Interlaboratory validation of an environmental monitoring method for trace analysis of endocrine disrupting compounds

Environmental pollution continues to be an emerging study field, as there are thousands of anthropogenic compounds mixed in the environment whose possible mechanisms of toxicity and physiological outcomes are of great concern. Developing methods to access and prioritize the screening of these compounds at trace levels in order to support regulatory efforts is, therefore, very important. A methodology based on solid phase extraction followed by derivatization and gas chromatography-mass spectrometry analysis was developed for the assessment of four endocrine disrupting compounds (EDCs) in water matrices: bisphenol A, estrone, 17b-estradiol and 17a-ethinylestradiol. The study was performed, simultaneously, by two different laboratories in order to evaluate the robustness of the method and to increase the quality control over its application in routine analysis. Validation was done according to the International Conference on Harmonisation recommendations and other international guidelines with specifications for the GC-MS methodology. Matrix-induced chromatographic response enhancement was avoided by using matrix-standard calibration solutions and heteroscedasticity has been overtaken by a weighted least squares linear regression model application. Consistent evaluation of key analytical parameters such as extraction efficiency, sensitivity, specificity, linearity, limits of detection and quantification, precision, accuracy and robustness was done in accordance with standards established for acceptance. Finally, the application of the optimized method in the assessment of the selected analytes in environmental samples suggested that it is an expedite methodology for routine analysis of EDC residues in water matrices.

Neural networks for condition monitoring of wind turbines gearbox

Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.

The importance of control monitoring systems in wind parks maintenance

The objective of every wind energy producer is to reduce operational costs associated to the production as a way to increase profits. One other issue that must be looked carefully is the equipment maintenance. Increase the availability of wind turbines by reducing the downtime associated to failures is a good strategy to achieve the main goal of increase profits. As a way to help in the definition of the best maintenance strategies, condition monitoring systems (CMS) have an important role to play. Informatics tools to make the condition monitoring of the wind turbines were developed and are now being installed as a way to help producers reducing the operational costs. There are a lot of developed systems to do the monitoring of a wind turbine or the whole wind park, in this paper will be made an overview of the most important systems.

Caracterização de Particulas de Desgaste do Rolamentos por Ferrografia e Ferrometria

Avarias em rolamentos são causas comuns de falhas em máquinas e equipamentos industriais. Portanto, é importante a aplicação de técnicas que permitam a deteção e a identificação do problema o mais cedo possível a fim de evitar a destruição do rolamento e consequente paragem da máquina. Logo, o processo de monitorização do estado dos rolamentos deve receber uma atenção especial no plano de manutenção de qualquer indústria. Este trabalho tem, assim, como principal objetivo a caracterização das partículas de desgaste provenientes de rolamentos através da análise dos seus lubrificantes por ferrometria e ferrografia analítica. Estas técnicas permitem identificar e caracterizar as várias partículas de desgaste presentes numa amostra de lubrificante, permitindo não só avaliar o grau de severidade do desgaste mas também identificar o tipo de desgaste predominante (fadiga, abrasão, corrosão,etc.), e até identificar os diferentes materiais das partículas que se podem associar a componentes específicos com falhas. A criação de uma base de dados para armazenar os resultados, os comentários e as informações mais importantes obtidos nos ensaios experimentais, assim como a análise de alguns casos práticos, foram também realizados no âmbito deste trabalho. Para desenvolver um conhecimento mais profundo sobre as técnicas utilizadas foi importante fazer uma análise aos diversos tipos de rolamentos, a sua lubrificação e as causas e tipos principais de avarias encontradas.

Static and hydrodynamic monitoring of citalopram based on its electro-oxidation behavior at a glassy-carbon surface

The electrooxidative behavior of citalopram (CTL) in aqueous media was studied by cyclic voltammetry (CV) and square-wave voltammetry (SWV) at a glassy-carbon electrode. The electrochemical behaviour of CTL involves two electrons and two protons in the irreversible and diffusion controlled oxidation of the tertiary amine group. The maximum analytical signal was obtained in a phosphate buffer (pH ¼ 8.2). For analytical purposes, an SWV method and a flow-injection analysis (FIA) system with amperometric detection were developed. The optimised SWV method showed a linear range between 1.10 10 5–1.20 10 4 molL 1, with a limit of detection (LOD) of 9.5 10 6 molL 1. Using the FIA method, a linear range between 2.00 10 6–9.00 10 5 molL 1 and an LODof 1.9 10 6 molL 1 were obtained. The validation of both methods revealed good performance characteristics confirming applicability for the quantification of CTL in several pharmaceutical products.

