Transition Dependency: A Gene-Gene Interaction Measure for Times Series Microarray Data

Gene-Gene dependency plays a very important role in system biology as it pertains to the crucial understanding of different biological mechanisms. Time-course microarray data provides a new platform useful to reveal the dynamic mechanism of gene-gene dependencies. Existing interaction measures are mostly based on association measures, such as Pearson or Spearman correlations. However, it is well known that such interaction measures can only capture linear or monotonic dependency relationships but not for nonlinear combinatorial dependency relationships. With the invocation of hidden Markov models, we propose a new measure of pairwise dependency based on transition probabilities. The new dynamic interaction measure checks whether or not the joint transition kernel of the bivariate state variables is the product of two marginal transition kernels. This new measure enables us not only to evaluate the strength, but also to infer the details of gene dependencies. It reveals nonlinear combinatorial dependency structure in two aspects: between two genes and across adjacent time points. We conduct a bootstrap-based Ç2 test for presence/absence of the dependency between every pair of genes. Simulation studies and real biological data analysis demonstrate the application of the proposed method. The software package is available under request

Turbulent Rectangular Compound Open Channel Flow Study Using Multi-Zonal Approach

YesIn this paper, an improved Shiono-Knight model (SKM) has been proposed to calculate the rectangular compound open channel flows by considering a Multi-Zonal (MZ) approach in modelling turbulence and secondary flows across lateral flow direction. This is an effort to represent natural flows with compound shape more closely. The proposed model improves the estimation of secondary flow by original SKM model to increase the accuracy of depthaveraged velocity profile solution formed within the transitional region between different sections (i.e. between main-channel and floodplain) of compound channel. This proposed MZ model works by sectioning intermediate zones between floodplain and main-channel for running computation in order to improve the modelling accuracy. The modelling results have been validated using the experimental data by national UK Flood Channel Facility (FCF). It has been proven to work reasonably well to model secondary flows within the investigated compound channel flow cases and hence produce better representation to their flow lateral velocity profile

Clustering Service Networks with Entity, Attribute, and Link Heterogeneity

Many popular web service networks are content-rich in terms of heterogeneous types of entities and links, associated with incomplete attributes. Clustering such heterogeneous service networks demands new clustering techniques that can handle two heterogeneity challenges: (1) multiple types of entities co-exist in the same service network with multiple attributes, and (2) links between entities have diverse types and carry different semantics. Existing heterogeneous graph clustering techniques tend to pick initial centroids uniformly at random, specify the number k of clusters in advance, and fix k during the clustering process. In this paper, we propose Service Cluster, a novel heterogeneous service network clustering algorithm with four unique features. First, we incorporate various types of entity, attribute and link information into a unified distance measure. Second, we design a Discrete Steepest Descent method to naturally produce initial k and initial centroids simultaneously. Third, we propose a dynamic learning method to automatically adjust the link weights towards clustering convergence. Fourth, we develop an effective optimization strategy to identify new suitable k and k well-chosen centroids at each clustering iteration. Extensive evaluation on real datasets demonstrates that Service Cluster outperforms existing representative methods in terms of both effectiveness and efficiency

Interpretability of Gradual Semantics in Abstract Argumentation

International audiencergumentation, in the field of Artificial Intelligence, is a for-malism allowing to reason with contradictory information as well as tomodel an exchange of arguments between one or several agents. For thispurpose, many semantics have been defined with, amongst them, grad-ual semantics aiming to assign an acceptability degree to each argument.Although the number of these semantics continues to increase, there iscurrently no method allowing to explain the results returned by thesesemantics. In this paper, we study the interpretability of these seman-tics by measuring, for each argument, the impact of the other argumentson its acceptability degree. We define a new property and show that thescore of an argument returned by a gradual semantics which satisfies thisproperty can also be computed by aggregating the impact of the otherarguments on it. This result allows to provide, for each argument in anargumentation framework, a ranking between arguments from the most to the least impacting ones w.r.t a given gradual semantic

Integrabilities of the t−Jt-J Model with Impurities

The hamiltonian with magnetic impurities coupled to the strongly correlated electron system is constructed from $t-J$ model. And it is diagonalized exactly by using the Bethe ansatz method. Our boundary matrices depend on the spins of the electrons. The Kondo problem in this system is discussed in details. The integral equations are derived with complex rapidities which describe the bound states in the system. The finite-size corrections for the ground-state energies are obtained.Comment: 24 pages, Revtex, To be published in J. Phys.

