Square wave adsorptive cathodic stripping voltarnmetry automated by sequential injection analysis - Potentialities and limitations exemplified by the determination of methyl parathion in water samples

This paper describes the development and evaluation of a sequential injection method to automate the determination of methyl parathion by square wave adsorptive cathodic stripping voltammetry exploiting the concept of monosegmented flow analysis to perform in-line sample conditioning and standard addition. Accumulation and stripping steps are made in the sample medium conditioned with 40 mmol L-1 Britton-Robinson buffer (pH 10) in 0.25 mol L-1 NaNO3. The homogenized mixture is injected at a flow rate of 10 mu Ls(-1) toward the flow cell, which is adapted to the capillary of a hanging drop mercury electrode. After a suitable deposition time, the flow is stopped and the potential is scanned from -0.3 to -1.0 V versus Ag/AgCl at frequency of 250 Hz and pulse height of 25 mV The linear dynamic range is observed for methyl parathion concentrations between 0.010 and 0.50 mgL(-1), with detection and quantification limits of 2 and 7 mu gL(-1), respectively. The sampling throughput is 25 h(-1) if the in line standard addition and sample conditioning protocols are followed, but this frequency can be increased up to 61 h(-1) if the sample is conditioned off-line and quantified using an external calibration curve. The method was applied for determination of methyl parathion in spiked water samples and the accuracy was evaluated either by comparison to high performance liquid chromatography with UV detection, or by the recovery percentages. Although no evidences of statistically significant differences were observed between the expected and obtained concentrations, because of the susceptibility of the method to interference by other pesticides (e.g., parathion, dichlorvos) and natural organic matter (e.g., fulvic and humic acids), isolation of the analyte may be required when more complex sample matrices are encountered. (C) 2007 Elsevier B.V. All rights reserved.

Phenol-furfural resins to elaborate composites, reinforced with sisal fibers - Molecular analysis of resin and properties of composites

Resol type resins were prepared in alkaline conditions (potassium hydroxide or potassium carbonate) using furfural obtained by acid hydrolysis of abundant renewable resources from agricultural and forestry waste residues. The structures of the resins were fully determined by H-1, C-13, and 2D NMR spectrometries with the help of four models compounds synthesized specially for this study. MALDI-Tof mass spectrometry experiments indicated that a majority of linear oligomers and a minority of cyclic ones constituted them. Composites were prepared with furfural-phenol resins and sisal fibers. These fibers were chosen mainly because they came from natural lignocellulosic material and they presented excellent mechanical microscopy images indicated that the composites displayed excellent adhesion between resin and fibers. Impact strength measurement showed that mild conditions were more suitable to prepare thermosets. Nevertheless, mild conditions induced a high-diffusion coefficient for water absorption by composites. Composites with good properties could be prepared using high proportion of materials obtained from biomass without formaldehyde. (c) 2008 Wiley Periodicals, Inc.

Ionized-air-treated curaua fibers as reinforcement for phenolic matrices

Curaua fibers were treated with ionized air to improve the fiber/phenolic matrix adhesion.The treatment with ionized air did not change the thermal stability of the fibers. The impact strength increased with increase in the fiber treatment time. SEM micrographs of the fibers showed that the ionized air treatment led to separation of the fiber bundles. Treatment for 12 h also caused a partial degradation of the fibers, which prompted the matrix to transfer the load to a poorer reinforcing agent during impact, thereby decreasing the impact strength of the related composite. The composites reinforced with fibers treated with ionized air absorbed less water than those reinforced with untreated fibers.

Determination of carbaryl in tomato ""in natura"" using an amperometric biosensor based on the inhibition of acetylcholinesterase activity

This work reports the utilization of two methodologies for carbaryl determination in tomatoes. The measurements were carried out using an amperometric biosensor technique based on the inhibition of acetylcholinesterase activity due to carbaryl adsorption and a HPLC procedure. The electrochemical experiments were performed in 0.1 mol L-1 phosphate buffer solutions at pH 7.4 with an incubation time of 8 min. The analytical curve obtained in pure solutions showed excellent linearity in the 5.0 x 10(-5) to 75 x 10(-5) mol L-1 range, with the limit of detection at 0.4 x 10(-3) gL(-1). The application of such a methodology in tomato samples involved solely liquidising the samples, which were spiked with 6.0 x 10(-6) and 5.0 x 10(-5) mol L-1 carbaryl. Recovery in such samples presented values of 99.0 and 92.4%, respectively. In order to obtain a comparison, HPLC experiments were also conducted under similar conditions. However, the tomato samples have to be manipulated by an extraction procedure (MSPD), which yielded much lower recovery values (78.3 and 84.8%, respectively). On the other hand, the detection limit obtained was much lower than that for the biosensor, i.e., 3.2 x 10(-6) g L-1. Finally, the biosensor methodology was employed to analyze carbaryl directly inside the tomato, without any previous manipulation. In this case, the biosensor was immersed in the tomato pulp, which had previously been spiked with the pesticide for 8 min, removed and inserted in the electrochemical cell. A recovery of 83.4% was obtained, showing very low interference of the matrix constituents. (C) 2007 Elsevier B.V. All rights reserved.

