Sharif Digital Repository

The quantities of residues of some triazines such as prometon, propazine, atrazine and simazine in complex matrices of apple samples were determined, using gas chromatography-selected ion mass (GC-SIM) spectrometry. Generalized rank annihilation method (GRAM) as a second-order calibration technique was used for screening, resolving and finally determining the amounts of the residues. Before the GRAM analysis, different steps of data preprocessing such as background correction, de-skewing and standardization for rank alignment was used for every target analyte. The de-skewing and rank alignment algorithms were used for bilinearity and trilinearity corrections, respectively. The two data... 

Characterization and determination of a complex mixture of fatty acid methyl esters was performed for commercial fish oil using two-dimensional GC-MS data coupled with resolution techniques. Various principle component analysis methods such as significant factor analysis and fixed size moving window evolving factor analysis were used for the number of factors, zero concentration and selective regions. Then, the convoluted chromatograms were resolved into pure chromatograms and mass spectra using heuristic evolving latent projections (HELP) method. Fatty acids of C16:1ω7, C18:4ω3, C18:1ω11, C18:1ω9, C18:0, C20:2ω6, C20:1ω9, C 22:1ω11, C22:1ω9 and C24:1ω9 were resolved and identified by using... 

Quantitative structure-activity relationship (QSAR) approach was carried out for the prediction of inhibitory activity of some novel quinazolinone derivatives on serotonin (5-HT7) using modified ant colony (ACO) method and adaptive neuro-fuzzy interference system (ANFIS) combined with shuffling cross-validation technique. A modified ACO algorithm is utilized to select the most important variables in QSAR modeling and then these variables were used as inputs of ANFIS to predict 5-HT7 receptor binding activities of quinazolinone derivatives. The best descriptors describing the inhibition mechanism are Qmax, Se, Hy, PJI3 and DELS which are among electronic, constitutional, geometric and... 

Quantitative Structure - Activity Relationship (QSAR) models for the inhibition action of some 1-phenylbenzimidazoles on platelet-derived growth are constructed using Genetic Algorithm and Artificial Neural Network (GA-ANN) method. The statistical parameters of R2 and root-mean-square error are 0.82 and 0.21, respectively using this method. These parameters show a considerable improvement compared to the stepwise multiple linear regression combined with ANN (stepwise MLR-ANN). Ten-fold shuffling crossvalidations are carried out to select the most important descriptors. Five descriptors of index of Balaban (J), average molecular weight (AMW), 3D-Wiener index (W3D), mean atomic van der Waals... 

The main aim of the present work was the development of a quantitative structure-activity relationship method using an artificial neural network (ANN) for predicting the thermal conductivity detector response factor. As a first step a multiple linear regression (MLR) model was developed and the descriptors appearing in this model were considered as inputs for the ANN. The descriptors of molecular mass, number of vibrational modes of the molecule, molecular surface area and Balaban index appeared in the MLR model. In agreement with the molecular diameter approach, molecular mass and molecular surface area play a major role in estimating the thermal conductivity detector response factor... 

A quantitative structure-property relationship study based on multiple linear regression (MLR) and artificial neural network (ANN) techniques was carried out to investigate the retention behavior of some terpenes on the polar stationary phase (Carbowax 20 M). A collection of 53 noncyclic and monocyclic terpenes was chosen as data set that was randomly divided into two groups, a training set and a prediction set consist of 41 and 12 molecules, respectively. A total of six descriptors appearing in the MLR model consist of one electronic, two geometric, two topological and one physicochemical descriptors. Except for the geometric parameters the remaining descriptors have a pronounced effect on... 

This chapter covers a part of the spectrum of neural-network uses in analytical chemistry. Different architectures of neural networks are described briefly. The chapter focuses on the development of three-layer artificial neural network for modeling the anti-HIV activity of the HETP derivatives and activity parameters (pIC 50) of heparanase inhibitors. The use of a genetic algorithm-kernel partial least squares algorithm combined with an artificial neural network (GA-KPLS-ANN) is described for predicting the activities of a series of aromatic sulfonamides. The retention behavior of terpenes and volatile organic compounds and predicting the response surface of different detection systems are... 

The critical micelle concentration (CMC) of a set of 58 alkylsulfates, alkylsulfonates, alkyltrimethyl ammonium and alkylpyridinium salts were predicted using an artificial neural network (ANN). The multiple linear regression (MLR) technique was used to select the important descriptors that act as inputs for artificial neural network. These descriptors are Balaban index, heat of formation, maximum distance between the atoms in the molecule, Randic index and volume of the molecule. Designed artificial neural network is a fully connected back-propagation network that has a 5-5-1 architecture. The results obtained using neural network were compared with those obtained using MLR technique.... 

The wave functions for calculating gas phase 1H chemical shifts of primary and secondary alcohols have been optimized using factorial design as multivariate technique. Gas-phase experimental 1H chemical shifts of 18 alcohols were used to establish the best levels of theory for obtaining 1H chemical shift, among them the new experimental values of 1H chemical shifts of 10 alcohols were obtained in our laboratory. HF/6-31G(d,p) wave function is proposed as the best level of theory for calculating 1H chemical shifts of primary alcohols. For secondary alcohols, ONIOM(B3LYP/6-31G(d,p): HF/6-31G(d,p)) are recommended. An additional series of primary and secondary alcohols were used as test sets... 

