15,670 research outputs found
Wage Inequality in Indian Manufacturing - Is it Trade, Technology or Labour Regulations?
This paper investigates the question of wage inequality in Indian manufacturing in the years of trade and investment liberalization. The objective is to test the hypothesis of skill biased technological change (SBTC) due to capital-skill complementarity and the impact of labour regulations on wage inequality between skilled and unskilled labour. The skill-wage bill share equation is estimated for a panel of 46 three-digit industries spanning the period 1981-2004 followed by 113 four-digit industries panel covering the period 1993 to 2004.The econometric results suggest the positive contribution of change in output (scale effect), capital-output ratio and contract-worker intensity to wage inequality in Indian manufacturing.wages inequality, skill technological change labour manufacturing
Active nematics are intrinsically phase-separated
Two-dimensional nonequilibrium nematic steady states, as found in agitated
granular-rod monolayers or films of orientable amoeboid cells, were predicted
[Europhys. Lett. {\bf 62} (2003) 196] to have giant number fluctuations, with
standard deviation proportional to the mean. We show numerically that the
steady state of such systems is {\em macroscopically phase-separated}, yet
dominated by fluctuations, as in the Das-Barma model [PRL {\bf 85} (2000)
1602]. We suggest experimental tests of our findings in granular and
living-cell systems.Comment: 4 pages, 6 .eps figures, accepted for publication in PRL 3 Aug 0
Stochastic recursive inclusion in two timescales with an application to the Lagrangian dual problem
In this paper we present a framework to analyze the asymptotic behavior of
two timescale stochastic approximation algorithms including those with
set-valued mean fields. This paper builds on the works of Borkar and Perkins &
Leslie. The framework presented herein is more general as compared to the
synchronous two timescale framework of Perkins \& Leslie, however the
assumptions involved are easily verifiable. As an application, we use this
framework to analyze the two timescale stochastic approximation algorithm
corresponding to the Lagrangian dual problem in optimization theory
Pooled systemic efficacy and safety data from the pivotal phase II studies (NP28673 and NP28761) of alectinib in ALK-positive non-small cell lung cancer
Maximal Lyapunov exponent at Crises
We study the variation of Lyapunov exponents of simple dynamical systems near
attractor-widening and attractor-merging crises. The largest Lyapunov exponent
has universal behaviour, showing abrupt variation as a function of the control
parameter as the system passes through the crisis point, either in the value
itself, in the case of the attractor-widening crisis, or in the slope, for
attractor merging crises. The distribution of local Lyapunov exponents is very
different for the two cases: the fluctuations remain constant through a merging
crisis, but there is a dramatic increase in the fluctuations at a widening
crisis.Comment: 22kb plus 3 figures available on request; to appear in Phys. Rev.
Approximate entropy as an indicator of non-linearity in self paced voluntary finger movement EEG
This study investigates the indications of non-linear dynamic structures in electroencephalogram signals. The iterative amplitude adjusted surrogate data method along with seven non-linear test statistics namely the third order autocorrelation, asymmetry due to time reversal, delay vector variance method, correlation dimension, largest Lyapunov exponent, non-linear prediction error and approximate entropy has been used for analysing the EEG data obtained during self paced voluntary finger-movement. The results have demonstrated that there are clear indications of non-linearity in the EEG signals. However the rejection of the null hypothesis of non-linearity rate varied based on different parameter settings demonstrating significance of embedding dimension and time lag parameters for capturing underlying non-linear dynamics in the signals. Across non-linear test statistics, the highest degree of non-linearity was indicated by approximate entropy (APEN) feature regardless of the parameter settings
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