Chemometric correction of drift effects in optical spectra

All quantitative data evaluation techniques applied to spectroscopy are based on the assumption that the baseline is stable in time. If this prerequisite is violated, major concentration errors can result since drifts are evaluated along with true spectroscopic features. For handling baseline drifts two improved principal component regression (PCR) methods are presented and compared to conventional Savitzky-Golay preprocessing followed by conventional PCR. The proposed drift-correction methods take advantage of baseline drifts being rather broad compared to the absorption features. The only assumption made is that drift effects can be modeled sufficiently by polynomials of user-selectable order. One correction method modifies principal components such that drifts of polynomial shape are orthogonal to the calibration model and thus cannot influence the concentration result. The second method extends the calibration model by synthetic so-called pseudo-principal components. While the principal components model the true spectral features, the pseudo-principal components describe drifts simultaneously and independently. Hence, drifts are explicitly included into the calibration and cannot cause erroneous concentration results. It is demonstrated that both correction methods are equivalently as powerful as the conventional PCR in the absence of drifts and superior if drifts are present. The overall performance--in the absence and presence of baseline drifts--of the novel methods makes them more versatile and reliable than the conventional Savitzky-Golay data preprocessing. In almost all investigated cases, the average concentration errors were significantly smaller than those obtained by Savitzky-Golay preprocessing. Furthermore, polyPCR and pPCR do not need laborious optimizations as Savitzky-Golay does for preventing suppression of relevant signal components. polyPCR demands less computation expense than Savitzky-Golay, and pPCR extracts the drift spectrum as additional qualitative information not provided by Savitzky-Golay.     

Chain of custody for samples of live crude oil using visible-near-infrared spectroscopy

In order to design oil production facilities and strategies, it is necessary to acquire crude oil samples from subsurface formations in oil wells in so-called openhole prior to production. In some environments, such as deepwater production of oil, decisions of huge economic importance are based on such samples. To date, there has been little quality control to verify that the crude oils collected in the sample bottles and analyzed up to a year later in the laboratory have any relation to the actual crude oils in the subsurface reservoirs. These high-pressure samples can undergo myriad deleterious alterations. Here, we introduce the chain-of-custody concept to the oilfield. The visible-near-infrared spectrum of the crude oil is measured in situ in the wellbore at the point of sample acquisition. This spectrum is compared with the spectrum measured on putatively the same fluid in the laboratory at the start of laboratory sample analysis. First, quantitative assessment is made of whether the fluid in the (high-pressure) sample bottle remains representative of formation fluids. Second, any specific changes in the spectrum of the fluid can be related to possible process control failures. Here, the entire process of chain of custody is proven. The chain of custody process can rapidly become routine in the petroleum industry, thereby significantly improving the reliability of any process that depends on fluid property determination.     

Discriminant analyzing system for wood wastes using a visible-near-infrared chemometric imaging technique

A new optical system was developed and applied to automated separation of wood wastes, using a combined technique of visible-near-infrared (Vis-NIR) imaging analysis and chemometrics. Three kinds of typical wood wastes were used, i.e., non-treated, impregnated, and plastic-film overlaid wood. The classification model based on soft independent modeling of class analogy (SIMCA) was examined using the difference luminance brightness of a sample. Our newly developed system showed a good/promising performance in separation of wood wastes, with an average rate of correct separation of 89%. Hence, it is concluded that the system is efficiently feasible for online monitoring and separation of wood wastes in recycling mills.     

In situ determination of growing stages and harvest time of tomato (Lycopersicon esculentum ) fruits using fiber-optic visible-near-infrared (Vis-NIR) spectroscopy

