Sharif Digital Repository

In this study, a multivariate-based strategy was developed for simultaneous determination of thirteen carcinogenic polycyclic aromatic hydrocarbons (PAHs) in water samples using gold nanoparticles (AuNPs) as solid-phase extraction (SPE) sorbent combined with gas chromatography (GC). The extraction technique is based on the strong affinity between citrate-capped AuNPs and PAHs. Furthermore, characterization of AuNPs was performed by UV-vis spectroscopy and transmission electron microscopy (TEM) techniques. A rotatable central composite design (CCD) combined with multiple linear regression (MLR) was used for designing the extraction procedure and developing models using the GC peak areas of 13... 

Conventional models of cardiovascular system frequently lack required detail and focus primarily on the overall relationship between pressure, flow and volume. This study proposes a localized and regional model of the cardiovascular system. It utilizes noninvasive blood flow and pressure seed data and temporal cardiac muscle regional activity to predict the operation of the heart under normal and congestive heart failure conditions. The analysis considers specific regions of the heart, namely, base, mid and apex of left ventricle. The proposed method of parameter estimation for hydraulic electric analogy model is recursive least squares algorithm. Based on simulation results and comparison... 

Conventional models of cardiovascular system (CV) frequently lack required detail. Once utilized to study the heart function, these models focus primarily on the overall relationship between pressure, flow and volume. This study proposes a localized and regional model of the CV system. It utilizes non-invasive blood flow and pressure seed data and temporal cardiac muscle regional activation to predict the operation of the heart. Proposed localized analysis considers specific regions of the heart, namely base, mid and apex sections of the left ventricle. This modular system is based on a hydraulic electric analogy model, estimating desired parameters, namely resistance (R), compliance (C),... 

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective... 

Node localization is of paramount importance to different wireless sensor network (WSN) applications. This paper investigates the received signal strength (RSS) based localization problem with unknown path-loss model parameters. Most works in RSS localization assume the transmit power and path-loss exponent (PLE) are known that is not a realistic assumption in some cases. However this paper, assumes the transmit power and the PLE are both unknown and a novel algorithm for sensor location is proposed. The algorithm is based on the generalized total least-squares (GTLS) method and gives an explicit solution for the localization problem. The performance of the proposed method is compared with... 

In this paper, a sensitivity-based finite element (FE) model updating method using singular value decomposition (SVD) of frequency response function (FRF) is introduced. An exact sensitivity equation is proposed by incorporating measured responses of a damaged structure in the mathematical formulations. A set of incompletely measured natural frequencies of a damaged structure and mode shapes of the intact structure are used to deal with incomplete measurement without the implementation of FE model reduction or data expansion algorithms. The insights provided from the variation of SVD of transfer functions are used for the selection of proper updating frequency ranges. The appropriate... 

Young’s modulus (E) is one of the most important parameters in the mechanical properties of solid materials. Young’s modulus is proportional to the stress and strain values. There are several experimental and theoretical methods for gaining Young’s modulus values, such as stress–strain curves in compression and tensile tests, electromagnetic-acoustic resonance, ultrasonic pulse echo and density functional theory (DFT) in different basis sets. Apparently, preparing specimens for measuring Young’s modulus through the experimental methods is not convenient and it is time-consuming. In addition, for calculating Young’s modulus values by software, presumptions of data and structures are needed.... 

This study describes spectrometric monitored kinetic processes to determine the size of citrate-capped Au nanoparticles (Au NPs) based on aggregation induced by L-cysteine (L-Cys) as a molecular linker. The Au NPs association process is thoroughly dependent on pH, concentration and size of nanoparticles. Size dependency of aggregation inspirits to determine the average diameters of Au NPs. For this aim the procedure is achieved in aqueous medium at pH 7 (phosphate buffer), and multivariate data including kinetic spectra of Au NPs are collected during aggregation process. Subsequently partial least squares (PLS) modeling is carried out analyzing the obtained data. The model is built on the... 

The present study aims to estimate nitrogen (N) content in tomato (Solanum lycopersicum L.) plant leaves using optimal hyperspectral imaging data by means of computational intelligence [artificial neural networks and the differential evolution algorithm (ANN-DE), partial least squares regression (PLSR), and convolutional neural network (CNN) regression] to detect potential plant stress to nutrients at early stages. First, pots containing control and treated tomato plants were prepared; three treatments (categories or classes) consisted in the application of an overdose of 30%, 60%, and 90% nitrogen fertilizer, called N-30%, N-60%, N-90%, respectively. Tomato plant leaves were then randomly... 

