Determination of phenolic profile and antioxidant activity of pistachio hull using high-performance liquid chromatography–diode array detector–electro-spray ionization–mass spectrometry as affected by ultrasound and microwave

The phytochemicals content and radical scavenging activity of pistachio (Pistacia vera L.) hull extract obtained by different solvents (water, ethanol, and butanol) were measured and compared. Water was selected as superior solvent. Ultrasound-assisted aqueous extraction of the hull by power ultrasound (35 kHz) was more efficient in ascending the phytochemicals content than the sonochemical ultrasonication (130 kHz). High-performance liquid chromatography-mass spectrometry showed increased amounts of vanillic acid, p-coumaric acid, naringenin, and catechin in ultrasound-assisted extracts. Post-extraction sonication declined significantly the phenolics amount and antioxidant property of the aqueous extract. Microwave-assisted extraction increased the phenolics and flavonoids content at extract in a power-dependent trend.     

Optimal control problem via neural networks

This paper attempts to propose a new method based on capabilities of artificial neural networks, in function approximation, to attain the solution of optimal control problems. To do so, we try to approximate the solution of Hamiltonian conditions based on the Pontryagin minimum principle (PMP). For this purpose, we introduce an error function that contains all PMP conditions. In the proposed error function, we used trial solutions for the trajectory function, control function and the Lagrange multipliers. These trial solutions are constructed by using neurons. Then, we minimize the error function that contains just the weights of the trial solutions. Substituting the optimal values of the weights in the trial solutions, we obtain the optimal trajectory function, optimal control function and the optimal Lagrange multipliers.     

Numerical simulation of heat transfer and fluid flow of molten metal in MMA–St copolymer lost foam casting process

In this study, a computational fluid dynamics (CFD) code was developed to calculate the filling pattern using volume of fluid (VOF) algorithm with donor–acceptor method for free surface simulation. This algorithm has been modified to include the pressure of the gas produced from foam degradation. For this purpose a heat transfer model and 2D foam degradation model were developed. In heat transfer model, radiation and conduction between foam and molten metal; and convection between gas and molten metal were considered. In order to evaluate the results of simulation, a bench scale casting apparatus was assembled and the casting was conducted in a transparent mold. The effect of several parameters such as coating thickness, foam density and vacuum level on the gap temperature, gap pressure and filling speed was studied with the developed software. It was found that the simulated results are in good agreement with experimental results.     

An Aqueous Phase Equilibrium Calculation Algorithm

A multiphase chemical equilibrium algorithm is developed which can be used with aqueous systems. The algorithm uses an average chemical potential for each species as a reference chemical potential. Incipient phases can be identified and their proximity to appearance can be determined through their tangent plane distance. Illustrative examples include the calculation of CaSO₄ solubility and the calculation of vapour pressures above an SO₂‐NaCl‐H₂O system, including the prediction of a three‐phase equilibrium. The algorithm proved robust and versatile. The appearance of incipient phases was easily tracked. Future work needs to be done to optimize damping/acceleration coefficients in the calculations.     

Synthesis and Analysis of Triphenylamine: A Review

In this paper, synthesis and characteristic of arylamine‐type molecules, particularly triphenylamine are discussed. An overview of the physical properties and chemical characteristics of these types of molecules is provided. Different synthesis methods and mechanisms involved for the production of these molecules and their analysis by HPLC are presented. Finally, a brief note about their purification is presented.     

A comparative study using direct hydrothermal and indirect fusion methods to produce zeolites from coal fly ash utilizing single-mode microwave energy

This paper investigates the effects of microwave irradiation on the synthesis of zeolite Na-A from coal fly ash at atmospheric pressure. Microwave irradiation has shown to accelerate zeolitization from several hours to several minutes. A single-mode laboratory-scale microwave was employed, which enabled control of irradiated power and temperature of the reaction mixture, while the pressure was controlled by affixing a condenser on the 40 mL Teflon reactor vessel with a working volume 20 mL. Design of Experiment was used to compare two methods of converting CFA to zeolite-A, direct hydrothermal method and indirect fusion method. Experiments conducted were two level four factorial designs. The first factor considered was the categorical factor of conversion method (hydrothermal vs fusion), while the other three factors investigated were power (P), time (θ), and aluminate concentration (δ). Zeolite produced from CFA (CFAZA) was characterized using XRD, FTIR, SEM, TGA, BET, and cation exchange capacity. It was observed that the crystallinity of the product was influenced by factors such as, conversion method, power, time, and aluminate concentration. The hydrothermal and fusion products were comparable to each other in their characteristics, however, hydrothermal CFAZA performed better at immobilizing heavy metal ions and showed better crystalline structure, whereas fusion CFAZA had a higher BET surface area and a slightly higher CEC. Regardless of the performance of the categorical factors the other factors, i.e., power, time, and aluminate concentration followed the same trend for both types of CFAZA.     

Quantitative determination of physical and chemical measurands in honey by near-infrared spectrometry

Fourier transform near-infrared spectroscopy (FT-NIR) was evaluated to quantitatively determine 24 different measurands in honey. The reference values of 421 honey samples of different botanical origins were determined by classical physical and chemical methods. Partial least squares regression was used to develop the calibration models for the measurands studied. These calibrations were then validated using independent samples and proved satisfying accuracies for the determination of water (standard error of prediction: 0.3 g/100 g), glucose (1.3 g/100 g), fructose (1.6 g/100 g), sucrose (0.4 g/100 g), total monosaccharide content (2.6 g/100 g) as well as fructose/glucose ratio (0.09) and glucose/water ratio (0.12). The prediction accuracy for hydroxymethylfurfural, proline, pH-value, electrical conductivity, free acidity and the minor sugars maltose, turanose, nigerose, erlose, trehalose, isomaltose, kojibiose, melezitose, raffinose, gentiobiose, melibiose, maltotriose was poor and unreliable. The results demonstrate that near-infrared spectrometry is a valuable, rapid and non-destructive tool for the quantitative analysis of some measurands related to the main components in honey.     

How many subjects to screen? A practical procedure for estimating multivariate normal probabilities for correlated variables.

Suggests a practical procedure for estimating the number of Ss that need to be screened to obtain a sample of fixed size that meets multiple correlated criteria. The procedure is based on the fact that least squares regression provides a good quadratic fit for Monte Carlo estimates of multivariate probabilities when they are plotted as a function of mean pairwise correlations (r) for the criterion variables. The equations given here can be used to predict selected 3- to 5-variable joint probabilities with reasonable accuracy as long as pairwise correlations for the selection criteria range from .10 to .90. (PsycINFO Database Record (c) 2010 APA, all rights reserved)