Nondestructive in situ measurement of tomato fruits is essential to determine growing stages and to assist in automatic picking of fruits. This study evaluates the applicability of visible and near-infrared (Vis-NIR) spectroscopy for in situ determination of growing stages and harvest time of three cultivars of tomato fruits. A mobile fiber-type AgroSpec Vis-NIR spectrophotometer (Tec5 Co., Germany) with a spectral range of 350-2200 nm was used to measure tomato spectra in reflection mode. A new growing stage (GS) index defined as the ratio of the current growing age in days to the on-vine duration before harvest in days was proposed. After dividing spectra into a calibration set (70%) and an independent prediction set (30%), spectra in the calibration set were subjected to a partial least squares regression (PLSR) with leave-one-out cross-validation to establish calibration models relating GS to the spectra of tomato fruits. Separate models were developed for each tomato cultivar and compared with a general model that used combined spectra of all three cultivars. The results show that PLSR based on the new GS is successful and robust in predicting the growing stages and harvest time of tomato fruits. Validation of calibration models on the independent prediction set indicates that successful prediction of GS can be achieved using the three models developed separately for each cultivar with a coefficient of determination (R(2)) of 0.91-0.92, root mean square error of prediction (RMSEP) of 0.081-0.097, and residual prediction deviation (RPD) of 3.29-3.70. General calibration using the combined spectra produces good prediction performance, although less accurate than that for the three individual cultivar models. The analysis of regression coefficient plots resulting from PLSR analysis indicates consistent assignment of important wavelengths for individual cultivar spectra and combined spectra. It is concluded that the Vis-NIR PLSR based on GS index can be adopted successfully for in situ determination of growing stages and harvest time of on-vine tomato fruits, which allows for automatic picking of fruits by a horticultural robot.     

Chemometric characterization of s-triazine derivatives in relation to structural parameters and biological activity

Objective: In this study 14 newly synthesized s-triazine derivatives were investigated by means of reversed-phase thin-layer chromatography (TLC) on C-18 stationary and five different mobile phases: acetone–water, acetonitrile–water, methanol–water, 2-propanol–water, and tetrahydrofuran–water. Methods: Principal component analysis (PCA) was performed to explore and visualize similarities and differences among the compounds and among the mobile phases. Observations from the PCA were supported using hierarchical cluster analysis (HCA). Results: Physicochemical parameters that are significant for activity, that is, absorption, distribution, and bonding for different receptors in target tissues were calculated. Conclusion: Highly predictive models, describing quantitative relationships between chromatographic retention and parameters that influence activity, were obtained using partial least squares (PLS) method.     

Experimental determination of stress field parameters in bi-material notches using photoelasticity

The experimental technique of photoelasticity has been utilized for calculating bi-material notch stress intensities as well as the coefficients of higher order terms. Employing the equations of multi-parameter stress field allows data collection from a larger zone from the notch tip and makes the data collection from experiments more convenient. Moreover, the effects of higher order terms in the region near the notch tip are taken into account. For the photoelasticity experiments, a laboratory specimen known as the Brazilian disk with a central notch, consisting of Aluminum and Polycarbonate, has been utilized. Using this specimen, different mode mixities could be easily produced by changing the loading angle. The bi-material notch stress intensities and the first non-singular stress term (called I-stress) were then calculated for different test configurations. In order to utilize the advantages of whole-field photoelasticity and minimize the experimental errors, a large number of data points were substituted in the multi-parameter stress field equations. Then the resulting system of nonlinear equations was solved by employing an over-deterministic least squares method coupled with the Newton–Raphson algorithm. It has been shown that considering the I-stress term improves, to a large extent, the accuracy of the stress intensities calculated through the photoelasticity technique. Moreover, by reconstructing the isochromatic fringes, the effects of the I-stress term on the shape and size of these fringes around the notch tip were investigated for a 30° notch. Finally, the experimental photoelasticity results were compared with the corresponding values obtained from finite element analysis and a good correlation was observed.     

Circulating blood volume determination using electronic spin resonance spectroscopy

There have been numerous methods proposed to measure the circulating blood volume (CBV). Nevertheless, none of them have been massively and routinely accepted in clinical diagnosis. This study describes a simple and rapid method, on a rabbit model, using the dilution of autologous red cells labeled with a nitroxide radical (Iodoacetamide-TEMPO), which can be detected by electronic spin resonance (ESR) spectroscopy. Blood samples were withdrawn and re-injected using the ears' marginal veins. The average CBV measured by the new method/body weight (CBV(IAT)/BW) was 59 +/- 7 mL/kg (n = 33). Simultaneously, blood volume determinations using the nitroxide radical and (51)Cr (CBV(Cr)) were performed. In the plot of the difference between the methods (CBV(IAT) - CBV(Cr)) against the average (CBV(IAT) + CBV(Cr))/2, the mean of the bias was -1.1 +/- 6.9 mL and the limits of agreement (mean difference +/-2 SD) were -14.9 and 12.7 mL. Lin's concordance correlation coefficient p(c) = 0.988. Thus, both methods are in close agreement. The development of a new method that allows a correct estimation of the CBV without using radioactivity, avoiding blood manipulation, and decreasing the possibility of blood contamination with similar accuracy and precision of that of the "gold standard method" is an innovative proposal.     

Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulfides

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of mineral samples are complex, comprised of large mass ranges and many peaks. Consequently, characterization and classification analysis of these systems is challenging. In this study, different chemometric and statistical data evaluation methods, based on monolayer sensitive TOF-SIMS data, have been tested for the characterization and classification of copper-iron sulfide minerals (chalcopyrite, chalcocite, bornite, and pyrite) at different flotation pulp conditions (feed, conditioned feed, and Eh modified). The complex mass spectral data sets were analyzed using the following chemometric and statistical techniques: principal component analysis (PCA); principal component-discriminant functional analysis (PC-DFA); soft independent modeling of class analogy (SIMCA); and k-Nearest Neighbor (k-NN) classification. PCA was found to be an important first step in multivariate analysis, providing insight into both the relative grouping of samples and the elemental/molecular basis for those groupings. For samples exposed to oxidative conditions (at Eh ~430 mV), each technique (PCA, PC-DFA, SIMCA, and k-NN) was found to produce excellent classification. For samples at reductive conditions (at Eh ~ -200 mV SHE), k-NN and SIMCA produced the most accurate classification. Phase identification of particles that contain the same elements but a different crystal structure in a mixed multimetal mineral system has been achieved.     

Nondestructive determination of electromagnetic parameters ofdielectric materials at X-band frequencies using a waveguide probesystem

An accurate technique used to measure complex permittivity and permeability of isotropic materials simultaneously has been developed by employing a flanged open-ended rectangular waveguide probe over a frequency range of 8-12 GHz. Two coupled integral equations for the aperture electric field are formulated and solved numerically using Galerkin's method. A series of experiments has been conducted, and the calibration of the probe system using an adjustable shorter is explained. The inverse results on the electromagnetic (EM) properties of various materials (including solid and liquid materials) based on the measured reflection coefficients of the incident dominant mode are presented. It is also shown that the EM parameters of isotropic materials having low complex permittivities can be determined accurately, while those with higher complex permittivities cause larger measurement errors     

Method for determination of crack bridging parameters using long optical fiber Bragg grating sensors

The state of the local fiber–matrix interface highly influences the propagation of cracks in fiber-reinforced composites and thus the stress distribution in any bridging fiber. This paper demonstrates that by embedding a long optical fiber Bragg grating into a reinforcing fiber and using an established model of the grating response to non-uniform stress distributions, one can determine key parameters of a crack bridging model. The grating extending into the epoxy on each side of the crack is subject to a strain function as a result of all micro-mechanical phenomena acting along the fiber. Furthermore, this technique does not require that one knows a priori the exact location of the crack. Two types of central crack specimens with an artificial crack were fabricated and tested, one with a strong interface and one with a weaker interface resulting in frictional sliding. The results demonstrate that this technique is efficient for the measurement of the bridging forces through validation by previous measurements using short Bragg gratings and the deduction of interface parameters. Analysis also shows that the sensitivity of the Bragg grating sensor to the bridging force is sufficient, even for the more realistic case of an initially zero-width crack e.g. grown by fatigue.     

Chemometric labeling of cereal tissues in multichannel fluorescence microscopy images using discriminant analysis

This paper presents a novel, semiautomatic method for microscopic identification of multicomponent samples, which allows the identification, location, and percentage quantity of each component to be determined. The method involves applying discriminant analysis to a sequence of multichannel fluorescence microscopy images via a supervised learning approach; by selecting groups of pixels that are representative for each component type in a "known" sample, a computer is "taught" how to recognize the behavior (i.e., fluorescence emission) of the various components when illuminated under different spectral conditions. The identity, quantity, and location of these components in "unknown" samples (i.e., samples with the same component types but in different ratios or distributions) can then be investigated. The technique therefore enables semiautomatic quantitative fluorescence microscopy and has potential as a quality control tool. This work demonstrates the application of the technique to artificial and natural samples and critically discusses its quality, potential, and limitations.     

