QEP Based Solution for Power Allocation in Amplify and Forward Networks

The problem of cooperative beamforming for maximizing the achievable data rate of an energy constrained two-hop amplify-and-forward (AF) network is considered. Assuming perfect channel state information (CSI) of all the nodes, we evaluate the optimal scaling factor for the relay nodes. Along with individual power constraint on each of the relay nodes, we consider a weighted sum power constraint. The proposed iterative algorithm initially solves a set of relaxed problems with weighted sum power constraint and then updates the solution to accommodate individual constraints. These relaxed problems in turn are solved using a sequence of Quadratic Eigenvalue Problems (QEP). The key contribution of this letter is the generalization of cooperative beamforming to incorporate both the individual and weighted sum constraint. Furthermore, we have proposed a novel algorithm based on Quadratic Eigenvalue Problem (QEP) and discussed its convergence.

Thermal, magnetic and electrical properties of Tb1-xDyxMnO3 multiferroics

A series of multiferroic materials with the compositional formula, Tb1 - xDyxMnO3 (where x=0, 0.1, 0.2, 0.3 and 0.4) were prepared by the sol gel method. After characterizing the samples structurally, a systematic investigation of specific heat, magnetization and dielectric properties over the temperature range, 4-300 K, was undertaken. Based on these studies, it was found that all the samples exhibit a transition at 40 K and the observed behavior may be attributed to the ordering of Mn3+ ions. Further, all the five samples are found to exhibit a ferroelectric transition in the temperature range 20-24 K. Finally, yet another transition was also exhibited by all the samples at temperatures below 10 K and is attributed to the antiferromagnetic (AF) ordering of rare-earth ionic moments. The magnetic entropy of all the samples was also computed with the help of their heat capacity data. (C) 2015 Elsevier B.V. All rights reserved.

Macroporous three-dimensional graphene oxide foams for dye adsorption and antibacterial applications

Several reports illustrate the wide range applicability of graphene oxide (GO) in water remediation. However, a few layers of graphene oxide tend to aggregate under saline conditions thereby reducing its activity. The effects of aggregation can be minimized by having a random arrangement of GO layers in a three dimensional architecture. The current study emphasizes the potential benefits of highly porous, ultralight graphene oxide foams in environmental applications. These foams were prepared by a facile and cost effective lyophilization technique. The 3D architecture allowed the direct use of these foams in the removal of aqueous pollutants without any pretreatment such as ultrasonication. Due to its macroporous nature, the foams exhibited excellent adsorption abilities towards carcinogenic dyes such as rhodamine B (RB), malachite green (MG) and acriflavine (AF) with respective sorption capacities of 446, 321 and 228 mg g(-1) of foam. These foams were also further investigated for antibacterial activities against E. coli bacteria in aqueous and nutrient growth media. The random arrangement of GO layers in the porous foam architecture allowed it to exhibit excellent antibacterial activity even under physiological conditions by following the classical wrapping-perturbation mechanism. These results demonstrate the vast scope of GO foam in water remediation for both dye removal and antibacterial activity.

Efficient density matrix renormalization group algorithm to study Y junctions with integer and half-integer spin

An efficient density matrix renormalization group (DMRG) algorithm is presented and applied to Y junctions, systems with three arms of n sites that meet at a central site. The accuracy is comparable to DMRG of chains. As in chains, new sites are always bonded to the most recently added sites and the superblock Hamiltonian contains only new or once renormalized operators. Junctions of up to N = 3n + 1 approximate to 500 sites are studied with antiferromagnetic (AF) Heisenberg exchange J between nearest-neighbor spins S or electron transfer t between nearest neighbors in half-filled Hubbard models. Exchange or electron transfer is exclusively between sites in two sublattices with N-A not equal N-B. The ground state (GS) and spin densities rho(r) = < S-r(z)> at site r are quite different for junctions with S = 1/2, 1, 3/2, and 2. The GS has finite total spin S-G = 2S(S) for even (odd) N and for M-G = S-G in the S-G spin manifold, rho(r) > 0(< 0) at sites of the larger (smaller) sublattice. S = 1/2 junctions have delocalized states and decreasing spin densities with increasing N. S = 1 junctions have four localized S-z = 1/2 states at the end of each arm and centered on the junction, consistent with localized states in S = 1 chains with finite Haldane gap. The GS of S = 3/2 or 2 junctions of up to 500 spins is a spin density wave with increased amplitude at the ends of arms or near the junction. Quantum fluctuations completely suppress AF order in S = 1/2 or 1 junctions, as well as in half-filled Hubbard junctions, but reduce rather than suppress AF order in S = 3/2 or 2 junctions.

Anthropogenic aerosol fraction over the Indian region: model simulations versus multi-satellite data analysis

Anthropogenic aerosols play a crucial role in our environment, climate, and health. Assessment of spatial and temporal variation in anthropogenic aerosols is essential to determine their impact. Aerosols are of natural and anthropogenic origin and together constitute a composite aerosol system. Information about either component needs elimination of the other from the composite aerosol system. In the present work we estimated the anthropogenic aerosol fraction (AF) over the Indian region following two different approaches and inter-compared the estimates. We espouse multi-satellite data analysis and model simulations (using the CHIMERE Chemical transport model) to derive natural aerosol distribution, which was subsequently used to estimate AF over the Indian subcontinent. These two approaches are significantly different from each other. Natural aerosol satellite-derived information was extracted in terms of optical depth while model simulations yielded mass concentration. Anthropogenic aerosol fraction distribution was studied over two periods in 2008: premonsoon (March-May) and winter (November-February) in regard to the known distinct seasonality in aerosol loading and type over the Indian region. Although both techniques have derived the same property, considerable differences were noted in temporal and spatial distribution. Satellite retrieval of AF showed maximum values during the pre-monsoon and summer months while lowest values were observed in winter. On the other hand, model simulations showed the highest concentration of AF in winter and the lowest during pre-monsoon and summer months. Both techniques provided an annual average AF of comparable magnitude (similar to 0.43 +/- 0.06 from the satellite and similar to 0.48 +/- 0.19 from the model). For winter months the model-estimated AF was similar to 0.62 +/- 0.09, significantly higher than that (0.39 +/- 0.05) estimated from the satellite, while during pre-monsoon months satellite-estimated AF was similar to 0.46 +/- 0.06 and the model simulation estimation similar to 0.53 +/- 0.14. Preliminary results from this work indicate that model-simulated results are nearer to the actual variation as compared to satellite estimation in view of general seasonal variation in aerosol concentrations.