Implementação e validação de um método para determinação de contaminantes em vinho por microextração em fase sólida e gc-ms/ms e sua correlação com a análise sensorial

Cada vez mais começa a notar-se, na indústria vitivinícola, uma grande preocupação com a qualidade dos seus produtos, motivada pela maior sensibilização e exigência dos consumidores. Deste modo, a presença de defeitos organoléticos no vinho representa uma fonte de perda financeira nesta indústria, pelo que o seu controlo se torna indispensável para que se obtenha um produto de elevada qualidade. Neste sentido, torna-se interessante desenvolver um método de análise que seja rápido de forma a permitir a quantificação simultânea das moléculas identificadas como principais responsáveis pelos distúrbios olfativos dos vinhos. Assim, este trabalho surge com o objetivo de implementar e validar um método para a determinação de contaminantes em vinho por microextração em fase sólida (SPME) e cromatografia gasosa acoplada à espetrometria de massa tandem (GC-MS/MS) e a sua correlação com a análise sensorial. A técnica de microextração em fase sólida é simples e rápida na medida em que não requer um pré-tratamento da amostra. Por sua vez, a análise por GC-MS permite identificar de forma clara os compostos em estudo, nomeadamente, 4-Etilfenol (4-EP), 4-Etilguaiacol (4-EG), 2,4,6-Tricloroanisol (TCA), 2,3,4,6-Tetracloroanisol (TeCA) e 2,4,6-Tribromoanisol (TBA). Foram realizados estudos de otimização das condições de extração, comparando as fibras 100 μm PDMS e 50/30 μm DVB/CAR/PDMS. Obtiveram-se resultados mais satisfatórios, em termos de resposta e da relação sinal/ruído, com a fibra 50/30 μm DVB/CAR/PDMS e estabeleceram-se como condições de extração 55ºC para a temperatura de incubação/extração, uma velocidade de agitação de 250 rpm e 60 minutos de tempo de extração. Ao longo deste trabalho, analisaram-se 50 amostras de vinho, das quais 48 eram amostras de Vinho Tinto do Douro e 2 de Vinho do Porto. Para validar a metodologia foram realizados estudos de linearidade, limiares analíticos, repetibilidade, precisão intermédia e recuperação. De um modo geral, obtiveram-se bons resultados ao nível da linearidade para as gamas de concentração escolhidas. Quanto aos limites de deteção e de quantificação, o 4-EP é o contaminante que apresenta uma gama de concentrações mais alta, notando-se limiares analíticos mais elevados, com valores próximos dos últimos níveis de concentração, oscilando entre 65 e 583 μg/L. No caso dos Anisóis, o TBA apresenta limites de deteção mais baixos, entre 0,4 e 17,0 ng/L. Os limiares analíticos foram validados com recurso a estudos de precisão intermédia e repetibilidade, cujos resultados se encontram dentro das especificações descritas no documento SANCO/10684/2009 (%RSD ≤ 30% para os Anisóis e %RSD ≤ 20% para os Fenóis Voláteis). Foram, ainda, realizados estudos de exatidão recorrendo a ensaios de recuperação e a ensaios interlaboratoriais. Muitas vezes conseguem-se boas recuperações, no entanto notam-se maiores dificuldades para o TBA e para o TeCA. Relativamente aos ensaios interlaboratoriais, verificam-se maiores discrepâncias para o 4-EP. Já os restantes contaminantes apresentam resultados, geralmente, satisfatórios (|z-score| ≤ 2).

ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

An embedded 1149.4 extension to support mixed-signal debugging

Debugging electronic circuits is traditionally done with bench equipment directly connected to the circuit under debug. In the digital domain, the difficulties associated with the direct physical access to circuit nodes led to the inclusion of resources providing support to that activity, first at the printed circuit level, and then at the integrated circuit level. The experience acquired with those solutions led to the emergence of dedicated infrastructures for debugging cores at the system-on-chip level. However, all these developments had a small impact in the analog and mixed-signal domain, where debugging still depends, to a large extent, on direct physical access to circuit nodes. As a consequence, when analog and mixed-signal circuits are integrated as cores inside a system-on-chip, the difficulties associated with debugging increase, which cause the time-to-market and the prototype verification costs to also increase. The present work considers the IEEE1149.4 infrastructure as a means to support the debugging of mixed-signal circuits, namely to access the circuit nodes and also an embedded debug mechanism named mixed-signal condition detector, necessary for watch-/breakpoints and real-time analysis operations. One of the main advantages associated with the proposed solution is the seamless migration to the system-on-chip level, as the access is done through electronic means, thus easing debugging operations at different hierarchical levels.

Sulphonamide-imprinted sol–gel materials as ionophores in potentiometric transduction

This work proposes different kind of solid-contact graphite-based electrodes for the selective determination of sulphonamides (SPHs) in pharmaceuticals, biological fluids and aquaculture waters. Sulfadiazine (SDZ) and sulfamethoxazole (SMX) were selected for this purpose for being the most representative compounds of this group. The template molecules were imprinted in sol–gel (ISG) and the resulting material was used as detecting element. This was made by employing it as either a sensing layer or an ionophore of PVC-based membranes and subsequent potentiometric transduction, a strategy never reported before. The corresponding non-imprinted sol–gel (NISG) membranes were used as blank. The effect of plasticizer and kind/charge of ionic lipophilic additive was also studied. The best performance in terms of slope, linearity ranges and signal reproducibility and repeatability was achieved by PVC membranes including a high dielectric constant plasticizer and 15 mg of ISG particles. The corresponding average slope was −51.4 and −52.4 mV/decade, linear responses were 9.0 × 10−6 and 1.7 × 10−5 M, and limits of detection were 0.74 and 1.3 μg/mL for SDZ and for SMX, respectively. Good selectivity with log Kpot < −0.3 was observed for carbonate, chloride, fluoride, hydrogenocarbonate, nitrate, nitrite, phosphate, cyanide, sulfate, borate, persulphate, citrate, tartrate, salicylate, tetracycline, ciprofloxacin, sulphamerazine, sulphatiazole, dopamine, glucose, galactose, cysteine and creatinine. The best sensors were successfully applied to the analysis of real samples with relative errors ranging from −6.8 to + 3.7%.

Myoelectric Signal Monitoring System

The Electromyography (EMG) is an important tool for gait analyzes and disorders diagnoses. Traditional methods involve equipment that can disturb the analyses, being gradually substituted by different approaches, like wearable and wireless systems. The cable replacement for autonomous systems demands for technologies capable of meeting the power constraints. This work presents the development of an EMG and kinematic data capture wireless module, designed taking into account power consumption issues. This module captures and converts the analog myoeletric signal to digital, synchronously with the capture of kinetic information. Both data are time multiplexed and sent to a PC via Bluetooth link. The work carried out comprised the development of the hardware, the firmware and a graphical interface running in an external PC. The hardware was developed using the PIC18F14K22, a low power family of microcontrollers. The link was established via Bluetooth, a protocol designed for low power communication. An application was also developed to recover and trace the signal to a Graphic User Interface (GUI), coordinating the message exchange with the firmware. Results were obtained which allowed validating the conceived system in static and with the subject performing short movements. Although it was not possible to perform the tests within more dynamic movements, it is shown that it is possible to capture, transmit and display the captured data as expected. Some suggestions to improve the system performance also were made.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.