914 resultados para Assortative matching


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This paper presents a strategy for solving the feature matching problem in calibrated very wide-baseline camera settings. In this kind of settings, perspective distortion, depth discontinuities and occlusion represent enormous challenges. The proposed strategy addresses them by using geometrical information, specifically by exploiting epipolar-constraints. As a result it provides a sparse number of reliable feature points for which 3D position is accurately recovered. Special features known as junctions are used for robust matching. In particular, a strategy for refinement of junction end-point matching is proposed which enhances usual junction-based approaches. This allows to compute cross-correlation between perfectly aligned plane patches in both images, thus yielding better matching results. Evaluation of experimental results proves the effectiveness of the proposed algorithm in very wide-baseline environments.

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Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without fltering the cost of SIENA-like topology changes.

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A coarse-grained model for protein-folding dynamics is introduced based on a discretized representation of torsional modes. The model, based on the Ramachandran map of the local torsional potential surface and the class (hydrophobic/polar/neutral) of each residue, recognizes patterns of both torsional conformations and hydrophobic-polar contacts, with tolerance for imperfect patterns. It incorporates empirical rates for formation of secondary and tertiary structure. The method yields a topological representation of the evolving local torsional configuration of the folding protein, modulo the basins of the Ramachandran map. The folding process is modeled as a sequence of transitions from one contact pattern to another, as the torsional patterns evolve. We test the model by applying it to the folding process of bovine pancreatic trypsin inhibitor, obtaining a kinetic description of the transitions between the contact patterns visited by the protein along the dominant folding pathway. The kinetics and detailed balance make it possible to invert the result to obtain a coarse topographic description of the potential energy surface along the dominant folding pathway, in effect to go backward or forward between a topological representation of the chain conformation and a topographical description of the potential energy surface governing the folding process. As a result, the strong structure-seeking character of bovine pancreatic trypsin inhibitor and the principal features of its folding pathway are reproduced in a reasonably quantitative way.

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This paper decomposes the conventional measure of selection bias in observational studies into three components. The first two components are due to differences in the distributions of characteristics between participant and nonparticipant (comparison) group members: the first arises from differences in the supports, and the second from differences in densities over the region of common support. The third component arises from selection bias precisely defined. Using data from a recent social experiment, we find that the component due to selection bias, precisely defined, is smaller than the first two components. However, selection bias still represents a substantial fraction of the experimental impact estimate. The empirical performance of matching methods of program evaluation is also examined. We find that matching based on the propensity score eliminates some but not all of the measured selection bias, with the remaining bias still a substantial fraction of the estimated impact. We find that the support of the distribution of propensity scores for the comparison group is typically only a small portion of the support for the participant group. For values outside the common support, it is impossible to reliably estimate the effect of program participation using matching methods. If the impact of participation depends on the propensity score, as we find in our data, the failure of the common support condition severely limits matching compared with random assignment as an evaluation estimator.

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Two potential outcomes of a coevolutionary interaction are an escalating arms race and stable cycling. The general expectation has been that arms races predominate in cases of polygenic inheritance of resistance traits and permanent cycling predominates in cases in which resistance is controlled by major genes. In the interaction between Depressaria pastinacella, the parsnip webworm, and Pastinaca sativa, the wild parsnip, traits for plant resistance to insect herbivory (production of defensive furanocoumarins) as well as traits for herbivore “virulence” (ability to metabolize furanocoumarins) are characterized by continuous heritable variation. Furanocoumarin production in plants and rates of metabolism in insects were compared among four midwestern populations; these traits then were classified into four clusters describing multitrait phenotypes occurring in all or most of the populations. When the frequency of plant phenotypes belonging to each of the clusters is compared with the frequency of the insect phenotypes in each of the clusters across populations, a remarkable degree of frequency matching is revealed in three of the populations. That frequencies of phenotypes vary among populations is consistent with the fact that spatial variation occurs in the temporal cycling of phenotypes; such processes contribute in generating a geographic mosaic in this coevolutionary interaction on the landscape scale. Comparisons of contemporary plant phenotype distributions with phenotypes of herbarium specimens collected 9–125 years ago from across a similar latitudinal gradient, however, suggest that for at least one resistance trait—sphondin concentration—interactions with webworms have led to escalatory change.

