Electrochemical Characterization of Gold 6‐Amino‐2‐mercaptobenzothiazole Self‐Assembled Monolayer for Dopamine Detection in Pharmaceutical Samples

A new sensor, gold‐6‐amino‐2‐mercaptobenzothiazole (6A2MBT), was fabricated via a self‐assembly procedure. Electrochemical properties of the monolayer were investigated by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The modified electrode showed excellent antifouling property against the oxidation products of DA, allowed us to construct a dynamic calibration curve with two linear parts, 1.00×10^?6 to 3.72×10^?4 and 3.72×10^?4 to 6.42×10^?4 M DA, with correlation coefficients of 0.997 and 0.992 and a detection limit of 1.57×10^?7 M DA by using differential pulse voltammetry (DPV), respectively. Finally, the performance of the Au‐6A2MBT modified electrode was successfully tested for electrochemical detection of DA in a pharmaceutical sample.     

Synthesis of phosphonato esters involving heterocyclic biological bases in a highly diastereoselective and chemoselective route

Abstract  

Synthesis of five phosphonato esters has been accomplished via reaction between dimethyl acetylenedicarboxylate and triphenyl phosphite in the presence of biological compounds such as theophylline, 4-hydroxypyrimidine, 2H-3,1-benzoxazine-2,4(1H)-dione, 2-chloroaniline, or 3-nitroaniline at ambient temperature. The configuration of the compounds was determined on the basis of coupling constants emerging from the Karplus equation.     

Matrix analysis of nonlinear trusses using Prandtl-2 Neural Networks

A new method, based on the concepts of matrix analysis as well as the learning capabilities of neural networks, for the analysis of nonlinear trusses under dynamic loading is presented. The method can be applied to static trusses too. While there have been attempts in the past to use neural networks to identify and model different structures based on data measured on structural response directly, the main feature and advantage of this new method is in its capability to model a nonlinear truss by assembling the data collected on the response of its members. The basics of the method are: (1) for each truss member, a neural network is trained to learn and simulate its load-response behavior, (2) the member neural networks are then assembled to build another neural network which can simulate the load-response behavior of the whole truss. Noticing test at member level is generally easier than at structure level, this can make the building of a neural network to simulate the response of the truss more affordable. Also this has potential application when it is hard to find a mathematical model from experimental data to describe the internal force vector for a truss, as well as identification and control of trusses where precise modeling of the structure is a key point to the success of the application. Prandtl Neural Network, developed recently by the authors for modeling of nonlinear hysteretic materials, has been improved and used in this study too. The improved version has been called Prandtl-2 Neural Network (PNN2) in this paper. The method has been applied to the static and dynamic analysis of a 3-bar and a 10-bar benchmark truss successfully, the results of which are reported in this paper.     

Fabrication, characterization, and measurement of viscosity of α-Fe2O3-glycerol nanofluids

Magnetic nanofluids, ferrofluids, are a special category of smart nanomaterials, consisting of stable dispersion of magnetic nanoparticles in different fluids. In this study, magnetic nanoparticles of hematite, α-Fe₂O₃, were prepared by solvothermal method using Fe(NO₃)₃ as a starting material. The nanoparticles were characterized by X-ray diffraction (XRD) and transmission electronic microscope (TEM).To the best of our knowledge, this is the first research on the rheological properties of nanofluids of α-Fe₂O₃ nanoparticles and glycerol. The experimental results showed that the viscosity of α-Fe₂O₃-glycerol nanofluids increases with increasing the particle volume fraction and decreases with increasing temperature. Our results clearly showed that the α-Fe₂O₃-glycerol nanofluids are non-Newtonian shear-thinning and their shear viscosity depends strongly on temperature. The experimental data were compared with some theoretical models. The measured values of the effective viscosity of nanofluids are underestimated by the theoretical models.     

Note on new solutions of LR fuzzy linear systems using ranking functions and ABS algorithms

Recently, Ghanbari and Mahdavi-Amiri focused on solving LR fuzzy linear systems by use of ranking functions. They applied a ranking function introduced by Cheng, which is based on the centroid point, to illustrate their method. Also, they presented an important lemma using the centroid formulae provided by Cheng, to determine the centroid point for a class of fuzzy numbers. Unfortunately, they didn’t consider that the formulae are incorrect and have led to some misapplications as pointed out by Wang and his colleagues. Therefore, in this paper, we first show that Lemma 19 of Ghanbari and Mahdavi-Amiri’s paper is not true and then correct it using the centroid formulae suggested by Wang. Finally, we correct the results obtained in Ghanbari and Mahdavi-Amiri’s paper for a special example.     

An experimental investigation of creaming phenomenon using a novel optical method: A case study of mineral oil-in-water emulsion

The present study elucidates the creaming phenomenon of mineral oil-in-water macroemulsion using a new noninvasive method based on turbidimetry. Additionally, microscopic observation of the phenomenon is carried out to derive an in-depth understanding of the mechanisms. Accumulation of the particles in the emulsions under the formed cream is monitored during a relatively prolonged period of time. Backflow of continuous and dispersed phases in temporary channels is observed at the proximity of the cream. In addition to the backflow, a high traffic density of the dispersed particles and deflocculation of the cream are the main reasons for the accumulation of the dispersed phase particles and a temporary stability against creaming. The deflocculation hinders cream growth and increases the stratification of the cream. A low concentration zone of the dispersed phase with the width of ～100?µm is observed under the cream.     

The first report on the catalytic oxidation of urazoles to their corresponding triazolinediones via in situ catalytic generation of Br using periodic acid or oxone/KBr system

A combination of periodic acid or oxone^® and a catalytic amount of KBr in the presence of few drops of water, were used for the catalytic oxidation of urazoles and bis-urazoles to their corresponding triazolinediones under mild and heterogeneous conditions with moderate to excellent yields.     

Distance-regular Cayley graphs with least eigenvalue $$$$

We classify the distance-regular Cayley graphs with least eigenvalue \(-2\) and diameter at most three. Besides sporadic examples, these comprise of the lattice graphs, certain triangular graphs, and line graphs of incidence graphs of certain projective planes. In addition, we classify the possible connection sets for the lattice graphs and obtain some results on the structure of distance-regular Cayley line graphs of incidence graphs of generalized polygons.     

Resource allocation based on cost efficiency

In this paper, we consider a resource allocation (RA) problem and develop an approach based on cost (overall) efficiency. The aim is to allocate some inputs among decision making units (DMUs) in such way that their cost efficiencies improve or stay unchanged after RA. We formulate a multi-objective linear programming problem using two different strategies. First, we propose an RA model which keeps the cost efficiencies of units unchanged. This is done assuming fixed technical and allocative efficiencies. The approach is based on the assumption that the decision maker (DM) may not have big changes in the structure of DMUs within a short term. The second strategy does not impose any restrictions on technical and allocative efficiencies. It guarantees that none of the cost efficiencies of DMUs get worse after RA, and the improvement for units is possible if it is feasible and beneficial. Two numerical examples and an empirical illustration are also provided.