Diffusion pattern in MSi2 and M5Si3 silicides in group VB (M = V, Nb, Ta) and VIB (M = Mo, W) refractory metal-silicon systems

Group VB and VIB M-Si systems are considered to show an interesting pattern in the diffusion of components with the change in atomic number in a particular group (M = V, Nb, Ta or M = Mo, W, respectively). Mainly two phases, MSi2 and M5Si3 are considered for this discussion. Except for Ta-silicides, the activation energy for the integrated diffusion of MSi2 is always lower than M5Si3. In both phases, the relative mobilities measured by the ratio of the tracer diffusion coefficients, , decrease with an increasing atomic number in the given group. If determined at the same homologous temperature, the interdiffusion coefficients increase with the atomic number of the refractory metal in the MSi2 phases and decrease in the M5Si3 ones. This behaviour features the basic changes in the defect concentrations on different sublattices with a change in the atomic number of the refractory components.

Model domains in C-3 with abelian automorphism group

It is shown that every hyperbolic rigid polynomial domain in C-3 of finite-type, with abelian automorphism group is equivalent to a domain that is balanced with respect to some weight.

Dynamics of the reaction between the free end of a tethered self-avoiding polymer and a flat penetrable surface: A renormalization group study

The average time tau(r) for one end of a long, self-avoiding polymer to interact for the first time with a flat penetrable surface to which it is attached at the other end is shown here to scale essentially as the square of the chain's contour length N. This result is obtained within the framework of the Wilemski-Fixman approximation to diffusion-limited reactions, in which the reaction time is expressed as a time correlation function of a ``sink'' term. In the present work, this sink-sink correlation function is calculated using perturbation expansions in the excluded volume and the polymer-surface interactions, with renormalization group methods being used to resum the expansion into a power law form. The quadratic dependence of tau(r) on N mirrors the behavior of the average time tau(c) of a free random walk to cyclize, but contrasts with the cyclization time of a free self-avoiding walk (SAW), for which tau(r) similar to N-2.2. A simulation study by Cheng and Makarov J. Phys. Chem. B 114, 3321 (2010)] of the chain-end reaction time of an SAW on a flat impenetrable surface leads to the same N-2.2 behavior, which is surprising given the reduced conformational space a tethered polymer has to explore in order to react. (C) 2014 AIP Publishing LLC.

Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

The polycomb group gene EMF2B is essential for maintenance of floral meristem determinacy in rice

Polycomb Repressive Complex 2 (PRC2) represses the transcriptional activity of target genes through trimethylation of lysine 27 of histone H3. The functions of plant PRC2 have been chiefly described in Arabidopsis, but specific functions in other plant species, especially cereals, are still largely unknown. Here we characterize mutants in the rice EMF2B gene, an ortholog of the Arabidopsis EMBRYONIC FLOWER2 (EMF2) gene. Loss of EMF2B in rice results in complete sterility, and mutant flowers have severe floral organ defects and indeterminacy that resemble loss-of-function mutants in E-function floral organ specification genes. Transcriptome analysis identified the E-function genes OsMADS1, OsMADS6 and OsMADS34 as differentially expressed in the emf2b mutant compared with wild type. OsMADS1 and OsMADS6, known to be required for meristem determinacy in rice, have reduced expression in the emf2b mutant, whereas OsMADS34 which interacts genetically with OsMADS1 was ectopically expressed. Chromatin immunoprecipitation for H3K27me3 followed by quantitative (q)RT-PCR showed that all three genes are presumptive targets of PRC2 in the meristem. Therefore, in rice, and possibly other cereals, PRC2 appears to play a major role in floral meristem determinacy through modulation of the expression of E-function genes.