Valorization of an Industrial Organosolv-Sugarcane Bagasse Lignin: Characterization and Use as a Matrix in Biobased Composites Reinforced With Sisal Fibers

In the present study, the main focus was the characterization and application of the by-product lignin isolated through an industrial organosolv acid hydrolysis process from sugarcane bagasse, aiming at the production of bioethanol. The sugarcane lignin was characterized and used to prepare phenolic-type resins. The analysis confirmed that the industrial sugarcane lignin is of HGS type, with a high proportion of the less substituted aromatic ring p-hydroxyphenyl units, which favors further reaction with formaldehyde. The lignin-formaldehyde resins were used to produce biobased composites reinforced with different proportions of randomly distributed sisal fibers. The presence of lignin moieties in both the fiber and matrix increases their mutual affinity, as confirmed by SEM images, which showed good adhesion at the biocomposite fiber/matrix interface. This in turn allowed good load transference from the matrix to the fiber, leading to biobased composites with good impact strength (near 500 J m(-1) for a 40 wt% sisal fiber-reinforced composite). The study demonstrates that sugarcane bagasse lignin obtained from a bioethanol plant can be used without excessive purification in the preparation of lignocellulosic fiber-reinforced biobased composites displaying high mechanical properties. Biotechnol. Bioeng. 2010;107: 612-621. (C) 2010 Wiley Periodicals, Inc.

Evaluation of the QuEChERS Method and Gas Chromatography-Mass Spectrometry for the Analysis Pesticide Residues in Water and Sediment

A method for the determination of pesticide residues in water and sediment was developed using the QuEChERS method followed by gas chromatography - mass spectrometry. The method was validated in terms of accuracy, specificity, linearity, detection and quantification limits. The recovery percentages obtained for the pesticides in water at different concentrations ranged from 63 to 116%, with relative standard deviations below 12%. The corresponding results from the sediment ranged from 48 to 115% with relative standard deviations below 16%. The limits of detection for the pesticides in water and sediment were below 0.003 mg L(-1) and 0.02 mg kg(-1), respectively.

Estimation of Parameters in Random Effect Models with Incidence Matrix Uncertainty

Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.

Exploratory semiparametric analysis of two-dimensional diffusions in finance

We examine bivariate extensions of Aït-Sahalia’s approach to the estimation of univariate diffusions. Our message is that extending his idea to a bivariate setting is not straightforward. In higher dimensions, as opposed to the univariate case, the elements of the Itô and Fokker-Planck representations do not coincide; and, even imposing sensible assumptions on the marginal drifts and volatilities is not sufficient to obtain direct generalisations. We develop exploratory estimation and testing procedures, by parametrizing the drifts of both component processes and setting restrictions on the terms of either the Itô or the Fokker-Planck covariance matrices. This may lead to highly nonlinear ordinary differential equations, where the definition of boundary conditions is crucial. For the methods developed, the Fokker-Planck representation seems more tractable than the Itô’s. Questions for further research include the design of regularity conditions on the time series dependence in the data, the kernels actually used and the bandwidths, to obtain asymptotic properties for the estimators proposed. A particular case seems promising: “causal bivariate models” in which only one of the diffusions contributes to the volatility of the other. Hedging strategies which estimate separately the univariate diffusions at stake may thus be improved.

We're Chained: an analysis of systemic risk in finance

This dissertation presents two papers on how to deal with simple systemic risk measures to assess portfolio risk characteristics. The first paper deals with the Granger-causation of systemic risk indicators based in correlation matrices in stock returns. Special focus is devoted to the Eigenvalue Entropy as some previous literature indicated strong re- sults, but not considering different macroeconomic scenarios; the Index Cohesion Force and the Absorption Ratio are also considered. Considering the S&P500, there is not ev- idence of Granger-causation from Eigenvalue Entropies and the Index Cohesion Force. The Absorption Ratio Granger-caused both the S&P500 and the VIX index, being the only simple measure that passed this test. The second paper develops this measure to capture the regimes underlying the American stock market. New indicators are built using filtering and random matrix theory. The returns of the S&P500 is modelled as a mixture of normal distributions. The activation of each normal distribution is governed by a Markov chain with the transition probabilities being a function of the indicators. The model shows that using a Herfindahl-Hirschman Index of the normalized eigenval- ues exhibits best fit to the returns from 1998-2013.

Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry combined with solid phase microextraction as a powerful tool for quantification of ethyl carbamate in fortified wines. The case study of Madeira wine

An analytical methodology based on headspace solid phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (GC × GC–ToFMS) was developed for the identification and quantification of the toxic contaminant ethyl carbamate (EC) directly in fortified wines. The method performance was assessed for dry/medium dry and sweet/medium sweet model wines, and for quantification purposes, calibration plots were performed for both matrices using the ion extraction chromatography (IEC) mode (m/z 62). Good linearity was obtained with a regression coefficient (r2) higher than 0.981. A good precision was attained (R.S.D. <20%) and low detection limits (LOD) were achieved for dry (4.31 μg/L) and sweet (2.75 μg/L) model wines. The quantification limits (LOQ) and recovery for dry wines were 14.38 μg/L and 88.6%, whereas for sweet wines were 9.16 μg/L and 99.4%, respectively. The higher performance was attainted with sweet model wine, as increasing of glucose content improves the volatile compound in headspace, and a better linearity, recovery and precision were achieved. The analytical methodology was applied to analyse 20 fortified Madeira wines including different types of wine (dry, medium dry, sweet, and medium sweet) obtained from several harvests in Madeira Island (Portugal). The EC levels ranged from 54.1 μg/L (medium dry) to 162.5 μg/L (medium sweet).

Optimisation of stir bar sorptive extraction and liquid desorption combined with large volume injection-gas chromatography–quadrupole mass spectrometry for the determination of volatile compounds in wines

Stir bar sorptive extraction and liquid desorption followed by large volume injection coupled to gas chromatography–quadrupole mass spectrometry (SBSE–LD/LVI-GC–qMS) had been applied for the determination of volatiles in wines. The methodology was optimised in terms of extraction time and influence of ethanol in the matrix; LD conditions, and instrumental settings. The optimisation was carried out by using 10 standards representative of the main chemical families of wine, i.e. guaiazulene, E,E-farnesol, β-ionone, geranylacetone, ethyl decanoate, β-citronellol, 2-phenylethanol, linalool, hexyl acetate and hexanol. The methodology shows good linearity over the concentration range tested, with correlation coefficients higher than 0.9821, a good reproducibility was attained (8.9–17.8%), and low detection limits were achieved for nine volatile compounds (0.05–9.09 μg L−1), with the exception of 2-phenylethanol due to low recovery by SBSE. The analytical ability of the SBSE–LD/LVI-GC–qMS methodology was tested in real matrices, such as sparkling and table wines using analytical curves prepared by using the 10 standards where each one was applied to quantify the structurally related compounds. This methodology allowed, in a single run, the quantification of 67 wine volatiles at levels lower than their respective olfactory thresholds. The proposed methodology demonstrated to be easy to work-up, reliable, sensitive and with low sample requirement to monitor the volatile fraction of wine.

Simultaneous analysis of free amino acids and biogenic amines in honey and wine samples using in loop orthophthalaldeyde derivatization procedure

This work presents a RP-HPLC method for the simultaneous quantification of free amino acids and biogenic amines in liquid food matrices and the results of the application to honey and wine samples obtained from different production processes and geographic origins. The developed methodology is based on a pre-column derivatization with o-phthaldialdehyde carried out in the sample injection loop. The compounds were separated in a Nova-Pack RP-C18 column (150 mm × 3.9 mm, 4 μm) at 35 °C. The mobile phase used was a mixture of phase A: 10 mM sodium phosphate buffer (pH 7.3), methanol and tetrahydrofuran (91:8:1); and phase B: methanol and phosphate buffer (80:20), with a flow rate of 1.0 ml/min. Fluorescence detection was used at an excitation wavelength of 335 nm and an emission wavelength of 440 nm. The separation and quantification of 19 amino acids and 6 amines was carried out in a single run as their OPA/MCE derivatives elute within 80 min, ensuring a reproducible quantification. The method showed to be adequate for the purpose, with an average RSD of 2% for the different amino acids; detection limits varying between 0.71 mg/l (Asn) and 8.26 mg/l (Lys) and recovery rates between 63.0% (Cad) and 98.0% (Asp). The amino acids present at the highest concentration in honey and wine samples were phenylalanine and arginine, respectively. Only residual levels of biogenic amines were detected in the analysed samples.

Evaluation of the genotoxicity of cellulose nanofibers

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)