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The concept of gametic isolation has its origins in the 1937 edition of T. Dobzhansky’s Genetics and the Origin of Species. Involving either positive assortative fertilization (as opposed to self-incompatibility) or negative assortative fertilization, it occurs after mating but prior to fertilization. Gametic isolation is generally subsumed under either prezygotic or postmating isolation and thus has not been the subject of extensive investigation. Examples of assortative fertilization in Drosophila are reviewed and compared with those of other organisms. Potential mechanisms leading to assortative fertilization are discussed, as are their evolutionary implications.

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Molecular and fragment ion data of intact 8- to 43-kDa proteins from electrospray Fourier-transform tandem mass spectrometry are matched against the corresponding data in sequence data bases. Extending the sequence tag concept of Mann and Wilm for matching peptides, a partial amino acid sequence in the unknown is first identified from the mass differences of a series of fragment ions, and the mass position of this sequence is defined from molecular weight and the fragment ion masses. For three studied proteins, a single sequence tag retrieved only the correct protein from the data base; a fourth protein required the input of two sequence tags. However, three of the data base proteins differed by having an extra methionine or by missing an acetyl or heme substitution. The positions of these modifications in the protein examined were greatly restricted by the mass differences of its molecular and fragment ions versus those of the data base. To characterize the primary structure of an unknown represented in the data base, this method is fast and specific and does not require prior enzymatic or chemical degradation.

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We have previously derived a theoretical measure of neural complexity (CN) in an attempt to characterize functional connectivity in the brain. CN measures the amount and heterogeneity of statistical correlations within a neural system in terms of the mutual information between subsets of its units. CN was initially used to characterize the functional connectivity of a neural system isolated from the environment. In the present paper, we introduce a related statistical measure, matching complexity (CM), which reflects the change in CN that occurs after a neural system receives signals from the environment. CM measures how well the ensemble of intrinsic correlations within a neural system fits the statistical structure of the sensory input. We show that CM is low when the intrinsic connectivity of a simulated cortical area is randomly organized. Conversely, CM is high when the intrinsic connectivity is modified so as to differentially amplify those intrinsic correlations that happen to be enhanced by sensory input. When the input is represented by an individual stimulus, a positive value of CM indicates that the limited mutual information between sensory sheets sampling the stimulus and the rest of the brain triggers a large increase in the mutual information between many functionally specialized subsets within the brain. In this way, a complex brain can deal with context and go "beyond the information given."

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We report a general mass spectrometric approach for the rapid identification and characterization of proteins isolated by preparative two-dimensional polyacrylamide gel electrophoresis. This method possesses the inherent power to detect and structurally characterize covalent modifications. Absolute sensitivities of matrix-assisted laser desorption ionization and high-energy collision-induced dissociation tandem mass spectrometry are exploited to determine the mass and sequence of subpicomole sample quantities of tryptic peptides. These data permit mass matching and sequence homology searching of computerized peptide mass and protein sequence data bases for known proteins and design of oligonucleotide probes for cloning unknown proteins. We have identified 11 proteins in lysates of human A375 melanoma cells, including: alpha-enolase, cytokeratin, stathmin, protein disulfide isomerase, tropomyosin, Cu/Zn superoxide dismutase, nucleoside diphosphate kinase A, galaptin, and triosephosphate isomerase. We have characterized several posttranslational modifications and chemical modifications that may result from electrophoresis or subsequent sample processing steps. Detection of comigrating and covalently modified proteins illustrates the necessity of peptide sequencing and the advantages of tandem mass spectrometry to reliably and unambiguously establish the identity of each protein. This technology paves the way for studies of cell-type dependent gene expression and studies of large suites of cellular proteins with unprecedented speed and rigor to provide information complementary to the ongoing Human Genome Project.

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Comunicación presentada en el XI Workshop of Physical Agents, Valencia, 9-10 septiembre 2010.

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In this paper, we present a novel coarse-to-fine visual localization approach: contextual visual localization. This approach relies on three elements: (i) a minimal-complexity classifier for performing fast coarse localization (submap classification); (ii) an optimized saliency detector which exploits the visual statistics of the submap; and (iii) a fast view-matching algorithm which filters initial matchings with a structural criterion. The latter algorithm yields fine localization. Our experiments show that these elements have been successfully integrated for solving the global localization problem. Context, that is, the awareness of being in a particular submap, is defined by a supervised classifier tuned for a minimal set of features. Visual context is exploited both for tuning (optimizing) the saliency detection process, and to select potential matching views in the visual database, close enough to the query view.

