Redshifts of the brightest X-ray QSO's

The plot of the X-ray luminosity (in 0.5–4.5 KeV band and for Friedmann universe withq ₀=+1) of the brightest X-ray QSO at each redshift against redshift shows that the X-ray luminosity increases more or less monotonically with redshift uptoz3. This result has been attributed to the selection effect known as the volume effect. When this selection effect is taken into account in the optical, radio and X-ray windows of the electromagnetic spectrum, a sample of the brightest X-ray QSO's is obtained which shows a small dispersion in X-ray luminosity: logL ₁=46.15±0.25. The redshift-X-ray flux density plot for this sample gives slopes of both regression lines which agree, at a confidence level of 95% or greater, with the slopes expected theoretically if the redshifts of the QSO's are cosmological in nature.     

On steady plane rotating hydromagnetic flows

We consider the steady plane rotating, constantly inclined magnetohydrodynamic flows of a viscous incompressible fluid when the velocity magnitude is constant on each individual stream line. Hodograph transformation is employed and resulting partial differential equations are used to obtain the solution and the geometries for these flows whenJ0 andJ=0.     

Rice-acreage estimation for Orrisa using remotely sensed data

Rice is one of the most important foodgrains grown in India. Attempts have been made to estimate kharif rice acreage of Orissa state since 1986 using digital remote sensing data from Landsat MSS/TM and/or IRS-1A. Accuracies of the estimates obtained have been evaluated against BES (Bureau of Economics and Statistics) estimate. This paper describes the methodology adopted for rice acreage estimation of Orissa state, the results obtained for three years, i.e. 1986–87, 1988–89 and 1989–90, and their accuracy.     

Evaluation of shale gas reservoir in Barakar and barren measures formations of north and south Karanpura Coalfields,Jharkhand

India recognizes the strategic importance for developing shale gas resources like other countries in the world. Shale gas reservoirs are known to be difficult for extracting gas in comparison to conventional reservoirs. Recently, due to high prices of gas, rising demand and enhancement in recovery technologies has attracted the Indian energy industries to explore the shale gas resource. Coal and lignite are the prime source of energy in India and these resources are well explored, while shale is ignored, despite it being associated with coal and lignite bearing formations. The paper presents reservoir characteristics of shale horizons in Barren Measures and Barakar formations of north and south Karanpura coalfields. Shale core samples were collected from exploratory boreholes in air tight canisters. In-situ gas content and adsorption capacities ascertained to be 0.51–1.69 m³/t and 3.90–5.82 m³/trespectively. Desorbed gas derived from canisters contains CH₄, C₂H₆, C₃H₈, CO₂, N₂ and O₂ and varies from 76.19–82.63, 0.38–0.76, 0.10–0.50, 8.65–12.34, 9.89–19.34 and 0.56–2.24 vol. % respectively. The permeability and porosity determined under reservoir simulated confining pressure is varying from 0.41–0.75 mD and 0.89–2.28 % respectively. The plots of Rock Eval S₂vs TOC and HI against Calc. VRo% indicates that all shale samples belong to Type III kerogen, which is prone to generate gas. It is evaluated that insitu gas content, sorption capacity, saturation level and low permeability of shale beds are critical parameters for development of shale gas resource in the studied area.     

Intercomparison of High-Resolution Bay of Bengal Circulation Models Forced with Different Winds

The high-resolution Bay of Bengal circulation modeling in the region [80E–95E; 5N–22N] is performed with a horizontal resolution of 10 km and the highest vertical resolution of 5 m near the surface. The intercomparison experiments, with ocean model forced with the near-surface (1) National Centers for Environmental Prediction (NCEP) reanalysis winds and (2) blended seawinds data (a combination of remotely sensed scatterometer and in situ observations) are carried out for a period of 17 years during 1998–2014. The seasonal variability of the realistically simulated surface hydrographic (temperature and salinity) and circulation (currents) variables from both the experiments is compared and contrasted with the observational data. The mixed layer depth seasonal variability of the region is also studied. The mesoscale features of currents at 50 and 100 m are also studied. The volume transport across different sections in the Bay of Bengal is computed and its relation with summer monsoon rainfall is investigated. The results suggest that there is no real advantage of using high-resolution blended seawinds over the much coarser NCEP reanalysis winds.     

Crustal structure in the North Arabian Sea from magnetic surveys

The spectral study of the aero-magnetic map of the North Arabian Sea (above 20°N) has delineated three horizons at average depths of 45 km, 21 km, and 8 km. Spectral estimates from smaller blocks of data drawn from the original map suggest that the 21 km horizon varies in depth from 14 km on the abyssal plain (oceanic crust) to 24 km towards the north and 28 km towards the east onto the continental shelf. This appears to correspond to the crust-mantle interface (Moho). The 8 km horizon corresponds to the top of the igneous basement. The significance of the deepest layer (45 km) is discussed as the maximum depth of the Curie point geotherm in this region. The spectral estimate of the block of data on the continental shelf off the west coast of India (above 20°N) has brought out some magnetic inhomogeneity at a shallower depth of 4 km. This appears to be connected with the sea-floor spreading phenomenon from the Carlsberg ridge. The presence of such a magnetic inhomogeneity at a depth of 4 km is further confirmed by the spectral estimate of a marine magnetic map off the west coast of India around Bombay. The depth of the basement inferred from this study is in close agreement with that obtained from other studies in this region, such as seismics.     

Derivation of coastal wind and wave parameters from offshore measurements of TOPEX satellite using ANN

The paper discusses an artificial neural network (ANN) approach to project information on wind speed and waves collected by the TOPEX satellite at deeper locations to a specified coastal site. The observations of significant wave heights, average wave period and wind speed at a number of locations over a satellite track parallel to a coastline are used to estimate corresponding values of these three parameters at the coastal site of interest. A combined network involving an input and output of all the three parameters, viz., wave height, period and wind speed instead of separate networks for each one of these variables was found to be necessary in order to train the network with sufficient flexibility. It was also found that network training based on statistical homogeneity of data sets is essential to obtain accurate results. The problem of modeling wind speeds that are always associated with very high variations in their magnitudes was tackled in this study by imparting training in an innovated manner.