dedicated to the possibility that there might be internal metabolic signals within the plant which affect the growth and development of leaves. In order to investigate this question, leaf growth and development must be considered beyond the level of the single organ and in the context of the whole plant because leaves do not grow autonomously but depend on resources and regulatory influences delivered by the rest of the plant. Due to the complexity of this question, three complementary approaches were taken. In the first and most specific approach it was asked whether a proposed down-stream component of sucrose signalling, trehalose-6-phosphate (Tre-6-P), might influence leaf development and growth. To investigate this question, transgenic Arabidopsis lines with perturbed levels of Tre-6-P were generated using the constitutive 35S promoter to express bacterial enzymes involved in trehalose metabolism. These experiments also led to an unanticipated project concerning a possible role for Tre-6-P in stomatal function, which is another very important function in leaves. In a second and more general approach it was investigated whether changes in sugar levels in plants affect the morphogenesis of leaves in response to light. For this, a series of metabolic mutants impaired in central metabolism were grown in one light environment and their leaf morphology was analysed. In a third and even more general approach the natural variation in leaf and rosette morphological traits was investigated in a panel of wild Arabidopsis accessions with the aim of understanding how leaf morphology affects leaf function and whole plant growth and how different traits relate to each other. The analysis included measurements of leaf morphological traits as well as the number of leaves in the plant to put leaf morphology in a whole plant context. The variance in plant growth could not be explained by variation in photosynthetic rates and only to a small degree by variation in rates of dark respiration. There were four key axes of variation in rosette and leaf morphology – leaf area growth, leaf thickness, cell expansion and leaf number. These four processes were integrated in the context of whole plant growth by models that employed a multiple linear regression approach. This then led to a theoretical approach in which a simple allometric mathematical model was constructed, linking leaf number, leaf size and plant growth rate together in a whole plant context in Arabidopsis.
The inspiral and merger of two black holes is among the most exciting and extreme events in our universe. Being one of the loudest sources of gravitational waves, they provide a unique dynamical probe of strong-field general relativity and a fertile ground for the observation of fundamental physics. While the detection of gravitational waves alone will allow us to observe our universe through an entirely new window, combining the information obtained from both gravitational wave and electro-magnetic observations will allow us to gain even greater insight in some of the most exciting astrophysical phenomena. In addition, binary black-hole mergers serve as an intriguing tool to study the geometry of space-time itself. In this dissertation we study the merger process of binary black-holes in a variety of conditions. Our results show that asymmetries in the curvature distribution on the common apparent horizon are correlated to the linear momentum acquired by the merger remnant. We propose useful tools for the analysis of black holes in the dynamical and isolated horizon frameworks and shed light on how the final merger of apparent horizons proceeds after a common horizon has already formed. We connect mathematical theorems with data obtained from numerical simulations and provide a first glimpse on the behavior of these surfaces in situations not accessible to analytical tools. We study electro-magnetic counterparts of super-massive binary black-hole mergers with fully 3D general relativistic simulations of binary black-holes immersed both in a uniform magnetic field in vacuum and in a tenuous plasma. We find that while a direct detection of merger signatures with current electro-magnetic telescopes is unlikely, secondary emission, either by altering the accretion rate of the circumbinary disk or by synchrotron radiation from accelerated charges, may be detectable. We propose a novel approach to measure the electro-magnetic radiation in these simulations and find a non-collimated emission that dominates over the collimated one appearing in the form of dual jets associated with each of the black holes. Finally, we provide an optimized gravitational wave detection pipeline using phenomenological waveforms for signals from compact binary coalescence and show that by including spin effects in the waveform templates, the detection efficiency is drastically improved as well as the bias on recovered source parameters reduced. On the whole, this disseration provides evidence that a multi-messenger approach to binary black-hole merger observations provides an exciting prospect to understand these sources and, ultimately, our universe.
Business process models are used within a range of organizational initiatives, where every stakeholder has a unique perspective on a process and demands the respective model. As a consequence, multiple process models capturing the very same business process coexist. Keeping such models in sync is a challenge within an ever changing business environment: once a process is changed, all its models have to be updated. Due to a large number of models and their complex relations, model maintenance becomes error-prone and expensive. Against this background, business process model abstraction emerged as an operation reducing the number of stored process models and facilitating model management. Business process model abstraction is an operation preserving essential process properties and leaving out insignificant details in order to retain information relevant for a particular purpose. Process model abstraction has been addressed by several researchers. The focus of their studies has been on particular use cases and model transformations supporting these use cases. This thesis systematically approaches the problem of business process model abstraction shaping the outcome into a framework. We investigate the current industry demand in abstraction summarizing it in a catalog of business process model abstraction use cases. The thesis focuses on one prominent use case where the user demands a model with coarse-grained activities and overall process ordering constraints. We develop model transformations that support this use case starting with the transformations based on process model structure analysis. Further, abstraction methods considering the semantics of process model elements are investigated. First, we suggest how semantically related activities can be discovered in process models-a barely researched challenge. The thesis validates the designed abstraction methods against sets of industrial process models and discusses the method implementation aspects. Second, we develop a novel model transformation, which combined with the related activity discovery allows flexible non-hierarchical abstraction. In this way this thesis advocates novel model transformations that facilitate business process model management and provides the foundations for innovative tool support.
