Markov Properties of Electrical Discharge Current Fluctuations in Plasma

Using the Markovian method, we study the stochastic nature of electrical discharge current fluctuations in the Helium plasma. Sinusoidal trends are extracted from the data set by the Fourier-Detrended Fluctuation analysis and consequently cleaned data is retrieved. We determine the Markov time scale of the detrended data set by using likelihood analysis. We also estimate the Kramers-Moyal’s coefficients of the discharge current fluctuations and derive the corresponding Fokker-Planck equation. In addition, the obtained Langevin equation enables us to reconstruct discharge time series with similar statistical properties compared with the observed in the experiment. We also provide an exact decomposition of temporal correlation function by using Kramers-Moyal’s coefficients. We show that for the stationary time series, the two point temporal correlation function has an exponential decaying behavior with a characteristic correlation time scale. Our results confirm that, there is no definite relation between correlation and Markov time scales. However both of them behave as monotonic increasing function of discharge current intensity. Finally to complete our analysis, the multifractal behavior of reconstructed time series using its Keramers-Moyal’s coefficients and original data set are investigated. Extended self similarity analysis demonstrates that fluctuations in our experimental setup deviates from Kolmogorov (K41) theory for fully developed turbulence regime.     

Synthesis of a novel molecularly imprinted polymer based on functionalized multi-walled carbon nanotubes for selective extraction of sulfadiazine prior to spectrophotometric determination

A novel and efficient sulfadiazine imprinted polymer was synthesized via co-precipitation method and successfully grafted on magnetic multi-walled carbon nanotubes. The synthesized magnetic imprinted polymer was characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray powder diffraction analysis, thermal analysis and applied as a sorbent for selective magnetic solid-phase extraction of sulfadiazine. The retained sulfadiazine was eluted by 150.0 µL methanol/acetic acid (6:4) solution and quantified by fiber optic linear array spectrophotometry via formation of a detectable azo dye. All parameters affecting the extraction of sulfadiazine were investigated and optimized. Under the optimized conditions, the method exhibited a linear dynamic range of 2.0–50.0 µg L^?1 with a detection limit of 0.56 µg L^?1 and enrichment factor of 300.0. The relative standard deviation at 30.0 µg L^?1 of sulfadiazine (N = 6) was 2.8 and 4.6% for intra-day and inter-day, respectively. The method was successfully applied to determine sulfadiazine in human urine, honey, milk and environmental water samples.     

A two-phase approach for setting targets in DEA with negative data

Conventional DEA models have been introduced to deal with non-negative data. In the real world, in some occasions, we have outputs and/or inputs, which can take negative data. In DEA literature some approaches have been presented for evaluating performance of units, which operate with negative data. In this paper, firstly, we give a brief review of these works, then we present a new additive based approach in this framework. The proposed model is designed to provide a target with non-negative value associated with negative components for each observed unit, failed by other methods. An empirical application in banking is then used to show the applicability of the proposed method and make a comparison with the other approaches in the literature.     

Slant Submanifolds of Almost Contact Metric 3-Structure Manifolds

In this paper we introduce the notion of slant submanifold of an almost contact metric 3-structure manifold. We give some examples and characterize these submanifolds. Moreover, Sasakian slant submanifolds of an almost contact 3-structure manifold are defined and studied. We also establish a sharp inequality including the squared mean curvature and Ricci curvature of a Sasakian slant submanifold.     

Wavelet analysis method for solving linear and nonlinear singular boundary value problems

In this paper, a robust and accurate algorithm for solving both linear and nonlinear singular boundary value problems is proposed. We introduce the Chebyshev wavelets operational matrix of derivative and product operation matrix. Chebyshev wavelets expansions together with operational matrix of derivative are employed to solve ordinary differential equations in which, at least, one of the coefficient functions or solution function is not analytic. Several examples are included to illustrate the efficiency and accuracy of the proposed method.     

