Superthermal effect of electrons on nonplanar dust-ion-acoustic solitary waves and double layers in a dusty plasma

The basic features of planar and nonplanar time-dependent dust-ion-acoustic (DIA) solitary waves (SWs) and double layers (DLs) have been studied in an unmagnetized dusty plasma system consisting of positively and negatively charged dust, Boltzmann distributed ions and superthermal electrons (represented by kappa distribution). Using the reductive perturbation technique (RPT) we have derived modified Gardner (MG) equation, which gives information beyond the Korteweg-de Vries (KdV) limits (corresponding to the vanishing of nonlinear coefficient of the KdV equation). It is seen that the properties of nonplanar DIA SWs and DLs are significantly differs as the value of spectral index kappa (κ) changes. The present investigation may have relevance in the study of propagation of DIA waves in space and laboratory plasmas.     

Identification of Glacial Isostatic Adjustment in Eastern Canada Using S Transform Filtering of GPS Observations

Over the years, a number of different models and techniques have been proposed to both quantify and explain the glacial isostatic adjustment (GIA) process. There are serious challenges, however, to obtaining accurate results from measurements, due to noise in the data and the long periods of time necessary to identify the relatively small-magnitude signal in certain regions. The primary difficulty, in general, is that most of the geophysical signals that occur in addition to GIA are nonstationary in nature. These signals are also corrupted by random as well as correlated noise added during data acquisition. The nonstationary characteristic of the data makes it difficult for traditional frequency-domain denoising approaches to be effective. Time–frequency filters present a more robust and reliable alternative to deal with this problem. This paper proposes an extended S transform filtering approach to separate the various signals and isolate that associated with GIA. Continuous global positioning system (GPS) data from eastern Canada for the period from June 2001 to June 2006 are analyzed here, and the vertical velocities computed after filtering are consistent with the GIA models put forward by other researchers.     

Multivariate statistical approach to identify significant sources influencing the physico-chemical variables in Aerial Bay,North Andaman,India

Aerial Bay is one of the harbor towns of Andaman and Nicobar Islands, the union territory of India. Nevertheless, it is least studied marine environment, particularly for physico-chemical assessment. Therefore, to evaluate the annual spatiotemporal variations of physico-chemical parameters, seawater samples collected from 20 sampling stations covering three seasons were analyzed. Multivariate statistics is applied to the investigated data in an attempt to understand the causes of variation in physico-chemical parameters. Cluster analysis distinguished mangrove and open sea stations from other areas by considering distinctive physico-chemical characteristics. Factor analysis revealed 79.5% of total variance in physico-chemical parameters. Strong loading included transparency, TSS, DO, BOD, salinity, nitrate, nitrite, inorganic phosphate, total phosphorus and silicate. In addition, box-whisker plots and Geographical Information System based land use data further facilitated and supported multivariate results.     

Bulk viscous string cosmological models with electromagnetic field

LRS Bianchi type-I string cosmological models are studied in the frame work of general relativity when the source for the energy momentum tensor is a bulk viscous stiff fluid containing one dimensional strings embedded in electromagnetic field. The bulk viscosity is assumed to be inversely proportional to the scalar expansion. The physical and kinematical properties of the models are discussed. The effects of Viscosity and electromagnetic field on the physical and kinematical properties are also investigated.     

Bulk viscous barotropic magnetised string cosmological models

Spatially homogeneous and anisotropic LRSBianchi type-I string cosmological models are studied in the frame work of general relativity when the source for the energy momentum tensor is a bulk viscous fluid containing one dimensional strings embedded in a magnetic field. A barotropic equation of state for the pressure and density is assumed to get determinate solutions of the field equations. The bulk viscous pressure is assumed to be proportional to the energy density. The effects of viscosity and electromagnetic field on the properties of the model are investigated. The role of bulk viscosity and electromagnetic field in getting an inflationary phase and in establishing a string phase in the universe is studied.     

Optical photometry and spectroscopy of the Type Ibn supernova SN 2006jc until the onset of dust formation

We present optical UBVRI photometric and spectroscopic data of the Type Ibn supernova SN 2006jc, until the onset of the dust-forming phase. The optical spectrum shows a blue continuum and is dominated by the presence of moderately narrow (velocity ∼2500 km s⁻¹) He  i emission lines superimposed over a relatively weak supernova spectrum. The helium lines are produced in a pre-existing He-rich circumstellar shell. The observed helium line fluxes indicate the circumstellar shell is dense, with a density of  ∼10⁹–10¹⁰ cm⁻³  . The helium mass in this shell is estimated to be  ≲0.07 M_⊙  . The optical light curves show a clear signature of dust formation, indicated by a sharp decrease in the magnitudes around day 50, accompanied by a reddening of the colours. The evolution of the optical light curves during the early phase and that of the uvoir bolometric light curve at all phases is reasonably similar to normal Ib/c supernovae.     

Distributions of O3, CO and NMHCs over the rural sites in central India

The surface level measurements of O₃, CO, CH₄ and light NMHCs were made at eight different rural sites in the central part of India during February, 2004. The online analyzer was used for in-situ measurement of O₃ while air samples were collected for the analyses of CO, CH₄ and NMHCs using the gas chromatography techniques. The average mixing ratios of O₃, which were in the range of 60–90 ppbv, are significantly higher compared to the typical values reported for urban sites of India. The increase rates of O₃ in the forenoon hours were estimated to be in the range of about 8.8–10 ppbv h⁻¹. The slopes of ∆O₃/∆CO, which is an indicator of the efficiency of photochemical production, were in the range of 0.24–0.33 ppbv ppbv⁻¹. However, levels of primary pollutants e.g., NMHCs, CO, etc. at these sites were much lower than urban sites, but higher compared to previously observed values surrounding marine region of India. The estimated ratios of NMHCs and CO indicate fossil fuel combustion process as the dominant source of primary pollutants in this corridor.     

Modeling of SH-Wave Propagation in a Pre-stressed Highly Anisotropic Layered Structure

Mathematical Geosciences - The present study presents the propagation of horizontally polarized shear waves (SH-waves) in highly anisotropic layered media under the effect of horizontal and...     

Univariate and multivariate stochastic modeling of the chemical composition of iron ores in Northern Goa, India

Chemical components such as SiO ₂,TiO ₂,MnO, P ₂ O ₅,and especially Fe ₂ O ₃ of the iron ores of Bicholim Mine, Northern Goa, have been determined for lateral and vertical sections of the mine at equal intervals of 3 and 1 m, respectively, so as to form the spatial (time) series. Univariate stationary models of the type Autoregressive moving average—ARMA (p, q)—were established for each series on the basis of statistical analyses of their auto (acf) and partial auto (pacf) correlation functions. These models were used for forecasting assay values at different lead distances from any pivot. Principles of parsimony simplified all of the candidate ARMA (p, q) models to pure AR (p) models, and the univariate forecasts were significantly improved by multivariate stochastic forecasts.     

Stochastic modelling of mineral deposits

Mineral deposits are characterized by certain continuity of assay values, thickness and top and bottom surfaces of ore zones etc., which are amenable to stochastic modelling with respect to spatial coordinates. The French School (Matheron, 1963) introduced rather difficult terminology of semi-variogram, kriging etc. for quantitative assessment of reserves and average grade of mining property under the assumption of second-order stationarity of first differenced (d=1) data. A more general, powerful and well-known time-domain (spatial) stochastic models (ARIMA (p, d, q); based on Box and Jenkins, 1970, 1976; Anderson, 1976) are introduced herein which include Matheron Model (d=1) as a special case.