896 resultados para Logical Inference


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K-Cl cotransporter 2 (KCC2) maintains a low intracellular Cl concentration required for fast hyperpolarizing responses of neurons to classical inhibitory neurotransmitters γ-aminobutyric acid (GABA) and glycine. Decreased Cl extrusion observed in genetically modified KCC2-deficient mice leads to depolarizing GABA responses, impaired brain inhibition, and as a consequence to epileptic seizures. Identification of mechanisms regulating activity of the SLC12A5 gene, which encodes the KCC2 cotransporter, in normal and pathological conditions is, thus, of extreme importance. Multiple reports have previously elucidated in details a spatio-temporal pattern of KCC2 expression. Among the characteristic features are an exclusive neuronal specificity, a dramatic upregulation during embryonic and early postnatal development, and a significant downregulation by neuronal trauma. Numerous studies confirmed these expressional features, however transcriptional mechanisms predetermining the SLC12A5 gene behaviour are still unknown. The aim of the presented thesis is to recognize such transcriptional mechanisms and, on their basis, to create a transcriptional model that would explain the established SLC12A5 gene behaviour. Up to recently, only one KCC2 transcript has been thought to exist. A particular novelty of the presented work is the identification of two SLC12A5 gene promoters (SLC12A5-1a and SLC12A5-1b) that produce at least two KCC2 isoforms (KCC2a and KCC2b) differing by their N-terminal parts. Even though a functional 86Rb+ assay reveals no significant difference between transport activities of the isoforms, consensus sites for several protein kinases, found in KCC2a but not in KCC2b, imply a distinct kinetic regulation. As a logical continuation, the current work presents a detailed analysis of the KCC2a and KCC2b expression patterns. This analysis shows an exclusively neuron-specific pattern and similar expression levels for both isoforms during embryonic and neonatal development in rodents. During subsequent postnatal development, the KCC2b expression dramatically increases, while KCC2a expression, depending on central nervous system (CNS) area, either remains at the same level or moderately decreases. In an attempt to explain both the neuronal specificity and the distinct expressional kinetics of the KCC2a and KCC2b isoforms during postnatal development, the corresponding SLC12A5-1a and SLC12A5-1b promoters have been subjected to a comprehensive bioinformatical analysis. Binding sites of several transcription factors (TFs), conserved in the mammalian SLC12A5 gene orthologs, have been identified that might shed light on the observed behaviour of the SLC12A5 gene. Possible roles of these TFs in the regulating of the SLC12A5 gene expression have been elucidated in subsequent experiments and are discussed in the current thesis.

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We extend some of the classical connections between automata and logic due to Büchi (1960) [5] and McNaughton and Papert (1971) [12] to languages of finitely varying functions or “signals”. In particular, we introduce a natural class of automata for generating finitely varying functions called View the MathML source’s, and show that it coincides in terms of language definability with a natural monadic second-order logic interpreted over finitely varying functions Rabinovich (2002) [15]. We also identify a “counter-free” subclass of View the MathML source’s which characterise the first-order definable languages of finitely varying functions. Our proofs mainly factor through the classical results for word languages. These results have applications in automata characterisations for continuously interpreted real-time logics like Metric Temporal Logic (MTL) Chevalier et al. (2006, 2007) [6] and [7].

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Background Multiple sclerosis (MS) is thought to be a T cell-mediated autoimmune disorder. MS pathogenesis is likely due to a genetic predisposition triggered by a variety of environmental factors. Epigenetics, particularly DNA methylation, provide a logical interface for environmental factors to influence the genome. In this study we aim to identify DNA methylation changes associated with MS in CD8+ T cells in 30 relapsing remitting MS patients and 28 healthy blood donors using Illumina 450K methylation arrays. Findings Seventy-nine differentially methylated CpGs were associated with MS. The methylation profile of CD8+ T cells was distinctive from our previously published data on CD4+ T cells in the same cohort. Most notably, there was no major CpG effect at the MS risk gene HLA-DRB1 locus in the CD8+ T cells. Conclusion CD8+ T cells and CD4+ T cells have distinct DNA methylation profiles. This case–control study highlights the importance of distinctive cell subtypes when investigating epigenetic changes in MS and other complex diseases.

