916 resultados para Conditional Directed Graph


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Small RNA-mediated chromatin silencing is well characterized for repeated sequences and transposons, but its role in regulating single-copy endogenous genes is unclear. We have identified two small RNAs (30 and 24 nucleotides) corresponding to the reverse strand 3' to the canonical poly(A) site of FLOWERING LOCUS C (FLC), an Arabidopsis gene encoding a repressor of flowering. Genome searches suggest that these RNAs originate from the FLC locus in a genomic region lacking repeats. The 24-nt small RNA, which is most abundant in developing fruits, is absent in mutants defective in RNA polymerase IVa, RNA-DEPENDENT RNA POLYMERASE 2, and DICER-LIKE 3, components required for RNAi-mediated chromatin silencing. The corresponding genomic region shows histone 3 lysine 9 dimethylation, which was reduced in a dcl2,3,4 triple mutant. Investigations into the origins of the small RNAs revealed a polymerase IVa-dependent spliced, antisense transcript covering the 3' FLC region. Mutation of this genomic region by T-DNA insertion led to FLC misexpression and delayed flowering, suggesting that RNAi-mediated chromatin modification is an important component of endogenous pathways that function to suppress FLC expression.

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We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick “repairs,” which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been l in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most l log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degree would have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network.

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Physical Access Control Systems are commonly used to secure doors in buildings such as airports, hospitals, government buildings and offices. These systems are designed primarily to provide an authentication mechanism, but they also log each door access as a transaction in a database. Unsupervised learning techniques can be used to detect inconsistencies or anomalies in the mobility data, such as a cloned or forged Access Badge, or unusual behaviour by staff members. In this paper, we present an overview of our method of inferring directed graphs to represent a physical building network and the flows of mobility within it. We demonstrate how the graphs can be used for Visual Data Exploration, and outline how to apply algorithms based on Information Theory to the graph data in order to detect inconsistent or abnormal behaviour.

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Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we present AGWAN (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the AGWAN model to real-world graphs and for generating random graphs from the model. Using the Enron “who communicates with whom” social graph, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to the structure of real-world graphs.

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We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick "repairs," which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions,without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been - in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most - log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degreewould have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network. © Springer-Verlag 2012.

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Posterior parietal cortex (PPC) constitutes a critical cortical node in the sensorimotor system in which goal-directed actions are computed. This information then must be transferred into commands suitable for hand movements to the primary motor cortex (M1). Complexity arises because reach-to-grasp actions not only require directing the hand towards the object (transport component), but also preshaping the hand according to the features of the object (grip component). Yet, the functional influence that specific PPC regions exert over ipsilateral M1 during the planning of different hand movements remains unclear in humans. Here we manipulated transport and grip components of goal-directed hand movements and exploited paired-pulse transcranial magnetic stimulation (ppTMS) to probe the functional interactions between M1 and two different PPC regions, namely superior parieto-occipital cortex (SPOC) and the anterior region of the intraparietal sulcus (aIPS), in the left hemisphere. We show that when the extension of the arm is required to contact a target object, SPOC selectively facilitates motor evoked potentials, suggesting that SPOC-M1 interactions are functionally specific to arm transport. In contrast, a different pathway, linking the aIPS and ipsilateral M1, shows enhanced functional connections during the sensorimotor planning of grip. These results support recent human neuroimaging findings arguing for specialized human parietal regions for the planning of arm transport and hand grip during goal-directed actions. Importantly, they provide new insight into the causal influences these different parietal regions exert over ipsilateral motor cortex for specific types of planned hand movements

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We address the presence of bound entanglement in strongly interacting spin systems at thermal equilibrium. In particular, we consider thermal graph states composed of an arbitrary number of particles. We show that for a certain range of temperatures no entanglement can be extracted by means of local operations and classical communication, even though the system is still entangled. This is found by harnessing the independence of the entanglement in some bipartitions of such states with the system's size. Specific examples for one- and two-dimensional systems are given. Our results thus prove the existence of thermal bound entanglement in an arbitrary large spin system with finite-range local interactions.

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A new pathway to (+)-inthomycin C is reported that exploits an O-directed free radical hydrostannation reaction on (−)-12 and a Stille cross-coupling as key steps. Significantly, the latter process was effected on 19 where a gauche-pentane repulsive interaction could interfere. Our stereochemical studies on the alkynol (−)-12 and the enyne (+)-7 confirm that Ryu and Hatakeyama’s (3S)-stereochemical revision of (+)-inthomycin C is invalid and that Zeeck and Taylor’s original (3R)-stereostructure for (+)-inthomycin C is correct.

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Abstract Image

Herein a new double O-directed free radical hydrostannation reaction is reported on the structurally complex dialkyldiyne 11. Through our use of a conformation-restraining acetal to help prevent stereocenter-compromising 1,5-H-atom abstraction reactions by vinyl radical intermediates, the two vinylstannanes of 10 were concurrently constructed with high stereocontrol using Ph3SnH/Et3B/O2. Distannane 10 was thereafter elaborated into the bis-vinyl iodide 9 via O-silylation and double I–Sn exchange; double Stille coupling of 9, O-desilylation, and oxidation thereafter furnished 8.