A scenario decomposition approach for stochastic production planning in sawmills

This study considers a real world stochastic multi-period, multi-product production planning problem. Motivated by the challenges encountered in sawmill production planning, the proposed model takes into account two important aspects: (i) randomness in yield and in demand; and (ii) set-up constraints. Rather than considering a single source of randomness, or ignoring set-up constraints as is typically the case in the literature, we retain all these characteristics while addressing real life-size instances of the problem. Uncertainties are modelled by a scenario tree in a multi-stage environment. In the case study, the resulting large-scale multi-stage stochastic mixed-integer model cannot be solved by using the mixed-integer solver of a commercial optimization package, such as CPLEX. Moreover, as the production planning model under discussion is a mixed-integer programming model lacking any special structure, the development of decomposition and cutting plane algorithms to obtain good solutions in a reasonable time-frame is not straightforward. We develop a scenario decomposition approach based on the progressive hedging algorithm, which iteratively solves the scenarios separately. CPLEX is then used for solving the sub-problems generated for each scenario. The proposed approach attempts to gradually steer the solutions of the sub-problems towards an implementable solution by adding some penalty terms in the objective function used when solving each scenario. Computational experiments for a real-world large-scale sawmill production planning model show the effectiveness of the proposed solution approach in finding good approximate solutions.     

Synthesis of acetamides via oxidative C–C bond cleavage of ketones catalyzed by Cu-immobilized magnetic nanoparticles

Copper supported on magnetite nanoparticles modified with environmentally friendly ligand tricine was devised for synthesis of acetamides via C–C oxidative cleavage of ketones with amines. The catalyst was characterized using different techniques, including Fourier transform infrared, X-ray diffraction, scannin electron microscopy, vibrating sample magnetometry, thermogravimetric analysis, and energy dispersive x-ray spectroscopy. The protocol showed relatively high yields of acetamide products. Furthermore, the magnetic recovery of the catalyst rendered the overall process fast and efficient. It was used in the reaction for six consecutive cycles with negligible loss of catalytic activity. This research is the first report of application of magnetic nanocatalysts for synthesis of acetamides from ketones of low activity through a C–C bond cleavage strategy.     

Pd(0) nanoparticles immobilized on multinitrogen functionalized halloysite for promoting Sonogashira reaction: studying the role of the number of surface nitrogens in catalytic performance

Halloysite nanoclay, Hal, was amine-functionalized and subsequently reacted with 2,4,6-trichloro-1,3,5-triazine, TCT, and ethylenediamine, EDA, to provide multinitrogen containing functionality on the surface of Hal. The resulting surface-modified Hal, Hal-2N-TCT-EDA, was then used for immobilization of Pd nanoparticles and affording a heterogeneous catalyst, Pd@Hal-2N-TCT-EDA, with utility for copper and ligand-free Sonogashira coupling of alkynes and aryl halides. The results established the efficiency of this protocol in terms of product yield, ecofriendly nature, and reaction time. Study of the reusability of the catalyst confirmed that the catalyst could be recovered and recycled up to seven times with slight loss of catalytic activity and Pd leaching, indicating the efficiency of Hal-2N-TCT-EDA for embedding Pd nanoparticles. To elucidate the role of the number of surface nitrogens on the catalytic performance, the catalytic activity, and recyclability of the catalyst was compared with those of Hal-2N and Hal-2N-TCT. It was found that more surface nitrogen atoms gave higher loading of Pd and lower Pd leaching. This result confirms the contribution of surface nitrogens to anchor the Pd species and suppress leaching.

     

An Efficient Method for the Synthesis of N-Acylsulfonamides: One-pot Sulfonylation and Acylation of Primary Arylamines under Solvent-Free Conditions

Summary. The preparation of N-acylsulfonamides is described using primary amines, arylsulfonyl chlorides and acyl chlorides. Reaction of primary aryl amines with arylsulfonyl chlorides in the presence of NaHCO₃ produced N-arylsulfonamides, which reacted in situ with benzoyl chloride furnishing the corresponding N-benzoyl-N-arylsulfonamides in 72–96% yields. Accordingly, 4-nitrobenzoyl chloride and 3,5-dinitrobenzoyl chloride were used as acylating agents. All the reactions were carried out under solvent-free conditions at room temperature and the products were isolated after simple work-up in high yields and purity.     

Practical reduction of imines by NaBH4/alumina under solvent-free conditions： An efficient route to secondary amine

Sodium borohydride supported on alumina reduces imines to the corresponding secondary amines in high to excellent isolated yields under solvent-free conditions. Noteworthy is that highly chemoselective reactions were achieved in the presence of other functional groups such as halogen, nitro, and cyano groups.