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Age-related macular degeneration (AMD; OMIM # 603075) is an eye disease of the elderly, signs of which appear after the age of 50. In the Western world it is a leading cause of permanent visual loss with a prevalence of 8.5% in persons under 54 years of age and of 37% in persons over 75 years of age. Early forms of AMD may be asymptomatic, but in the late forms usually a central scotoma in the visual field follows severely complicating daily tasks. Smoking, age, and genetic predisposition are known risk factors for AMD. Until recently no true susceptibility genes had been identified though the composition of drusen deposits, the hallmarks of AMD, has suggested that the complement system might play a role in the pathogenesis of AMD. When four groups reported in March 2005, that, on chromosome 1q32, a Y402H variant in the complement factor H (CFH) gene confers risk for AMD in independent Caucasian samples, a new period in the field of genetic research of AMD started. CFH is a key regulator of the complement system. Thus, it is logical to speculate, that it plays a role in the pathogenesis of AMD. We performed a case-control association study to analyse whether the CFH Y402H variant contain a risk for AMD in the Finnish population. Although the population of Finland represents a genetic isolate, the CFH Y402H polymorphism was associated with AMD also in our patient sample with similar risk allele frequencies as in the other Caucasian populations. We further evaluated the effects of this variant, but no association between lesion subtype (predominantly classic, minimally classic or occult lesion) or lesion size of neovascular AMD and the CFH Y402H variant was detected. Neither did the variant have an effect on the photodynamic therapy (PDT) outcome. The patients that respond to PDT carried the risk genotype as frequently as those who did not respond, and no difference was found in the number of PDT sessions needed in patients with or without the risk genotypes of CFH Y402H. Functional analyses, however, showed that the binding of C-reactive protein (CRP) to CFH was significantly reduced in patients with the risk genotype of Y402H. In the past two years, the LOC387715/ high-temperature requirement factor A1 (HTRA1) locus on 10q26 has also been repeatedly associated with AMD in several populations. The recent discovery of the LOC387715 protein on the mitochondrial outer membrane suggests that the LOC387715 gene, not HTRA1, is the true predisposing gene in this region, although its biological function is still unknown. In our Finnish patient material, patients with AMD carried the A69S risk genotype of LOC387715 more frequently than the controls. Also, for the first time, an interaction between the CFH Y402H and the LOC387715 A69S variants was found. The most recently detected susceptibilty gene of AMD, the complement component 3 (C3) gene, encodes the central component of the complement system, C3. In our Finnish sample, an additive gene effect for the C3 locus was detected, though weaker than the effects for the two main loci, CFH and LOC387715. Instead, the hemicentin-1 or the elongation of very long chain fatty acids-like 4 genes that have also been suggested as candidate genes for AMD did not carry a risk for AMD in the Finnish population. This was the first series of molecular genetic study of AMD in Finland. We showed that two common risk variants, CFH Y402H and LOC387715 A69S, represent a high risk of AMD also in the isolated Finnish population, and furthermore, that they had a statistical interaction. It was demonstrated that the CFH Y402H risk genotype affects the binding of CFH to CRP thus suggesting that complement indeed plays an important role in the pathogenesis of AMD.

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In the current era of high-throughput sequencing and structure determination, functional annotation has become a bottleneck in biomedical science. Here, we show that automated inference of molecular function using functional linkages among genes increases the accuracy of functional assignments by >= 8% and enriches functional descriptions in >= 34% of top assignments. Furthermore, biochemical literature supports >80% of automated inferences for previously unannotated proteins. These results emphasize the benefit of incorporating functional linkages in protein annotation.

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The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.

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This thesis studies the nature and logic of collective doxastic attitudes, or what is referred to in ordinary language as "group beliefs". Beliefs and other intentional attitudes are attributed to groups and collections of people, and such attributions are used to explain and predict the actions of groups. The thesis develops an understanding of group beliefs as voluntarily adopted views or acceptances rather than as ordinary beliefs. Such an understanding can provide new answers to questions concerning collective knowledge and justification of group beliefs, and it allows developing modal logics with collective doxastic and epistemic notions. The thesis consists of six articles. The first three articles are philosophical studies concerned with the nature of group beliefs. The last three articles are logical studies that aim at developing proof-theoretical calculi for reasoning about collective doxastic attitudes.

