An improved successive projections algorithm version to variable selection in multiple linear regression.

The aim of the successive projections algorithm (SPA) is to enhance the accuracy of multiple linear regressions (MLR) by minimizing the impact of collinearity effects in the calibration data set. Combining SPA with MLR as a variable selection approach has resulted in the SPA-MLR method, which has been reported in literature to produce models with good prediction ability compared to conventional full-spectrum models obtained with partial-least-squares (PLS) in some cases. This paper proposes the addition of a filter step to the current version of the SPA algorithm to reduce the number of uninformative variables before the projection phase and assist the algorithm in selecting the best variables on subsequent steps. The proposed fSPA-MLR algorithm is evaluated in two case studies involving the near-infrared spectrometric analysis of pharmaceutical tablet and diesel/biodiesel mixture samples. Compared to PLS, the fSPA-MLR models demonstrate similar or better performance. Moreover, the fSPA-MLR models outperform the original SPA-MLR in both cross-validation and external prediction. The fSPA-MLR models deliver superior results regardless of the pre-processing algorithm tested, including first-derivative Savitzky-Golay (SG) and Standard Normal Variate (SNV), or even in raw spectra data.

Tea authentication and determination of chemical constituents using digital image-based fingerprint signatures and chemometrics.

Tea (Camellia sinensis) fraud has been frequently identified and involves tampering with the labelling of inferior products or without geographical origin certification and even mixing them with superior quality teas to mask an adulteration. Consequently, economic losses and health damage to consumers are observed. Thus, a Chemometrics-assisted Color Histogram-based Analytical System (CACHAS) was employed a simple, cost-effective, reliable, and green analytical tool to screen the quality of teas. Data-Driven Soft Independent Modeling of Class Analogy was used to authenticate their geographical origin and category simultaneously, recognizing correctly all Argentinean and Sri Lankan black teas and Argentinean green teas. For the determination of moisture, total polyphenols, and caffeine, Partial Least Squares obtained satisfactory predictive abilities, with values of root mean squared error of prediction (RMSEP) of 0.50, 0.788, and 0.25 mg kg-1, rpred of 0.81, 0.902, and 0.81, and relative error of prediction (REP) of 6.38, 9.031, and 14.58%., respectively. CACHAS proved to be a good alternative tool for environmentally-friendly non-destructive chemical analysis.

Open Source Automated Flow Analysis Instrument for Detecting Arsenic in Water.

In this paper the design and implementation of an embedded system based on Flow-Batch methodology with a Quartz Crystal Microbalance (QCM) sensor technology and a commercial FPGA admittance meter is presented to detect the presence of arsenic in water. The system's performance was evaluated with lab made samples and it is foresee that this open source automated flow instrument could help develop analytical methodologies for the future quantification of this analyte. A description of the components is presented and assembling and operation instructions are provided together with the dynamic range and linear regression coefficients for the line and R.

Capillary electrophoresis coupled to chemometrics for analysis of carbon dots in nanoparticles mixtures.

Since their discovery in 2004, carbon dots (CDs) have attracted attention due to their intrinsic physicochemical properties and the easy synthesis from simple precursors. However, quantification of CDs in mixtures of nanoparticles with similar sizes and surface functionality is still a challenging issue for research applications or regulatory purposes. In this work, CDs and silver nanoparticles were first synthesized under alkaline conditions by using glucose as precursor and capping agent, respectively. Mixtures of these nanoparticles were made at micromolar range, without purification, and then analyzed by CE-DAD, using an electrolyte solution composed of 20 mM sodium borate and 20 mM SDS at pH 8.5, in a total time of <15 min. The three-way electrophoretic data were then decomposed by advanced chemometric models, parallel factor analysis and multivariate curve resolution-alternating least-squares. The explained variances for both models were 95.8% (parallel factor analysis) and 85.3% (multivariate curve resolution-alternating least-squares). In both cases, the quality of the results was verified by the root mean square standard deviation coefficient variation, which resulted lower than 5%, and no significant bias was observed at 95% of statistical confidence. Satisfactory prediction for CDs concentration was obtained with recovery values between 80.0% and 115%.

NIR-Reflective and Hydrophobic Bio-Inspired Nano-Holed Configurations on Titanium Alloy.

