Dunkl operators and a family of realizations of osp(1|2)

In this paper, a family of radial deformations of the realization of the Lie superalgebra osp(1|2) in the theory of Dunkl operators is obtained. This leads to a Dirac operator depending on 3 parameters. Several function theoretical aspects of this operator are studied, such as the associated measure, the related Laguerre polynomials and the related Fourier transform. For special values of the parameters, it is possible to construct the kernel of the Fourier transform explicitly, as well as the related intertwining operator.Comment: 28 pages, some small changes, accepted in Trans. Amer. Math. So

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

ISAR image matching and three-dimensional scattering imaging based on extracted dominant scatterers

This paper studies inverse synthetic aperture radar (ISAR) image matching and three-dimensional (3D) scattering imaging based on extracted dominant scatterers. In the condition of a long baseline between two radars, it is easy for obvious rotation, scale, distortion, and shift to occur between two-dimensional (2D) radar images. These problems lead to the difficulty of radar-image matching, which cannot be resolved by motion compensation and cross-correlation. What is more, due to the anisotropy, existing image-matching algorithms, such as scale invariant feature transform (SIFT), do not adapt to ISAR images very well. In addition, the angle between the target rotation axis and the radar line of sight (LOS) cannot be neglected. If so, the calibration result will be smaller than the real projection size. Furthermore, this angle cannot be estimated by monostatic radar. Therefore, instead of matching image by image, this paper proposes a novel ISAR imaging matching and 3D imaging based on extracted scatterers to deal with these issues. First, taking advantage of ISAR image sparsity, radar images are converted into scattering point sets. Then, a coarse scatterer matching based on the random sampling consistency algorithm (RANSAC) is performed. The scatterer height and accurate affine transformation parameters are estimated iteratively. Based on matched scatterers, information such as the angle and 3D image can be obtained. Finally, experiments based on the electromagnetic simulation software CADFEKO have been conducted to demonstrate the effectiveness of the proposed algorithm

Evidence of oxidative stress and mitochondrial dysfunction in spinocerebellar ataxia type 2 (SCA2) patient fibroblasts: Effect of coenzyme Q10 supplementation on these parameters

Spinocerebellar ataxia type 2 (SCA2) is a rare neurodegenerative disorder caused by a CAG repeat expansion in the ataxin-2 gene. We show increased oxidative stress, abnormalities in the antioxidant system, changes in complexes involved in oxidative phosphorylation and changes in mitochondrial morphology in SCA2 patient fibroblasts compared to controls, and we show that treatment with CoQ10 can partially reverse these changes. Together, our results suggest that oxidative stress and mitochondrial dysfunction may be contributory factors to the pathophysiology of SCA2 and that therapeutic strategies involving manipulation of the antioxidant system could prove to be of clinical benefit

Stamp transferred suspended graphene mechanical resonators for radio-frequency electrical readout

We present a simple micromanipulation technique to transfer suspended graphene flakes onto any substrate and to assemble them with small localized gates into mechanical resonators. The mechanical motion of the graphene is detected using an electrical, radio-frequency (RF) reflection readout scheme where the time-varying graphene capacitor reflects a RF carrier at f=5-6 GHz producing modulation sidebands at f +/- fm. A mechanical resonance frequency up to fm=178 MHz is demonstrated. We find both hardening/softening Duffing effects on different samples, and obtain a critical amplitude of ~40 pm for the onset of nonlinearity in graphene mechanical resonators. Measurements of the quality factor of the mechanical resonance as a function of DC bias voltage Vdc indicate that dissipation due to motion-induced displacement currents in graphene electrode is important at high frequencies and large Vdc

Supervised Human-Guided Data Exploration

Peer reviewe

Invariant integration on orthosymplectic and unitary supergroups

The orthosymplectic supergroup OSp(m|2n) and unitary supergroup U(p|q) are studied following a new approach that starts from Harish-Chandra pairs and links the sheaf-theoretical supermanifold approach of Berezin and others with the differential geometry approach of Rogers and others. The matrix elements of the fundamental representation of the Lie supergroup G are expressed in terms of functions on the product supermanifold G_0 x R^{0|N}, with G_0 the underlying Lie group and N the odd dimension of G. This product supermanifold is isomorphic to the supermanifold of G. This leads to a new expression for the standard generators of the corresponding Lie superalgebra g as invariant derivations on G. Using these results a new and transparent formula for the invariant integrals on OSp(m|2n) and U(p|q) is obtained

Generation and physiological roles of linear ubiquitin chains

Ubiquitination now ranks with phosphorylation as one of the best-studied post-translational modifications of proteins with broad regulatory roles across all of biology. Ubiquitination usually involves the addition of ubiquitin chains to target protein molecules, and these may be of eight different types, seven of which involve the linkage of one of the seven internal lysine (K) residues in one ubiquitin molecule to the carboxy-terminal diglycine of the next. In the eighth, the so-called linear ubiquitin chains, the linkage is between the amino-terminal amino group of methionine on a ubiquitin that is conjugated with a target protein and the carboxy-terminal carboxy group of the incoming ubiquitin. Physiological roles are well established for K48-linked chains, which are essential for signaling proteasomal degradation of proteins, and for K63-linked chains, which play a part in recruitment of DNA repair enzymes, cell signaling and endocytosis. We focus here on linear ubiquitin chains, how they are assembled, and how three different avenues of research have indicated physiological roles for linear ubiquitination in innate and adaptive immunity and suppression of inflammation

Supervised selective kernel fusion for membrane protein prediction

Membrane protein prediction is a significant classification problem, requiring the integration of data derived from different sources such as protein sequences, gene expression, protein interactions etc. A generalized probabilistic approach for combining different data sources via supervised selective kernel fusion was proposed in our previous papers. It includes, as particular cases, SVM, Lasso SVM, Elastic Net SVM and others. In this paper we apply a further instantiation of this approach, the Supervised Selective Support Kernel SVM and demonstrate that the proposed approach achieves the top-rank position among the selective kernel fusion variants on benchmark data for membrane protein prediction. The method differs from the previous approaches in that it naturally derives a subset of “support kernels” (analogous to support objects within SVMs), thereby allowing the memory-efficient exclusion of significant numbers of irrelevant kernel matrixes from a decision rule in a manner particularly suited to membrane protein prediction