Constructing a measure of industry-specific human capital using Tobin's q theory

In this paper, we develop a measure of industry specific human capital using the Tobin's q theory. The measure is derived from a structural model of heterogeneous knowledge labor, which is homogeneous physical labor embodied with industry specific human capital.

Distinguishing RBL-like objects and XBL-like objects with the peak emission frequency of the overall energy spectrum

We investigate quantitatively how the peak emission frequency of the overall energy spectrum is at work in distinguishing RBL-like and XBL-like objects. We employ the sample of Giommi et al. (1995) to study the distribution of BL Lacertae objects with various locations of the cutoff of the overall energy spectrum. We find that the sources with the cutoff located at lower frequency are indeed sited in the RBL region of the $\alpha_{ro}-\alpha_{ox}$ plane, while those with the cutoff located at higher frequency are distributed in the XBL region. For a more quantitative study, we employ the BL Lacertae samples presented by Sambruna et al. (1996), where, the peak emission frequency, $\nu _p$, of each source is estimated by fitting the data with a parabolic function. In the plot of $\alpha_{rx}-\log \nu_p$ we find that, in the four different regions divided by the $\alpha_{rx}=0.75$ line and the $\log \nu_p=14.7$ line, all the RBL-like objects are inside the upper left region, while most XBL-like objects are within the lower right region. A few sources are located in the lower left region. No sources are in the upper right region. This result is rather quantitative. It provides an evidence supporting what Giommi et al. (1995) suggested: RBL-like and XBL-like objects can be distinguished by the difference of the peak emission frequency of the overall energy spectrum.Comment: 7 pages, 2 figure

Employee Turnover: Less is Not Necessarily More?

Theoretical studies have suggested firm specific human capital and job matching as the major, but opposite, mechanisms through which employee turnover affects labour productivity. This study finds that the former dominates when turnover is high, while the latter dominates when turnover is low. The optimal turnover rate that maximises productivity is about 0.22 per annum. Bringing the observed turnover rates in the sample to the optimal level increases the average productivity by 1.1 per cent. The large gap between the observed and the optimal rate could be explained by the lack of decision coordination between agents in labour markets

Heavy Metals Migration in Soil in Tailing Dam Region of Shuikoushan, Hunan Province, China

AbstractThe nonferrous mining industry in China has been exploiting rich domestic mineral resources in order to sustain rapidly economic and social development. The paper chooses the tailing dam region as the research object in the Shuikoushan, and researches the distribution of Pb, Zn, Cu, Cd, As, Cr, which reveals heavy metal migration regularities in layers from new and old tailing dam region. In addition, this article focuses on making the research of Potential Ecological Risk Index appraisal to the heavy metal contamination level. The results showed that the concentrations of heavy metals in old tailing dam region were much higher than those of in the new tailing dam region. As well, the concentrations of most heavy metal reduced progressively with the soil depth increasing for the new tailing dam region, while the change tendency was inversely for the old one. Potential ecological risk index showed that the potential ecological risks were at low and low to moderate level in tailing dam region

Metabolic classification of microbial genomes using functional probes

<p>Abstract</p> <p>Background</p> <p>Microorganisms able to grow under artificial culture conditions comprise only a small proportion of the biosphere's total microbial community. Until recently, scientists have been unable to perform thorough analyses of difficult-to-culture microorganisms due to limitations in sequencing technology. As modern techniques have dramatically increased sequencing rates and rapidly expanded the number of sequenced genomes, in addition to traditional taxonomic classifications which focus on the evolutionary relationships of organisms, classifications of the genomes based on alternative points of view may help advance our understanding of the delicate relationships of organisms.</p> <p>Results</p> <p>We have developed a proteome-based method for classifying microbial species. This classification method uses a set of probes comprising short, highly conserved amino acid sequences. For each genome, <it>in silico </it>translation is performed to obtained its proteome, based on which a probe-set frequency pattern is generated. Then, the probe-set frequency patterns are used to cluster the proteomes/genomes.</p> <p>Conclusions</p> <p>Features of the proposed method include a high running speed in challenge of a large number of genomes, and high applicability for classifying organisms with incomplete genome sequences. Moreover, the probe-set clustering method is sensitive to the metabolic phenotypic similarities/differences among species and is thus supposed potential for the classification or differentiation of closely-related organisms.</p