Testing the homogeneity of the Universe using gamma-ray bursts

In this paper, we study the homogeneity of the GRB distribution using a subsample of the Greiner GRB catalogue, which contains 314 objects with redshift $0<z<2.5$ (244 of them discovered by the Swift GRB Mission). We try to reconcile the dilemma between the new observations and the current theory of structure formation and growth. To test the results against the possible biases in redshift determination and the incompleteness of the Greiner sample, we also apply our analysis to the 244 GRBs discovered by Swift and the subsample presented by the Swift Gamma-Ray Burst Host Galaxy Legacy Survey (SHOALS). The real space two-point correlation function (2PCF) of GRBs, $\xi(r),$ is calculated using a Landy-Szalay estimator. We perform a standard least-$\chi^2$ fit to the measured 2PCFs of GRBs. We use the best-fit 2PCF to deduce a recently defined homogeneity scale. The homogeneity scale, $R_H$, is defined as the comoving radius of the sphere inside which the number of GRBs $N(<r)$ is proportional to $r^3$ within $1\%$, or equivalently above which the correlation dimension of the sample $D_2$ is within $1\%$ of $D_2=3$. For the Swift subsample of 244 GRBs, the correlation length and slope are $r_0= 387.51 \pm 132.75~h^{-1}$Mpc and $\gamma = 1.57\pm 0.65$ (at $1\sigma$ confidence level). The corresponding scale for a homogeneous distribution of GRBs is $r\geq 7,700~h^{-1}$Mpc. The results help to alleviate the tension between the new discovery of the excess clustering of GRBs and the cosmological principle of large-scale homogeneity. It implies that very massive structures in the relatively local Universe do not necessarily violate the cosmological principle and could conceivably be present.Comment: 7 pages, 5 figures, accepted by Astronomy & Astrophysics. The data used in this work (e.g. Tables 1 and 2) are publicly available online in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A

Incentive reward with organizational life cycle from competitive advantage viewpoint

[[abstract]]This paper develops a framework of incentive reward match to organizational life cycle from the viewpoint of competitive advantage. Different strategy, such as differentiation, overall cost leadership and focus, can create different competitive advantage in each stage of organizational life cycle. Implementing different types of incentive reward strategy to motive unique human resources to execute the corresponding strategy and then competitive advantage can be built. Three types of incentive reward strategy, human capital, output and position, are proposed respectively in each stage of organizational life cycle to attract, nurture, and retain distinctive manpower. It will create and sustain competitive advantage in the long run.[[notice]]補正完畢[[incitationindex]]SSCI[[incitationindex]]EI[[incitationindex]]A&HCI[[booktype]]紙本[[booktype]]電子

Statistical properties of volatility in fractal dimension and probability distribution among six stock markets - USA, Japan, Taiwan, South Korea, Singapore, and Hong Kong

This study examines the statistical properties of volatility. Fractal dimension, probability distribution and two-point volatility correlation are used to measure and compare volatility among six different markets for the 12-year period from Jan. 1 1990 to Dec. 31 2001. New York market is found to be the strongest among the six in terms of market efficiency. Moreover, the Tokyo and Singapore markets are found to be very similar in fractal dimension and probability distribution, but different in their resistance to volatility : Tokyo has a higher ability to dissipate volatility. This phenomenon implies that the Tokyo market is more efficient than the Singapore market. The Hong Kong market is similar to the Singapore market in its ability to dissipate volatility. Meanwhile, the Taiwanese and Korean markets are the two most volatile markets among the six. Notably, the Taiwanese market is weaker than the Korean market in dissipating volatility.Volatility, fractal dimension, probability distribution.