Stability criteria for stochastic Takagi‐Sugeno fuzzy Cohen‐Grossberg BAM neural networks with mixed time‐varying delays

This article is concerned with the asymptotic stability analysis of Takagi–Sugeno stochastic fuzzy Cohen–Grossberg neural networks with discrete and distributed time‐varying delays. Based on the Lyapunov functional and linear matrix inequality (LMI) technique, sufficient conditions are derived to ensure the global convergence of the equilibrium point. The proposed conditions can be checked easily by LMI Control Toolbox in Matlab. It has been shown that the results are less restrictive than previously known criteria. They are obtained under mild conditions, assuming neither differentiability nor strict monotonicity for activation function. Numerical examples are given to demonstrate the effectiveness of our results. © 2014 Wiley Periodicals, Inc. Complexity 21: 143–154, 2016     

Studies on rhizosphere microbial diversity of some commercially important medicinal plants

A preliminary study was made on four medicinal plants viz., Ocimum sanctum L., Coleus forskholii Briq, Catharanthus roseus (L.) G. Don. and Aloe vera in order to identify and enumerate the rhizosphere, non-rhizosphere and diazotrophic microorganisms in soil. The diazotrophic bacterial population studied includes Azospirillum, Azotobacter and Pseudomonas. The rhizosphere bacterial populations were 23.33 x 10(6)g(-1) in O. sanctum followed by C. roseus (20.46 x 10(6)g(-1)), A. vera (18.44 x 10(6)g(-1)) and C. forskholii (16.64 x 10(6)g(-1)). The fungi populations were 19.44 x 10(4)g(-1) in C. roseus, 18.66 x 10(4)g(-1) in O. sanctum, 16.44 x 10(4)g(-1) in A. vera and 14.22 x 10(4)g(-1) in C. forskholii. The actinomycetes population was 12.22 x 10(5)g(-1) in O. sanctum, 10.44 x 10(5)g(-1) in C. roseus, 8.44 x 10(5)g(-1) in A. vera and 6.22 x 10(5)g(-1) in C. forskholii. The diazotrophic bacterial population of Azospirillum, Azotobacter and Pseudomonas is 8.2 x 10(4)g(-1), 12 x 10(4)g(-1), 6 x 10(4)g(-1) in the rhizosphere soil. In all the four medicinal plants the microbial population is more in the rhizosphere soil, when compared to non-rhizosphere soil. These results are helpful in developing a biofertilizer consortium for these commercially grown medicinal plants.     

Kinetics and mechanism of oxidation of excited state Tris-(2,2′-bipyridyl)-ruthenium (II) complex by peroxomonosulfate,peroxodisulfate, and peroxodiphosphate

Excitation of Ru(bipy)₃²⁺ ion by visible radiation of wavelength λ = 436 nm in aqueous medium in presence of inorganic peroxides, peroxomonosulfate (PMS), peroxodisulfate (PDS), and peroxodiphosphate (PDP) was found to generate Ru(bipy)₃³⁺. The kinetics of this photochemical oxidation of Ru(bipy)₃²⁺ by each peroxide was followed spectrophotometrically and found to obey a total second-order, first-order each in [Ru(bipy)₃²⁺] and [peroxide]. In the absence of light, thermal reaction of PMS and PDS with Ru(bipy)₃²⁺ occurred but only when at 1.0 M [H⁺] and > 10^?2M [peroxide]. The reaction of PMS with the complex is found to be cyclic, ie., Ru(bipy)₃³⁺ formed oxidizes PMS itself and such a reaction was not observed in the case of PDS and PDP. The effects of pH, [peroxide], and [Ru(bipy)₃²⁺] on the visible light induced oxidation of Ru(bipy)₃²⁺ by these peroxides are investigated. The results are discussed with suitable reaction mechanisms.     

One-pot,four-component synthesis of benzylpyrazolyl naphthoquinone derivatives and molecular docking studies

A highly efficient, green, one-pot, four-component approach for the synthesis of benzylpyrazolyl naphthoquinone derivatives (5a–p) have been developed by the domino reaction of 2-hydroxy naphthoquinone, aromatic aldehyde, ethyl acetoacetate, and phenyl hydrazine derivatives in water and employed p-toluene sulfonic acid (p-TSA) as the right choice of catalyst at reflux. Docking simulation was performed to position compounds 5a, 5b, and 5g into the anaplastic lymphoma kinase (ALK) structure active site to determine the probable binding model.     

