Determining co-combustion characteristics,kinetics and synergy behaviors of raw and torrefied forms of two distinct types of biomass and their blends with lignite

Journal of Thermal Analysis and Calorimetry - In this study, the combustion characteristics and kinetics of various mixtures of both raw and torrefied rose pulp and red pine sawdust with each other...     

Artificial intelligence–based models for the qualitative and quantitative prediction of a phytochemical compound using HPLC method

Isoquercitrin is a flavonoid chemical compound that can be extracted from different plant species such as Mangifera indica (mango), Rheum nobile , Annona squamosal , Camellia sinensis (tea), and coriander ( Coriandrum sativum L.). It possesses various biological activities such as the prevention of thromboembolism and has anticancer, antiinflammatory, and antifatigue activities. Therefore, there is a critical need to elucidate and predict the qualitative and quantitative properties of this phytochemical compound using the high performance liquid chromatography (HPLC) technique. In this paper, three different nonlinear models including artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machine (SVM),in addition to a classical linear model [multilinear regression analysis (MLR)], were used for the prediction of the retention time (tR) and peak area (PA) for isoquercitrin using HPLC. The simulation uses concentration of the standard, composition of the mobile phases (MP-A and MP-B), and pH as the corresponding input variables. The performance efficiency of the models was evaluated using relative mean square error (RMSE), mean square error (MSE), determination coefficient (DC), and correlation coefficient (CC). The obtained results demonstrated that all four models are capable of predicting the qualitative and quantitative properties of the bioactive compound. A predictive comparison of the models showed that M3 had the highest prediction accuracy among the three models. Further evaluation of the results showed that ANFIS–M3 outperformed the other models and serves as the best model for the prediction of PA. On the other hand, ANN–M3proved its merit and emerged as the best model for tR simulation. The overall predictive accuracy of the best models showed them to be reliable tools for both qualitative and quantitative determination.     

Estimate of the crystallization factor of epitaxial layers of semiconducting solid solutions

An estimate of the layer thickness of multicomponent solid solutions grown by the liquid-phase epitaxy (LPE) method can be obtained simply by using magnitudes of the crystallization factor. Values of the crystallization factor were computed for the system GaInPAs/InP by numerical methods for different compositions and the temperature range 873–973 K. Epitaxial layers of GaInPAs were grown by the method of cooling a preliminarily supercooled melt for an experimental verification of the computation. Results of the computation are sufficiently close to experimental and literature data, except for the domain of spinodal dissociation at low temperatures.Translated from Izvestiya Vysshikh Uchenbykh Zavedenii, Fizika, No. 9, pp. 77–80, September, 1988.     

A note on “A mixed integer programming model for advanced planning and scheduling (APS)”

In a recent paper, Chen and Ji [Chen, K., Ji, P., 2007. A mixed integer programming model for advanced planning and scheduling (APS). European Journal of Operational Research 181, 515–522] develop a mixed integer programming model for advanced planning and scheduling problem that considers capacity constraints and precedence relations between the operations. The orders require processing of several operations on eligible machines. The model presented in the above paper works for the case where each operation can be processed on only one machine. However, machine eligibility means that only a subset of machines are capable of processing a job and this subset may include more than one machine. We provide a general model for advanced planning and scheduling problems with machine eligibility. Our model can be used for problems where there are alternative machines that an operation can be assigned to.     

Chink antenna in the long line approximation

We give proofs for the sinusoidal nature of the current distribution over an insulated chink antenna with allowance for finite dimensions of the antenna, its feeder region, and the layer of environmental inhomogeneity. The problem of tuning of a chink antenna to resonance is considered in detail, and the possibility of detecting the inhomogeneity of the ambient medium by the antenna detuning is shown. Institute of Atomic Energy, Obninsk, Kaluga region, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 40, No. 4, pp. 432–440, April, 1997.     

Insulated antenna in a layered medium

The article presents a generalization of the integral equation of an insulated linear antenna immersed in a cylindrically layered lossy dielectric medium. The insulation is provided by a lossless dielectric layer. The kernel of the integral equation is represented as a superposition of the fundamental solutions of the wave equation with equivalent propagation constants for the given media. A generalization to a plane-layered medium is proposed. The problem of a vertical radiator above a layered half-space is considered. Translated from Chislennye Metody v Matematicheskoi Fiziki, Published by Moscow University, Moscow, 1996, pp. 80–88.