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     

An approach to quantitative analysis of regional economic links

Aimed at promoting regional coalitions and expanding the approach to economic links, this paper puts forward some new concepts such as link intensity and receiving coefficient, expounds the indexes of quantitative analysis of economic links and establishes the quantitative-analysis model of economic links. With help of the model, this paper calculates the values of the link intensities between Su-Xi-Chang (Suzhou-Wuxi-Changzhou) region and Shanghai, and analyzes the regional difference of the economic links.     

Models for the magnitude‐distribution of brightest cluster galaxies

The brightest, or first-ranked, galaxies (BCGs) in rich clusters show a very small dispersion in luminosity, making them excellent standard candles. This small dispersion raises questions about the nature of BCGs. Are they simply the extremes of normal galaxies formed via a stochastic process, or do they belong to a special class of atypical objects? If they do, are all BCGs special, or do normal galaxies compete for the first rank? To answer these questions, we undertake a statistical study of BCG magnitudes using results from extreme value theory. Two-population models do better than one-population models. A simple scenario where a random boost in the magnitude of a fraction of bright normal galaxies forms a class of atypical galaxies best describes the observed distribution of BCG magnitudes.     

REVIEWS OF GEOGRAPHIC SOFTWARE

Reviews of geographic software in this article: DEMO-GRAPHICS: WORLD POPULATIONS AND PROJECTIONS. ESP GAUSS. CEMODEL S. Damus LIMDEP. William H. Greene MICROSTAT 4.1 OTIS PCIPS. (Personal Computer Image Processing System) . H.J. Meyers and R. Bernstein. REGRESSION ANALYSIS OF TIME SERIES (RATS) SPSS/PC+ URBAN DATA MANAGEMENT SOFTWARE (UDMS)     

Statistical analysis of sand grain/bed collision process recorded by high-speed digital camera

A high‐speed digital camera was employed to record the sand grain/bed collision process. With image processing and a statistical method, a series of parameters of the collision process were obtained. The results show that the collision process of a grain with rebounding can be represented by two parameters: the kinetic energy restitution coefficient and the collision angle. Both parameters satisfy a normal distribution, and they are dependent on one another. With an increase of the collision angle, the distribution of the kinetic energy restitution gradually reduces from a broad to a narrow range with low values. The percentage of vertical velocity restitution coefficients greater than 1 can reach 70% or more, which ensures that the settling time of the sand grains in the air increases and that they receive more energy from the air to progress the saltation movement.     

Soil erosion susceptibility assessment and validation using a geostatistical multivariate approach: a test in Southern Sicily

A certain number of studies have been carried out in recent years that aim at developing and applying a model capable of assessing water erosion of soil. Some of these have tried to quantitatively evaluate the volumes of soil loss, while others have focused their efforts on the recognition of the areas most prone to water erosion processes. This article presents the results of a research whose objective was that of evaluating water erosion susceptibility in a Sicilian watershed: the Naro river basin. A geomorphological study was carried out to recognize the water erosion landforms and define a set of parameters expressing both the intensity of hydraulic forces and the resistance of rocks/soils. The landforms were mapped and classified according to the dominant process in landsurfaces affected by diffuse or linear water erosion. A GIS layer was obtained by combining six determining factors (bedrock lithology, land use, soil texture, plan curvature, stream power index and slope-length factor) in unique conditions units. A geostatistical multivariate approach was applied by analysing the relationships between the spatial distributions of the erosion landforms and the unique condition units. Particularly, the density of eroded area for each combination of determining factors has been calculated: such function corresponds, in fact, to the conditional probability of erosion landforms to develop, under the same geoenvironmental conditions. In light of the obtained results, a general geomorphologic model for water erosion in the Naro river basin can be depicted: cultivated areas in clayey slopes, having fine-medium soil texture, are the most prone to be eroded; linear or diffuse water erosion processes dominate where the topography is favourable to a convergent or divergent runoff, respectively. For each of the two erosion process types, a susceptibility map was produced and submitted to a validation procedure based on a spatial random partition strategy. Both the success of the validation procedure of the susceptibility models and the geomorphological coherence of the relationships between factors and process that such models suggest, confirm the reliability of the method and the goodness of the predictions.