2,120 research outputs found

    Is your EPL attractive? Classification of publications through download statistics

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    Here we consider the download statistics of EPL publications. We find that papers in the journal are characterised by fast accumulations of downloads during the first couple of months after publication, followed by slower rates thereafter, behaviour which can be represented by a model with predictive power. We also find that individual papers can be classified in various ways, allowing us to compare categories for open-access and non-open-access papers. For example, for the latter publications, which comprise the bulk of EPL papers, a small proportion (2%) display intense bursts of download activity, possibly following an extended period of less remarkable behaviour. About 18% have an especially high degree of attractiveness over and above what is typical for the journal. One can also classify the ageing of attractiveness by examining download half-lives. Approximately 18% have strong interest initially, waning in time. A further 20% exhibit "delayed recognition" with relatively late spurs in download activity. Although open-access papers enjoy more downloads on average, the proportions falling into each category are similar.Comment: 6 pages, 8 figures, accepted for publication in EP

    The 13 November 1984 occultation of BD +08 deg 0471 by (1) Ceres

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    The 13 November 1984 occultation of BD +08 deg 0471 was discovered during a photographic search carried out with the 0.5 meter Carnegie Double Astrograph at Lick Observatory and the Lowell Observatory PDS microdensitometer. Such a search was stimulated by the curious fact that few favorably located occultations of AGK3 or SAO catalog starts by Ceres will occur during the 1980s. The occultation on 13 November, however, is a particularly good event. The star is 1000 cubic M in V, yielding a predicted drop at occultation of about 10%. Such a drop can be detected by small telescopes equipped with photoelectric photometers, but is too small to be seen visually. The track was predicted to cross the Caribbean, Florida, southern Texas, and Mexico. Based on this prediction, preparations were made to observe the event in Mexico using four portable occultation data systems

    Investigating interaction-induced chaos using time-dependent density functional theory

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    Systems whose underlying classical dynamics are chaotic exhibit signatures of the chaos in their quantum mechanics. We investigate the possibility of using time-dependent density functional theory (TDDFT) to study the case when chaos is induced by electron-interaction alone. Nearest-neighbour level-spacing statistics are in principle exactly and directly accessible from TDDFT. We discuss how the TDDFT linear response procedure can reveal the mechanism of chaos induced by electron-interaction alone. A simple model of a two-electron quantum dot highlights the necessity to go beyond the adiabatic approximation in TDDFT.Comment: 8 pages, 4 figure

    Long-term Tracking in the Wild: A Benchmark

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    We introduce the OxUvA dataset and benchmark for evaluating single-object tracking algorithms. Benchmarks have enabled great strides in the field of object tracking by defining standardized evaluations on large sets of diverse videos. However, these works have focused exclusively on sequences that are just tens of seconds in length and in which the target is always visible. Consequently, most researchers have designed methods tailored to this "short-term" scenario, which is poorly representative of practitioners' needs. Aiming to address this disparity, we compile a long-term, large-scale tracking dataset of sequences with average length greater than two minutes and with frequent target object disappearance. The OxUvA dataset is much larger than the object tracking datasets of recent years: it comprises 366 sequences spanning 14 hours of video. We assess the performance of several algorithms, considering both the ability to locate the target and to determine whether it is present or absent. Our goal is to offer the community a large and diverse benchmark to enable the design and evaluation of tracking methods ready to be used "in the wild". The project website is http://oxuva.netComment: To appear at ECCV 201

    Electronic Control of Spin Alignment in pi-Conjugated Molecular Magnets

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    Intramolecular spin alignment in pi-conjugated molecules is studied theoretically in a model of a Peierls-Hubbard chain coupled with two localized spins. By means of the exact diagonalization technique, we demonstrate that a spin singlet (S=0) to quartet (S=3/2) transition can be induced by electronic doping, depending on the chain length, the positions of the localized spins, and the sign of the electron-spin coupling. The calculated results provides a theoretical basis for understanding the mechanism of spin alignment recently observed in a diradical donor molecule.Comment: 4 pages, 4 figures, Physical Review Letters (in press

