Determination of flonicamid and its metabolites in bell pepper using ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry (Orbitrap)

The development and validation of a method to determine flonicamid and its metabolites as TFNA (4-trifluoromethylnicotinic acid), TFNG (N-(4-trifluoromethylnicotinoyl) glycine) and TFNA-AM (4-trifluoromethylnicotinamide) in bell pepper samples by ultra-high-performance liquid chromatography coupled to Orbitrap mass spectrometry (UHPLC-Orbitrap-MS) was performed. A fast and simple extraction procedure with acidified acetonitrile and salts (magnesium sulfate and sodium chloride) was used. The methodology was validated, checking for specificity, recovery, precision, limits of detection (LODs) and limits of quantification (LOQs). The recoveries ranged from 84% to 98%, and precisions were lower than 17%. Finally, LODs ranged from 1 µg kg^–1 (flonicamid) to 6 µg kg^–1 (TFNA-AM), while LOQs ranged from 10 µg kg^–1 (flonicamid) to 30 µg kg^–1 (TFNA-AM). Bell pepper samples were analysed and concentrations up to 98 µg kg^–1 (flonicamid) were detected, although the sum of flonicamid and metabolites did not exceed the maximum residue limit (MRL) set by the European Union.     

Automated resolution of connector architectures using constraint solving (ARCAS method)

In current software systems, connectors play an important role by encapsulating the communication and coordination logic. Since they share common patterns (elements) depending on characteristics of the connections, the elements can be predefined and reused. A method of connector implementation based on a composition of predefined elements naturally comprises two steps: resolution of the connector architecture, and creation of the actual connector code based on the architecture. However, manual resolution of a connector architecture is very difficult due to the number of factors to be considered. Thus, the challenge is to come up with an automated method, able to address all the important factors. In this paper, we present a method for automated resolution of connector architectures based on constraint solving techniques. We exploit a propositional logic with relational calculus for defining a connector theory, a constraint specification reflecting both the predefined parts and the important resolution factors, and employ a constraint solver to find a suitable connector architecture as a model of the theory. As a proof of the concept, we show how the theory can be captured in the Alloy language and resolved via the Alloy Analyzer.     

An energy efficient middleware for an ad-hoc AAL wireless sensor network

DIA (Dispositivo Inteligente de Alarma, in Spanish) is an AAL (Ambient Assisted Living) system that allows to infer a potential dangerous action of an elderly person living alone at home. This inference is obtained by a specific sensorisation with sensor nodes (portables and fixes) and a reasoning layer embedded in a PC that learns of the users behaviour patterns and advices when actual one differs significantly of the normal patterns. In AAL systems, energy is a limited resource therefore sensor devices need to be properly managed to conserve energy. In this paper, we introduce the design and implementation of innovative and specific mechanisms at the sensory layer middleware which is capable of, first to discriminate spurious motion detections assuming that these signals do not resemble the patterns of real motion detections and, second to reduce the dynamics of messages by a sensor signal processing in order to compress the whole information in one single event. The middleware achieves power saving by modifying the raw information from sensors and adapting it to the predefined semantic of the reasoning layer. It manages the important task of data processing from sensors (raw information), and transfers the pre-processed information into the top layer of reasoning in a more energy efficient way. We also address the trade-off between reducing power consumption and reducing delay for incoming data. We present results from experiments using our implementation of these mechanisms at the middleware that comprises from node firmware to the PC driver. The number of messages of the proposed method with respect to the raw data is reduced by approximately 98.5%. The resources used in the PIR signal processing is reduced by approximately 85%. The resulting delay introduced is small (10–19 s) but system dynamics is slow enough to avoid contextualisation errors or reduction of system performance. We consider these results as very satisfactory.     

Assessment of the Use of NaClO as an Alternative to H2O2 in the Oxidant-Titanium Ore-Simulated Solar Light System for Thiabendazole Degradation

Topics in Catalysis - The use of the magnetic fraction (MF) of a low-grade titanium ore (TO) and two oxidants (H2O2 and NaClO), testing each one separately, were compared in photo-Fenton like...     

Nonwoven Ni–NiO/carbon fibers for electrochemical water oxidation

The development of technologically efficient anodes for water oxidation is crucial to improve hydrogen production via water splitting. Electrodes based on metallic active sites dispersed in carbon matrices have been shown to be an attractive way to attain this goal. However, challenges remain to prevent catalyst agglomeration that otherwise can result in a decrease of performance over time.In this work, we report an alternative and efficient method to produce nickel-nickel oxide nanoparticles-embedded in carbon nanofibers (Ni–NiO/C), by the solution blow spinning (SBS) process. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses show the carbon nanofibrillar matrix as a robust support, with well-dispersed nickel nanoparticles on the surface. The responses of the linear scanning voltammetry, cyclic voltammetry and electrochemical impedance spectroscopy demonstrate how a small fraction of nickel on the fiber surface (≈1.2–5.3%) is enough to promote substantial improvement in performance (η = 278 and 309 mV vs RHE for 10 mA cm^?2) and a significant turnover frequency (TOF) values of 1.38 (η = 278) and 1.30 s^?1 (η = 309). These promising results are correlated with a large amount of Ni³⁺ present on the fiber surfaces, as identified by X-ray Photoelectron Spectroscopy (XPS). This work provides a low-cost and rapid preparation technique that can be extended for the manufacture of a wide variety of electrodes based on metals supported on carbon nanofibers.