2,037 research outputs found

    Control Plane Compression

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    We develop an algorithm capable of compressing large networks into a smaller ones with similar control plane behavior: For every stable routing solution in the large, original network, there exists a corresponding solution in the compressed network, and vice versa. Our compression algorithm preserves a wide variety of network properties including reachability, loop freedom, and path length. Consequently, operators may speed up network analysis, based on simulation, emulation, or verification, by analyzing only the compressed network. Our approach is based on a new theory of control plane equivalence. We implement these ideas in a tool called Bonsai and apply it to real and synthetic networks. Bonsai can shrink real networks by over a factor of 5 and speed up analysis by several orders of magnitude.Comment: Extended version of the paper appearing in ACM SIGCOMM 201

    Strain-induced partially flat band, helical snake states, and interface superconductivity in topological crystalline insulators

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    Topological crystalline insulators in IV-VI compounds host novel topological surface states consisting of multi-valley massless Dirac fermions at low energy. Here we show that strain generically acts as an effective gauge field on these Dirac fermions and creates pseudo-Landau orbitals without breaking time-reversal symmetry. We predict the realization of this phenomenon in IV-VI semiconductor heterostructures, due to a naturally occurring misfit dislocation array at the interface that produces a periodically varying strain field. Remarkably, the zero-energy Landau orbitals form a flat band in the vicinity of the Dirac point, and coexist with a network of snake states at higher energy. We propose that the high density of states of this flat band gives rise to interface superconductivity observed in IV-VI semiconductor multilayers at unusually high temperatures, with non-BCS behavior. Our work demonstrates a new route to altering macroscopic electronic properties to achieve a partially flat band, and paves the way for realizing novel correlated states of matter.Comment: Accepted by Nature Physic

    Compatibility between entomopathogenic fungi and biorational insecticides in toxicity against Ronderosia bergi under laboratory conditions

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    Our aim was to evaluate the efficacy of combinations between two biorational insecticides (luphenuron, methoxyfenozide), a new synthetic chemical pesticide (rynaxypyr), and three entomopathogenic fungi strains (Beauveria bassianaLPSc 1067, LPSc1082), and Metarhizium anisopliae (LPSc 907) in the biocontrol of the pest grasshopper Ronderosia bergi (Stål) under laboratory conditions. The insecticides were tested at three concentrations: the average concentration recommended for application in the field (100%) and 50% and finally 25% of that level. The fungal strains used were adjusted to 1×108, 1×106, and 1×104conidia ml-1. The combinations of those insecticides with B. bassiana (LPSc 1067, LPSc 1082) and M. anisopliae (LPSc 907) caused higher mortality to R. bergi nymphs than any of the individual agents used alone. The three insecticides tested did not affect the isolates of the two species of entomopathogenic fungi employed. In conclusion, the use of these biorational insecticides in an IPM program aimed at control of the grasshopper R. bergicould be of value

    Polarography of Te (IV) Anions in Neutral Solutions in Presence of 2,2'- Dipyridyl and Fe(dipy)3 2+ - Complexes

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    The electroreduction of Te (IV) ions in neutral non-buffer solutions containing 2,2'-dipyridyl (4в‹…10-5- 4в‹…10-3 M) or tris-dipyridyl iron (II) complexes is studied by the polarographic method. NaF (0.01-0.5 M) or NaNO3 (0.1-1 M) are used as supporting electrolytes. The mechanism of electrochemical reactions of Te (IV) anions on mercury electrodes in the presence of the additives is discussed. The electroreduction of Te (IV) anions is shown to proceed through electron transfer and proton addition. The obtained results point to a considerable influence of electric double layer structure on electrochemical reactions of Te (IV) ions in the presence of inorganic and specifically adsorbed organic compounds in the electrolyte. It is shown, that 2,2'-dipyridyl does not form complexes with Te (IV) anions. Having been adsorbed on the surface of mercury electrode, 2,2'-dipyridyl complexes increase negative ОЁ'-potential that results in a shift of Te (IV) electroreduction wave to more negative potentials and decrease in the current of Te (IV) wave and peak at -1.19 V. It is shown that 2,2'-dipyridyl molecules at Оµ > 0, (Оµ вЂ“ charge of an electrode) are adsorbed in plane orientation, and at Оµ < 0, plane or vertical. Vertically adsorbed molecules cause a significant decrease in the double layer capacitance. At negative potentials orientation of 2,2'-dipyridyl molecules changes from plane to vertical with the increasing 2,2'-dipyridyl concentration. This change of orientation results in a typical maximum capacitance emerging in the potential range of -0.7 to -1.2 V. It is shown that the supporting electrolyte, 2,2'-dipyridyl and Fe(dipy)32+ В have influence on the electroreduction of Te (IV) anions in neutral non-buffer solutions through a change in the ОЁ'-potential of mercury electrode

    Critical assessment of the quartz crystal microbalance with dissipation as an analytical tool for biosensor development and fundamental studies

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    One of the challenges in electrochemical biosensor design is gaining a fundamental knowledge of the processes underlying immobilisation of the molecules onto the electrode surface. This is of particular importance in biocomposite sensors where concerns have arisen as to the nature of the interaction between the biological and synthetic molecules immobilised. We examined the use of the Quartz Crystal Microbalance with Dissipation (QCM-D) as a tool for fundamental analyses of a model sensor constructed by the immobilisation of cobalt(II) phthalocyanine (TCACoPc) and glucose oxidase (GOx) onto a gold-quartz electrode (electrode surface) for the enhanced detection of glucose. The model sensor was constructed in aqueous phase and covalently linked the gold surface to the TCACoPc, and the TCACoPc to the GOx, using the QCM-D. The aqueous metallophthalocyanine (MPc) formed a multi-layer over the surface of the electrode, which could be removed to leave a monolayer with a mass loading that compared favourably to the theoretical value expected. Analysis of frequency and dissipation plots indicated covalent attachment of glucose oxidase onto the metallophthalocyanine layer. The amount of GOx bound using the model system compared favourably to calculations derived from the maximal amperometric functioning of the electrochemical sensor (examined in previously-published literature, Mashazi, P.N., Ozoemena, K.I., Nyokong, T., 2006. Electrochim. Acta 52, 177–186), but not to theoretical values derived from dimensions of GOx as established by crystallography. The strength of the binding of the GOx film with the TCACoPc layer was tested by using 2% SDS as a denaturant/surfactant, and the GOx film was not found to be significantly affected by exposure to this. This paper thus showed that QCM-D can be used in order to model essential processes and interactions that dictate the functional parameters of a biosensor

    Beyond single-photon localization at the edge of a Photonic Band Gap

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    We study spontaneous emission in an atomic ladder system, with both transitions coupled near-resonantly to the edge of a photonic band gap continuum. The problem is solved through a recently developed technique and leads to the formation of a ``two-photon+atom'' bound state with fractional population trapping in both upper states. In the long-time limit, the atom can be found excited in a superposition of the upper states and a ``direct'' two-photon process coexists with the stepwise one. The sensitivity of the effect to the particular form of the density of states is also explored.Comment: to appear in Physical Review

    Unsupervised Bayesian linear unmixing of gene expression microarrays

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    Background: This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Results: Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. Conclusions: The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor
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