850 resultados para Detailed mapping


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Robotic mapping is the process of automatically constructing an environment representation using mobile robots. We address the problem of semantic mapping, which consists of using mobile robots to create maps that represent not only metric occupancy but also other properties of the environment. Specifically, we develop techniques to build maps that represent activity and navigability of the environment. Our approach to semantic mapping is to combine machine learning techniques with standard mapping algorithms. Supervised learning methods are used to automatically associate properties of space to the desired classification patterns. We present two methods, the first based on hidden Markov models and the second on support vector machines. Both approaches have been tested and experimentally validated in two problem domains: terrain mapping and activity-based mapping.

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In medical processes where ionizing radiation is used, dose planning and dose delivery are the key elements to patient safety and treatment success, particularly, when the delivered dose in a single session of treatment can be an order of magnitude higher than the regular doses of radiotherapy. Therefore, the radiation dose should be well defined and precisely delivered to the target while minimizing radiation exposure to surrounding normal tissues [1]. Several methods have been proposed to obtain three-dimensional (3-D) dose distribution [2, 3]. In this paper, we propose an alternative method, which can be easily implemented in any stereotactic radiosurgery center with a magnetic resonance imaging (MRI) facility. A phantom with or without scattering centers filled with Fricke gel solution is irradiated with Gamma Knife(A (R)) system at a chosen spot. The phantom can be a replica of a human organ such as head, breast or any other organ. It can even be constructed from a real 3-D MR image of an organ of a patient using a computer-aided construction and irradiated at a specific region corresponding to the tumor position determined by MRI. The spin-lattice relaxation time T (1) of different parts of the irradiated phantom is determined by localized spectroscopy. The T (1)-weighted phantom images are used to correlate the image pixels intensity to the absorbed dose and consequently a 3-D dose distribution with a high resolution is obtained.

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The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

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To facilitate the design of laser host materials with optimized emission properties, detailed structural information at the atomic level is essential, regarding the local bonding environment of the active ions (distribution over distinct lattice sites) and their extent of local clustering as well as their population distribution over separate micro- or nanophases. The present study explores the potential of solid state NMR spectroscopy to provide such understanding for rare-earth doped lead lanthanum zirconate titanate (PLZT) ceramics. As the NMR signals of the paramagnetic dopant species cannot be observed directly, two complementary approaches are utilized: (1) direct observation of diamagnetic mimics using Sc-45 NMR and (2) study of the paramagnetic interaction of the constituent host lattice nuclei with the rare-earth dopant, using Pb-207 NMR lineshape analysis. Sc-45 MAS NMR spectra of scandium-doped PLZT samples unambiguously reveal scandium to be six-coordinated, suggesting that this rare-earth ion substitutes in the B site. Static Pb-207 spin echo NMR spectra of a series of Tm-doped PLZT samples reveal a clear influence of paramagnetic rare-earth dopant concentration on the NMR lineshape. In the latter case high-fidelity spectra can be obtained by spin echo mapping under systematic incrementation of the excitation frequency, benefiting from the signal-to-noise enhancement afforded by spin echo train Fourier transforms. Consistent with XRD data, the Pb-207 NMR lineshape analysis suggests that statistical incorporation into the PLZT lattice occurs at dopant levels of up to 1 wt.% Tm3+, while at higher levels the solubility limit is reached. (C) 2008 Elsevier Masson SAS. All rights reserved.

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Unveiling the mechanisms of energy relaxation in biomolecules is key to our understanding of protein stability, allostery, intramolecular signaling, and long-lasting quantum coherence phenomena at ambient temperatures. Yet, the relationship between the pathways of energy transfer and the functional role of the residues involved remains largely unknown. Here, we develop a simulation method of mapping out residues that are highly efficient in relaxing an initially localized excess vibrational energy and perform site-directed mutagenesis functional assays to assess the relevance of these residues to protein function. We use the ligand binding domains of thyroid hormone receptor (TR) subtypes as a test case and find that conserved arginines, which are critical to TR transactivation function, are the most effective heat diffusers across the protein structure. These results suggest a hitherto unsuspected connection between a residue`s ability to mediate intramolecular vibrational energy redistribution and its functional relevance.

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We prove that the symplectic group Sp(2n, Z) and the mapping class group Mod(S) of a compact surface S satisfy the R(infinity) property. We also show that B(n)(S), the full braid group on n-strings of a surface S, satisfies the R(infinity) property in the cases where S is either the compact disk D, or the sphere S(2). This means that for any automorphism phi of G, where G is one of the above groups, the number of twisted phi-conjugacy classes is infinite.