Sparse Representation Based Acoustic Rangefinders: From Sensor Platforms to Mobile Devices

Acoustic rangerfinders are a promising technology for accurate proximity detection, a critical requirement for many emerging mobile computing applications. While state-of-the-art systems deliver robust ranging performance, the computational intensiveness of their detection mechanism expedites the energy depletion of the associated devices that are typically powered by batteries. The contribution of this article is fourfold. First, it outlines the common factors that are important for ranging. Second, it presents a review of acoustic rangers and identifies their potential problems. Third, it explores the design of an information processing framework based on sparse representation that could potentially address existing challenges, especially for mobile devices. Finally, it presents mu-BeepBeep: a low energy acoustic ranging service for mobile devices, and empirically evaluates its benefits.

Robust tracking with interest points: A sparse representation approach

Visual tracking is an important task in various computer vision applications including visual surveillance, human computer interaction, event detection, video indexing and retrieval. Recent state of the art sparse representation (SR) based trackers show better robustness than many of the other existing trackers. One of the issues with these SR trackers is low execution speed. The particle filter framework is one of the major aspects responsible for slow execution, and is common to most of the existing SR trackers. In this paper,(1) we propose a robust interest point based tracker in l(1) minimization framework that runs at real-time with performance comparable to the state of the art trackers. In the proposed tracker, the target dictionary is obtained from the patches around target interest points. Next, the interest points from the candidate window of the current frame are obtained. The correspondence between target and candidate points is obtained via solving the proposed l(1) minimization problem. In order to prune the noisy matches, a robust matching criterion is proposed, where only the reliable candidate points that mutually match with target and candidate dictionary elements are considered for tracking. The object is localized by measuring the displacement of these interest points. The reliable candidate patches are used for updating the target dictionary. The performance and accuracy of the proposed tracker is benchmarked with several complex video sequences. The tracker is found to be considerably fast as compared to the reported state of the art trackers. The proposed tracker is further evaluated for various local patch sizes, number of interest points and regularization parameters. The performance of the tracker for various challenges including illumination change, occlusion, and background clutter has been quantified with a benchmark dataset containing 50 videos. (C) 2014 Elsevier B.V. All rights reserved.

Three centered hydrogen bonds of the type C=O...H(N)...X-C in diphenyloxamide derivatives involving halogens and a rotating CF3 group: NMR, QTAIM, NCI and NBO studies

The existence of three centered C=O...H(N)...X-C hydrogen bonds (H-bonds) involving organic fluorine and other halogens in diphenyloxamide derivatives has been explored by NMR spectroscopy and quantum theoretical studies. The three centered H-bond with the participation of a rotating CF3 group and the F...H-N intramolecular hydrogen bonds, a rare observation of its kind in organofluorine compounds, has been detected. It is also unambiguously established by a number of one and two dimensional NMR experiments, such as temperature perturbation, solvent titration, N-15-H-1 HSQC, and F-19-H-1 HOESY, and is also confirmed by theoretical calculations, such as quantum theory of atoms in molecules (QTAIM), natural bond orbital (NBO) and non-covalent interaction (NCI).

Markov chains, R-trivial monoids and representation theory

We develop a general theory of Markov chains realizable as random walks on R-trivial monoids. It provides explicit and simple formulas for the eigenvalues of the transition matrix, for multiplicities of the eigenvalues via Mobius inversion along a lattice, a condition for diagonalizability of the transition matrix and some techniques for bounding the mixing time. In addition, we discuss several examples, such as Toom-Tsetlin models, an exchange walk for finite Coxeter groups, as well as examples previously studied by the authors, such as nonabelian sandpile models and the promotion Markov chain on posets. Many of these examples can be viewed as random walks on quotients of free tree monoids, a new class of monoids whose combinatorics we develop.

Structural variations in aromatic 2 pi-electron three-membered rings of the main group elements

Structural variations of different Z pi-aromatic three-membered ring systems of main group elements, especially group 14 and 13 elements as compared to the classical description of cyclopropenyl cation has been reviewed in this article. The structures of heavier analogues as well as group 13 analogues of cyclopropenyl cation showed an emergence of dramatic structural patterns which do not conform, to the general norms of carbon chemistry. Isolobal analogies between the main group fragments have been efficiently used to explain the peculiarities observed in these three-membered ring systems.

