244 research outputs found

    Discriminating different classes of biological networks by analyzing the graphs spectra distribution

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    The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them on (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed

    Improving RANSAC for Fast Landmark Recognition. Workshop on Visual Localization for Mobile Platforms

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    We introduce a procedure for recognizing and locating planar landmarks for mobile robot navigation, based in the detection and recognition of a set of interest points. We use RANSAC for fitting a homography and locating the land mark. Our main contribution is the introduction of a geometrical constraint that reduces the number of RANSAC iterations by discarding minimal subsets. In the experiments conducted we conclude that this constraint increases RANSAC performance by reducing in about 35% and 75%the number of iterations for affine and projective cameras, respectively

    Conformal Enhancement of Holographic Scaling in Black Hole Thermodynamics: A Near-Horizon Heat-Kernel Framework

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    Standard thermodynamic treatments of quantum field theory in the presence of black-hole backgrounds reproduce the black hole entropy by usually specializing to the leading order of the heat-kernel or the high-temperature expansion. By contrast, this work develops a hybrid framework centered on geometric spectral asymptotics whereby these assumptions are shown to be unwarranted insofar as black hole thermodynamics is concerned. The approach--consisting of the concurrent use of near-horizon and heat-kernel asymptotic expansions--leads to a proof of the holographic scaling of the entropy as a universal feature driven by conformal quantum mechanics.Comment: 13 pages, JHEP style. Added section 3 in the new version and a few typos were correcte

    Sources of VGI for Mapping

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    Drastic Vegetation Change in the Guajira Peninsula (Colombia) during the Neogene

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    Dry biomes occupy ~35% of the landscape in the Neotropics, but these are heavily human-disturbed. In spite of their importance, we still do not fully understand their origins and how they are sustained. The Guajira Peninsula in northern Colombia is dominated by dry biomes and has a rich Neogene fossil record. Here, we have analyzed its changes in vegetation and precipitation during the Neogene using a fossil pollen and spore dataset of 20 samples taken from a well and we also dated the stratigraphic sequence using microfossils. In addition, we analyzed the pollen and spore contents of 10 Holocene samples to establish a modern baseline for comparison with the Neogene as well as a study of the modern vegetation to assess both its spatial distribution and anthropic disturbances during the initial stages of European colonization. The section was dated to span from the latest Oligocene to the early Miocene (~24.2 to 17.3 Ma), with the Oligocene/Miocene boundary being in the lower Uitpa Formation. The early Miocene vegetation is dominated by a rainforest biome with a mean annual precipitation of ~2,000 mm/yr, which strongly contrasts with Guajira\u27s modern xerophytic vegetation and a precipitation of ~300 mm/yr. The shift to the dry modern vegetation probably occurred over the past three millions years, but the mechanism that led to this change is still uncertain. Global circulation models that include the vegetation could explain the ancient climate of Guajira, but further work is required to assess the feedbacks of vegetation, precipitation, and CO2

    Bubbles from Nothing

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    Within the framework of flux compactifications, we construct an instanton describing the quantum creation of an open universe from nothing. The solution has many features in common with the smooth 6d bubble of nothing solutions discussed recently, where the spacetime is described by a 4d compactification of a 6d Einstein-Maxwell theory on S^2 stabilized by flux. The four-dimensional description of this instanton reduces to that of Hawking and Turok. The choice of parameters uniquely determines all future evolution, which we additionally find to be stable against bubble of nothing instabilities.Comment: 19 pages, 6 figure

    Conformal Tightness of Holographic Scaling in Black Hole Thermodynamics

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    The near-horizon conformal symmetry of nonextremal black holes is shown to be a mandatory ingredient for the holographic scaling of the scalar-field contribution to the black hole entropy. This conformal tightness is revealed by semiclassical first-principle scaling arguments through an analysis of the multiplicative factors in the entropy due to the radial and angular degrees of freedom associated with a scalar field. Specifically, the conformal SO(2,1) invariance of the radial degree of freedom conspires with the area proportionality of the angular momentum sums to yield a robust holographic outcome.Comment: 23 pages, 1 figure. v2 & v3: expanded explanations and proofs, references added, typos corrected; v3: published versio
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