66 resultados para kriging maps


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The U7 snRNA, together with both common and unique snRNP proteins, forms the U7 snRNP particle. This particle is a major component of the 3' processing machinery that converts histone pre-mRNA into mature mRNA in the eukaryotic nucleus. The genes for many snRNAs are present in multiple copies and often have many pseudogenes. Southern blot experiments using U7 oligonucleotide and gene probes have identified only one strongly hybridizing band and three weakly hybridizing bands in mouse genomic DNA. Previously, two laboratories isolated genomic clones encoding one functional U7 gene and three presumed pseudogenes. Since all the genes were isolated on separate, nonoverlapping genomic fragments, the four genes are not tightly clustered in the mouse genome. In this study, we use fluorescence in situ hybridization to determine the chromosomal locations of these clones and their possible linkage to histone loci. Two of the pseudogenes map to mouse Chromosome 1, but are many megabases apart, whereas the active U7 gene maps to Chromosome 6. Possible mechanisms for this localization pattern are discussed.

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State of the art methods for disparity estimation achieve good results for single stereo frames, but temporal coherence in stereo videos is often neglected. In this paper we present a method to compute temporally coherent disparity maps. We define an energy over whole stereo sequences and optimize their Conditional Random Field (CRF) distributions using mean-field approximation. We introduce novel terms for smoothness and consistency between the left and right views, and perform CRF optimization by fast, iterative spatio-temporal filtering with linear complexity in the total number of pixels. Our results rank among the state of the art while having significantly less flickering artifacts in stereo sequences.

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Let $\H^n$ be the Heisenberg group of topological dimension 2n+1 . We prove that if n is odd, the pair of metric spaces $(\H^n, \H^n)$ does not have the Lipschitz extension property.

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This paper presents a conceptual approach to enhance knowledge management by synchronizing mind maps and fuzzy cognitive maps. The use of mind maps allows taking advantage of human creativity, while the application of fuzzy cognitive maps enables to store information expressed in natural language. By applying cognitive computing, it makes possible to gather and extract relevant information out of a data pool. Therefore, this approach is supposed to give a framework that enhances knowledge management. To demonstrate the potential of this framework, a use case concerning the development of a smart city app is presented.

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Polymineralic rocks undergo grain coarsening with increasing temperature in both static and deformational environments, as long as no mineral reactions occur. The grain coarsening in such rocks is complex because the different phases influence each other, and it is this interaction that controls the rate of grain coarsening of the entire aggregate. We present a mathematical approach to investigate coupled grain coarsening using a set of microstructural parameters, including grain size and volume fraction of both second phases and matrix mineral in combination with temperature information. Based on samples from polymineralic carbonate mylonites that were deformed at different temperatures, we demonstrate how the mathematical relation can be calibrated for this natural system. Using such data sets for other lithologies, grain coarsening maps can be generated, which allow the prediction of microstructural evolution in polymineralic rocks. Such predictions are crucial for all subdisciplines in the earth sciences that require fundamental knowledge about microstructural changes and rheology of an orogen at different depths, such as structural geology, geophysics, geodynamics, and metamorphic petrology.