Tiler : Software for Human-Guided Data Exploration

Peer reviewe

A tool for subjective and interactive visual data exploration

We present SIDE, a tool for Subjective and Interactive Visual Data Exploration, which lets users explore high dimensional data via subjectively informative 2D data visualizations. Many existing visual analytics tools are either restricted to specific problems and domains or they aim to find visualizations that align with user’s belief about the data. In contrast, our generic tool computes data visualizations that are surprising given a user’s current understanding of the data. The user’s belief state is represented as a set of projection tiles. Hence, this user-awareness offers users an efficient way to interactively explore yet-unknown features of complex high dimensional datasets

Fluid modeling of the conversion of CH4 in presence of O2 of CO2 into methanol and syngas in an atmospheric pressure dielectric barrier discharge

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Cloning and expression analysis of a blue copperbinding protein gene from Dasypyrum Villosum

Adifferentially expressed fragment EST145 was isolated by suppression subtractive hybridization (SSH) method. Using EST145 as the probe, a blue copper-binding protein gene designated as DvBCB was screened from Dasypyrum villosum cDNA Library. The DvBCB gene was 845 bp in length with an open reading frame (ORF) which encoded a 178-amino acid polypeptide and contained the deduced functional sites: H66, C107, H112 and M121. Northern blot analysis showed that, the expression of DvBCB gene was enhanced in leaves after inoculation with Erysiphe graminis; reached a peak level at 24 h and decreased to constitutive level at 72 h after inoculation in resistant Gh21 line. The expression level in susceptible mutant M14S line was slightly lower than that in the resistant Gh21 line at all stages after inoculation, and the peak could not appear in M14S line. The function of DvBCB gene might include lignification of cell wall or scavenging of reactive oxygen species (ROS) during powdery mildew attack.Key words: Dasypyrum villosum, powdery mildew, suppression subtractive hybridization, blue copper-binding protein gene

Dielectric barrier discharges used for the conversion of greenhouse gases : modeling the plasma chemistry by fluid simulations

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CSNE: Conditional Signed Network Embedding

Signed networks are mathematical structures that encode positive and negative relations between entities such as friend/foe or trust/distrust. Recently, several papers studied the construction of useful low-dimensional representations (embeddings) of these networks for the prediction of missing relations or signs. Existing embedding methods for sign prediction generally enforce different notions of status or balance theories in their optimization function. These theories, however, are often inaccurate or incomplete, which negatively impacts method performance. In this context, we introduce conditional signed network embedding (CSNE). Our probabilistic approach models structural information about the signs in the network separately from fine-grained detail. Structural information is represented in the form of a prior, while the embedding itself is used for capturing fine-grained information. These components are then integrated in a rigorous manner. CSNE's accuracy depends on the existence of sufficiently powerful structural priors for modelling signed networks, currently unavailable in the literature. Thus, as a second main contribution, which we find to be highly valuable in its own right, we also introduce a novel approach to construct priors based on the Maximum Entropy (MaxEnt) principle. These priors can model the \emph{polarity} of nodes (degree to which their links are positive) as well as signed \emph{triangle counts} (a measure of the degree structural balance holds to in a network). Experiments on a variety of real-world networks confirm that CSNE outperforms the state-of-the-art on the task of sign prediction. Moreover, the MaxEnt priors on their own, while less accurate than full CSNE, achieve accuracies competitive with the state-of-the-art at very limited computational cost, thus providing an excellent runtime-accuracy trade-off in resource-constrained situations

On the Efetov-Wegner terms by diagonalizing a Hermitian supermatrix

The diagonalization of Hermitian supermatrices is studied. Such a change of coordinates is inevitable to find certain structures in random matrix theory. However it still poses serious problems since up to now the calculation of all Rothstein contributions known as Efetov-Wegner terms in physics was quite cumbersome. We derive the supermatrix Bessel function with all Efetov-Wegner terms for an arbitrary rotation invariant probability density function. As applications we consider representations of generating functions for Hermitian random matrices with and without an external field as integrals over eigenvalues of Hermitian supermatrices. All results are obtained with all Efetov-Wegner terms which were unknown before in such an explicit and compact representation.Comment: 23 pages, PACS: 02.30.Cj, 02.30.Fn, 02.30.Px, 05.30.Ch, 05.30.-d, 05.45.M