Near-infrared (NIR) radiation plays an important role in guided external stimulus therapies; its application in bone-related treatments is becoming more and more frequent. Therefore, metallic biomaterials that exhibit properties activated by NIR are promising for further orthopedic procedures. In this work, we present an adapted electroforming approach to attain a biomorphic nano-holed TiO2 coating on Ti6Al4V alloy. Through a precise control of the anodization conditions, structures revealed the formation of localized nano-pores arranged in a periodic assembly. This specific organization provoked higher stability against thermal oxidation and precise hydrophobic wettability behavior according to Cassie-Baxter's model; both characteristics are a prerequisite to ensure a favorable biological response in an implantable structure for guided bone regeneration. In addition, the periodically arranged sub-wavelength-sized unit cell on the metallic-dielectric structure exhibits a peculiar optical response, which results in higher NIR reflectivity. Accordingly, we have proved that this effect enhances the efficiency of the scattering processes and provokes a significant improvement of light confinement producing a spontaneous NIR fluorescence emission. The combination of the already favorable mechanical and biocompatibility properties of Ti6Al4V, along with suitable thermal stability, wetting, and electro-optical behavior, opens a promising path toward strategic bone therapeutic procedures.

Experimental and DFT Studies of Hybrid Silver/Cdots Nanoparticles.

In this work, the combination of experimental and theoretical results was employed to confirm an interaction between Cdots and AgNPs in the silver/Cdots hybrid nanoparticles. The experimental data obtained by UV-vis, IR, ζ potential, and TGA techniques were correlated and interpreted by calculations obtained by DFT. In particular, an interaction between the -COO- functional group of the Cdots with AgNPs was revealed. As consequence of this interaction, a frequency shift and a higher absorption intensity in the IR of the -OH group in the Cdots was theoretically predicted and also observed in the experimental IR spectra. Moreover, a bonding and charge distribution analysis was also carried out. These results constitute new physical insight for the Ag@Cdots system. Additionally, based in this type of interaction, energy calculations explained the negative charge surrounding the AgNPs, which was detected by ζ potential measurements. This systematic methodology not only is useful for this nanoparticles system but also could be used to analyze the interaction between the components that constitute other types of hybrid nanoparticles.

Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS).

Determining fat content in hamburgers is very important to minimize or control the negative effects of fat on human health, effects such as cardiovascular diseases and obesity, which are caused by the high consumption of saturated fatty acids and cholesterol. This study proposed an alternative analytical method based on Near Infrared Spectroscopy (NIR) and Successive Projections Algorithm for interval selection in Partial Least Squares regression (iSPA-PLS) for fat content determination in commercial chicken hamburgers. For this, 70 hamburger samples with a fat content ranging from 14.27 to 32.12mgkg-1 were prepared based on the upper limit recommended by the Argentinean Food Codex, which is 20% (ww-1). NIR spectra were then recorded and then preprocessed by applying different approaches: base line correction, SNV, MSC, and Savitzky-Golay smoothing. For comparison, full-spectrum PLS and the Interval PLS are also used. The best performance for the prediction set was obtained for the first derivative Savitzky-Golay smoothing with a second-order polynomial and window size of 19 points, achieving a coefficient of correlation of 0.94, RMSEP of 1.59mgkg-1, REP of 7.69% and RPD of 3.02. The proposed methodology represents an excellent alternative to the conventional Soxhlet extraction method, since waste generation is avoided, yet without the use of either chemical reagents or solvents, which follows the primary principles of Green Chemistry. The new method was successfully applied to chicken hamburger analysis, and the results agreed with those with reference values at a 95% confidence level, making it very attractive for routine analysis.

A porphyrin-based fluorescence method for zinc determination in commercial propolis extracts without sample pretreatment.