This paper considers Pressure Oscillation (PO) experiments for which we find the minimum experiment time that guarantees user-imposed parameter variance upper bounds and honours actuator limits. The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated. This expression is used to tackle the optimization problem. We study the Dynamic Darcy Cell experiment set-up (Heller et al., 2002) and focus on data generation using square wave actuator signals, which, as we shall prove, deliver shorter experiment times than sinusoidal ones. Parameter identification is achieved using... 

The choice of technology to transport passengers in large metropolitan areas is an important issue everywhere. There are many factors involved in this choice. This paper deals with the possibility of the objective use of available information in the analysis of the suitability of a rail public transport system for a city. A database has been made from publications on public city transportation and country level information. Logit models of choice have been calibrated by the maximum likelihood and nonlinear least square methods based on the acquired information. Each city is treated as an "individual", choosing rail or non-rail modes for its trips. Only cities with a population of more than... 

This article presents experimental results on the electrophoretic deposition (EPD) of bioresorbable chitosan/45S5 Bioglass® composite coatings for orthopaedic implants based on the Taguchi design of experiments (DOE) approach. The influence of EPD parameters including Bioglass® concentration, electric voltage and deposition time on deposition yield was studied by an orthogonal Taguchi array of L18 type. Multivariate analysis of variance (MANOVA) and regression analysis based on the partial least-square method were used to identify the significant factors affecting the deposition yield and its stability during constant-voltage EPD. The coatings were characterised by high resolution scanning... 

Side weirs are hydraulic control structures widely used in irrigation and drainage systems as well as wastewater treatment plants. These structures also serve as adjusting/diverting flow structures with a minimum head loss. In the present study, by applying experimental data of more than 400 laboratory tests and using the multivariable nonlinear partial least-squares (PLS) method, three nonlinear equations are proposed for discharge coefficient, CM, of triangular and asymmetric labyrinth side weirs. These equations relate the discharge coefficient to the relevant geometrical and hydraulic dimensionless characteristics of flow. Results indicate that the new proposed equations are more... 

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... 

In this article, we examine Independent Component Analysis (ICA) and the concept of Mutual information (MI) as a quantitative measure of independence from the point of view of analytical chemistry. We compare results obtained by different ICA methods with results obtained by Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). These results have shown that, when non-negativity constraints are applied, values of MI increase considerably and the resolved components cannot anymore be considered to be independent (i.e. they can only be considered to be the " least dependent" components). MI values of profiles resolved by MCR-ALS and ICA did not differ significantly when... 

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... 

Comprehensive two-dimensional gas chromatography and flame ionization detection combined with unfolded-partial least squares is proposed as a simple, fast and reliable method to assess the quality of gasoline and to detect its potential adulterants. The data for the calibration set are first baseline corrected using a two-dimensional asymmetric least squares algorithm. The number of significant partial least squares components to build the model is determined using the minimum value of root-mean square error of leave-one out cross validation, which was 4. In this regard, blends of gasoline with kerosene, white spirit and paint thinner as frequently used adulterants are used to make... 

Fuzzy C-means clustering (FCM) is proposed as a promising method for the clustering of chromatographic fingerprints of complex samples, such as essential oils. As an example, secondary metabolites of 14 citrus leaves samples are extracted and analyzed by gas chromatography-mass spectrometry (GC-MS). The obtained chromatographic fingerprints are divided to desired number of chromatographic regions. Owing to the fact that chromatographic problems, such as elution time shift and peak overlap can significantly affect the clustering results, therefore, each chromatographic region is analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to address these problems. Then,... 

The performances of gas chromatography with mass spectrometry and of comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry are examined through the comparison of Daphnia magna metabolic profiles. Gas chromatography with mass spectrometry and comprehensive two-dimensional gas chromatography with mass spectrometry were used to compare the concentration changes of metabolites under saline conditions. In this regard, a chemometric strategy based on wavelet compression and multivariate curve resolution–alternating least squares is used to compare the performances of gas chromatography with mass spectrometry and comprehensive two-dimensional gas chromatography with... 

Biogenic amines (BAs) are known as substantial indicators of the quality and safety of food. Developing rapid and visual detection methods capable of simultaneously monitoring BAs is highly desired due to their harmful effects on human health. In the present study, we have designed a multicolor sensor array consisting of two types of gold nanostructures (i.e., gold nanorods (AuNRs) and gold nanospheres (AuNSs)) for the discrimination and determination of critical BAs (i.e., spermine (SM), tryptamine (TT), ethylenediamine (EA), tyramine (TR), spermidine (SD), and histamine (HT)). The design principle of the probe was based on the metallization of silver ions on the surface of AuNRs and AuNSs...