Accurate Steady-State Representation of a Doubly Fed Induction Machine

This letter presents an accurate steady-state phasor model for a doubly fed induction machine. The drawback of existing steady-state phasor model is discussed. In particular, the inconsistency of existing equivalent model with respect to reactive power flows when operated at supersynchronous speeds is highlighted. Relevant mathematical basis for the proposed model is presented and its validity is illustrated on a 2-MW doubly fed induction machine.

Maximum group velocity in a one-dimensional model with a sinusoidally varying staggered potential

We use Floquet theory to study the maximum value of the stroboscopic group velocity in a one-dimensional tight-binding model subjected to an on-site staggered potential varying sinusoidally in time. The results obtained by numerically diagonalizing the Floquet operator are analyzed using a variety of analytical schemes. In the low-frequency limit we use adiabatic theory, while in the high-frequency limit the Magnus expansion of the Floquet Hamiltonian turns out to be appropriate. When the magnitude of the staggered potential is much greater or much less than the hopping, we use degenerate Floquet perturbation theory; we find that dynamical localization occurs in the former case when the maximum group velocity vanishes. Finally, starting from an ``engineered'' initial state where the particles (taken to be hard-core bosons) are localized in one part of the chain, we demonstrate that the existence of a maximum stroboscopic group velocity manifests in a light-cone-like spreading of the particles in real space.

Microwave Spectrum of Hexafluoroisopropanol and Torsional Behavior of Molecules with a CF3-C-CF3 Group

This paper presents the first microwave spectroscopic investigation on hexafluoroisopropanol (HFIP). A pulsed nozzle Fourier transform microwave spectrometer has been used to determine the rotational constants for HFIP as A = 2105.12166(18) MHz, B = 1053.99503(12) MHz, and C = 932.33959(13) MHz. In addition, five isotopologues of HFIP have been observed experimentally to determine the accurate structure of HFIP. The observed spectrum could be assigned to the most stable conformer of HFIP, called antiperiplanar. Available spectroscopic information and ab initio calculations on five prototype molecules helped in exploring the torsional behavior of molecules having a CF3-C-CF3 group. Two-dimensional potential energy surfaces have been analyzed for all molecules, which explained the presence/absence of doubling in the rotational transitions. With the help of natural bond orbital (NBO) analysis, reasons for the conformational preference of HFIP have been explained.

REPERTOIRE OF PROTEIN KINASES ENCODED IN THE GENOME OF ZEBRAFISH SHOWS REMARKABLY LARGE POPULATION OF PIM KINASES

In recent times, zebrafish has garnered lot of popularity as model organism to study human cancers. Despite high evolutionary divergence from humans, zebrafish develops almost all types of human tumors when induced. However, mechanistic details of tumor formation have remained largely unknown. Present study is aimed at analysis of repertoire of kinases in zebrafish proteome to provide insights into various cellular components. Annotation using highly sensitive remote homology detection methods revealed ``substantial expansion'' of Ser/Thr/Tyr kinase family in zebrafish compared to humans, constituting over 3% of proteome. Subsequent classification of kinases into subfamilies revealed presence of large number of CAMK group of kinases, with massive representation of PIM kinases, important for cell cycle regulation and growth. Extensive sequence comparison between human and zebrafish PIM kinases revealed high conservation of functionally important residues with a few organism specific variations. There are about 300 PIM kinases in zebrafish kinome, while human genome codes for only about 500 kinases altogether. PIM kinases have been implicated in various human cancers and are currently being targeted to explore their therapeutic potentials. Hence, in depth analysis of PIM kinases in zebrafish has opened up new avenues of research to verify the model organism status of zebrafish.

A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation: Application to Image Denoising

In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.