On the retreat of near-Earth neutral line during substorm expansion phase: a THEMIS case study during the 9 January 2008 substorm

The location of magnetic reconnection in the mid-tail during a substorm was studied in many researches. Here we present multi-point THEMIS observations of a reconnection event in the near-Earth magnetotail during substorm. In this event, THEMIS probes stayed in the near-Earth and mid-tail region aligning along the magnetotail. This allows reconnection evolution to be probed simultaneously from about −10 <I>R</I>_E to −23 <I>R</I>_E down tail. The Hall current related electron streams were observed at the same time by two probes far away from the reconnection site. Before near-Earth reconnection involved the tail lobe magnetic field, the reconnection site was restricted in earthward −23 <I>R</I>_E. When reconnection involved into the tail lobe region, the reconnection site started to retreat gradually

Three‐dimensional lunar wake reconstructed from ARTEMIS data

Data from the two‐spacecraft Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon's Interaction with the Sun mission to the Moon have been exploited to characterize the lunar wake with unprecedented fidelity. The differences between measurements made by a spacecraft in the solar wind very near the Moon and concurrent measurements made by a second spacecraft in the near lunar wake are small but systematic. They enabled us to establish the perturbations of plasma density, temperature, thermal, magnetic and total pressure, field, and flow downstream of the Moon to distances of 12 lunar radii ( R M ). The wake disturbances are initiated immediately behind the Moon by the diamagnetic currents at the lunar terminator. Rarefaction waves propagate outward at fast MHD wave velocities. Beyond ~6.5 R M , all plasma and field parameters are poorly structured which suggests the presence of instabilities excited by counter‐streaming particles. Inward flowing plasma accelerated through pressure gradient force and ambipolar electric field compresses the magnetic field and leads to continuous increase in magnitude of magnetic perturbations. Besides the downstream distance, the field perturbation magnitude is also a function of the solar wind ion beta and the angle between the solar wind and the interplanetary magnetic field (IMF). Both ion and electron temperatures increase as a consequence of an energy dispersion effect, whose explanation requires fully kinetic models. Downstream of the Moon, the IMF field lines are observed to bulge toward the Moon, which is unexpected and may be caused by a plasma pressure gradient force or/and the pickup of heavy charged dust grains behind the Moon. Key Points The 3‐D lunar wake is studied with well‐determined solar wind conditions The field lines bend in the wake due to flow deceleration The 3‐D wake structure is investigated by observation dataPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108259/1/jgra51135.pd

Realization of a crosstalk-avoided quantum network node with dual-type qubits by the same ion species

Generating ion-photon entanglement is a crucial step for scalable trapped-ion quantum networks. To avoid the crosstalk on memory qubits carrying quantum information, it is common to use a different ion species for ion-photon entanglement generation such that the scattered photons are far off-resonant for the memory qubits. However, such a dual-species scheme requires elaborate control of the portion and the location of different ion species, and can be subject to inefficient sympathetic cooling. Here we demonstrate a trapped-ion quantum network node in the dual-type qubit scheme where two types of qubits are encoded in the $S$ and $F$ hyperfine structure levels of ${}^{171}\mathrm{Yb}^+$ ions. We generate ion photon entanglement for the $S$-qubit in a typical timescale of hundreds of milliseconds, and verify its small crosstalk on a nearby $F$-qubit with coherence time above seconds. Our work demonstrates an enabling function of the dual-type qubit scheme for scalable quantum networks