Singlet axial-vector coupling constant of the nucleon in QCD without instantons

We have analyzed axial-vector current-current correlation functions between one-nucleon states to calculate the singlet axial-vector coupling constant of the nucleon. The octet-octet and the octet-singlet current correlators, investigated in this work, do not require any use of instanton effects. The QCD and hadronic parameters used for the evaluation of correlators have been varied by (10 - 20)%. The value of the singlet axial-vector coupling constant of the nucleon obtained from this analysis is consistent with its current determination from experiments and QCD theory.Comment: A slightly modified version to be published in Physics Letters B; 14 pages with 6 figures and 1 tabl

Eta-nucleon and eta-prime-nucleon coupling constants in QCD and the role of gluons

Coupling constants of $\eta$ and $\eta^{\prime}$ mesons with nucleons have been calculated using the method of QCD sum rules. Starting from vacuum-to-meson correlation function of interpolating fields of two nucleons, its matrix element with respect to nucleon spinors has been considered. Coupling constants at the physical points have been estimated from extrapolation of results obtained at two other points. Anomalous glue has been found to give substantial contribution to the coupling constants and also accounts for a significant OZI-rule violation.Comment: 6 pages, 3 figures and 2 table

A technique for adding range restrictions to generalized searching problems

In a generalized searching problem, a set $S$ of $n$ colored geometric objects has to be stored in a data structure, such that for any given query object $q$, the distinct colors of the objects of $S$ intersected by $q$ can be reported efficiently. In this paper, a general technique is presented for adding a range restriction to such a problem. The technique is applied to the problem of querying a set of colored points (resp.\ fat triangles) with a fat triangle (resp.\ point). For both problems, a data structure is obtained having size $O(n^{1+\epsilon})$ and query time $O((\log n)^2 + C)$. Here, $C$ denotes the number of colors reported by the query, and $\epsilon$ is an arbitrarily small positive constant

Evidence of Fear in Fixed Income and Bourses: A Study on Certain G-7 Economies

The paper aimed to predict the Fear index for certain G7 countries (Canada, France, Germany and Japan) considering the two variables Stock Price (Close) and Bond Yield(LBY). Daily data were analyzed for the period from April 2013 to June 2017. The main purpose was to identify the degree in which fear affecting the stock market percolates to Fixed Income Instruments. Using Panel Data Regression (Fixed Effect Model) the two variables were able to predict the VIX index and the model was found to be robust in nature. The major finding is that Fixed Income and stocks share a negative relationship with VIX (Fear Index)