Sharif Digital Repository

The potentials of partial least squares regression (PLSR) and multivariate curve resolution alternating least squares (MCR-ALS) are evaluated for the simultaneous determination of diclofenac (DCF), naproxen (NAP), mefenamic acid (MEF) and carbamazepine (CBZ) as target analytes and gemfibrozil (GEM) as an interference in synthetic and real environmental samples. The analysis of first-order UV-Vis spectra is performed using PLSR with different variable selection methods, which include variable importance in projection (VIP), recursive weighted partial least squares (rPLS), regression coefficient (RV) and uninformative variable elimination (UVE), and using MCR-ALS with correlation constraint... 

In this work, a novel smartphone application entitled ". MVC app" is developed to perform different multivariate calibration methods. This app is designed for chemists who are not expert in programming or in advanced statistics. The developed application can use any Android-powered device as an environment for running. It is an easy to use app which can simply install in your smartphone and play. Different multivariate calibration methods, such as multiple linear regression (MLR), principal component regression (PCR) and partial least squares (PLS) are included in this app. As an instance, for performing PLS modeling, first calibration and validation data sets are imported (via USB or... 

In the present study, the profiling of 17 fatty acids (FAs) in avocado seed and pulp was investigated. The fatty acids were extracted with vortex-assisted extraction, methyl esterified and finally preconcentrated by dispersive liquid–liquid microextraction. The preconcentrated fatty acid methyl esters (FAMEs) were analyzed using gas chromatography–mass spectrometry (GC–MS) to obtain qualitative and quantitative information. The GC–MS data were analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) method to overcome general chromatographic problems such as overlapped peaks, background interference and peak shifts. The calibration data were prepared using pure... 

In the present research, ultrasonic-assisted emulsification-microextraction (USAEME) coupled with gas chromatography-mass spectrometry (GC-MS) has been proposed for analysis of thirteen environmental protection agency (EPA) polycyclic aromatic hydrocarbons (PAHs) in aqueous samples. Tetrachloroethylene was selected as extraction solvent. The main parameters of USAEME affecting the efficiency of the method were modeled and optimized using a central composite design (CCD). Under the optimum conditions (9 μL for extraction solvent, 1.15% (w/v) NaCl (salt concentration) and 10min for ultrasonication time), preconcentration factor (PF) of the PAHs was in the range of 500-950. In order to have a... 

Multivariate curve resolution-alternating least squares (MCR-ALS) as a second-order calibration algorithm was proposed for the simultaneous analysis of eighteen fatty acid methyl esters (FAMEs) in a standard mixture and pomegranate seed sample using vortex-assisted extraction-dispersive liquid-liquid microextraction (VAE-DLLME), followed by gas chromatography-mass spectrometry (GC-MS). The chemometric resolution, identification and quantification of the target FAMEs in the standard mixture and real sample (i.e., the pomegranate seed) were carried out successfully in the presence of some uncalibrated interferences. The lack of fit (LOF) and reverse match factor (RMF) were used for the... 

Chromatographic fingerprinting is an effective methodology for authentication and quality control of herbal products. In the presented study, a chemometric strategy based on multivariate curve resolution-alternating least squares (MCR-ALS) and multivariate pattern recognition methods was used to establish a gas chromatography-mass spectrometry (GC-MS) fingerprint of saffron. For this purpose, the volatile metabolites of 17 Iranian saffron samples, collected from different geographical regions, were determined using the combined method of ultrasound-assisted solvent extraction (UASE) and dispersive liquid-liquid microextraction (DLLME), coupled with GC-MS. The resolved elution profiles and... 

Dispersive liquid-liquid microextraction (DLLME) coupled with gas chromatography-mass spectrometry-selective ion monitoring (GC-MS-SIM) was applied to the determination of methyl tert-butyl ether (MTBE) in water samples. The effect of main parameters affecting the extraction efficiency was studied simultaneously. From selected parameters, volume of extraction solvent, volume of dispersive solvent, and salt concentration were optimized by means of experimental design. The statistical parameters of the derived model were R 2=0.9987 and F=17.83. The optimal conditions were 42.0μL for extraction solvent, 0.30mL for disperser solvent and 5% (w/v) for sodium chloride. The calibration linear range... 

In this study, multivariate classification techniques combined with proton nuclear magnetic resonance (1HNMR) spectroscopy is proposed to identify breast cancer biomarkers that can precisely distinguish between healthy control and breast cancer (BC) patients. In this regard, first optimizing the metabolite extraction procedure was performed using Box-Behnken design (BBD). Then, data-driven soft independent modeling of class analogy (DD-SIMCA) model and partial least squares-discriminant analysis (PLS-DA) were successfully utilized for separating healthy from BC patient's classes. On this matter, both DD-SIMCA and PLS-DA models could successfully distinguish the healthy class from the BC... 

Combination of fast high-performance liquid chromatography–diode array detection (HPLC–DAD) technique and ultrasonic assisted emulsification micro-extraction (USAEME) as extraction method are used for simultaneous determination of sixteen polycyclic aromatic hydrocarbons (PAHs) in river samples. The optimum conditions of USAEME procedure are selected according to the literature. Due to presence of different chromatographic issues and the complexity of water matrices, multivariate curve resolution-alternating least squares (MCR-ALS) is a good resolution technique for simultaneous quantification of PAHs in standard and real samples. On this matter, region-based and whole chromatographic data... 