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Based on the Aristotelian criterion referred to as 'abductio', Peirce suggests a method of hypothetical inference, which operates in a different way than the deductive and inductive methods. “Abduction is nothing but guessing” (Peirce, 7.219). This principle is of extreme value for the study of our understanding of mathematical self-similarity in both of its typical presentations: relative or absolute. For the first case, abduction incarnates the quantitative/qualitative relationships of a self-similar object or process; for the second case, abduction makes understandable the statistical treatment of self-similarity, 'guessing' the continuity of geometric features to the infinity through the use of a systematic stereotype (for instance, the assumption that the general shape of the Sierpiński triangle continuates identically into its particular shapes). The metaphor coined by Peirce, of an exact map containig itself the same exact map (a map of itself), is not only the most important precedent of Mandelbrot’s problem of measuring the boundaries of a continuous irregular surface with a logarithmic ruler, but also still being a useful abstraction for the conceptualisation of relative and absolute self-similarity, and its mechanisms of implementation. It is useful, also, for explaining some of the most basic geometric ontologies as mental constructions: in the notion of infinite convergence of points in the corners of a triangle, or the intuition for defining two parallel straight lines as two lines in a plane that 'never' intersect.

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In Somalia the central government collapsed in 1991 and since then state failure became a widespread phenomenon and one of the greatest political and humanitarian problems facing the world in this century. Thus, the main objective of this research is to answer the following question: What went wrong? Most of the existing literature on the political economy of conflict starts from the assumption that state in Africa is predatory by nature. Unlike these studies, the present research, although it uses predation theory, starts from the social contract approach of state definition. Therefore, rather than contemplating actions and policies of the rulers alone, this approach allows us to deliberately bring the role of the society – as citizens – and other players into the analyses. In Chapter 1, after introducing the study, a simple principal-agent model will be developed to check the logical consistence of the argument and to make the identification of causal mechanism easier. I also identify three main actors in the process of state failure in Somalia: the Somali state, Somali society and the superpowers. In Chapter 2, so as to understand the incentives, preferences and constraints of each player in the state failure game, I in some depth analyse the evolution and structure of three central informal institutions: identity based patronage system of leadership, political tribalism, and the Cold War. These three institutions are considered as the rules of the game in the Somali state failure. Chapter 3 summarises the successive civilian governments’ achievements and failures (1960-69) concerning the main national goals, national unification and socio-economic development. Chapter 4 shows that the military regime, although it assumed power through extralegal means, served to some extent the developmental interest of the citizens in the first five years of its rule. Chapter 5 shows the process, and the factors involved, of the military regime’s self-transformation from being an agent for the developmental interests of the society to a predatory state that not only undermines the interests of the society but that also destroys the state itself. Chapter 6 addresses the process of disintegration of the post-colonial state of Somalia. The chapter shows how the regime’s merciless reactions to political ventures by power-seeking opposition leaders shattered the entire country and wrecked the state institutions. Chapter 7 concludes the study by summarising the main findings: due to the incentive structures generated by the informal institutions, the formal state institutions fell apart.

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Knowledge-based clusters are studied from the structural point of view. Generalized descriptions for such clusters are stated and illustrated. Peculiarities of certain knowledge-based cluster configurations are highlighted. The adequacy of the connectives logical and (“and”) logical or (“exclusive-or”) in describing such clusters is justified. The definition of “concept” is elaborated from the clustering point of view and used to establish the equivalence between, descriptions of clusters and concepts. The order-independence of semantic-directed clustering approach is established formally based on axiomatic considerations.

