235 research outputs found

    2-Vertex Connectivity in Directed Graphs

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    We complement our study of 2-connectivity in directed graphs, by considering the computation of the following 2-vertex-connectivity relations: We say that two vertices v and w are 2-vertex-connected if there are two internally vertex-disjoint paths from v to w and two internally vertex-disjoint paths from w to v. We also say that v and w are vertex-resilient if the removal of any vertex different from v and w leaves v and w in the same strongly connected component. We show how to compute the above relations in linear time so that we can report in constant time if two vertices are 2-vertex-connected or if they are vertex-resilient. We also show how to compute in linear time a sparse certificate for these relations, i.e., a subgraph of the input graph that has O(n) edges and maintains the same 2-vertex-connectivity and vertex-resilience relations as the input graph, where n is the number of vertices.Comment: arXiv admin note: substantial text overlap with arXiv:1407.304

    Finding 2-Edge and 2-Vertex Strongly Connected Components in Quadratic Time

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    We present faster algorithms for computing the 2-edge and 2-vertex strongly connected components of a directed graph, which are straightforward generalizations of strongly connected components. While in undirected graphs the 2-edge and 2-vertex connected components can be found in linear time, in directed graphs only rather simple O(mn)O(m n)-time algorithms were known. We use a hierarchical sparsification technique to obtain algorithms that run in time O(n2)O(n^2). For 2-edge strongly connected components our algorithm gives the first running time improvement in 20 years. Additionally we present an O(m2/logn)O(m^2 / \log{n})-time algorithm for 2-edge strongly connected components, and thus improve over the O(mn)O(m n) running time also when m=O(n)m = O(n). Our approach extends to k-edge and k-vertex strongly connected components for any constant k with a running time of O(n2log2n)O(n^2 \log^2 n) for edges and O(n3)O(n^3) for vertices

    Triangle-Free Penny Graphs: Degeneracy, Choosability, and Edge Count

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    We show that triangle-free penny graphs have degeneracy at most two, list coloring number (choosability) at most three, diameter D=Ω(n)D=\Omega(\sqrt n), and at most min(2nΩ(n),2nD2)\min\bigl(2n-\Omega(\sqrt n),2n-D-2\bigr) edges.Comment: 10 pages, 2 figures. To appear at the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

    An Improved Upper Bound for the Ring Loading Problem

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    The Ring Loading Problem emerged in the 1990s to model an important special case of telecommunication networks (SONET rings) which gained attention from practitioners and theorists alike. Given an undirected cycle on nn nodes together with non-negative demands between any pair of nodes, the Ring Loading Problem asks for an unsplittable routing of the demands such that the maximum cumulated demand on any edge is minimized. Let LL be the value of such a solution. In the relaxed version of the problem, each demand can be split into two parts where the first part is routed clockwise while the second part is routed counter-clockwise. Denote with LL^* the maximum load of a minimum split routing solution. In a landmark paper, Schrijver, Seymour and Winkler [SSW98] showed that LL+1.5DL \leq L^* + 1.5D, where DD is the maximum demand value. They also found (implicitly) an instance of the Ring Loading Problem with L=L+1.01DL = L^* + 1.01D. Recently, Skutella [Sku16] improved these bounds by showing that LL+1914DL \leq L^* + \frac{19}{14}D, and there exists an instance with L=L+1.1DL = L^* + 1.1D. We contribute to this line of research by showing that LL+1.3DL \leq L^* + 1.3D. We also take a first step towards lower and upper bounds for small instances

    Neural Decision Boundaries for Maximal Information Transmission

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    We consider here how to separate multidimensional signals into two categories, such that the binary decision transmits the maximum possible information transmitted about those signals. Our motivation comes from the nervous system, where neurons process multidimensional signals into a binary sequence of responses (spikes). In a small noise limit, we derive a general equation for the decision boundary that locally relates its curvature to the probability distribution of inputs. We show that for Gaussian inputs the optimal boundaries are planar, but for non-Gaussian inputs the curvature is nonzero. As an example, we consider exponentially distributed inputs, which are known to approximate a variety of signals from natural environment.Comment: 5 pages, 3 figure

    Pixel and Voxel Representations of Graphs

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    We study contact representations for graphs, which we call pixel representations in 2D and voxel representations in 3D. Our representations are based on the unit square grid whose cells we call pixels in 2D and voxels in 3D. Two pixels are adjacent if they share an edge, two voxels if they share a face. We call a connected set of pixels or voxels a blob. Given a graph, we represent its vertices by disjoint blobs such that two blobs contain adjacent pixels or voxels if and only if the corresponding vertices are adjacent. We are interested in the size of a representation, which is the number of pixels or voxels it consists of. We first show that finding minimum-size representations is NP-complete. Then, we bound representation sizes needed for certain graph classes. In 2D, we show that, for kk-outerplanar graphs with nn vertices, Θ(kn)\Theta(kn) pixels are always sufficient and sometimes necessary. In particular, outerplanar graphs can be represented with a linear number of pixels, whereas general planar graphs sometimes need a quadratic number. In 3D, Θ(n2)\Theta(n^2) voxels are always sufficient and sometimes necessary for any nn-vertex graph. We improve this bound to Θ(nτ)\Theta(n\cdot \tau) for graphs of treewidth τ\tau and to O((g+1)2nlog2n)O((g+1)^2n\log^2n) for graphs of genus gg. In particular, planar graphs admit representations with O(nlog2n)O(n\log^2n) voxels

    Network adaptation improves temporal representation of naturalistic stimuli in drosophila eye: II Mechanisms

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    Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information

    Stability of oligosaccharides derived from lactulose during the processing of milk and apple juice

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    The scientific evidence on the bioactivity of oligosaccharides from lactulose has encouraged us to study their physicochemical modifications during the processing of milk and apple juice. The carbohydrate fraction with a degree of polymerization ≥3 was stable in milk heated at temperatures up to 100°C for 30 min and in apple juice heated up to 90°C for 15 min. An assessment of the Maillard reaction in heated milk pointed out a higher formation of furosine in milk with oligosaccharides from lactulose as compared to its counterpart without this ingredient, due to a higher presence of galactose. The organoleptic properties of juice with oligosaccharides from lactulose were acceptable and similar to those of apple juice with commercial galactooligosaccharides. The results presented herein demonstrate that oligosaccharides from lactulose can be used as prebiotic ingredients in a wide range of functional foods, including those intended for diabetics and lactose intolerant individuals.This work has been supported by project AGL2011-27884 from Spanish Ministerio de Economía y Competitividad.Peer Reviewe

    Status, Trends, and Conservation of Eelgrass in Atlantic Canada and the Northeastern United States: Workshop Report

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    Eelgrass (Zostera marina L) is the dominant seagrass occurring in eastern Canada and the northeastern United States, where it often forms extensive meadows in coastal and estuarine areas. Eelgrass beds are extremely productive and provide many valuable ecological functions and ecosystem services. They serve as critical feeding and nursery habitat for a wide variety of commercially and recreationally important fish and shellfish and as feeding areas for waterfowl and other waterbirds. Eelgrass detritus is also transported considerable distances to fuel offshore food webs. In addition, eelgrass beds stabilize bottom sediments, dampen wave energy, absorb nutrients from surrounding waters, and retain carbon through burial
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