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.

Influence of long-term wearing of unstable shoes on compensatory control of posture: An electromyography-based analysis

Purpose: This study investigated the influence of long-term wearing of unstable shoes (WUS) on compensatory postural adjustments (CPA) to an external perturbation. Methods: Participants were divided into two groups: one wore unstable shoes while the other wore conventional shoes for 8 weeks. The ground reaction force signal was used to calculate the anterior– posterior (AP) displacement of the centre of pressure (CoP) and the electromyographic signal of gastrocnemius medialis (GM), tibialis anterior (TA), rectus femoris (RF) and biceps femoris (BF) muscles was used to assess individual muscle activity, antagonist co-activation and reciprocal activation at the joint (TA/GM and RF/(BF + GM) pairs) and muscle group levels (ventral (TA + RF)/dorsal (GM + BF) pair) within time intervals typical for CPA. The electromyographic signal was also used to assess muscle latency. The variables described were evaluated before and after the 8-week period while wearing the unstable shoes and barefoot. Results: Long-term WUS led to: an increase of BF activity in both conditions (barefoot and wearing the unstable shoes); a decrease of GM activity; an increase of antagonist co-activation and a decrease of reciprocal activation level at the TA/GM and ventral/dorsal pairs in the unstable shoe condition. Additionally, WUS led to a decrease in CoP displacement. However, no differences were observed in muscle onset and offset. Conclusion: Results suggest that the prolonged use of unstable shoes leads to increased ankle and muscle groups’ antagonist co-activation levels and higher performance by the postural control system.

BANMAC: an opportunistic MAC protocol for reliable communications in body area networks

We consider reliable communications in Body Area Networks (BAN), where a set of nodes placed on human body are connected using wireless links. In order to keep the Specific Absorption Rate (SAR) as low as possible for health safety reasons, these networks operate in low transmit power regime, which however, is known to be error prone. It has been observed that the fluctuations of the Received Signal Strength (RSS) at the nodes of a BAN on a moving person show certain regularities and that the magnitude of these fluctuations are significant (5 - 20 dB). In this paper, we present BANMAC, a MAC protocol that monitors and predicts the channel fluctuations and schedules transmissions opportunistically when the RSS is likely to be higher. The MAC protocol is capable of providing differentiated service and resolves co-channel interference in the event of multiple co-located BANs in a vicinity. We report the design and implementation details of BANMAC integrated with the IEEE 802.15.4 protocol stack. We present experimental data which show that the packet loss rate (PLR) of BANMAC is significantly lower as compared to that of the IEEE 802.15.4 MAC. For comparable PLR, the power consumption of BANMAC is also significantly lower than that of the IEEE 802.15.4. For co-located networks, the convergence time to find a conflict-free channel allocation was approximately 1 s for the centralized coordination mechanism and was approximately 4 s for the distributed coordination mechanism.

A lightweight indoor localization model based on motley-keenan and COST

This paper presents a novel approach to WLAN propagation models for use in indoor localization. The major goal of this work is to eliminate the need for in situ data collection to generate the Fingerprinting map, instead, it is generated by using analytical propagation models such as: COST Multi-Wall, COST 231 average wall and Motley- Keenan. As Location Estimation Algorithms kNN (K-Nearest Neighbour) and WkNN (Weighted K-Nearest Neighbour) were used to determine the accuracy of the proposed technique. This work is based on analytical and measurement tools to determine which path loss propagation models are better for location estimation applications, based on Receive Signal Strength Indicator (RSSI).This study presents different proposals for choosing the most appropriate values for the models parameters, like obstacles attenuation and coefficients. Some adjustments to these models, particularly to Motley-Keenan, considering the thickness of walls, are proposed. The best found solution is based on the adjusted Motley-Keenan and COST models that allows to obtain the propagation loss estimation for several environments.Results obtained from two testing scenarios showed the reliability of the adjustments, providing smaller errors in the measured values values in comparison with the predicted values.

Low-loss austempered ductile iron gears: experimental evaluation comparing materials and lubricants

An experimental study to evaluate the power dissipation of gears was performed. Three low-loss gear models were manufactured using standard 20° pressure angle tools. Austempered ductile iron (ADI) and 20MnCr5 carburized steel gears were tested in an FZG gear test machine using mineral, ester and polyalphaolephine (PAO)-based oils. The results compare power dissipation, the influence of different tooth flank geometries, materials and lubricants. This work concludes that conventional power-transmission gears can be replaced by these improved and more efficient low–loss models, which can be produced using common tools and that steel gears can be successfully replaced by austempered ductile iron gears.

Low torque loss gears: austempered ductile iron versus carburized steel

Low-loss power transmission gears operate at lower temperature than conventional ones because their teeth geometry is optimized to reduce friction. The main objective of this work is to compare the operating stabilization temperature and efficiency of low-loss austempered ductile iron (ADI) and carburized steel gears. Three different low-loss tooth geometries were adopted (types 311, 411 and 611, all produced using standard 20° pressure angle tools) and corresponding steel and ADI gears were tested in a FZG machine. The results obtained showed that low-loss geometries had a significant influence on power loss, gears 611 generating lower power loss than gears 311. At low speeds (500 and 1000 rpm) and high torque ADI gears generated lower power loss than steel gears. However, at high speed and high torque (high input power and high stabilization temperature) steel gears had better efficiency.

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.

Automated synthesis procedure of RF discrete tuning differential capacitance circuits

The paper presents a RFDSCA automated synthesis procedure. This algorithm determines several RFDSCA circuits from the top-level system specifications all with the same maximum performance. The genetic synthesis tool optimizes a fitness function proportional to the RFDSCA quality factor and uses the epsiv-concept and maximin sorting scheme to achieve a set of solutions well distributed along a non-dominated front. To confirm the results of the algorithm, three RFDSCAs were simulated in SpectreRF and one of them was implemented and tested. The design used a 0.25 mum BiCMOS process. All the results (synthesized, simulated and measured) are very close, which indicate that the genetic synthesis method is a very useful tool to design optimum performance RFDSCAs.

Influence of grease formulation on thrust bearings power loss

The minimization of the power loss and the use of the biodegradable greases have attracting considerable attention. To compare the energetic performance of biodegradable lubricant greases, power loss tests were performed on a modified four-ball machine. A correlation between the grease formulation and rheology was established with its energetic performance

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

Automated Synthesis Procedure of RF Discrete Tuning Differential Capacitance Circuits

The paper presents a RFDSCA automated synthesis procedure. This algorithm determines several RFDSCA circuits from the top-level system specifications all with the same maximum performance. The genetic synthesis tool optimizes a fitness function proportional to the RFDSCA quality factor and uses the epsiv-concept and maximin sorting scheme to achieve a set of solutions well distributed along a non-dominated front. To confirm the results of the algorithm, three RFDSCAs were simulated in SpectreRF and one of them was implemented and tested. The design used a 0.25 mum BiCMOS process. All the results (synthesized, simulated and measured) are very close, which indicate that the genetic synthesis method is a very useful tool to design optimum performance RFDSCAs.

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.