    Quantifying the connectivity of a network: The network correlation function method

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    Networks are useful for describing systems of interacting objects, where the nodes represent the objects and the edges represent the interactions between them. The applications include chemical and metabolic systems, food webs as well as social networks. Lately, it was found that many of these networks display some common topological features, such as high clustering, small average path length (small world networks) and a power-law degree distribution (scale free networks). The topological features of a network are commonly related to the network's functionality. However, the topology alone does not account for the nature of the interactions in the network and their strength. Here we introduce a method for evaluating the correlations between pairs of nodes in the network. These correlations depend both on the topology and on the functionality of the network. A network with high connectivity displays strong correlations between its interacting nodes and thus features small-world functionality. We quantify the correlations between all pairs of nodes in the network, and express them as matrix elements in the correlation matrix. From this information one can plot the correlation function for the network and to extract the correlation length. The connectivity of a network is then defined as the ratio between this correlation length and the average path length of the network. Using this method we distinguish between a topological small world and a functional small world, where the latter is characterized by long range correlations and high connectivity. Clearly, networks which share the same topology, may have different connectivities, based on the nature and strength of their interactions. The method is demonstrated on metabolic networks, but can be readily generalized to other types of networks.Comment: 10 figure

    Topological interactions in systems of mutually interlinked polymer rings

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    The topological interaction arising in interlinked polymeric rings such as DNA catenanes is considered. More specifically, the free energy for a pair of linked random walk rings is derived where the distance RR between two segments each of which is part of a different ring is kept constant. The topology conservation is imposed by the Gauss invariant. A previous approach (M.Otto, T.A. Vilgis, Phys.Rev.Lett. {\bf 80}, 881 (1998)) to the problem is refined in several ways. It is confirmed, that asymptotically, i.e. for large RRGR\gg R_G where RGR_G is average size of single random walk ring, the effective topological interaction (free energy) scales R4\propto R^4.Comment: 16 pages, 3 figur

    Efficient Triangle Counting in Large Graphs via Degree-based Vertex Partitioning

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    The number of triangles is a computationally expensive graph statistic which is frequently used in complex network analysis (e.g., transitivity ratio), in various random graph models (e.g., exponential random graph model) and in important real world applications such as spam detection, uncovering of the hidden thematic structure of the Web and link recommendation. Counting triangles in graphs with millions and billions of edges requires algorithms which run fast, use small amount of space, provide accurate estimates of the number of triangles and preferably are parallelizable. In this paper we present an efficient triangle counting algorithm which can be adapted to the semistreaming model. The key idea of our algorithm is to combine the sampling algorithm of Tsourakakis et al. and the partitioning of the set of vertices into a high degree and a low degree subset respectively as in the Alon, Yuster and Zwick work treating each set appropriately. We obtain a running time O(m+m3/2Δlogntϵ2)O \left(m + \frac{m^{3/2} \Delta \log{n}}{t \epsilon^2} \right) and an ϵ\epsilon approximation (multiplicative error), where nn is the number of vertices, mm the number of edges and Δ\Delta the maximum number of triangles an edge is contained. Furthermore, we show how this algorithm can be adapted to the semistreaming model with space usage O(m1/2logn+m3/2Δlogntϵ2)O\left(m^{1/2}\log{n} + \frac{m^{3/2} \Delta \log{n}}{t \epsilon^2} \right) and a constant number of passes (three) over the graph stream. We apply our methods in various networks with several millions of edges and we obtain excellent results. Finally, we propose a random projection based method for triangle counting and provide a sufficient condition to obtain an estimate with low variance.Comment: 1) 12 pages 2) To appear in the 7th Workshop on Algorithms and Models for the Web Graph (WAW 2010
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