Structural and magnetic properties of Co1+ySnyFe2-2y-xCrxO4 ferrite system

The samples of the series Co_1+ySn_yFe_{2- 2y- x}Cr_xO₄ ferrites with x = 0.0, 0.1, 0.2, 0.3, 0.4, 0.5 and y = 0.05, were prepared by the usual double sintering ceramic technique. The single- phase spinel structure of the samples was confirmed by using X- ray diffractometry technique. The lattice parameter ’a’ with an accuracy of ± 0.002 Å were determined using Bragg peaks of XRD pattern. The lattice parameter ’a’ decreases with concentration, x, which is due to the difference in the ionic radii of Cr³⁺ and Fe³⁺ ions. The X- ray intensity calculations were carried out in order to determine the possible cation distribution amongst tetrahedral (A) and octahedral [B] sites. The X- ray intensity calculations show Cr³⁺ ions occupying B site. The saturation magnetization, σ_s, and magneton number, n_B (the saturation magnetization per formula unit), measured at 300 K determined from high field hysteresis loop technique decrease with increase in concentration, x, suggesting a decrease in ferrimagnetic behaviour. Thermal variation of low field a.c. susceptibility measurements from room temperature to about 800 K exhibits almost normal ferrimagnetic behaviour and the Curie temperature, T_C determined from a.c. susceptibility data decreases with increase in x.

     

Stepwise-Graded Si3N4–SiC Ceramics with Improved Wear Properties

The processing of stepwise graded Si₃N₄/SiC ceramics by pressureless co-sintering is described. Here, SiC (high elastic modulus, high thermal expansion coefficient) forms the substrate and Si₃N₄ (low elastic modulus, low thermal expansion coefficient) forms the top contact surface, with a stepwise gradient in composition existing between the two over a depth of ∼1.7 mm. The resulting Si₃N₄ contact surface is fine-grained and dense, and it contains only 2 vol% yttrium aluminum garnet (YAG) additive. This graded ceramic shows resistance to cone-crack formation under Hertzian indentation, which is attributed to a combined effect of the elastic-modulus gradient and the compressive thermal-expansion-mismatch residual stress present at the contact surface. The presence of the residual stress is corroborated and quantified using Vickers indentation tests. The graded ceramic also possesses wear properties that are significantly improved compared with dense, monolithic Si₃N₄ containing 2 vol% YAG additive. The improved wear resistance is attributed solely to the large compressive stress present at the contact surface. A modification of the simple wear model by Lawn and co-workers is used to rationalize the wear results. Results from this work clearly show that the introduction of surface compressive residual stresses can significantly improve the wear resistance of polycrystalline ceramics, which may have important implications for the design of contact-damage-resistant ceramics.     

An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch

Economic dispatch is carried out at the energy control center to find out the optimal output of thermal generating units such that power balance criterion is met, unit operating limits are satisfied and the fuel cost is minimized. With growing environmental awareness and strict government regulations throughout the world, it has become essential to optimize not only the total fuel cost but also the harmful emissions, both, under static as well as dynamic conditions. The static environment economic dispatch finds the optimal output of generating units for a fixed load demand at a given time, while the dynamic environmental economic dispatch schedules the output of online generators with changing power demands over a certain time period (normally one day) so as to minimize these two conflicting objectives, simultaneously. In this paper, the price penalty factor approach is employed for simultaneous minimization of cost and emission. The generator ramp rate constraints, non-convex and discontinuous nature of cost function and the large number of generators in practical power plants, make this problem very difficult to solve. Here, a fuzzy ranking approach is employed to identify the solution which offers the best compromise between cost and emission objectives.     

A composite numerical scheme for the numerical simulation of coupled Burgers’ equation

In this work, a composite numerical scheme based on finite difference and Haar wavelets is proposed to solve time dependent coupled Burgers’ equation with appropriate initial and boundary conditions. Time derivative is discretized by forward difference and then quasilinearization technique is used to linearize the coupled Burgers’ equation. Space derivatives discretization with Haar wavelets leads to a system of linear equations and is solved using Matlab7.0. Convergence analysis of proposed scheme exhibits that the error bound is inversely proportional to the resolution level of the Haar wavelet. Finally, the adaptability of proposed scheme is demonstrated by numerical experiments and shows that the present composite scheme offers better accuracy in comparison with other existing numerical methods.     

