Determination of the total acid number (TAN) of used mineral oils in aviation engines by FTIR using regression models

[EN] Total acid number (TAN) has been considered an important indicator of the oil quality of used oils. TAN is determined by potentiometric titration, which is time-consuming and requires solvent. A more convenient approach to determine TAN is based on infrared (IR) spectral data and multivariate regression models. Predictive models for the determination of TAN using the IR data measured from ashless dispersant oils developed for aviation piston engines (SAE 50) have been developed. Different techniques, including Projection Pursuit Regression (PPR), Partial Least Square, Support Vector Machines, Linear Models and Random Forest (RF), have been used. The used methodology involved a five folder cross validation to derive the best model. Then a full error measure over the whole dataset was taken. A backward variable selection was used and 25 highly relevant variables were extracted. RF provided an acceptable modelling technology with grouped dataset predictions that allowed transformations to be performed that fitted the measured values. A hybrid method considering group of bands as features was used for modelling. An innovative mechanism for wider features selection based on genetic algorithm has been implemented. This method showed better performance than the results obtained using the other methodologies. RMSE and MAE values obtained in the validation were 0.759 and 0.359 for PPR model respectively.The authors would like to thank Roland Tones of the Universidad Metropolitana for his collaboration in oil sample processing. BLDR acknowledges financial support from the Venoco Company. The authors also thank the Universidad Politecnica de Madrid for granting access to the CESVIMA (http://www.cesvima.upm.es/) HPC infrastructure. We would also like to thank the author Beatriz Leal de Rivas (in memoriam), for her efforts to conform this team of researchers from different areas of expertise, and we want to dedicate this work to her loving memory.Leal De-Rivas, BC.; Vivancos, J.; Ordieres Meré, J.; Capuz-Rizo, SF. (2017). Determination of the total acid number (TAN) of used mineral oils in aviation engines by FTIR using regression models. Chemometrics and Intelligent Laboratory Systems. 160:32-39. doi:10.1016/j.chemolab.2016.10.015S323916

Near infrared hyperspectral imaging for forensic analysis of document forgery

[EN] Hyperspectral images in the near infrared range (HSI-NIR) were evaluated as a nondestructive method to detect fraud in documents. Three different types of typical forgeries were simulated by (a) obliterating text, (b) adding text and (c) approaching the crossing lines problem. The simulated samples were imaged in the range of 928 2524 nm with spectral and spatial resolutions of 6.3 nm and 10 mm, respectively. After data pre-processing, different chemometric techniques were evaluated for each type of forgery. Principal component analysis (PCA) was performed to elucidate the first two types of adulteration, (a) and (b). Moreover, Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) was used in an attempt to improve the results of the type (a) obliteration and type (b) adding text problems. Finally, MCR-ALS and Partial Least Squares Discriminant Analysis (PLS-DA), employed as a variable selection tool, were used to study the type (c) forgeries, i.e. crossing lines problem. Type (a) forgeries (obliterating text) were successfully identified in 43% of the samples using both the chemometric methods (PCA and MCR-ALS). Type (b) forgeries (adding text) were successfully identified in 82% of the samples using both the methods (PCA and MCR-ALS). Finally, type (c) forgeries (crossing lines) were successfully identified in 85% of the samples. The results demonstrate the potential of HSI-NIR associated with chemometric tools to support document forgery identificationINCTAA (Processes no. : CNPq 573894/2008-6; FAPESP 2008/57808-1), NUQAAPE, FACEPE, CNPq, CAPES, Spanish Ministry of Science and Innovation MICINN (grant DPI2011-28112-C04-02).Silva, CS.; Pimentel, MF.; Honorato, RS.; Pasquini, C.; Prats Montalbán, JM.; Ferrer Riquelme, AJ. (2014). Near infrared hyperspectral imaging for forensic analysis of document forgery. Analyst. 139(20):5176-5184. https://doi.org/10.1039/C4AN00961DS517651841392

A Two-Level Model for Evidence Evaluation in the Presence of Zeros

Likelihood ratios (LRs) provide a natural way of computing the value of evidence under competing propositions. We propose LR models for classification and comparison that extend the ideas of Aitken, Zadora, and Lucy and Aitken and Lucy to include consideration of zeros. Instead of substituting zeros by a small value, we view the presence of zeros as informative and model it using Bernoulli distributions. The proposed models are used for evaluation of forensic glass (comparison and classification problem) and paint data (comparison problem). Two hundred and sixty-four glass samples were analyzed by scanning electron microscopy, coupled with an energy dispersive X-ray spectrometer method and 36 acrylic topcoat paint samples by pyrolysis gas chromatography hyphened with mass spectrometer method. The proposed LR model gave very satisfactory results for the glass comparison problem and for most of the classification tasks for glass. Results of comparison of paints were also highly satisfactory, with only 3.0% false positive answers and 2.8% false negative answers

Forensic examination of multilayer white paint by lateral scanning Raman spectroscopy

Multilayer samples of white architectural paint potentially have very high evidential value in forensic casework, because the probability that two unrelated samples will have the same sequence of layers is extremely low. However, discrimination between the different layers using optical microscopy is often difficult or impossible. Here, lateral scanning Raman spectroscopy has been used to chemically map the cross‐sections of multilayer white paint chips. It was found that the spectra did allow the different layers to be delineated on the basis of their spectral features. The boundaries between different layers were not as sharp as expected, with transitions occurring over length scales of > 20 µm, even with laser spot diameters < 4 µm. However, the blurring of the boundaries was not so large as to prevent recording and identification of spectra from each of the layers in the samples. This method clearly provides excellent discrimination between different multilayer white paint samples and can readily be incorporated into existing procedures for examination of paint transfer evidence

Thermal and fire degradation of recycled and polluted polypropylene-based materials

International audiencen this study, the effect of processing cycles and two pollutants (engine oil (HM) and ethylene glycol (EG)) on the thermal and rheological properties of polypropylene-based materials (108MF97 and 7510) has been studied. It was investigated if polymers coming from bumper face bar could keep their properties and can be reused after recycling. The different results demonstrate that the two polymers that were polluted and recycled do not show any decrease of their intrinsic properties. Moreover, for one of the two polymers (108MF97), the presence of engine oil enables to increase the thermal stability and reaction to fire. Finally, it appears that the reuse of such polymers is possible