The wave functions for calculating gas-phase 13C nuclear magnetic shielding constants of 22 molecules have been optimally selected using factorial design as a multivariate technique. GIAO and CSGT methods were used for computation of shielding constants. Different wave functions for different types of carbons were recommended. A wave function as the best level of the theory is proposed for almost similar carbons. ONIOM approach for molecules with different types of carbons is applied. The results of GIAO method using the proposed wave function are in very good agreement with the experimental values. An additional series (21 carbons) were used as test sets and their results confirmed the... 

In the present work a central composite design based on response surface methodology (RSM) is employed for fine tuning of the aspect ratios of seed-mediated synthesized gold nanorods (GNRs). The relations between the affecting parameters, including ratio of l-ascorbic acid to Au3+ ions, concentrations of silver nitrate, CTAB, and CTAB-capped gold seeds, were explored using a RSM model. It is observed that the effect of each parameter on the aspect ratio of developing nanorods highly depends on the value of the other parameters. The concentrations of silver ions, ascorbic acid and seeds are found to have a high contribution in controlling the aspect ratios of NRs. The optimized parameters led... 

The wave functions for calculating gas phase 19F chemical shifts were optimally selected using the factorial design as a multivariate technique. The effects of electron correlation, triple-ξ valance shell, diffuse function, and polarization function on calculated 19F chemical shifts were discussed. It is shown that of the four factors, electron correlation and the polarization functions affect the results significantly. B3LYP/6-31 + G(df,p) wave functions have been proposed as the best and the most efficient level of theory for calculating 19F chemical shifts. An additional series of fluoro compounds were used as a test set and their predicted 19F chemical shifts values confirmed the... 

A 1H-NMR procedure based on an analysis of its data by a multivariate calibration method was conducted for the simultaneous determination of theophylline and caffeine in synthetic and real samples. Partial least squares regression (PLS) was chosen as the calibration method. The methyl signals of theophilline at 3.36 and 3.54 ppm that overlapped with those of caffeine were significant characteristics which were employed in this study for their analyses. The proposed method was successfully applied to recovery studies of theophylline and caffeine from real tablet samples  

This paper reviews the applications of experimental design to optimize some analytical chemistry techniques such as extraction, chromatography separation, capillary electrophoresis, spectroscopy, and electroanalytical methods  

This paper reviews the main concepts of experimental design applicable to the optimization of analytical chemistry techniques. The critical steps and tools for screening, including Plackett-Burman, factorial and fractional factorial designs, and response surface methodology such as central composite, Box-Behnken, and Doehlert designs, are discussed. Some useful routines are also presented for performing the procedures  

Multivariate curve resolution-particle swarm optimization (MCR-PSO) algorithm is proposed to exploit pure chromatographic and spectroscopic information from multi-component hyphenated chromatographic signals. This new MCR method is based on rotation of mathematically unique PCA solutions into the chemically meaningful MCR solutions. To obtain a proper rotation matrix, an objective function based on non-fulfillment of constraints is defined and is optimized using particle swarm optimization (PSO) algorithm. Initial values of rotation matrix are calculated using local rank analysis and heuristic evolving latent projection (HELP) method. The ability of MCR-PSO in resolving the chromatographic... 

A linear and non-linear quantitative structure-activity relationship (QSAR) study is presented for modeling and predicting heparanase inhibitors' activity. A data set that consisted of 92 derivatives of 2,3-dihydro-1,3-dioxo-1H-isoindole-5-carboxylic acid, furanyl-1,3-thiazol-2-yl and benzoxazol-5-yl acetic acids is used in this study. Among a large number of descriptors, four parameters classified as physico-chemical, topological and electronic indices are chosen using stepwise multiple regression technique. The artificial neural networks (ANNs) model shows superiority over the multiple linear regressions (MLR) by accounting 87.9% of the variances of antiviral potency of the heparanase... 

Essential oils (EOs) are valuable natural products that are popular nowadays in the world due to their effects on the health conditions of human beings and their role in preventing and curing diseases. In addition, EOs have a broad range of applications in foods, perfumes, cosmetics and human nutrition. Among different techniques for analysis of EOs, gas chromatography-mass spectrometry (GC-MS) is the most important one in recent years. However, there are some fundamental problems in GC-MS analysis including baseline drift, spectral background, noise, low S/N (signal to noise) ratio, changes in the peak shapes and co-elution. Multivariate curve resolution (MCR) approaches cope with ongoing... 

Multivariate curve resolution based on the minimization of an objective function (MCR-FMIN) defined directly from the non-fulfillment of constraints was applied for the first time as a deconvolution method to separate co-eluted gas chromatographic-mass spectrometric (GC-MS) signals. Simulated and real (standard real mixture and limon oil) GC-MS data were used to evaluate the feasibility of this method. The MCR-FMIN solutions have been obtained based on the rotation of principal component analysis (PCA) solutions using the non-linear optimization algorithms. Calculation of the initial values of R rotation matrix using model free analysis methods such as fixed-size moving window-evolving...