Finding perfect polynomials mod 2

A number is said to be “perfect” if it equals the sum of its proper divisors. For example 6 is “perfect” because 6 = 1 + 2 + 3. On the other hand, a polynomial with integer coefficients modulo 2 is said to be “perfect” if the sum of its divisors equals the polynomial itself. In this presentation, we will highlight work that has been done to identify and classify all “perfect” polynomials

Molecular characterization of cDNA encoding resistance gene-like sequences in Buchloe dactyloides

Current knowledge of resistance (R) genes and their use for genetic improvement in buffalograss (Buchloe dactyloides [Nutt.] Engelm.) lag behind most crop plants. This study was conducted to clone and characterize cDNA encoding R gene-like (RGL) sequences in buffalograss. This report is the first to clone and-characterize of buffalograss RGLs. Degenerate primers designed from the conserved motifs of known R genes were used to amplify RGLs and fragments of expected size were isolated and cloned. Sequence analysis of cDNA clones and analysis of putative translation products revealed that most encoded amino acid sequences shared the similar conserved motifs found in the cloned plant disease resistance genes RPS2, MLA6, L6, RPM1, and Xa1. These results indicated diversity of the R gene candidate sequences in buffalograss. Analysis of 5' rapid amplification of cDNA ends (RACE), applied to investigate upstream of RGLs, indicated that regulatory sequences such as TATA box were conserved among the RGLs identified. The cloned RGL in this study will further enhance our knowledge on organization, function, and evolution of R gene family in buffalograss. With the sequences of the primers and sizes of the markers provided, these RGL markers are readily available for use in a genomics-assisted selection in buffalograss

SAR image reconstruction by expectation maximization based matching pursuit

Cataloged from PDF version of article.Synthetic Aperture Radar (SAR) provides high resolution images of terrain and target reflectivity. SAR systems are indispensable in many remote sensing applications. Phase errors due to uncompensated platform motion degrade resolution in reconstructed images. A multitude of autofocusing techniques has been proposed to estimate and correct phase errors in SAR images. Some autofocus techniques work as a post-processor on reconstructed images and some are integrated into the image reconstruction algorithms. Compressed Sensing (CS), as a relatively new theory, can be applied to sparse SAR image reconstruction especially in detection of strong targets. Autofocus can also be integrated into CS based SAR image reconstruction techniques. However, due to their high computational complexity, CS based techniques are not commonly used in practice. To improve efficiency of image reconstruction we propose a novel CS based SAR imaging technique which utilizes recently proposed Expectation Maximization based Matching Pursuit (EMMP) algorithm. EMMP algorithm is greedy and computationally less complex enabling fast SAR image reconstructions. The proposed EMMP based SAR image reconstruction technique also performs autofocus and image reconstruction simultaneously. Based on a variety of metrics, performance of the proposed EMMP based SAR image reconstruction technique is investigated. The obtained results show that the proposed technique provides high resolution images of sparse target scenes while performing highly accurate motion compensation. (C) 2014 Elsevier Inc. All rights reserved

Probability densities for the sums of iterates of the sine-circle map in the vicinity of the quasi-periodic edge of chaos

We investigate the probability density of rescaled sum of iterates of sine-circle map within quasi-periodic route to chaos. When the dynamical system is strongly mixing (i.e., ergodic), standard Central Limit Theorem (CLT) is expected to be valid, but at the edge of chaos where iterates have strong correlations, the standard CLT is not necessarily to be valid anymore. We discuss here the main characteristics of the central limit behavior of deterministic dynamical systems which exhibit quasi-periodic route to chaos. At the golden-mean onset of chaos for the sine-circle map, we numerically verify that the probability density appears to converge to a q-Gaussian with q<1 as the golden mean value is approached.Comment: 7 pages, 7 figures, 1 tabl

Chaos edges of zz-logistic maps: Connection between the relaxation and sensitivity entropic indices

Chaos thresholds of the $z$-logistic maps $x_{t+1}=1-a|x_t|^z$ $(z>1; t=0,1,2,...)$ are numerically analysed at accumulation points of cycles 2, 3 and 5. We verify that the nonextensive $q$-generalization of a Pesin-like identity is preserved through averaging over the entire phase space. More precisely, we computationally verify $\lim_{t \to\infty}< S_{q_{sen}^{av}} >(t)/t= \lim_{t \to\infty}(t)/t \equiv \lambda_{q_{sen}^{av}}^{av}$, where the entropy $S_{q} \equiv (1- \sum_i p_i^q)/ (q-1)$ ($S_1=-\sum_ip_i \ln p_i$), the sensitivity to the initial conditions $\xi \equiv \lim_{\Delta x(0) \to 0} \Delta x(t)/\Delta x(0)$, and $\ln_q x \equiv (x^{1-q}-1)/ (1-q)$ ($\ln_1 x=\ln x$). The entropic index $q_{sen}^{av}0$ depend on both $z$ and the cycle. We also study the relaxation that occurs if we start with an ensemble of initial conditions homogeneously occupying the entire phase space. The associated Lebesgue measure asymptotically decreases as $1/t^{1/(q_{rel}-1)}$ ($q_{rel}>1$). These results led to (i) the first illustration of the connection (conjectured by one of us) between sensitivity and relaxation entropic indices, namely $q_{rel}-1 \simeq A (1-q_{sen}^{av})^\alpha$, where the positive numbers $(A,\alpha)$ depend on the cycle; (ii) an unexpected and new scaling, namely $q_{sen}^{av}(cycle n)=2.5 q_{sen}^{av}(cycle 2)+ \epsilon$ ($\epsilon=-0.03$ for $n=3$, and $\epsilon = 0.03$ for $n=5$).Comment: 5 pages, 5 figure

Analysis of return distributions in the coherent noise model

The return distributions of the coherent noise model are studied for the system size independent case. It is shown that, in this case, these distributions are in the shape of q-Gaussians, which are the standard distributions obtained in nonextensive statistical mechanics. Moreover, an exact relation connecting the exponent $\tau$ of avalanche size distribution and the q value of appropriate q-Gaussian has been obtained as q=(tau+2)/tau. Making use of this relation one can easily determine the q parameter values of the appropriate q-Gaussians a priori from one of the well-known exponents of the system. Since the coherent noise model has the advantage of producing different tau values by varying a model parameter \sigma, clear numerical evidences on the validity of the proposed relation have been achieved for different cases. Finally, the effect of the system size has also been analysed and an analytical expression has been proposed, which is corroborated by the numerical results.Comment: 14 pages, 3 fig