The quantification of zinc in over-the-counter drugs as commercial propolis extracts by molecular fluorescence technique using meso-tetrakis(4-carboxyphenyl)porphyrin (H2 TCPP4 ) was developed for the first time. The calibration curve is linear from 6.60 to 100 nmol L-1 of Zn2+ . The detection and quantification limits were 6.22 nmol L-1 and 19.0 nmol L-1 , respectively. The reproducibility and repeatability calculated as the percentage variation of slopes of seven calibration curves were 6.75% and 4.61%, respectively. Commercial propolis extract samples from four Brazilian states were analyzed and the results (0.329-0.797 mg/100 mL) obtained with this method are in good agreement with that obtained with the Atomic Absorption Spectroscopy (AAS) technique. The method is simple, fast, of low cost and allows the analysis of the samples without pretreatment. Moreover the major advantage is that Zn-porphyrin complex presents fluorescent characteristic promoting the selectivity and sensitivity of the method.

A MAC Protocol to Support Monitoring of Underwater Spaces.

Underwater sensor networks are becoming an important field of research, because of their everyday increasing application scope. Examples of their application areas are environmental and pollution monitoring (mainly oil spills), oceanographic data collection, support for submarine geolocalization, ocean sampling and early tsunamis alert. The challenge of performing underwater communications is well known, provided that radio signals are useless in this medium, and a wired solution is too expensive. Therefore, the sensors in these networks transmit their information using acoustic signals that propagate well under water. This data transmission type not only brings an opportunity, but also several challenges to the implementation of these networks, e.g., in terms of energy consumption, data transmission and signal interference. In order to help advance the knowledge in the design and implementation of these networks for monitoring underwater spaces, this paper proposes a MAC protocol for acoustic communications between the nodes, based on a self-organized time division multiple access mechanism. The proposal was evaluated using simulations of a real monitoring scenario, and the obtained results are highly encouraging.

Determination of tryptamine in foods using square wave adsorptive stripping voltammetry.

Tryptamine, a biogenic amine, is an indole derivative with an electrophilic substituent at the C3 position of the pyrrole ring of the indole moiety. The electrochemical oxidation of tryptamine was investigated using glassy carbon electrode (GCE), and focusing on trace level determination in food products by square wave adsorptive stripping voltammetry (SWAdSV). The electrochemical responses of tryptamine were evaluated using differing voltammetric techniques over a wide pH range, a quasi-reversible electron-transfer to redox system represented by coupled peaks P1-P3, and an irreversible reaction for peak P2 were demonstrated. The proton and electron counts associated with the oxidation reactions were estimated. The nature of the mass transfer process was predominantly diffusion-limited for the oxidation process of P1, the most selective and sensitive analytical response (acetate buffer solution pH 5.3), being used for the development of SWAdSV method, under optimum conditions. The excellent response allowed the development of an electroanalytical method with a linear response range of from 4.7-54.5)×10(-)(8)molL(-1), low detection limit (0.8×10(-)(9)molL(-)(1)), and quantification limit (2.7×10(-9)molL(-1)), and acceptable levels of repeatability (3.6%), and reproducibility (3.8%). Tryptamine content was determined in bananas, tomatoes, cheese (mozzarella and gorgonzola), and cold meats (chicken sausage and pepperoni sausage), yielding recoveries above 90%, with excellent analytical performance using simple and low cost instrumentation.

Using UV-Vis spectroscopy for simultaneous geographical and varietal classification of tea infusions simulating a home-made tea cup.

In this work we proposed a method to verify the differentiating characteristics of simple tea infusions prepared in boiling water alone (simulating a home-made tea cup), which represents the final product as ingested by the consumers. For this purpose we used UV-Vis spectroscopy and variable selection through the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA) for simultaneous classification of the teas according to their variety and geographic origin. For comparison, KNN, CART, SIMCA, PLS-DA and PCA-LDA were also used. SPA-LDA and PCA-LDA provided significantly better results for tea classification of the five studied classes (Argentinean green tea; Brazilian green tea; Argentinean black tea; Brazilian black tea; and Sri Lankan black tea). The proposed methodology provides a simpler, faster and more affordable classification of simple tea infusions, and can be used as an alternative approach to traditional tea quality evaluation as made by skilful tasters, which is evidently partial and cannot assess geographic origins.

Eco-friendly sonoluminescent determination of free glycerol in biodiesel samples.