Change point detection for compositional multivariate data

Change point detection algorithms have numerous applications in areas of medical condition monitoring, fault detection in industrial processes, human activity analysis, climate change detection, and speech recognition. We consider the problem of change point detection on compositional multivariate data (each sample is a probability mass function), which is a practically important sub-class of general multivariate data. While the problem of change-point detection is well studied in univariate setting, and there are few viable implementations for a general multivariate data, the existing methods do not perform well on compositional data. In this paper, we propose a parametric approach for change point detection in compositional data. Moreover, using simple transformations on data, we extend our approach to handle any general multivariate data. Experimentally, we show that our method performs significantly better on compositional data and is competitive on general data compared to the available state of the art implementations.

     

Biosynthesis of zinc oxide nanoparticles by petals extract of Rosa indica L., its formulation as nail paint and evaluation of antifungal activity against fungi causing onychomycosis

Aim: The authors report the biological synthesis of zinc oxide nanoparticles (ZnO‐NPs) from the petals extract of Rosa indica L. (rose). Its efficacy was evaluated against two dermatophytes: namely: Trichophyton mentagrophytes and Microsporum canis which cause onychomycosis. The activity of antibiotics against the tested dermatophytes was enhanced, when evaluated in combination with ZnO‐NPs. Methods and results: The synthesised ZnO‐NPs were preliminary detected by using ultraviolet UV visible spectroscopy, which showed specific absorbance. The ZnO‐NPs were further characterised by nanoparticle tracking analysis (NTA), Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), X‐ray diffraction and Zetasizer. Moreover, nanoparticles containing nail paint (nanopaint) was formulated and its antifungal activity was also assessed against T. mentagrophytes and M. canis. ZnO‐NPs and formulated nanopaint containing ZnO‐NPs, both showed significant antifungal activity. The maximum activity was noted against M. canis and lesser against T. mentagrophytes. Minimum inhibitory concentration of ZnO‐NPs was also determined against the dermatophytes causing onychomycosis infection. Conclusion: ZnO‐NPs can be utilised as a potential antifungal agent for the treatment of onychomycosis after more experimental trials.Inspec keywords: diseases, zinc compounds, nanoparticles, nanofabrication, antibacterial activity, microorganisms, nanomedicine, ultraviolet spectra, visible spectra, Fourier transform infrared spectra, transmission electron microscopy, X‐ray diffraction, biomedical materials, patient treatmentOther keywords: zinc oxide nanoparticle biosynthesis, Rosa indica L petals extract, nail paint, antifungal activity evaluation, dermatophyte, Trichophyton mentagrophytes, Microsporum canis, antibiotics activity, ultraviolet‐visible spectroscopy, nanoparticle tracking analysis, Fourier transform infrared spectroscopy, transmission electron microscopy, X‐ray diffraction, zetasizer, antifungal agent, onychomycosis treatment     

Modified neo-fuzzy neuron-based approach for economic and environmental optimal power dispatch

At the central energy management center in a power system, the real time controls continuously track the load changes and endeavor to match the total power demand with total generation in such a manner that the operating cost is minimized while all the operating constraints are satisfied. However, due to the strict government regulations on environmental protection, operation at minimum cost is no longer the only criterion for dispatching electrical power. The idea behind the environmentally constrained economic dispatch formulation is to estimate the optimal generation schedule of generating units in such a manner that fuel cost and harmful emission levels are both simultaneously minimized for a given load demand. Conventional optimization techniques become very time consuming and computationally extensive for such complex optimization tasks. These methods are hence not suitable for on-line use. Neural networks and fuzzy systems can be trained to generate accurate relations among variables in complex non-linear dynamical environment, as both are model-free estimators. The existing synergy between these two fields has been exploited in this paper for solving the economic and environmental dispatch problem on-line. A multi-output modified neo-fuzzy neuron (NFN), capable of real time training is proposed for economic and environmental power generation allocation.This model is found to achieve accurate results and the training is observed to be faster than other popular neural networks. The proposed method has been tested on medium-sized sample power systems with three and six generating units and found to be suitable for on-line combined environmental economic dispatch (CEED).