The Exotic Barium Bismuthates

We review the remarkable properties, including superconductivity, charge-density-wave ordering, and metal-insulator transitions, of lead- and potassium-doped barium bismuthate. We discuss some of the early theoretical studies of these systems. Our recent theoretical work, on the negative-U\/, extended-Hubbard model for these systems, is also described. Both the large- and intermediate-U\/ regimes of this model are examined, using mean-field and random-phase approximations, particularly with a view to fitting various experimental properties of these bismuthates. On the basis of our studies, we point out possibilities for exotic physics in these systems. We also emphasize the different consequences of electronic and phonon-mediated mechanisms for the negative U.\/ We show that, for an electronic mechanism, the \secin \,\,phases of these bismuthates must be unique, with their transport properties {\it dominated by charge $\pm 2e$ Cooperon bound states}. This can explain the observed difference between the optical and transport gaps. We propose other experimental tests for this novel mechanism of charge transport and comment on the effects of disorder.Comment: UUencoded LaTex file, 122 pages, figures available on request To appear in Int. J. Mod. Phys. B as a review articl

Distribution-Free Tests for Two-Sample Location Problems Based on Subsamples

Nonparametric tests for location problems have received much attention in the literature. Many nonparametric tests have been proposed for one, two and several samples location problems. In this paper a class of test statistics is proposed for two sample location problem when the underlying distributions of the samples are symmetric. The class of test statistics proposed is linear combination of U-statistics whose kernel is based on subsamples extrema. The members of the new class are shown to be asymptotically normal. The performance of the proposed class of tests is evaluated using Pitman Asymptotic Relative Efficiency. It is observed that the members of the proposed class of tests are better than the existing tests in the literature

Nonequilibrium Phase Transitions in a Driven Sandpile Model

We construct a driven sandpile slope model and study it by numerical simulations in one dimension. The model is specified by a threshold slope \sigma_c\/, a parameter \alpha\/, governing the local current-slope relation (beyond threshold), and $j_{\rm in}$, the mean input current of sand. A nonequilibrium phase diagram is obtained in the \alpha\, -\, j_{\rm in}\/ plane. We find an infinity of phases, characterized by different mean slopes and separated by continuous or first-order boundaries, some of which we obtain analytically. Extensions to two dimensions are discussed.Comment: 11 pages, RevTeX (preprint format), 4 figures available upon requs

Random spread on the family of small-world networks

We present the analytical and numerical results of a random walk on the family of small-world graphs. The average access time shows a crossover from the regular to random behavior with increasing distance from the starting point of the random walk. We introduce an {\em independent step approximation}, which enables us to obtain analytic results for the average access time. We observe a scaling relation for the average access time in the degree of the nodes. The behavior of average access time as a function of $p$, shows striking similarity with that of the {\em characteristic length} of the graph. This observation may have important applications in routing and switching in networks with large number of nodes.Comment: RevTeX4 file with 6 figure

SOME CLASSES OF NONPARAMETRIC TESTS FOR SPECIAL TWO-SAMPLE LOCATION PROBLEM BASED ON SUBSAMPLE EXTREMES

The special two-sample location problem is an important problem which is useful in comparing the performance of two measuring instruments. The problem of comparing the performances of two packing machines in which one machine may underfill the packets and the other may overfill the packets on an average, fits into special twosample location setup wherein one wishes to test for the point of symmetry versus an appropriate alternative. The only test available in the literature to the best of our knowledge is the class of tests due to Shetty and Umarani [13] which is based on U-statistics. In this paper, two classes of test statistics are proposed which are based on extremes of subsamples. The performances of the proposed classes of tests ar

A Class of Nonparametric Tests for the Two-Sample Location Problem

The two-sample location problem is one of the fundamental problems encountered in Statistics. In many applications of Statistics, two-sample problems arise in such a way as to lead naturally to the formulations of the null hypothesis to the effect that the two samples come from identical populations. A class of nonparametric test statistics is proposed for two-sample location problem based on U-statistic with the kernel depending on a constant ’a’ when the underlying distribution is symmetric. The optimal choice of ’a’ for different underlying distributions is determined. An alternative expression for the class of test statistics is established. Pitman asymptotic relative efficiencies indicate that the proposed class of test statistics does well in comparison with many of the test statistics available in the literature. The small sample performance is also studied through Monte-Carlo Simulation techniqu

DINeR: Database for Insect Neuropeptide Research

Neuropeptides are responsible for regulating a variety of functions, including development, metabolism, water and ion homeostasis, and as neuromodulators in circuits of the central nervous system. Numerous neuropeptides have been identified and characterized. However, both discovery and functional characterization of neuropeptides across the massive Class Insecta has been sporadic. To leverage advances in post-genomic technologies for this rapidly growing field, insect neuroendocrinology requires a consolidated, comprehensive and standardised resource for managing neuropeptide information. The Database for Insect Neuropeptide Research (DINeR) is a web-based database-application used for search and retrieval of neuropeptide information of various insect species detailing their isoform sequences, physiological functionality and images of their receptor-binding sites, in an intuitive, accessible and user-friendly format. The curated data includes representatives of 50 well described neuropeptide families from over 400 different insect species. Approximately 4700 FASTA formatted, neuropeptide isoform amino acid sequences and over 200 records of physiological functionality have been recorded based on published literature. Also available are images of neuropeptide receptor locations. In addition, the data include comprehensive summaries for each neuropeptide family, including their function, location, known functionality, as well as cladograms, sequence alignments and logos covering most insect orders. Moreover, we have adopted a standardized nomenclature to address inconsistent classification of neuropeptides

Dyadic Cantor set and its kinetic and stochastic counterpart

Firstly, we propose and investigate a dyadic Cantor set (DCS) and its kinetic counterpart where a generator divides an interval into two equal parts and removes one with probability $(1-p)$. The generator is then applied at each step to all the existing intervals in the case of DCS and to only one interval, picked with probability according to interval size, in the case of kinetic DCS. Secondly, we propose a stochastic DCS in which, unlike the kinetic DCS, the generator divides an interval randomly instead of equally into two parts. Finally, the models are solved analytically; an exact expression for fractal dimension in each case is presented and the relationship between fractal dimension and the corresponding conserved quantity is pointed out. Besides, we show that the interval size distribution function in both variants of DCS exhibits dynamic scaling and we verify it numerically using the idea of data-collapse.Comment: 8 pages, 6 figures, To appear in Chaos, Solitons & Fractal

Signature of clustering in quantum many body systems probed by the giant dipole resonance

The present experimental study illustrates how large deformations attained by nuclei due to cluster formation are perceived through the giant dipole resonance (GDR) strength function. The high energy GDR $\gamma$-rays have been measured from $^{32}$S at different angular momenta ($J$) but similar temperatures in the reactions $^{4}$He(E$_{lab}$=45MeV) + $^{28}$Si and $^{20}$Ne(E$_{lab}$=145MeV) + $^{12}$C. The experimental data at lower J ($\sim$ 10$\hbar$) suggests a normal deformation, similar to the ground state value, showing no potential signature of clustering. However, it is found that the GDR lineshape is fragmented into two prominent peaks at high J ($\sim$ 20$\hbar$) providing a direct measurement of the large deformation developed in the nucleus. The observed lineshape is also completely different from the ones seen for Jacobi shape transition at high $J$ pointing towards the formation of cluster structure in super-deformed states of $^{32}$S at such high spin. Thus, the GDR can be regarded as a unique tool to study cluster formation at high excitation energies and angular momenta.Comment: Published in PRC, 6 pages, 4 figure