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Digital image
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Olkiluoto Island is situated in the northern Baltic Sea, near the southwestern coast of Finland, and is the proposed location of a spent nuclear fuel repository. This study examined Holocene palaeoseismicity in the Olkiluoto area and in the surrounding sea areas by computer simulations together with acoustic-seismic, sedimentological and dating methods. The most abundant rock type on the island is migmatic mica gneiss, intruded by tonalites, granodiorites and granites. The surrounding Baltic Sea seabed consists of Palaeoproterozoic crystalline bedrock, which is to a great extent covered by younger Mesoproterozoic sedimentary rocks. The area contains several ancient deep-seated fracture zones that divide it into bedrock blocks. The response of bedrock at the Olkiluoto site was modelled considering four future ice-age scenarios. Each scenario produced shear displacements of fractures with different times of occurrence and varying recovery rates. Generally, the larger the maximum ice load, the larger were the permanent shear displacements. For a basic case, the maximum shear displacements were a few centimetres at the proposed nuclear waste repository level, at proximately 500 m b.s.l. High-resolution, low-frequency echo-sounding was used to examine the Holocene submarine sedimentary structures and possible direct and indirect indicators of palaeoseismic activity in the northern Baltic Sea. Echo-sounding profiles of Holocene submarine sediments revealed slides and slumps, normal faults, debris flows and turbidite-type structures. The profiles also showed pockmarks and other structures related to gas or groundwater seepages, which might be related to fracture zone activation. Evidence of postglacial reactivation in the study area was derived from the spatial occurrence of some of the structures, especial the faults and the seepages, in the vicinity of some old bedrock fracture zones. Palaeoseismic event(s) (a single or several events) in the Olkiluoto area were dated and the palaeoenvironment was characterized using palaeomagnetic, biostratigraphical and lithostratigraphical methods, enhancing the reliability of the chronology. Combined lithostratigraphy, biostratigraphy and palaeomagnetic stratigraphy revealed an age estimation of 10 650 to 10 200 cal. years BP for the palaeoseismic event(s). All Holocene sediment faults in the northern Baltic Sea occur at the same stratigraphical level, the age of which is estimated at 10 700 cal. years BP (9500 radiocarbon years BP). Their movement is suggested to have been triggered by palaeoseismic event(s) when the Late Weichselian ice sheet was retreating from the site and bedrock stresses were released along the bedrock fracture zones. Since no younger or repeated traces of seismic events were found, it corroborates the suggestion that the major seismic activity occurred within a short time during and after the last deglaciation. The origin of the gas/groundwater seepages remains unclear. Their reflections in the echo-sounding profiles imply that part of the gas is derived from the organic-bearing Litorina and modern gyttja clays. However, at least some of the gas is derived from the bedrock. Additional information could be gained by pore water analysis from the pockmarks. Information on postglacial fault activation and possible gas and/or fluid discharges under high hydraulic heads has relevance in evaluating the safety assessment of a planned spent nuclear fuel repository in the region.
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Nisäkkäiden levinneisyyteen, niiden morfologisiin ja ekologisiin piirteisiin vaikuttavat ympäristön sekä lyhyet että pitkäkestoiset muutokset, etenkin ilmaston ja kasvillisuuden vaihtelut. Työssä tutkittiin nisäkkäiden sopeutumista ilmastonmuutoksiin Euraasiassa viimeisen 24 miljoonan vuoden aikana. Tutkimuksessa keskityttiin varsinkin viimeiseen kahteen miljoonaan vuoteen, jonka aikana ilmasto muuttui voimakkaasti ja ihmisen toiminta alkoi tulla merkittäväksi. Tämän takia on usein vaikea erottaa, kummasta em. seikasta jonkin nisäkäslajin sukupuutto tai häviäminen alueelta johtui. Aineistona käytettiin laajaa venäjänkielistä kirjallisuutta, josta löytyvät tiedot ovat kääntämättöminä jääneet aiemmin länsimaisen tutkimuksen ulkopuolelle. Työssä käytettiin myös NOW-tietokantaa, jossa on fossiilisten nisäkkäiden löytöpaikat sekä niiden iät.
