On-line microwave-based preconcentration device for inductively coupled plasma atomic emission spectrometry: Application to the elemental analysis of spirit samples

A microwave-based thermal nebulizer (MWTN) has been employed for the first time as on-line preconcentration device in inductively coupled plasma atomic emission spectrometry (ICP-AES). By the appropriate selection of the experimental conditions, the MWTN could be either operated as a conventional thermal nebulizer or as on-line analyte preconcentration and nebulization device. Thus, when operating at microwave power values above 100 W and highly concentrated alcohol solutions, the amount of energy per solvent mass liquid unit (EMR) is high enough to completely evaporate the solvent inside the system and, as a consequence, the analyte is deposited (and then preconcentrated) on the inner walls of the MWTN capillary. When reducing the EMR to the appropriate value (e.g., by reducing the microwave power at a constant sample uptake rate) the retained analyte is swept along by the liquid-gas stream and an analyte-enriched aerosol is generated and next introduced into the plasma cell. Emission signals obtained with the MWTN operating in preconcentration-nebulization mode improved when increasing preconcentration time and sample uptake rate as well as when decreasing the nozzle inner diameter. When running with pure ethanol solution at its optimum experimental conditions, the MWTN in preconcentration-nebulization mode afforded limits of detection up to one order of magnitude lowers than those obtained operating the MWTN exclusively as a nebulizer. To validate the method, the multi-element analysis (i.e. Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Pb and Zn) of different commercial spirit samples in ICP-AES has been performed. Analyte recoveries for all the elements studied ranged between 93% and 107% and the dynamic linear range covered up to 4 orders of magnitude (i.e. from 0.1 to 1000 μg L−1). In these analysis, both MWTN operating modes afforded similar results. Nevertheless, the preconcentration-nebulization mode permits to determine a higher number of analytes due to its higher detection capabilities.

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

This paper addresses the problem of the automatic recognition and classification of temporal expressions and events in human language. Efficacy in these tasks is crucial if the broader task of temporal information processing is to be successfully performed. We analyze whether the application of semantic knowledge to these tasks improves the performance of current approaches. We therefore present and evaluate a data-driven approach as part of a system: TIPSem. Our approach uses lexical semantics and semantic roles as additional information to extend classical approaches which are principally based on morphosyntax. The results obtained for English show that semantic knowledge aids in temporal expression and event recognition, achieving an error reduction of 59% and 21%, while in classification the contribution is limited. From the analysis of the results it may be concluded that the application of semantic knowledge leads to more general models and aids in the recognition of temporal entities that are ambiguous at shallower language analysis levels. We also discovered that lexical semantics and semantic roles have complementary advantages, and that it is useful to combine them. Finally, we carried out the same analysis for Spanish. The results obtained show comparable advantages. This supports the hypothesis that applying the proposed semantic knowledge may be useful for different languages.

Disposable electrochromic polyaniline sensor based on a redox response using a conventional camera: A first approach to handheld analysis

We present a disposable optical sensor for Ascorbic Acid (AA). It uses a polyaniline based electrochromic sensing film that undergoes a color change when exposed to solutions of ascorbic acid at pH 3.0. The color is monitored by a conventional digital camera working with the hue (H) color coordinate. The electrochromic film was deposited on an Indium Tin Oxide (ITO) electrode by cyclic voltammetry and then characterized by atomic force microscopy, electrochemical and spectroscopic techniques. An estimation of the initial rate of H, as ΔH/Δt, is used as the analytical parameter and resulted in the following logarithmic relationship: ΔH/Δt = 0.029 log[AA] + 0.14, with a limit of detection of 17 μM. The relative standard deviation when using the same membrane 5 times was 7.4% for the blank, and 2.6% (for n = 3) on exposure to ascorbic acid in 160 μM concentration. The sensor is disposable and its applicability to pharmaceutical analysis was demonstrated. This configuration can be extended for future handheld configurations.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.