Depth Estimation from Gravity Data Using the Maximum Entropy Method (MEM) and the Multi Taper Method (MTM)

The depth determination from the gravity data in frequency domain is carried out using the classical fast Fourier transform (FFT) method utilizing scaling properties of ensemble of anomalous source. The problem of calculating power spectrum from the FFT is well described in the literature. Here, the application of other high-resolution methods of power spectrum calculation, such as maximum entropy method (MEM) and multi-taper method (MTM) are explored to estimate depth to anomalous sources. At the outset, the FFT, the MEM and the MTM are tested on synthetic gravity data, generated for different types of synthetic models and then all these methods are applied to the field gravity data of the Bengal basin. The MTM with scaling is found to be superior for providing the detailed subsurface information rather than the MEM and the FFT methods in the case of synthetic as well as field examples.     

Anisotropic bulk viscous cosmological models in a modified gravity

A spatially homogeneous Bianchi type-VI₀ space-time is considered in the frame work of f(R,T) gravity proposed by Harko et al. (Phys. Rev. D 84:024020, 2011) when the source for energy momentum tensor is a bulk viscous fluid containing one dimensional cosmic strings. Exact solutions of the field equations are obtained both in the absence and in the presence of cosmic strings under some specific plausible physical conditions. Some physical and kinematical properties of the model are, also, studied.     

Pullout capacity of multi-plate horizontal anchors in sand: an experimental study

Acta Geotechnica - A horizontal anchor is a structural member designed to resist the vertical pullout forces and ensure the stability of structures like the tower foundations, masts and bridges....     

Prediction of Elastic Modulus of Jointed Rock Mass Using Artificial Neural Networks

Two artificial neural network models for the prediction of elastic modulus of jointed rock mass from the elastic modulus of corresponding intact rock and joint parameters have been demonstrated in this paper. The data collected from uniaxial and triaxial compression tests on different rocks with different joint configurations and different confining pressure conditions, reported in the literature are used as input for training the networks. Important joint properties like joint frequency, joint inclination and roughness of joints are considered separately for making the network more versatile. Two different techniques of artificial neural networks namely feed forward back propagation (FFBP) and radial basis function (RBF) are used to predict the elastic modulus ratio.     

2015–16 ENSO contributed reduction in oil sardines along the Kerala coast,south‐west India

Fishery along the west coast of India largely depends on pelagic fish such as oil sardines, which are dominant during the south‐west monsoon. However, the response of sardine population to the warming caused by the climatic events such as El Niño/Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) is poorly studied. Here, we hypothesize that the ENSO‐related changes in biogeochemistry can adversely affect the oil sardines. We have used biogeochemical data collected along the Kerala coast during September 2015 (ENSO year) and September 2017 (a normal year) supported by catch per unit effort (CPUE) and fishery landing data to show the ENSO‐related bio‐physical dynamics and its impact on the oil sardine population along the south‐west coast of India. During the 2015 ENSO year, upwelling velocity decreased minimizing cooling of surface waters and resulted with an increase in sea surface temperature (SST) (~1.8°C). Consequent decrease in nutrient levels favoured nano‐phytoplankton and pico‐phytoplankton. On the other hand, during September 2017 when the ENSO effect was nullified, the decreased SST and availability of nutrients in the euphotic zone resulted in the dominance of micro‐phytoplankton. The hydrographic conditions (reduction in upwelling intensity), and reduction in micro‐phytoplankton abundance and zooplankton density in turn perhaps affected the fishery potential of the region. Oil sardines population (along the west coast) collapsed from 1.55 lakh tones (2014) to 0.46 lakh tones during 2015–2016 ENSO event, while in 2017 the conditions become favorable and their population was back to normal (1.27 lakh tones). Our results are in close agreement with our hypothesis and suggest that ENSO events could reduce phytoplankton productivity and disrupt the food chain, which in turn can affect the oil sardine population along the west coast of India.     

Bianchi type-III bulk viscous string cosmological model in Brans-Dicke theory of gravitation

A spatially homogeneous and anisotropic Bianchi type-III space-time is considered in the framework of a scalar-tensor theory of gravitation proposed by Brans and Dicke (Phys. Rev. 124:925, 1961) in the presence of bulk viscous fluid containing one dimensional cosmic strings. We have found a determinate solution of the field equations using the plausible physical conditions (i) a barotropic equation state for the pressure and density, (ii) special law of variation for Hubble’s parameter proposed by Berman (Nuovo Cimento B74:182, 1983), (iii) shear scalar is proportional to scalar expansion and (iv) the trace of the energy tensor of the fluid vanishes. We have also assumed that bulk viscous pressure is proportional to energy density. Some physical and kinematical properties of the model are, also, discussed.