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Microarrays are high throughput biological assays that allow the screening of thousands of genes for their expression. The main idea behind microarrays is to compute for each gene a unique signal that is directly proportional to the quantity of mRNA that was hybridized on the chip. A large number of steps and errors associated with each step make the generated expression signal noisy. As a result, microarray data need to be carefully pre-processed before their analysis can be assumed to lead to reliable and biologically relevant conclusions. This thesis focuses on developing methods for improving gene signal and further utilizing this improved signal for higher level analysis. To achieve this, first, approaches for designing microarray experiments using various optimality criteria, considering both biological and technical replicates, are described. A carefully designed experiment leads to signal with low noise, as the effect of unwanted variations is minimized and the precision of the estimates of the parameters of interest are maximized. Second, a system for improving the gene signal by using three scans at varying scanner sensitivities is developed. A novel Bayesian latent intensity model is then applied on these three sets of expression values, corresponding to the three scans, to estimate the suitably calibrated true signal of genes. Third, a novel image segmentation approach that segregates the fluorescent signal from the undesired noise is developed using an additional dye, SYBR green RNA II. This technique helped in identifying signal only with respect to the hybridized DNA, and signal corresponding to dust, scratch, spilling of dye, and other noises, are avoided. Fourth, an integrated statistical model is developed, where signal correction, systematic array effects, dye effects, and differential expression, are modelled jointly as opposed to a sequential application of several methods of analysis. The methods described in here have been tested only for cDNA microarrays, but can also, with some modifications, be applied to other high-throughput technologies. Keywords: High-throughput technology, microarray, cDNA, multiple scans, Bayesian hierarchical models, image analysis, experimental design, MCMC, WinBUGS.
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Many problems in analysis have been solved using the theory of Hodge structures. P. Deligne started to treat these structures in a categorical way. Following him, we introduce the categories of mixed real and complex Hodge structures. Category of mixed Hodge structures over the field of real or complex numbers is a rigid abelian tensor category, and in fact, a neutral Tannakian category. Therefore it is equivalent to the category of representations of an affine group scheme. The direct sums of pure Hodge structures of different weights over real or complex numbers can be realized as a representation of the torus group, whose complex points is the Cartesian product of two punctured complex planes. Mixed Hodge structures turn out to consist of information of a direct sum of pure Hodge structures of different weights and a nilpotent automorphism. Therefore mixed Hodge structures correspond to the representations of certain semidirect product of a nilpotent group and the torus group acting on it.
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Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.
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Reuse of existing carefully designed and tested software improves the quality of new software systems and reduces their development costs. Object-oriented frameworks provide an established means for software reuse on the levels of both architectural design and concrete implementation. Unfortunately, due to frame-works complexity that typically results from their flexibility and overall abstract nature, there are severe problems in using frameworks. Patterns are generally accepted as a convenient way of documenting frameworks and their reuse interfaces. In this thesis it is argued, however, that mere static documentation is not enough to solve the problems related to framework usage. Instead, proper interactive assistance tools are needed in order to enable system-atic framework-based software production. This thesis shows how patterns that document a framework s reuse interface can be represented as dependency graphs, and how dynamic lists of programming tasks can be generated from those graphs to assist the process of using a framework to build an application. This approach to framework specialization combines the ideas of framework cookbooks and task-oriented user interfaces. Tasks provide assistance in (1) cre-ating new code that complies with the framework reuse interface specification, (2) assuring the consistency between existing code and the specification, and (3) adjusting existing code to meet the terms of the specification. Besides illustrating how task-orientation can be applied in the context of using frameworks, this thesis describes a systematic methodology for modeling any framework reuse interface in terms of software patterns based on dependency graphs. The methodology shows how framework-specific reuse interface specifi-cations can be derived from a library of existing reusable pattern hierarchies. Since the methodology focuses on reusing patterns, it also alleviates the recog-nized problem of framework reuse interface specification becoming complicated and unmanageable for frameworks of realistic size. The ideas and methods proposed in this thesis have been tested through imple-menting a framework specialization tool called JavaFrames. JavaFrames uses role-based patterns that specify a reuse interface of a framework to guide frame-work specialization in a task-oriented manner. This thesis reports the results of cases studies in which JavaFrames and the hierarchical framework reuse inter-face modeling methodology were applied to the Struts web application frame-work and the JHotDraw drawing editor framework.