S. lanata has been traditionally used as a medicinal plant due to its various biological activities such as antioxidant activity. Therefore, identification and quality control studies of this plant are of great importance. To this end, gas chromatography (GC) combined with chemometrics was proposed for fingerprint analysis of S. lanata samples. This study sought to classify GC fingerprints of twenty-eight S. lanata samples from eight different regions of Iran and more importantly, to correlate fingerprints to the antioxidant activity to select S. lanata volatile antioxidant markers. S. lanata samples were classified into five and three classes using partial least squares-discriminant... 

A multi-residue method using gas chromatography coupled with flame ionisation detector has been developed for simultaneous determination of 10 pesticides in milk. The methodology involved a sample clean-up procedure using ‘quick, easy, cheap, effective, rugged and safe’ followed by a preconcentration step based on dispersive liquid–liquid microextraction. In this regard, acetonitrile was added to the milk sample with specific pH and ionic strength, and the mixture was rigorously shaken. The extracts were centrifuged; then, the organic phase (acetonitrile) was transferred to a test tube and was mixed with deionised water. The mixture was sonicated and chloroform was added as an acceptor phase... 

In the present study, an analytical strategy was developed using reduced graphene oxide (rGO) as an effective sorbent in dispersive micro-solid phase extraction (DMSPE) for simultaneous determination of seven polycyclic aromatic hydrocarbons (PAHs) combined with gas chromatography (GC-FID). rGO was synthesized using modified Hummer's method and characterized using scanning electron microscope (SEM), atomic force microscope (AFM) and Raman spectroscopy. A rotatable central composite design (CCD) combined with multiple linear regression (MLR) and analysis of variance (ANOVA) was used for designing, modelling and optimization of the extraction procedure. In this regard, principal component... 

A multi-residue method using gas chromatography coupled with flame ionisation detector has been developed for simultaneous determination of 10 pesticides in milk. The methodology involved a sample clean-up procedure using ‘quick, easy, cheap, effective, rugged and safe’ followed by a preconcentration step based on dispersive liquid–liquid microextraction. In this regard, acetonitrile was added to the milk sample with specific pH and ionic strength, and the mixture was rigorously shaken. The extracts were centrifuged; then, the organic phase (acetonitrile) was transferred to a test tube and was mixed with deionised water. The mixture was sonicated and chloroform was added as an acceptor phase... 

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... 

There are, to date, few general answers to fundamental questions related to the interactions of nanoparticles (NPs) with living cells. Studies reported in the literature have delivered only limited principles about the nano-bio interface and thus the biological behavior of NPs is yet far from being completely understood. Combining computational tools with experimental approaches in this regard helps to precisely probe the nano-bio interface and allows the development of predictive and descriptive relationships between the structure and the activity of nanomaterials. In the present contribution, a nano-quantitative structure-activity relationship (nano-QSAR) model has been statistically... 

In the present contribution, a new approach based on mutual information (MI) is proposed for exploring the independence of feasible solutions in two component systems. Investigating how independent are different feasible solutions can be a way to bridge the gap between independent component analysis (ICA) and multivariate curve resolution (MCR) approaches and, to the best of our knowledge, has not been investigated before. For this purpose, different chromatographic and hyperspectral imaging (HSI) datasets were simulated, considering different noise levels and different degrees of overlap for two-component systems. Feasible solutions were then calculated by both grid search (GS) and... 

This work scrutinized the adulteration of pistachio butter with three potential edible oils using Fourier transform infrared spectroscopy (FT-IR) and multivariate classification methods. Each of the classes, including non-adulterated samples and adulterated samples consisting of pistachio butter mixed with various concentrations of peanut oil, corn oil and sunflower oil, were classified. For this purpose, multivariate methods, including soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA), were applied to classify the FTIR data. After evaluating the model on unknown samples, the results indicated that PLS-DA was better than the SIMCA... 

In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; however, few reports have been published on their properties and characteristics of analytical figures of merit. Currently, most performance measures for these types of networks only incorporate some function of prediction error. While useful, these measures are incomplete and cannot be used as an objective comparison among different models. In this report, a new method for calculating the sensitivity of any type of neural network is proposed and studied on both simulated and real... 

In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; however, few reports have been published on their properties and characteristics of analytical figures of merit. Currently, most performance measures for these types of networks only incorporate some function of prediction error. While useful, these measures are incomplete and cannot be used as an objective comparison among different models. In this report, a new method for calculating the sensitivity of any type of neural network is proposed and studied on both simulated and real... 

A new method for the evaluation of separation quality in hyphenated chromatographic measurements based on the information-theoretic concept of mutual information (MI) is developed. The MI values for the purest spectra selected using the simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) and orthogonal projection approach (OPA) methods are calculated according to the differential information entropy (Shannon entropy). To calculate the MI values for more than two variables, the Kozachenko-Leonenko (KL) estimation of the Shannon entropy is used. The MI values of the purest spectra can reliably reflect the degree of peak overlap in the chromatographic direction. Herein, the...