Anodic oxidation of mecoprop herbicide at lead dioxide

The electrochemical oxidation of an aqueous solution containing mecoprop (2-(2-methyl-4-chlorophenoxy)propionic acid) has been studied at PbO₂ anodes by cyclic voltammetry and bulk electrolysis. The influence of current density, hydrodynamic conditions, temperature and pH on the degradation rate and current efficiency is reported. The results obtained show that the use of PbO₂ leads to total mineralization of mecoprop due to the production of oxidant hydroxyl radical electrogenerated from water discharge. The current efficiency for the electro-oxidation of mecoprop is enhanced by low current density, high recycle flow-rates and high temperature. In contrast, the pH effect was not significant. It has also been observed that mecoprop decay kinetics follows a pseudo-first-order reaction and the rate constant increases with rising current density.     

Development of calibration models for quality control in the production of ethylene/propylene copolymers by FTIR spectroscopy,multivariate statistical tools,and artificial neural networks

Principal component regression (PCR), partial least squares (PLS), StepWise ordinary least squares regression (OLS), and back‐propagation artificial neural network (BP‐ANN) are applied here for the determination of the propylene concentration of a set of 83 production samples of ethylene–propylene copolymers from their infrared spectra. The set of available samples was split into (a) a training set, for models calculation; (b) a test set, for selecting the correct number of latent variables in PCR and PLS and the end point of the training phase of BP‐ANN; (c) a production set, for evaluating the predictive ability of the models. The predictive ability of the models is thus evaluated by genuine predictions. The model obtained by StepWise OLS turned out to be the best one, both in fitting and prediction. The study of the breakdown number of samples to be included in the training set showed that at least 52 experiments are necessary to build a reliable and predictive calibration model. It can be concluded that FTIR spectroscopy and OLS can be properly employed for monitoring the synthesis or the final product of ethylene–propylene copolymers, by predicting the concentration of propylene directly along the process line. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Assessment of the final metrological characteristics of a MOEMS-based NDIR spectrometer through system modeling and data processing

A model of a miniaturized non-dispersive infrared (NDIR) gas analysis system, aiming to predict the final system specifications, is presented. It comprises the different elements of the NDIR detector, including a surface micromachined Fabry-Perot tunable filter. These models have been used to estimate the response of the NDIR system to different gas mixtures. Multivariate regression methods like partial least squares allow recovering the true sample composition from the IR absorption spectra measured with the NDIR system, despite the limited selectivity of the filter. Combining model and data processing permits to predict the effect on the final system specification of design parameters. Here, we compare the effect of the technology used for the filter on the system errors.     

Aerobic degradation by white‐rot fungi of trichloroethylene (TCE) and mixtures of TCE and perchloroethylene (PCE)

BACKGROUND: Trichloroethylene (TCE) and perchloroethylene (PCE) are considered among the most important groundwater pollutants around the world. These compounds are usually found together in polluted environments but little is known about the ability of microorganisms to simultaneously degrade TCE and PCE. RESULTS: Data showed that several species of white‐rot fungi, including Trametes versicolor, Ganoderma lucidum, and Irpex lacteus, degrade substantial levels of TCE in pure culture. T. versicolor was chosen for further study since it degraded higher levels of TCE than the other organisms. Initial glucose concentration and reoxygenation of samples increased the amount of TCE dechlorination, but no significant difference in percentage TCE degradation was observed. T. versicolor was able to degrade 34.1 and 47.7% of PCE and TCE added as mixtures (containing 5 and 10 mg L⁻¹, respectively). CONCLUSIONS: The degradation ability of TCE was extended to other species of white‐rot fungi. Percentage degradation as well as chloride release from mixtures of TCE and PCE showed that T. versicolor degrades mixtures of TCE and PCE almost as well as its ability to degrade individually added TCE or PCE. The results suggest the potential promise of T. versicolor for bioremediation of TCE and PCE in the environment. Copyright © 2008 Society of Chemical Industry     

Kinetic modelling of textural changes in ready-to-eat breakfast cereals during soaking in semi-skimmed milk

Summary Ready‐to‐eat breakfast cereals immersed in milk undergo undesirable changes in texture because of sudden moisture uptake. The textural changes are ascribable to a plasticizing effect of water, which modifies the mechanical strength of products by softening the starch/protein matrix. In this work, some textural parameters of different cereal flakes were derived from the force–displacement curves monitored during 300 s of immersion in milk. Hardness loss, deformability increment and changes in the force–displacement curve profile were calculated and plotted against soaking time. The application of a sugar coating process to a model cereal flake increased the initial product hardness and improved the preservation of the textural parameters during immersion. The Peleg model closely fitted the experimental data, with regression coefficients from 0.967 to 0.999.     

Shear mode coupling and tilted grain growth of A1N thin films in BAW resonators.

Polycrystalline A1N thin films were deposited by RF reactive magnetron sputtering on Pt(111)/Ti electrode films. The substrates were tilted by an angle ranging from 40 degrees to 70 degrees with respect to the target normal. A low deposition temperature and a high sputter gas pressure were found ideal for tilted growth. The resulting grain tilt angle amounts to about half the substrate tilt angle. For coupling evaluation, 5 GHz solidly mounted resonator structures have been realized. The tilted grain A1N films exhibited a permittivity in the 9.5-10.5 range and loss tangent of 0.3%. Two shear modes as well as the longitudinal mode could be clearly identified. The coupling coefficient k2(eff) of the fundamental thickness shear mode (TS0) was found to be about 0.5%, which is compatible with a c-axis tilt of about 6 degrees.     

On the non-blocking conditions of self-routeing multistage interconnection networks

This paper studies the non-blocking conditions of a generic N × N multistage interconnection network, such as an omega network or an n-cube network, in which only one path connects any inlet to each outlet and different I/O paths can share interstage links. It is widely known that any of these networks is non-blocking for a compact and monotone pattern of k ≤ N I/O paths. Recently it has become very important to show the network non-blocking property for permutation sets, wider than the compact and monotone, which are usually encountered in broadband ATM networks. By using a new approach based on the concept of distance between I/O paths, we show here that these networks are non-blocking for a set of I/O paths obtained by shifting cyclically the inlets of a compact and monotone pattern of I/O paths by an arbitrary number of steps.     

Parameter identification for nonlinear systems: Guaranteed confidence regions through LSCR

In this paper we consider the problem of constructing confidence regions for the parameters of nonlinear dynamical systems. The proposed method uses higher order statistics and extends the LSCR (leave-out sign-dominant correlation regions) algorithm for linear systems introduced in Campi and Weyer [2005, Guaranteed non-asymptotic confidence regions in system identification. Automatica 41(10), 1751-1764. Extended version available at 〈http://www.ing.unibs.it/∼campi〉]. The confidence regions contain the true parameter value with a guaranteed probability for any finite number of data points. Moreover, the confidence regions shrink around the true parameter value as the number of data points increases. The usefulness of the proposed approach is illustrated on some simple examples.