An Online Actor–Critic Algorithm with Function Approximation for Constrained Markov Decision Processes

We develop an online actor–critic reinforcement learning algorithm with function approximation for a problem of control under inequality constraints. We consider the long-run average cost Markov decision process (MDP) framework in which both the objective and the constraint functions are suitable policy-dependent long-run averages of certain sample path functions. The Lagrange multiplier method is used to handle the inequality constraints. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal solution. We also provide the results of numerical experiments on a problem of routing in a multi-stage queueing network with constraints on long-run average queue lengths. We observe that our algorithm exhibits good performance on this setting and converges to a feasible point.     

Nonlinear dynamics: Challenges and perspectives

The study of nonlinear dynamics has been an active area of research since 1960s, after certain path-breaking discoveries, leading to the concepts of solitons, integrability, bifurcations, chaos and spatio-temporal patterns, to name a few. Several new techniques and methods have been developed to understand nonlinear systems at different levels. Along with these, a multitude of potential applications of nonlinear dynamics have also been enunciated. In spite of these developments, several challenges, some of them fundamental and others on the efficacy of these methods in developing cutting edge technologies, remain to be tackled. In this article, a brief personal perspective of these issues is presented.     

The Jungebad apparatus for the production of oil-dispersion baths

The Jungebad apparatus is used to generate oil-dispersion baths in medical applications. The oil-water dispersion is produced by dispersing medically-effective oil while filling the bathtub. The aim is to produce smaller droplets in comparison to conventionally produced oil-dispersion baths to generate a high surface-to-volume ratio of the oil. Additionally, the oil should be dispersed homogenously in the bath. Due to the greater surface of the oil, a better admission through the skin of the patient is achieved. Experimental investigations with regard to the functionality of the Jungebad apparatus are presented. The analysis of the functionality and the oil-water dispersion generation is accomplished by observations with a high-speed camera. Results are discussed with respect to the required characteristics of the dispersion. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Exponential stability for markovian jumping stochastic BAM neural networks with mode‐dependent probabilistic time‐varying delays and impulse control

In this article, an exponential stability analysis of Markovian jumping stochastic bidirectional associative memory (BAM) neural networks with mode‐dependent probabilistic time‐varying delays and impulsive control is investigated. By establishment of a stochastic variable with Bernoulli distribution, the information of probabilistic time‐varying delay is considered and transformed into one with deterministic time‐varying delay and stochastic parameters. By fully taking the inherent characteristic of such kind of stochastic BAM neural networks into account, a novel Lyapunov‐Krasovskii functional is constructed with as many as possible positive definite matrices which depends on the system mode and a triple‐integral term is introduced for deriving the delay‐dependent stability conditions. Furthermore, mode‐dependent mean square exponential stability criteria are derived by constructing a new Lyapunov‐Krasovskii functional with modes in the integral terms and using some stochastic analysis techniques. The criteria are formulated in terms of a set of linear matrix inequalities, which can be checked efficiently by use of some standard numerical packages. Finally, numerical examples and its simulations are given to demonstrate the usefulness and effectiveness of the proposed results. © 2014 Wiley Periodicals, Inc. Complexity 20: 39–65, 2015     

Preparation and Performance of Polysulfone‐Cellulose Acetate Blend Ultrafiltration Membrane

In the development of high performance polymeric membranes, it is essential to design the molecular and morphological characteristics for specific applications. Polysulfone and cellulose acetate of blend membranes with various concentration of polymer pore former, PEG600 were prepared by phase inversion technique and used for ultrafiltration. Polymer blend composition, additive concentration, and casting conditions were optimized. The blend membranes were characterized in terms of compaction, pure water flux, water content, hydraulic resistance and separation of dextran studies. Surface morphology of the embranes was analyzed using scanning electron microscopy at different magnifications. Further, the characterized membranes were attempted for treatment of distillery effluents after secondary treatment and the results are discussed in detail.