Chemometric study on the forensic discrimination of soil types using their infrared spectral characteristics

Soil has been utilized in criminal investigations for some time because of its prevalence and transferability. It is usually the physical characteristics that are studied; however, the research carried out here aims to make use of the chemical profile of soil samples. The research we are presenting in this work used sieved (2 mm) soil samples taken from the top soil layer (about 10 cm) that were then analyzed using mid-infrared spectroscopy. The spectra obtained were pretreated and then input into two chemometric classification tools: nonlinear iterative partial least squares followed by linear discriminant analysis (NIPALS-LDA) and partial least squares discriminant analysis (PLS-DA). The models produced show that it is possible to discriminate between soil samples from different land use types and both approaches are comparable in performance. NIPALS-LDA performs much better than PLS-DA in classifying samples to location.     

Cloud point extraction for determination of Diazinon: Optimization of the effective parameters using Taguchi method

Since Diazinon is one of the organophosphorous compounds which are harmful for human organisms, a simple, sensitive and accurate testing method for extraction and determination of this pesticide is mandatory. In this project, Cloud Point Extraction (CPE) method was developed for determination of Diazinon in aqueous samples. CTAB (cetyl trimethyl ammonium bromide) was used as cationic surfactant to extract and preconcentrate of Diazinon at the same time and the extracted Diazinon was determined by UV spectrophotometery. Taguchi L₉ array was employed for design of experiments to investigate influences of surfactant concentration, salt concentration, temperature and incubation time as effective parameters. According to the analysis of variance (ANOVA) results, the most effective parameter of the process is incubation time. The results show that a surfactant concentration of 10^− 5% (w/v), an incubation time of 30 min, a KI concentration of 10^− 6 mol L^− 1 and a temperature of 35 °C are the best operating conditions. Also, the linear calibration graph in the range of 0.02-24 ng ml^− 1 of Diazinon with r = 0.999 was obtained. The limit of detection (LOD) was 0.02 ng ml^− 1 and relative standard deviation (RSD) for 15 ng ml^− 1 of Diazinon was 0.76%.     

Process parameters determination for precision manufacturing

Conventional process planning in manufacturing operations presents fixed process means and process tolerances for all operations and allows actual outputs to be distributed around these fixed values, as long as the final outputs fall within acceptable specifications. Some approaches attempt to maximize the process tolerances of all manufacturing operations for part production. Other approaches intend to minimize the tolerance cost or quality loss based on known functions. Most of them consider process mean and process tolerance as independent decision variables in process planning, with the condition that the resultant working dimensions are equal to the design target values of blueprint dimensions. These approaches assume that there is no process drift or deterioration. However, these conventional approaches are inappropriate for small‐volume, high‐value and precision processing, particularly of a complex part. Hence this study introduces an alternative approach to the tolerance‐balancing problem that does not provide specific objective functions, which determines process means and process tolerances simultaneously and adjusts them sequentially. Copyright © 2000 John Wiley & Sons, Ltd.     

Planning a physical experiment on determination of the parameters of a material by using mathematical methods

A method is developed for solving an inverse problem on the determination of thermomechanical parameters of a material that undergoes phase transformations in the process of hardening. The dependence of the error of determination of parameters on the error admissible in direct measurements of physical fields is established.Translated from Inzhenerno-fizicheskii Zhurnal, Vol. 61, No. 2, pp. 181–186, August, 1991.     

Numerical determination of hysteresis parameters for the modelingof magnetic properties using the theory of ferromagnetic hysteresis

The authors describe how the various model parameters needed to describe hysteresis on the basis of the Jiles-Atherton theory can be calculated from experimental measurements of the coercivity, remanence, saturation magnetization, initial anhysteretic susceptibility, initial normal susceptibility, and maximum differential susceptibility. The determination of hysteresis parameters based on this limited set of magnetic properties is of the most practical use since these are the properties of magnetic materials that are most likely to be available