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Objective. Given their involvement in pathological and physiological angiogenesis, there has been growing interest in understanding and manipulating endothellial progenitor cells (EPC) for therapeutic purposes. However, detailed molecular analysis of EPC before and during endothelial differentiation is lacking and is the subject of the present study. Materials and Methods. We report a detailed microarray gene-expression profile of freshly isolated (day 0) human cord blood (CB)-derived EPC (CD133(+)KDR(+) or CD34(+)KDR(+)), and at different time points during in vitro differentiation (early: day 13; late: day 27). Results. Data obtained reflect an EPC transcriptome enriched in genes related to stem/progenitor cells properties (chromatin remodeling, self-renewal, signaling, cytoskeleton organization and biogenesis, recruitment, and adhesion). Using a complementary DNA microarray enriched in intronic transcribed sequences, we observed, as well, that naturally transcribed intronic noncoding RNAs were specifically expressed at the EPC stage. Conclusion. Taken together, we have defined the global gene-expression profile of CB-derived EPC during the process of endothelial differentiation, which can be used to identify genes involved in different vascular pathologies. (C) 2008 ISEH - Society for Hematology and Stem Cells. Published by Elsevier Inc.

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Although the amine sulfur dioxide chemistry was well characterized in the past both experimentally and theoretically, no systematic Raman spectroscopic study describes the interaction between N,N-dimethylaniline (DMA) and sulfur dioxide (SO(2)). The formation of a deep red oil by the reaction of SO(2) with DMA is an evidence of the charge transfer (CT) nature of the DMA-SO(2) interaction. The DMA -SO(2) normal Raman spectrum shows the appearance of two intense bands at 1110 and 1151 cm(-1), which are enhanced when resonance is approached. These bands are assigned to nu(s)(SO(2)) and nu(phi-N) vibrational modes, respectively, confirming the interaction between SO(2) and the amine via the nitrogen atom. The dimethyl group steric effect favors the interaction of SO(2) with the ring pi electrons, which gives rise to a pi-pi* low-energy CT electronic transition, as confirmed by time-dependent density functional theory (TDDFT) calculations. In addition, the calculated Raman DMA-SO(2) spectrum at the B3LYP/6-311++g(3df,3pd) level shows good agreement with the experimental results (vibrational wavenumbers and relative intensities), allowing a complete assignment of the vibrational modes. A better understanding of the intermolecular interactions in this model system can be extremely useful in designing new materials to absorb, detect, or even quantify SO(2). Copyright (C) 2009 John Wiley & Sons, Ltd.

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This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

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This Minor Field Study was carried out during November and December in 2011 in the Mount Elgon District in Western Kenya. The objective was to examine nine small-scale farming household´s land use and socioeconomic situation when they have joined a non-governmental organization (NGO) project, which specifically targets small-scale farming households to improve land use system and socioeconomic situation by the extension of soil and water conservation measures. The survey has worked along three integral examinations methods which are mapping and processing data using GIS, semi structured interviews and literature studies.   This study has adopted a theoretical approach referred to as political ecology, in which landesque capital is a central concept. The result shows that all farmers, except one, have issues with land degradation. However, the extent of the problem and also implemented sustainable soil and water conservation measures were diverse among the farmers. The main causes of this can both be linked to how the farmers themselves utilized their farmland and how impacts from the climate change have modified the terms of the farmers working conditions. These factors have consequently resulted in impacts on the informants’ socioeconomic conditions. Furthermore it was also registered that social and economic elements, in some cases, were the causes of how the farmers manage their farmland. The farmer who had no significant problem with soil erosion had invested in trees and opportunities to irrigate the farmland. In addition, it was also recorded that certain farmers had invested in particular soil and water conservation measures without any significant result. This was probably due to the time span these land measures cover before they start to generate revenue.  The outcome of this study has traced how global, national and local elements exist in a context when it comes to the conditions of the farmers´ land use and their socioeconomic situation. The farmers atMt.Elgon are thereby a component of a wider context when they are both contributory to their socioeconomic situation, mainly due to their land management, and also exposed to core-periphery relationships on which the farmers themselves have no influence.

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Background: Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F2 populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F2 animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature. Methods: We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F2 population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight. Results: Five of the nine QTL detected with the original F2 population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL. Conclusions: Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.

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Background qtl.outbred is an extendible interface in the statistical environment, R, for combining quantitative trait loci (QTL) mapping tools. It is built as an umbrella package that enables outbred genotype probabilities to be calculated and/or imported into the software package R/qtl. Findings Using qtl.outbred, the genotype probabilities from outbred line cross data can be calculated by interfacing with a new and efficient algorithm developed for analyzing arbitrarily large datasets (included in the package) or imported from other sources such as the web-based tool, GridQTL. Conclusion qtl.outbred will improve the speed for calculating probabilities and the ability to analyse large future datasets. This package enables the user to analyse outbred line cross data accurately, but with similar effort than inbred line cross data.

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This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

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MAPfastR is a software package developed to analyze QTL data from inbred and outbred line-crosses. The package includes a number of modules for fast and accurate QTL analyses. It has been developed in the R language for fast and comprehensive analyses of large datasets. MAPfastR is freely available at: http://www.computationalgenetics.se/?page_id=7.