131 research outputs found

    Squarepants in a Tree: Sum of Subtree Clustering and Hyperbolic Pants Decomposition

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    We provide efficient constant factor approximation algorithms for the problems of finding a hierarchical clustering of a point set in any metric space, minimizing the sum of minimimum spanning tree lengths within each cluster, and in the hyperbolic or Euclidean planes, minimizing the sum of cluster perimeters. Our algorithms for the hyperbolic and Euclidean planes can also be used to provide a pants decomposition, that is, a set of disjoint simple closed curves partitioning the plane minus the input points into subsets with exactly three boundary components, with approximately minimum total length. In the Euclidean case, these curves are squares; in the hyperbolic case, they combine our Euclidean square pants decomposition with our tree clustering method for general metric spaces.Comment: 22 pages, 14 figures. This version replaces the proof of what is now Lemma 5.2, as the previous proof was erroneou

    Labeling Schemes for Bounded Degree Graphs

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    We investigate adjacency labeling schemes for graphs of bounded degree Δ=O(1)\Delta = O(1). In particular, we present an optimal (up to an additive constant) logn+O(1)\log n + O(1) adjacency labeling scheme for bounded degree trees. The latter scheme is derived from a labeling scheme for bounded degree outerplanar graphs. Our results complement a similar bound recently obtained for bounded depth trees [Fraigniaud and Korman, SODA 10], and may provide new insights for closing the long standing gap for adjacency in trees [Alstrup and Rauhe, FOCS 02]. We also provide improved labeling schemes for bounded degree planar graphs. Finally, we use combinatorial number systems and present an improved adjacency labeling schemes for graphs of bounded degree Δ\Delta with (e+1)n<Δn/5(e+1)\sqrt{n} < \Delta \leq n/5

    Dynamic and Multi-functional Labeling Schemes

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    We investigate labeling schemes supporting adjacency, ancestry, sibling, and connectivity queries in forests. In the course of more than 20 years, the existence of logn+O(loglog)\log n + O(\log \log) labeling schemes supporting each of these functions was proven, with the most recent being ancestry [Fraigniaud and Korman, STOC '10]. Several multi-functional labeling schemes also enjoy lower or upper bounds of logn+Ω(loglogn)\log n + \Omega(\log \log n) or logn+O(loglogn)\log n + O(\log \log n) respectively. Notably an upper bound of logn+5loglogn\log n + 5\log \log n for adjacency+siblings and a lower bound of logn+loglogn\log n + \log \log n for each of the functions siblings, ancestry, and connectivity [Alstrup et al., SODA '03]. We improve the constants hidden in the OO-notation. In particular we show a logn+2loglogn\log n + 2\log \log n lower bound for connectivity+ancestry and connectivity+siblings, as well as an upper bound of logn+3loglogn+O(logloglogn)\log n + 3\log \log n + O(\log \log \log n) for connectivity+adjacency+siblings by altering existing methods. In the context of dynamic labeling schemes it is known that ancestry requires Ω(n)\Omega(n) bits [Cohen, et al. PODS '02]. In contrast, we show upper and lower bounds on the label size for adjacency, siblings, and connectivity of 2logn2\log n bits, and 3logn3 \log n to support all three functions. There exist efficient adjacency labeling schemes for planar, bounded treewidth, bounded arboricity and interval graphs. In a dynamic setting, we show a lower bound of Ω(n)\Omega(n) for each of those families.Comment: 17 pages, 5 figure

    Adjacency labeling schemes and induced-universal graphs

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    We describe a way of assigning labels to the vertices of any undirected graph on up to nn vertices, each composed of n/2+O(1)n/2+O(1) bits, such that given the labels of two vertices, and no other information regarding the graph, it is possible to decide whether or not the vertices are adjacent in the graph. This is optimal, up to an additive constant, and constitutes the first improvement in almost 50 years of an n/2+O(logn)n/2+O(\log n) bound of Moon. As a consequence, we obtain an induced-universal graph for nn-vertex graphs containing only O(2n/2)O(2^{n/2}) vertices, which is optimal up to a multiplicative constant, solving an open problem of Vizing from 1968. We obtain similar tight results for directed graphs, tournaments and bipartite graphs

    Basic Surgical Techniques in the Göttingen Minipig: Intubation, Bladder Catheterization, Femoral Vessel Catheterization, and Transcardial Perfusion

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    The emergence of the Göttingen minipig in research of topics such as neuroscience, toxicology, diabetes, obesity, and experimental surgery reflects the close resemblance of these animals to human anatomy and physiology 1-6.The size of the Göttingen minipig permits the use of surgical equipment and advanced imaging modalities similar to those used in humans 6-8. The aim of this instructional video is to increase the awareness on the value of minipigs in biomedical research, by demonstrating how to perform tracheal intubation, transurethral bladder catheterization, femoral artery and vein catheterization, as well as transcardial perfusion

    Compressed Membership for NFA (DFA) with Compressed Labels is in NP (P)

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    In this paper, a compressed membership problem for finite automata, both deterministic and non-deterministic, with compressed transition labels is studied. The compression is represented by straight-line programs (SLPs), i.e. context-free grammars generating exactly one string. A novel technique of dealing with SLPs is introduced: the SLPs are recompressed, so that substrings of the input text are encoded in SLPs labelling the transitions of the NFA (DFA) in the same way, as in the SLP representing the input text. To this end, the SLPs are locally decompressed and then recompressed in a uniform way. Furthermore, such recompression induces only small changes in the automaton, in particular, the size of the automaton remains polynomial. Using this technique it is shown that the compressed membership for NFA with compressed labels is in NP, thus confirming the conjecture of Plandowski and Rytter and extending the partial result of Lohrey and Mathissen; as it is already known, that this problem is NP-hard, we settle its exact computational complexity. Moreover, the same technique applied to the compressed membership for DFA with compressed labels yields that this problem is in P; for this problem, only trivial upper-bound PSPACE was known
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