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Drawing on a unique, farm-level panel dataset with 37,409 observations and employing a matching estimator, this paper analyses how farm access to credit affects farm input allocation and farm efficiency in the Central and Eastern European transition countries. We find that farms are asymmetrically credit constrained with respect to inputs. Farm use of variable inputs and capital investment increases up to 2.3% and 29%, respectively, per €1,000 of additional credit. Our estimates also suggest that farm access to credit increases total factor productivity up to 1.9% per €1,000 of additional credit, indicating that an improvement in access to credit results in an adjustment in the relative input intensities on farms. This finding is further supported by a negative effect of better access to credit on labour, suggesting that these two are substitutes. Interestingly, farms are found not to be credit constrained with respect to land.

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The European Union has prioritised the pursuit of innovation based growth and targeting of resources to promote research and development, but performance on innovation remains weak.With the lack of results comes fatigue, waning interest and mounting criticism about policy. Should the EU abandon its ambition to become the most innovative region in the world?We examine EU member state research and innovation policies. We assess whether the deployment of innovation policy instruments in EU countries matches their innovation capacity performance relative to other EU countries.We find a relative homogeneity of policy mixes in EU countries, despite the fairly wide and stable differences in their innovation capacities.Our analysis therefore provides a rationale for a more comprehensive review of innovation policy mixes to assess their adequacy in addressing country specific innovation challenges.

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A matemÆtica discreta Ø um dos ramos mais antigos da matemÆtica. Nos tempos mais recentes sofreu grandes avanos em especial na teoria dos grafos, a qual tornou-se numa poderosa ferramenta de anÆlise para entender e dar soluªo a vÆrios tipos de problemas complexos. O objectivo deste trabalho Ø contribuir para a obtenªo de possveis relaıes entre assuntos que partida poderamos pensar que sªo dspares (quando na realidade nªo o sªo), como coloraªo, planaridade e a existŒncia de matching em grafos. Esta dissertaªo Ø um trabalho de natureza reexiva, sobre a teoria dos grafos onde a ideia principal passa por questionarmos e discutirmos alguns temas pertinentes, deniıes e teoremas relacionando sempre com a planaridade dos grafos. DesenvolveremosumraciocnioecriaremosargumentosquefundamentemaexistŒncia de uma relaªo entre este tema e a coloraªo de grafos e a existŒncia de matching em grafos, utilizando exemplos e estabelecendo relaıes de causa e consequŒncia, deduzindo assim as respetivas conclusıes. Por vezes, os grafos nªo planares podem conter um aspeto visual um pouco complexo, devido aos vÆrios cruzamentos entre as suas arestas, originando assim um certo desencorajamento em utilizÆ-los como ferramenta para a soluªo de vÆrios problemas, quer sejam bÆsicos do quotidiano, ou mais complexos das mais vastas Æreas ligadas investigaªo. Um dos propsitos deste trabalho passa por desmisticar esta ideia e provar que existem muitas deniıes, propriedades, teoremas e algoritmos que podem ser aplicados em qualquer tipo de grafos, independentement da sua planaridade.

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A sociedade mudou nas últimas décadas abrindo a possibilidade para cientistas sociais estudarem essas mudanças e analisar os seus impactos na unidade familiar. Nesta tese pretendemos analisar como as decisões dos agentes com relação a decisão de casar e estudar pode estar conectado considerando que homens e mulheres têm preferências pelo casamento intragrupo. No modelo estudado encontramos que as preferências para o casamento intragrupo podem aumentar a proporção de homens e mulheres que decidem se casar e estudar. Mostramos também que empiricamente há um positive assortative mating entre pessoas com as mesmas características, tais como, educação, religião ou raça. Além disso, a probabilidade de casais casados na mesma religião aumenta a probabilidade dos casais estarem casados dentro do mesmo nível de escolaridade. Considerando as mudanças em como os casais se formam, a composição educacional e os retornos da educação que aconteceram no Brasil nos últimos anos, investiga-se os impactos dessas mudanças na desigualdade de renda dos casais. Calculamos cenários contrafactuais para o Coeficiente de Gini mantendo uma dessas três variáveis fixas em um determinado ano, comparando o contrafactual estimado com o Gini real. Se o casamento for formado aleatoriamente com relação à educação, o Coeficiente de Gini seria menor do que o real. Mantendo os retornos da educação fixos no ano de 2014 encontramos um Gini contrafactual menor do que o real.