Voltammetry of resazurin at a mercury electrode

Electrochemical behavior of resazurin on HMDE in Britton-Robinson (B-R) buffers (pH 2.0–10.0) was studied using the square-wave voltammetry (SWV), square-wave adsorptive stripping voltammetry (SWAdSV), and cyclic voltammetry (CV) techniques. The voltammogram of resazurin in B-R buffer at pH < 4.0 exhibited two cathodic reduction peaks. The voltammetric peaks were obtained at −0.144 V (reversible) and −1.250 V (irreversible) at pH 3.2, and correspond to the reduction of resorufin to dihydroresorufin and to the catalytic hydrogen wave, respectively. At pH > 4.0, a new irreversible cathodic reduction peak, assigned to the protonation of N-oxide on the phenoxazin ring, was observed. Electrochemical parameters (I _p/E _p, I _p/v, I _p/pH, I _p/t _acc) of the compound were determined. From the voltammetric data, electrochemical reduction mechanisms for all peaks have been suggested. Maximum peak current for the reversible peak was obtained at pH 4.1. A linear relationship between the current and concentration was determined, and also the lowest detection limit was found as 3.25 × 10⁻⁸ mol L⁻¹ and 1.98 × 10⁻¹⁰ mol L⁻¹ for SWV and SWAdSV, respectively.     

Assessing the predictive effectiveness of the variety seeking and reinforcement models

Prediction of customer choice behaviour has been a big challenge for marketing researchers. They have adopted various models to represent customers purchase patterns. Some researchers considered simple zero–order models. Others proposed higher–order models to represent explicitly customers tendency to seek [variety] or [reinforcement] as they make repetitive choices. Nevertheless, the question [Which model has the highest probability of representing some future data?] still prevails. The objective of this paper is to address this question. We assess the predictive effectiveness of the well–known customer choice models. In particular, we compare the predictive ability of the [dynamic attribute satiation] (DAS) model due to McAlister (Journal of Consumer Research, 91, pp. 141–150, 1982) with that of the well–known stochastic variety seeking and reinforcement behaviour models. We found that the stochastic [beta binomial] model has the best predictive effectiveness on both simulated and real purchase data. Using simulations, we also assessed the effectiveness of the stochastic models in representing various complex choice processes generated by the DAS. The beta binomial model mimicked the DAS processes the best. In this research we also propose, for the first time, a stochastic choice rule for the DAS model.     

On the two classes of high‐order convergent methods of approximate inverse preconditioners for solving linear systems

Two classes of methods for approximate matrix inversion with convergence orders p =3?2^k +1 (Class 1) and p =5?2^k ?1 (Class 2), k ≥1 an integer, are given based on matrix multiplication and matrix addition. These methods perform less number of matrix multiplications compared to the known hyperpower method or p th‐order method for the same orders and can be used to construct approximate inverse preconditioners for solving linear systems. Convergence, error, and stability analyses of the proposed classes of methods are provided. Theoretical results are justified with numerical results obtained by using the proposed methods of orders p =7,13 from Class 1 and the methods with orders p =9,19 from Class 2 to obtain polynomial preconditioners for preconditioning the biconjugate gradient (BICG) method for solving well‐ and ill‐posed problems. From the literature, methods with orders p =8,16 belonging to a family developed by the effective representation of the p th‐order method for orders p =2^k , k is integer k ≥1, and other recently given high‐order convergent methods of orders p =6,7,8,12 for approximate matrix inversion are also used to construct polynomial preconditioners for preconditioning the BICG method to solve the considered problems. Numerical comparisons are given to show the applicability, stability, and computational complexity of the proposed methods by paying attention to the asymptotic convergence rates. It is shown that the BICG method converges very quickly when applied to solve the preconditioned system. Therefore, the cost of constructing these preconditioners is amortized if the preconditioner is to be reused over several systems of same coefficient matrix with different right sides.     

Investigation of Cs(I) adsorption on densely crosslinked poly(sodium methacrylate) from aqueous solutions

In this study, a crosslinked copolymer bearing sodium methacrylate functional groups has been proposed to remove Cs(I) ions from aqueous solutions. For this purpose, the crosslinked copolymer of ethylene glycol dimethacrylate (EGDM) and methacrylic acid (MA) containing 25% MA as weight percentage was synthesized by using benzoyl peroxide (BPO)-N,N-dimethyl aniline initiator system. The available carboxyl groups in copolymer were converted to the groups of sodium methacrylate using 2 N NaOH. The adsorption behavior of cesium ions on the densely crosslinked poly(sodium methacrylate) from aqueous solutions were investigated by the technique of ICP-MS measurements of cesium ions in solutions. Batch adsorption method was used to analyze the Cs(I) adsorption as a function of parameters such as the amount of adsorbent, contact time, pH of solution, initial Cs(I) concentration and temperature. The adsorption data were evaluated by the Freundlich, Langmuir and Dubinin–Radushkevich (D–R) isotherms. The adsorption capacity and free energy change were calculated by using D–R isotherm. The adsorption data obtained from experimental results have been tested by the fractional power, the Elovich, the pseudo-first order and the pseudo-second order kinetic models.     

A characterization of Möbius transformations by use of hyperbolic regular polygons

In this paper we present a new characterization of Möbius transformations by use of hyperbolic regular polygons.     