This paper proposes a flow-batch methodology for the determination of free glycerol in biodiesel that is notably eco-friendly, since non-chemical reagents are used. Deionized water (the solvent) was used alone for glycerol (sample) extractions from the biodiesel. The same water was used to generate water-cavitation sonoluminescence signals, which were modulated by the quenching effect associated with the amount of extracted glycerol. The necessarily reproducible signal generation was achieved by using a simple and inexpensive piezoelectric device. A linear response was observed for glycerol within the 0.001-100 mg/L range, equivalent to 0.004-400 mg/kg free glycerol in biodiesel. The lowest measurable concentration of free glycerol was estimated at 1.0 µg/L. The selectivity of the proposed method was confirmed by comparing the shape and retention of both real and calibration samples to standard solution chromatograms, presenting no peaks other than glycerol. All samples (after extraction) are greatly diluted; this minimizes (toward non-detectability) potential interference effects. The methodology was successfully applied to biodiesel analysis at a high sampling rate, with neither reagent nor solvent (other than water), and with minimum waste generation. The results agreed with the reference method (ASTM D6584-07), at a 95% confidence level.

Screening analysis of biodiesel feedstock using UV-vis, NIR and synchronous fluorescence spectrometries and the successive projections algorithm.

This paper investigates the use of UV-vis, near infrared (NIR) and synchronous fluorescence (SF) spectrometries coupled with multivariate classification methods to discriminate biodiesel samples with respect to the base oil employed in their production. More specifically, the present work extends previous studies by investigating the discrimination of corn-based biodiesel from two other biodiesel types (sunflower and soybean). Two classification methods are compared, namely full-spectrum SIMCA (soft independent modelling of class analogies) and SPA-LDA (linear discriminant analysis with variables selected by the successive projections algorithm). Regardless of the spectrometric technique employed, full-spectrum SIMCA did not provide an appropriate discrimination of the three biodiesel types. In contrast, all samples were correctly classified on the basis of a reduced number of wavelengths selected by SPA-LDA. It can be concluded that UV-vis, NIR and SF spectrometries can be successfully employed to discriminate corn-based biodiesel from the two other biodiesel types, but wavelength selection by SPA-LDA is key to the proper separation of the classes.

Automatic flow-batch system for cold vapor atomic absorption spectroscopy determination of mercury in honey from Argentina using online sample treatment.

An automatic flow-batch system that includes two borosilicate glass chambers to perform sample digestion and cold vapor atomic absorption spectroscopy determination of mercury in honey samples was designed. The sample digestion was performed by using a low-cost halogen lamp to obtain the optimum temperature. Optimization of the digestion procedure was done using a Box-Behnken experimental design. A linear response was observed from 2.30 to 11.20 µg Hg L(-1). The relative standard deviation was 3.20% (n = 11, 6.81 µg Hg L(-1)), the sample throughput was 4 sample h(-1), and the detection limit was 0.68 µg Hg L(-1). The obtained results with the flow-batch method are in good agreement with those obtained with the reference method. The flow-batch system is simple, allows the use of both chambers simultaneously, is seen as a promising methodology for achieving green chemistry goals, and is a good proposal to improving the quality control of honey.

Turbidimetric and photometric determination of total tannins in tea using a micro-flow-batch analyzer.

Both turbidimetric and photometric determinations of total tannins in samples of green and black tea, using a micro-flow-batch analyzer (µFBA) were studied. The miniaturized system was formed using photocurable urethane-acrylate resin and ultraviolet lithography technique. The turbidimetric method was based on the precipitation reaction of Cu (II) with tannins in acetate medium at a pH of 4.5. The photometric method was based on the complexation reaction of tannins with ferrous tartrate. The turbidimetric µFBA was able to test 200 samples per hour. The photometric µFBA allowed 300 analyses per hour, generating 136µL of residue per analysis. The paired t test, at a 95% confidence level, showed no statistically significant differences between results obtained by both methods and the reference method. The urethane-acrylate µFBA maintained satisfactory physical and chemical properties, and represents an improvement over conventional flow-batch analyzer.

Automatized flow-batch method for fluorescent determination of free glycerol in biodiesel samples using on-line extraction.