A key non-destructive technique for analysis, optimization and developing of new functional materials such as sensors, transducers, electro-optical and memory devices is presented. The Thermal-Pulse Tomography (TPT) provides high-resolution three-dimensional images of electric field and polarization distribution in a material. This thermal technique use a pulsed heating by means of focused laser light which is absorbed by opaque electrodes. The diffusion of the heat causes changes in the sample geometry, generating a short-circuit current or change in surface potential, which contains information about the spatial distribution of electric dipoles or space charges. Afterwards, a reconstruction of the internal electric field and polarization distribution in the material is possible via Scale Transformation or Regularization methods. In this way, the TPT was used for the first time to image the inhomogeneous ferroelectric switching in polymer ferroelectric films (candidates to memory devices). The results shows the typical pinning of electric dipoles in the ferroelectric polymer under study and support the previous hypotheses of a ferroelectric reversal at a grain level via nucleation and growth. In order to obtain more information about the impact of the lateral and depth resolution of the thermal techniques, the TPT and its counterpart called Focused Laser Intensity Modulation Method (FLIMM) were implemented in ferroelectric films with grid-shaped electrodes. The results from both techniques, after the data analysis with different regularization and scale methods, are in total agreement. It was also revealed a possible overestimated lateral resolution of the FLIMM and highlights the TPT method as the most efficient and reliable thermal technique. After an improvement in the optics, the Thermal-Pulse Tomography method was implemented in polymer-dispersed liquid crystals (PDLCs) films, which are used in electro-optical applications. The results indicated a possible electrostatic interaction between the COH group in the liquid crystals and the fluorinate atoms of the used ferroelectric matrix. The geometrical parameters of the LC droplets were partially reproduced as they were compared with Scanning Electron Microscopy (SEM) images. For further applications, it is suggested the use of a non-strong-ferroelectric polymer matrix. In an effort to develop new polymerferroelectrets and for optimizing their properties, new multilayer systems were inspected. The results of the TPT method showed the non-uniformity of the internal electric-field distribution in the shaped-macrodipoles and thus suggested the instability of the sample. Further investigation on multilayers ferroelectrets was suggested and the implementation of less conductive polymers layers too.
Biology has made great progress in identifying and measuring the building blocks of life. The availability of high-throughput methods in molecular biology has dramatically accelerated the growth of biological knowledge for various organisms. The advancements in genomic, proteomic and metabolomic technologies allow for constructing complex models of biological systems. An increasing number of biological repositories is available on the web, incorporating thousands of biochemical reactions and genetic regulations. Systems Biology is a recent research trend in life science, which fosters a systemic view on biology. In Systems Biology one is interested in integrating the knowledge from all these different sources into models that capture the interaction of these entities. By studying these models one wants to understand the emerging properties of the whole system, such as robustness. However, both measurements as well as biological networks are prone to considerable incompleteness, heterogeneity and mutual inconsistency, which makes it highly non-trivial to draw biologically meaningful conclusions in an automated way. Therefore, we want to promote Answer Set Programming (ASP) as a tool for discrete modeling in Systems Biology. ASP is a declarative problem solving paradigm, in which a problem is encoded as a logic program such that its answer sets represent solutions to the problem. ASP has intrinsic features to cope with incompleteness, offers a rich modeling language and highly efficient solving technology. We present ASP solutions, for the analysis of genetic regulatory networks, determining consistency with observed measurements and identifying minimal causes for inconsistency. We extend this approach for computing minimal repairs on model and data that restore consistency. This method allows for predicting unobserved data even in case of inconsistency. Further, we present an ASP approach to metabolic network expansion. This approach exploits the easy characterization of reachability in ASP and its various reasoning methods, to explore the biosynthetic capabilities of metabolic reaction networks and generate hypotheses for extending the network. Finally, we present the BioASP library, a Python library which encapsulates our ASP solutions into the imperative programming paradigm. The library allows for an easy integration of ASP solution into system rich environments, as they exist in Systems Biology.
Most of the microelectronic circuits fabricated today are synchronous, i.e. they are driven by one or several clock signals. Synchronous circuit design faces several fundamental challenges such as high-speed clock distribution, integration of multiple cores operating at different clock rates, reduction of power consumption and dealing with voltage, temperature, manufacturing and runtime variations. Asynchronous or clockless design plays a key role in alleviating these challenges, however the design and test of asynchronous circuits is much more difficult in comparison to their synchronous counterparts. A driving force for a widespread use of asynchronous technology is the availability of mature EDA (Electronic Design Automation) tools which provide an entire automated design flow starting from an HDL (Hardware Description Language) specification yielding the final circuit layout. Even though there was much progress in developing such EDA tools for asynchronous circuit design during the last two decades, the maturity level as well as the acceptance of them is still not comparable with tools for synchronous circuit design. In particular, logic synthesis (which implies the application of Boolean minimisation techniques) for the entire system's control path can significantly improve the efficiency of the resulting asynchronous implementation, e.g. in terms of chip area and performance. However, logic synthesis, in particular for asynchronous circuits, suffers from complexity problems. Signal Transitions Graphs (STGs) are labelled Petri nets which are a widely used to specify the interface behaviour of speed independent (SI) circuits - a robust subclass of asynchronous circuits. STG decomposition is a promising approach to tackle complexity problems like state space explosion in logic synthesis of SI circuits. The (structural) decomposition of STGs is guided by a partition of the output signals and generates a usually much smaller component STG for each partition member, i.e. a component STG with a much smaller state space than the initial specification. However, decomposition can result in component STGs that in isolation have so-called irreducible CSC conflicts (i.e. these components are not SI synthesisable anymore) even if the specification has none of them. A new approach is presented to avoid such conflicts by introducing internal communication between the components. So far, STG decompositions are guided by the finest output partitions, i.e. one output per component. However, this might not yield optimal circuit implementations. Efficient heuristics are presented to determine coarser partitions leading to improved circuits in terms of chip area. For the new algorithms correctness proofs are given and their implementations are incorporated into the decomposition tool DESIJ. The presented techniques are successfully applied to some benchmarks - including 'real-life' specifications arising in the context of control resynthesis - which delivered promising results.