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.     

Analysis of the structures,energetics, and vibrational frequencies for the hydrogen-bonded interaction of nucleic acid bases with Carmustine pharmaceutical agent: a detailed computational approach

In the present study, it is attempted to scrutinize the hydrogen bonding interaction between Carmustine drug and DNA pyrimidine bases by means of density functional theory calculations regarding their geometries, binding energies, vibrational frequencies, and topological features of the electron density in the gas phase and the water solution. Based on the density functional theory results, it is found that the process of intermolecular interaction between Carmustine drug and nucleobases is exothermic and all of the optimized configurations are stable. Furthermore, the negative stability energy represented by a polarizable continuum model shows the significant increase in the solubility of the nucleobase after hydrogen bonding intermolecular interaction in the presence of water solvent. It is also found that the intermolecular hydrogen bonds between drug and the nucleobases play the significant role in the stability of the physisorption configurations. Hydrogen bond energies for hydrogen-bonded complexes are obtained from Espinosa method and the atoms-in-molecules theory are also applied to get a more precise insight into the nature of the intermolecular hydrogen bond interactions.     

Sensitivity analysis on the priority of the objective functions in lexicographic multiple objective linear programs

This paper deals with a class of multiple objective linear programs (MOLP) called lexicographic multiple objective linear programs (LMOLP). In this paper, by providing an efficient algorithm which employs the preceding computations as well, it is shown how we can solve the LMOLP problem if the priority of the objective functions is changed. In fact, the proposed algorithm is a kind of sensitivity analysis on the priority of the objective functions in the LMOLP problems.     

A fuzzy shortest path with the highest reliability

This paper concentrates on a shortest path problem on a network where arc lengths (costs) are not deterministic numbers, but imprecise ones. Here, costs of the shortest path problem are fuzzy intervals with increasing membership functions, whereas the membership function of the total cost of the shortest path is a fuzzy interval with a decreasing linear membership function. By the max–min criterion suggested in [R.E. Bellman, L.A. Zade, Decision-making in a fuzzy environment, Management Science 17B (1970) 141–164], the fuzzy shortest path problem can be treated as a mixed integer nonlinear programming problem. We show that this problem can be simplified into a bi-level programming problem that is very solvable. Here, we propose an efficient algorithm, based on the parametric shortest path problem for solving the bi-level programming problem. An illustrative example is given to demonstrate our proposed algorithm.     

Development of a new microextraction method based on a dynamic single drop in a narrow-bore tube: application in extraction and preconcentration of some organic pollutants in well water and grape juice samples

A novel sample preparation technique, the microextraction method based on a dynamic single drop in a narrow-bore tube, coupled with gas chromatography-flame ionization detection (GC-FID) is presented in this paper. The most important features of this method are simplicity and high enrichment factors. In this method, a microdrop of an extraction solvent assisted by an air bubble was repeatedly passed through a narrow-bore closed end tube containing aqueous sample. It has been successfully used for the analysis of some pesticides as model analytes in aqueous samples. Parameters affecting the method's performance such as selection of extraction solvent type and volume, number of extractions, volume of aqueous sample (tube length), and salt effect were studied and optimized. Under the optimal conditions, the enrichment factors (EFs) for triazole pesticides were in the range of 141-214 and the limits of detection (LODs) were between 2 and 112 μg L⁻¹. The relative standard deviations (C = 1000 μg L⁻¹, n = 6) were obtained in the range of 2.9-4.5%. The recoveries obtained for the spiked well water and grape juice samples were between 71 and 106%. Low cost, relatively short sample preparation time and less solvent consumption are other advantages of the proposed method.     

Development of a new dispersive liquid–liquid microextraction method in a narrow-bore tube for preconcentration of triazole pesticides from aqueous samples

In the present work a new, simple, rapid and environmentally friendly dispersive liquid–liquid microextraction (DLLME) method has been developed for extraction/preconcentration of some triazole pesticides in aqueous samples and in grape juice. The extract was analyzed with gas chromatography–flame ionization detection (GC–FID) or gas chromatography–mass spectrometry (GC–MS). The DLLME method was performed in a narrow-bore tube containing aqueous sample. Acetonitrile and a mixture of n-hexanol and n-hexane (75:25, v/v) were used as disperser and extraction solvents, respectively. The effect of several factors that influence performance of the method, including the chemical nature and volume of the disperser and extraction solvents, number of extraction, pH and salt addition, were investigated and optimized. Figures of merit such as linearity (r² > 0.995), enrichment factors (EFs) (263–380), limits of detection (0.3–5 μg L^?1) and quantification (0.9–16.7 μg L^?1), and relative standard deviations (3.2–5%) of the proposed method were satisfactory for determination of the model analytes. The method was successfully applied for determination of target pesticides in grape juice and good recoveries (74–99%) were achieved for spiked samples. As compared with the conventional DLLME, the proposed DLLME method showed higher EFs and less environmental hazards with no need for centrifuging.     

Solid‐based disperser liquid–liquid microextraction for the preconcentration of phthalate esters and di‐(2‐ethylhexyl) adipate followed by gas chromatography with flame ionization detection or mass spectrometry

A new approach for the development of a dispersive liquid–liquid microextraction followed by GC with flame ionization detection was proposed for the determination of phthalate esters and di‐(2‐ethylhexyl) adipate in aqueous samples. In the proposed method, solid and liquid phases were used as the disperser and extractant, respectively, providing a simple and fast mode for the extraction of the analytes into a small volume of an organic solvent. In this method, microliter levels of an extraction solvent was added onto a sugar cube and it was transferred into the aqueous phase containing the analytes. By manual shaking, the sugar was dissolved and the extractant was released into the aqueous phase as very tiny droplets to provide a cloudy solution. Under optimized conditions, the proposed method showed good precision (RSD less than 5.2%), high enrichment factors (266–556), and low LODs (0.09–0.25 μg/L). The method was successfully applied for the determination of the target analytes in different samples, and good recoveries (71–103%) were achieved for the spiked samples. No need for a disperser solvent and higher enrichment factors compared with conventional dispersive liquid–liquid microextraction and low cost and short sample preparation time are other advantages of the method.     

Multi-objective optimization problems with Fuzzy relation equation constraints regarding max-average composition

A multiple objective optimization model subject to a system of fuzzy relation equations with max-average composition and a reduction procedure in order to reduce problem dimension are presented. Furthermore, a genetic algorithm is reviewed and some of its components are modified to solve the problem. Finally, the algorithm is performed on different problems and its major components role in detecting the solution is examined.