An automatic method, based on flow-batch (FB), for determining glycerol in biodiesel was developed. The FB systems draw upon the useful features of flow, batch and multi-commutation approaches. The standards and samples preparation, as well as, derivatization and analysis were fully automated. For that purpose, a homemade chamber was built. The proposed method is based on liquid-liquid extraction of glycerol and simultaneous oxidation with periodate, generating formaldehyde that reacts with acetylacetone. A fluorescent product of 3,5-diacetyl-1,4-dihydrolutidine was obtained. The fluorescence signal was recorded at λ(ex) =417 nm and λ(em) = 514 nm. A linear response was observed from 0.10 to 5.00 mg L(-1) glycerol, variation coefficient 1.5%, sampling rate 14 h(-1) and detection limit 0.036 mg L(-1) glycerol. The procedure was successfully applied to the analysis of biodiesel samples, and the results agreed with the reference method (ASTM D6584-07) at 95% confidence level.

Simultaneous determination of hydroquinone, resorcinol, phenol, m-cresol and p-cresol in untreated air samples using spectrofluorimetry and a custom multiple linear regression-successive projection algorithm.

In this study, a novel, simple, and efficient spectrofluorimetric method to determine directly and simultaneously five phenolic compounds (hydroquinone, resorcinol, phenol, m-cresol and p-cresol) in air samples is presented. For this purpose, variable selection by the successive projections algorithm (SPA) is used in order to obtain simple multiple linear regression (MLR) models based on a small subset of wavelengths. For comparison, partial least square (PLS) regression is also employed in full-spectrum. The concentrations of the calibration matrix ranged from 0.02 to 0.2 mg L(-1) for hydroquinone, from 0.05 to 0.6 mg L(-1) for resorcinol, and from 0.05 to 0.4 mg L(-1) for phenol, m-cresol and p-cresol; incidentally, such ranges are in accordance with the Argentinean environmental legislation. To verify the accuracy of the proposed method a recovery study on real air samples of smoking environment was carried out with satisfactory results (94-104%). The advantage of the proposed method is that it requires only spectrofluorimetric measurements of samples and chemometric modeling for simultaneous determination of five phenols. With it, air is simply sampled and no pre-treatment sample is needed (i.e., separation steps and derivatization reagents are avoided) that means a great saving of time.

A new automated approach to determine monosodium glutamate in dehydrated broths by using the flow-batch methodology.

The advantages of the flow-batch methodology were exploited to implement a simple system with nephelometric detection for the determination of monosodium glutamate (MSG) in food samples. The method is based on the inhibitory effect of the MSG over the crystallization of L-lysine in an isopropanol/acetone mixture. The calibration curve was prepared on-line. The method was linear over the range of 2.8 x 10(-3) to 1.1 x 10(-2)gL(-1) and a detection limit of 9.7 x 10(-5)gL(-1) was achieved. It was successfully applied to determine the MSG concentration in food samples, without a previous treatment. A recovery study was carried out on real samples and the percentages were between 98 and 106%.

Determination of phenol, resorcinol and hydroquinone in air samples by synchronous fluorescence using partial least-squares (PLS).

The determination of phenolic compounds is of great importance owing to their high toxicity. Some of them are present in tobacco smoke and it is important for their monitoring in air of closed room. A simple, rapid and sensitive method was developed for simultaneous determination of hydroquinone, resorcinol and phenol in this kind of samples. Synchronous fluorescence technique was used and the data were processed by using the partial least-squares (PLS) chemometric algorithm. The concentrations for experimental calibration matrix were varied between 0.02 and 0.2 mg L(-1) for hydroquinone, between 0.05 and 0.6 mg L(-1) for resorcinol and between 0.05 and 0.4 mg L(-1) for phenol in accordance with the national legislation. The cross-validation method was used to select the number of factors. To check the accuracy of the proposed method a recovery study on real samples was carried out.

Simultaneous determination of levodopa and benserazide by stopped-flow injection analysis and three-way multivariate calibration of kinetic-spectrophotometric data.

The simultaneous determination of levodopa and benserazide in pharmaceutical formulations is described, based on the application of multidimensional partial least-squares regression to the kinetic-spectrophotometric data provided by diode-array detection within a stopped-flow injection method where analytes react with periodate. Flow injection parameters were adequately optimized. Accurate analysis is performed with no sample pre-treatment steps, and with minimum experimental effort. Satisfactory recovery results were obtained on a number of synthetic and commercial samples, in the latter case including the comparison with liquid chromatography measurements.