The electrochemical behavior of some podands at a benzo[c]cinnoline modified glassy carbon electrode

This paper describes the grafting of benzo[c]cinnoline (BCC) molecules on glassy carbon (GC) electrode surface. The attachment of BCC molecules to carbon substrate is induced by the electrochemical reduction of the corresponding diazonium salt. The modification of GC with BCC diazonium salt was done in aprotic solution and proved by blocking of dopamine electron transfer. The presence of BCC at the GC surface was characterized by cyclic voltammetry and X-ray photoelectron spectroscopy (XPS). On modified surface, the electrochemical behavior of two different types of podands and the catalytic effects of the GC-BCC surface were studied. The XPS was used to monitor element characteristics of the adsorbates on the GC surface and confirm the attachment of BCC molecules to the GC surface.     

Characterization of a 2‐Benzo[c]cinnoline Modified Glassy Carbon Electrode by Raman Spectroscopy,Electrochemical Impedance Spectroscopy,and Ellipsometry

This work describes the characterization of the grafted 2‐benzo[c]cinnoline (2BCC) molecules at a glassy carbon (GC) electrode surface by voltammetry and spectroscopy. Attachment of the molecule to the carbon substrate was achieved by the electrochemical reduction of 2‐benzo[c]cinnoline diazonium salt (2BCC‐DAS). GC electrode modification was carried out in aprotic solution with 2BCC diazonium salt. Dopamine (DA) and ascorbic acid (AA) were used to prove the surface modification to see the blockage of the electron transfer. The presence of 2BCC at the GC electrode surface was characterized by cyclic voltammetry and Raman spectroscopy. Raman spectroscopy was used to monitor molecular bound properties of the adsorbates at the 2BCC‐GC surface and confirm the attachment of 2BCC molecules onto the GC surface. The thickness of the 2BCC film on GC was also investigated by ellipsometric measurement.     

Vanishing Derivations and Co-Centralizing Generalized Derivations on Multilinear Polynomials in Prime Rings

Let R be a noncommutative prime ring of characteristic different from 2 with Utumi quotient ring U and extended centroid C, and f(x₁,…, x_n) be a multilinear polynomial over C, which is not central valued on R. Suppose that F and G are two generalized derivations of R and d is a nonzero derivation of R such that d(F(f(r))f(r) ? f(r)G(f(r))) = 0 for all r = (r₁,…, r_n) ∈ Rⁿ, then one of the following holds:

1. There exist a, p, q, c ∈ U and λ ∈C such that F(x) = ax + xp + λx, G(x) = px + xq and d(x) = [c, x] for all x ∈ R, with [c, a ? q] = 0 and f(x₁,…, x_n)² is central valued on R;

2. There exists a ∈ U such that F(x) = xa and G(x) = ax for all x ∈ R;

3. There exist a, b, c ∈ U and λ ∈C such that F(x) = λx + xa ? bx, G(x) = ax + xb and d(x) = [c, x] for all x ∈ R, with b + αc ∈ C for some α ∈C;

4. R satisfies s₄ and there exist a, b ∈ U and λ ∈C such that F(x) = λx + xa ? bx and G(x) = ax + xb for all x ∈ R;

5. There exist a′, b, c ∈ U and δ a derivation of R such that F(x) = a′x + xb ? δ(x), G(x) = bx + δ(x) and d(x) = [c, x] for all x ∈ R, with [c, a′] = 0 and f(x₁,…, x_n)² is central valued on R.

     

A new proposed model of restricted data envelopment analysis by correlation coefficients

The concept of efficiency in data envelopment analysis (DEA) is defined as weighted sum of outputs/weighted sum of inputs. In order to calculate the maximum efficiency score, each decision making unit (DMU)’s inputs and outputs are assigned to different weights. Hence, the classical DEA allows the weight flexibility. Therefore, even if they are important, the inputs or outputs of some DMUs can be assigned zero (0) weights. Thus, these inputs or outputs are neglected in the evaluation. Also, some DMUs may be defined as efficient even if they are inefficient. This situation leads to unrealistic results. Also to eliminate the problem of weight flexibility, weight restrictions are made in DEA. In our study, we proposed a new model which has not been published in the literature. We describe it as the restricted data envelopment analysis ((ARIII(COR))) model with correlation coefficients. The aim for developing this new model, is to take into account the relations between variables using correlation coefficients. Also, these relations were added as constraints to the CCR and BCC models. For this purpose, the correlation coefficients were used in the restrictions of input–output each one alone and their combination together. Inputs and outputs are related to the degree of correlation between each other in the production. Previous studies did not take into account the relationship between inputs/outputs variables. So, only with expert opinions or an objective method, weight restrictions have been made. In our study, the weights for input and output variables were determined, according to the correlations between input and output variables. The proposed new method is different from other methods in the literature, because the efficiency scores were calculated at the level of correlations between the input and/or output variables.     

An electrochemical chiral sensor based on electrochemically modified electrode for the enantioselective discrimination of D-/L-tryptophan

Journal of Solid State Electrochemistry - Chirality is a universal characteristic of natural systems and discrimination of enantiomers of a chiral molecule plays a major role particularly in...