Socio-economic and Environmental Implications of the Hydroelectric Projects in Uttarakhand Himalaya, India

This paper deals with detailed analysis of the fiasco created by the Tehri High Dam in Uttarakhand, India, particularly in terms of resettlement and rehabilitation of the local inhabitants. Aspects pertaining to the environmental issues are also discussed. Currently, the river valleys in Uttarakhand state of India are the targets of increasing hydroelectric projects. Virtually all rivers are being exploited for generating environmental friendly power. Having being learned the hard lesson from Tehri Dam, it has been decided to opt for such schemes in which comparatively little submergence and tempering with the fragile eco-systems is involved.However, our observations suggest that even in such schemes if due care is not taken they may turn out to be a failure.     

On the Spectral Index－Flux Density Relation for Large Samples of Radio Sources

We present new statistical results on the spectral index-flux density relation for large samples of radio sources using archival data of the most sensitive surveys, such as 6C, Miyun, WENSS, B3, NVSS, GB87. Instrumental selection effects and the completeness of the catalogs are discussed. Based on the spectral indices calculated for about 200 000 sources from the WENSS (327 MHz) and NVSS (1.4 GHz) catalogs, we obtained (1) The median spectral index increases from amed --0.9 toαmed --0.8 (Svαvα), while S327 flux densities decrease from 0.1 Jy down to 25mJy. The median spectral indices nearly show no variation within the error bars when the flux density is larger than 0.1 Jy. (2) A dependence of the fraction of ultra-steep spectrum sources (USS, -1.5 <α<-1.0), steep spectrum sources (SSS, -1.0 <α< -0.5) and flat spectrum sources (FSS, -0.5≤α≤0.0) is partly responsible for the spectral flattening. Another contribution to the spectral flattening comes from the variation of αmed of steep spectrum so     

气候研究及其应用方面

本文的基本目的在于分析导致气候在社会生活中的作用急剧增长的原因及其趋向,在于评价气候研究和应用气候学方面的研究,特别是随着实现全世界气候研究计划而出现的研究趋向。此种分析极其重要,因为气候科学已有明显地转变成真实力量的趋势,它通过人们对气候资源的合理利用而促进社会生产效率的提高。     

Fatty Acid Composition Analyses of the DCMU Resistant Mutants of Nannochloropsis oculata (Eustigmatophyceae)

1　Introduction　Nannochloropsissp .areoneofpotentialsourcesofpolyunsaturatedfattyacids ,especiallytheeicosapen taentaenoicacid (EPA ,C2 0∶5 ) ,whichisimportantforbothanimalsandhumans .　Thefattyacidcompositionofthisalgaisaffectedbyvariousenvironmentalfactors ,suchaslightintensity(Sukeniketal.,1989;Sukeniketal.,1990 ) ,imply ingthatafactorinfluencingthephotosyntheticprocessmayaffectcellularfattyacidsynthesisandtheirmetabolism .AselectionprogramofincreasingcellularEPAcontenthasbeencarriedo…     

The Effect of Solar Activity on the Annual Precipitation in the Beijing Area

Using continuous wavelet transform, we examine the relationship between solar activity and the annual precipitation in the Beijing area. The results indicate that the annual precipitation is closely related to the variation of sunspot numbers, and that solar activity probably plays an important role in influencing the precipitation on land.     

Automated Separation of Stars and Normal Galaxies Based on Statistical Mixture Modeling with RBF Neural Networks

For LAMOST, the largest sky survey program in China, the solution of the problem of automatic discrimination of stars from galaxies by spectra has shown that the results of the PSF test can be significantly refined. However, the problem is made worse when the redshifts of galaxies are not available. We present a new automatic method of star/(normal) galaxy separation, which is based on Statistical Mixture Modeling with Radial Basis Function Neural Networks (SMM-RBFNN). This work is a continuation of our previous one, where active and non-active celestial objects were successfully segregated. By combining the method in this paper and the previous one, stars can now be effectively separated from galaxies and AGNs by their spectra-a major goal of LAMOST, and an indispensable step in any automatic spectrum classification system. In our work, the training set includes standard stellar spectra from Jacoby's spectrum library and simulated galaxy spectra of EO, SO, Sa, Sb types with redshift ranging from 0 to 1