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Topics in Spatial Econometrics — With Applications to House Prices Spatial effects in data occur when geographical closeness of observations influences the relation between the observations. When two points on a map are close to each other, the observed values on a variable at those points tend to be similar. The further away the two points are from each other, the less similar the observed values tend to be. Recent technical developments, geographical information systems (GIS) and global positioning systems (GPS) have brought about a renewed interest in spatial matters. For instance, it is possible to observe the exact location of an observation and combine it with other characteristics. Spatial econometrics integrates spatial aspects into econometric models and analysis. The thesis concentrates mainly on methodological issues, but the findings are illustrated by empirical studies on house price data. The thesis consists of an introductory chapter and four essays. The introductory chapter presents an overview of topics and problems in spatial econometrics. It discusses spatial effects, spatial weights matrices, especially k-nearest neighbours weights matrices, and various spatial econometric models, as well as estimation methods and inference. Further, the problem of omitted variables, a few computational and empirical aspects, the bootstrap procedure and the spatial J-test are presented. In addition, a discussion on hedonic house price models is included. In the first essay a comparison is made between spatial econometrics and time series analysis. By restricting the attention to unilateral spatial autoregressive processes, it is shown that a unilateral spatial autoregression, which enjoys similar properties as an autoregression with time series, can be defined. By an empirical study on house price data the second essay shows that it is possible to form coordinate-based, spatially autoregressive variables, which are at least to some extent able to replace the spatial structure in a spatial econometric model. In the third essay a strategy for specifying a k-nearest neighbours weights matrix by applying the spatial J-test is suggested, studied and demonstrated. In the final fourth essay the properties of the asymptotic spatial J-test are further examined. A simulation study shows that the spatial J-test can be used for distinguishing between general spatial models with different k-nearest neighbours weights matrices. A bootstrap spatial J-test is suggested to correct the size of the asymptotic test in small samples.

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This qualitative, explorative study, which comprises four essays, focuses on knowledge management (KM). It seeks to answer the question: How can the knowledge creation theory of KM benefit from social learning theories? While studying the five development phases of knowledge creation theory of KM through 1995-2008 and applying some social learning theories in essays, the concepts of knowing, learning and becoming have emerged. Drawing on these three concepts and on becoming ontology and extended epistemology as research philosophies the study suggests the ‘becoming epistemology’ concept and develops the ‘becoming to know’ framework. The framework proposes becoming as phronesis of dialectic interactions between learning and knowing. It shows how becoming to know evolves as an interplay between concrete experience and logical thinking in the present and in a living context. The proposed framework could be considered a contribution to the current development phase of the knowledge creation theory of KM because it illustrates how ontological and epistemological knowledge spirals come together, which is the essence of the knowledge creation theory of KM.

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We propose a dialogue protocol for situations in which an agent makes to another agent an assertion that the other agent finds impossible to believe. In this interaction, unbelievable assertions are rejected using explanations formed by logical interpolation and new assertions are being made such that all previous rebuttals are taken into account.

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Preferential cleavage of active genes by DNase I has been correlated with a structurally altered conformation of DNA at the hypersensitive site in chromatin. To have a better understanding of the structural requirements for gene activation as probed by DNase I action, digestability by DNase I of synthetic polynucleotides having the ability to adopt B and non-B conformation (like Z-form) was studied which indicated a marked higher digestability of the B-form of DNA. Left handed Z form present within a natural sequence in supercoiled plasmid also showed marked resistance towards DNase I digestion. We show that alternating purine-pyrimidine sequences adopting Z-conformation exhibit DNAse I foot printing even in a protein free system. The logical deductions from the results indicate that 1) altered structure like Z-DNA is not a favourable substrate for DNase I, 2) both the ends of the alternating purine-pyrimidine insert showed hypersensitivity, 3) B-form with a minor groove of 12-13 A is a more favourable substrate for DNase I than an altered structure, 4) any structure of DNA deviating largely from B form with a capacity to flip over to the B-form are potential targets for the DNase I enzymic probes in naked DNA.

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Markov random fields (MRF) are popular in image processing applications to describe spatial dependencies between image units. Here, we take a look at the theory and the models of MRFs with an application to improve forest inventory estimates. Typically, autocorrelation between study units is a nuisance in statistical inference, but we take an advantage of the dependencies to smooth noisy measurements by borrowing information from the neighbouring units. We build a stochastic spatial model, which we estimate with a Markov chain Monte Carlo simulation method. The smooth values are validated against another data set increasing our confidence that the estimates are more accurate than the originals.