Optimization of the Microwave-Assisted Saponification and Extraction of Organic Pollutants from Marine Biota Using Experimental Design and Artificial Neural Networks

Several improvements in sample pretreatment for the determination of organic pollutants (i.e. n-alkanes, polycyclic aromatic hydrocarbons, PAHs) in marine biota (mussels) are presented. The use of liquid nitrogen and homogenization of the samples are shown to be an alternative to the time consuming liophilization step required for the analysis of biota samples. Microwave-assisted hydrolysis and extraction are combined to isolate organic pollutants (19 n-alkanes and 27 PAHs) from biota matrices. Experimental design (ED) and artificial neural networks (ANNs) were used to optimize the experimental conditions. NIST-CRM 2978 was used to test the validity of the developed method which shows a good agreement with certified values.     

Sequential injection system with higher dimensional electrochemical sensor signals Part 1. Voltammetric e-tongue for the determination of oxidizable compounds

A sequential injection analysis (SIA) system was developed with the aim of obtaining an automatic and versatile way to prepare standards needed in the study of systems with higher dimensional sensor signals. To illustrate this, different analytical techniques were used in determinations of several analytes. Automated potentiometric calibrations of different potentiometric sensors, with and without interference, were carried out. Useful determinations of selectivity coefficients with two degrees of freedom were obtained. Simultaneous voltammetric determinations have also been done. Firstly, simultaneous determinations of lead and cadmium, using epoxy-graphite composite as the working electrode, have enabled a separate calibration for each metal to be obtained. Next, a voltammetric electronic tongue was designed and applied to the determination of oxidizable species. The use of artificial neural networks has solved the overlapped signal of ascorbic acid, 4-aminophenol and 4-acetamidophenol (paracetamol). A set of 63 data points was prepared automatically and has facilitated the training of an electronic tongue for these three analytes. Accurate predictions of test solutions, in the range of 12–410 μM for ascorbic acid, 17–530 μM for 4-aminophenol and 10–420 μM for paracetamol, have been achieved with RMSEs lower than 0.10 μM.     

Effects of structural imperfections on the dynamic mechanical response of main-chain smectic elastomers

We examine the influence of structural imperfections on mechanical damping in polydomain smectic main-chain liquid crystalline elastomers (MCLCE) subjected to small strain oscillatory shear. The mechanical loss factor tan δ = G″(ω)/G′(ω) exhibits a strong maximum (tan δ ≈ 1.0) near the smectic-isotropic (clearing) transition. “Optimal” elastomers that exhibit minimal equilibrium swelling in a good solvent are compared with highly swelling “imperfect elastomers” that contain higher concentrations of structural imperfections such as pendant chains. For the imperfect elastomers, tan δ is markedly enhanced in the isotropic state because of relaxation of pendant chains and other imperfections. However, within the smectic state, the magnitude of tan δ and its temperature dependence are similar for optimal and imperfect elastomers at ω = 1 Hz. The prominent loss peak near the clearing transition arises from segment-level relaxations that are insensitive to the details of chain connectivity. Smectic MCLCE can be tailored for applications as vibration-damping materials by manipulating the clearing transition temperature through the backbone structure or by deliberate introduction of structural imperfections such as pendant chains. © 2007 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 45: 3267–3276, 2007     

Radiation synthesis of n-vinyl 2-pyrrolidone/acrylonitrile interpenetrating polymer networks and their use in uranium recovery from aqueous systems

Interpenetrating Polymer Networks (IPNs) based on Poly n-vinyl 2-pyrrolidone (PVP) and Acrylonitrile (AN) were prepared by irradiating PVP solutions prepared in AN. PVP/AN mixtures were irradiated by ⁶⁰Co-γ rays at room temperature at a dose rate of 0.5 kGy/hour. IPNs were characterized by using FT-IR and Thermal Analysis techniques. The chelating adsorbents containing amidoxime groups were prepared by the reaction of these IPNs with hydroxylamine in aqueous NaOH solution at 50°C. These amidoxime containing adsorbents were used in adsorption studies for the recovery of uranium from aqueous systems. The adsorption capacity of an IPN with equivolume fraction of PVP and amidoximated PAN was found to be 750mg UO₂²⁺/g dry amidoximated IPN.     

Sorption of binary liquid mixtures on polymer networks Part I. Determination of surface excess isotherms and free energy functions

Two groups of polymer networks (polymer resins) are investigated by selective liquid sorption fromn-propanol-water mixtures. Group 1 consists of gel polymerized polar (hydrophilic) ion exchangers which swell in the binary liquid mixture. Group 2 consists of non-polar, non-swelling, macroporous resins. The free energy isotherms accompanying the sorption processes are calculated from the excess isotherms and the bulk activities. The adsorption excess free energies reveal the differences in polarity of the polymer network.     

Sequential injection system with higher dimensional electrochemical sensor signals Part 2. Potentiometric e-tongue for the determination of alkaline ions

An intelligent, automatic system based on an array of non-specific-response chemical sensors was developed. As a great amount of information is required for its correct modelling, we propose a system generating it itself. The sequential injection analysis (SIA) technique was chosen as it enables the processes of training, calibration, validation and operation to be automated simply. Detection was carried out using an array of potentiometric sensors based on PVC membranes of different selectivity. The diluted standard solutions needed for system learning and response modelling are automatically prepared from more concentrated standards. The electrodes used were characterised with respect to one and two analytes, by means of high-dimensionality calibrations, and the response surface of each was represented; this characterisation enabled an interference study of great practical utility. The combined response was modelled by means of artificial neural networks (ANNs), and thus it was possible to obtain an automated electronic tongue based on SIA. In order to identify the ANN which provided the best model of the electrode responses, some of the network's parameters were optimised and its usefulness in determining NH₄⁺, K⁺ and Na⁺ ions in synthetic samples was then tested. Finally, it was used to determine these ions in commercial fertilisers, the obtained results being compared with reference methods.     

Light traffic for workload in queues

General exact light traffic limit theorems are given for the distribution of steadystate workloadV, in open queueing networks having as input a general stationary ergodic marked point process {(t _n ,K _n )n0 (where t_n denotes the arrival time and K_n the routing and service times of the nth customer). No independence assumptions of any kind are required of the input. As the light traffic regime, it is only required that the Palm distribution for the exogenous interarrival time converges weakly to infinity (while the service mechanism is not allowed to change much). As is already known in the context of a single-server queue, work is much easier to deal with mathematically in light traffic than is customer delayD, and consequently, our results are far more general than existing results forD. We obtain analogous results for multi-channel and infinite-channel queues. In the context of open queueing networks, we handle both the total workload in the network as well as the workload at isolated nodes.Research supported in part by the Japan Society for the Promotion of Science during the author's fellowship in Tokyo, and by NSF Grant DDM 895 7825.     

A multineuron interaction model for neural networks

A multineuron interaction model (RS model) with an energy function given by the product of the squared distances in phase space between the state of the net and the stored patterns is studied in detail within a mean-field approach. Two limits are considered: when the patterns and antipatterns are stored (as in the Hopfield model), PAS case, and when only the patterns are taken into account, OPS case. TheT=0 solutions for the proper memories are exactly obtained for all finite values of, as a consequence of the energy function: whenever one of the overlaps is exactly one the corresponding equations decouple and no configuration average is required. Special interest is focused on the OPS situation, which presents a peculiar phase space topology. On the other hand, the PAS configuration recovers the Hopfield model in the appropriate limit, while keeping associative memory abilities far beyond the critical values of other models when the full Hamiltonian is considered.