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The ever expanding growth of the wireless access to the Internet in recent years has led to the proliferation of wireless and mobile devices to connect to the Internet. This has created the possibility of mobile devices equipped with multiple radio interfaces to connect to the Internet using any of several wireless access network technologies such as GPRS, WLAN and WiMAX in order to get the connectivity best suited for the application. These access networks are highly heterogeneous and they vary widely in their characteristics such as bandwidth, propagation delay and geographical coverage. The mechanism by which a mobile device switches between these access networks during an ongoing connection is referred to as vertical handoff and it often results in an abrupt and significant change in the access link characteristics. The most common Internet applications such as Web browsing and e-mail make use of the Transmission Control Protocol (TCP) as their transport protocol and the behaviour of TCP depends on the end-to-end path characteristics such as bandwidth and round-trip time (RTT). As the wireless access link is most likely the bottleneck of a TCP end-to-end path, the abrupt changes in the link characteristics due to a vertical handoff may affect TCP behaviour adversely degrading the performance of the application. The focus of this thesis is to study the effect of a vertical handoff on TCP behaviour and to propose algorithms that improve the handoff behaviour of TCP using cross-layer information about the changes in the access link characteristics. We begin this study by identifying the various problems of TCP due to a vertical handoff based on extensive simulation experiments. We use this study as a basis to develop cross-layer assisted TCP algorithms in handoff scenarios involving GPRS and WLAN access networks. We then extend the scope of the study by developing cross-layer assisted TCP algorithms in a broader context applicable to a wide range of bandwidth and delay changes during a handoff. And finally, the algorithms developed here are shown to be easily extendable to the multiple-TCP flow scenario. We evaluate the proposed algorithms by comparison with standard TCP (TCP SACK) and show that the proposed algorithms are effective in improving TCP behavior in vertical handoff involving a wide range of bandwidth and delay of the access networks. Our algorithms are easy to implement in real systems and they involve modifications to the TCP sender algorithm only. The proposed algorithms are conservative in nature and they do not adversely affect the performance of TCP in the absence of cross-layer information.
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In recent years, XML has been widely adopted as a universal format for structured data. A variety of XML-based systems have emerged, most prominently SOAP for Web services, XMPP for instant messaging, and RSS and Atom for content syndication. This popularity is helped by the excellent support for XML processing in many programming languages and by the variety of XML-based technologies for more complex needs of applications. Concurrently with this rise of XML, there has also been a qualitative expansion of the Internet's scope. Namely, mobile devices are becoming capable enough to be full-fledged members of various distributed systems. Such devices are battery-powered, their network connections are based on wireless technologies, and their processing capabilities are typically much lower than those of stationary computers. This dissertation presents work performed to try to reconcile these two developments. XML as a highly redundant text-based format is not obviously suitable for mobile devices that need to avoid extraneous processing and communication. Furthermore, the protocols and systems commonly used in XML messaging are often designed for fixed networks and may make assumptions that do not hold in wireless environments. This work identifies four areas of improvement in XML messaging systems: the programming interfaces to the system itself and to XML processing, the serialization format used for the messages, and the protocol used to transmit the messages. We show a complete system that improves the overall performance of XML messaging through consideration of these areas. The work is centered on actually implementing the proposals in a form usable on real mobile devices. The experimentation is performed on actual devices and real networks using the messaging system implemented as a part of this work. The experimentation is extensive and, due to using several different devices, also provides a glimpse of what the performance of these systems may look like in the future.
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What can the statistical structure of natural images teach us about the human brain? Even though the visual cortex is one of the most studied parts of the brain, surprisingly little is known about how exactly images are processed to leave us with a coherent percept of the world around us, so we can recognize a friend or drive on a crowded street without any effort. By constructing probabilistic models of natural images, the goal of this thesis is to understand the structure of the stimulus that is the raison d etre for the visual system. Following the hypothesis that the optimal processing has to be matched to the structure of that stimulus, we attempt to derive computational principles, features that the visual system should compute, and properties that cells in the visual system should have. Starting from machine learning techniques such as principal component analysis and independent component analysis we construct a variety of sta- tistical models to discover structure in natural images that can be linked to receptive field properties of neurons in primary visual cortex such as simple and complex cells. We show that by representing images with phase invariant, complex cell-like units, a better statistical description of the vi- sual environment is obtained than with linear simple cell units, and that complex cell pooling can be learned by estimating both layers of a two-layer model of natural images. We investigate how a simplified model of the processing in the retina, where adaptation and contrast normalization take place, is connected to the nat- ural stimulus statistics. Analyzing the effect that retinal gain control has on later cortical processing, we propose a novel method to perform gain control in a data-driven way. Finally we show how models like those pre- sented here can be extended to capture whole visual scenes rather than just small image patches. By using a Markov random field approach we can model images of arbitrary size, while still being able to estimate the model parameters from the data.