Distributed Forest Fire Monitoring Using Wireless Sensor Networks

Disaster management is one of the most relevant application fields of wireless sensor networks. In this application, the role of the sensor network usually consists of obtaining a representation or a model of a physical phenomenon spreading through the affected area. In this work we focus on forest firefighting operations, proposing three fully distributed ways for approximating the actual shape of the fire. In the simplest approach, a circular burnt area is assumed around each node that has detected the fire and the union of these circles gives the overall fire’s shape. However, as this approach makes an intensive use of the wireless sensor network resources, we have proposed to incorporate two in-network aggregation techniques, which do not require considering the complete set of fire detections. The first technique models the fire by means of a complex shape composed of multiple convex hulls representing different burning areas, while the second technique uses a set of arbitrary polygons. Performance evaluation of realistic fire models on computer simulations reveals that the method based on arbitrary polygons obtains an improvement of 20% in terms of accuracy of the fire shape approximation, reducing the overhead in-network resources to 10% in the best case.

Optimizing potentiometric ionophore and electrode design for environmental on-site control of antibiotic drugs: Application to sulfamethoxazole

Potentiometric sensors are typically unable to carry out on-site monitoring of environmental drug contaminants because of their high limits of detection (LODs). Designing a novel ligand material for the target analyte and managing the composition of the internal reference solution have been the strategies employed here to produce for the first time a potentiometric-based direct reading method for an environmental drug contaminant. This concept has been applied to sulfamethoxazole (SMX), one of the many antibiotics used in aquaculture practices that may occur in environmental waters. The novel ligand has been produced by imprinting SMX on the surface of graphitic carbon nanostructures (CN) < 500 nm. The imprinted carbon nanostructures (ICN) were dispersed in plasticizer and entrapped in a PVC matrix that included (or not) a small amount of a lipophilic additive. The membrane composition was optimized on solid-contact electrodes, allowing near-Nernstian responses down to 5.2 μg/mL and detecting 1.6 μg/mL. The membranes offered good selectivity against most of the ionic compounds in environmental water. The best membrane cocktail was applied on the smaller end of a 1000 μL micropipette tip made of polypropylene. The tip was then filled with inner reference solution containing SMX and chlorate (as interfering compound). The corresponding concentrations were studied for 1 × 10−5 to 1 × 10−10 and 1 × 10−3 to 1 × 10−8 mol/L. The best condition allowed the detection of 5.92 ng/L (or 2.3 × 10−8 mol/L) SMX for a sub-Nernstian slope of −40.3 mV/decade from 5.0 × 10−8 to 2.4 × 10−5 mol/L.

Rapid automated method for on-site determination of sulfadiazine in fish farming: a stainless steel veterinary syringe coated with a selective membrane of PVC serving as a potentiometric detector in a flow-injection-analysis system

Sulfadiazine is an antibiotic of the sulfonamide group and is used as a veterinary drug in fish farming. Monitoring it in the tanks is fundamental to control the applied doses and avoid environmental dissemination. Pursuing this goal, we included a novel potentiometric design in a flow-injection assembly. The electrode body was a stainless steel needle veterinary syringe of 0.8-mm inner diameter. A selective membrane of PVC acted as a sensory surface. Its composition, the length of the electrode, and other flow variables were optimized. The best performance was obtained for sensors of 1.5-cm length and a membrane composition of 33% PVC, 66% onitrophenyloctyl ether, 1% ion exchanger, and a small amount of a cationic additive. It exhibited Nernstian slopes of 61.0 mV decade-1 down to 1.0×10-5 mol L-1, with a limit of detection of 3.1×10-6 mol L-1 in flowing media. All necessary pH/ionic strength adjustments were performed online by merging the sample plug with a buffer carrier of 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid, pH 4.9. The sensor exhibited the advantages of a fast response time (less than 15 s), long operational lifetime (60 days), and good selectivity for chloride, nitrite, acetate, tartrate, citrate, and ascorbate. The flow setup was successfully applied to the analysis of aquaculture waters. The analytical results were validated against those obtained with liquid chromatography–tandem mass spectrometry procedures. The sampling rate was about 84 samples per hour and recoveries ranged from 95.9 to 106.9%.

A disposable glass-based immunosensor for monitoring the cancer biomarker CEA in urine

NanoPT 2014 International Conference, in Portugal, on February 12-14. Poster presentation based on topic Nanobio/Nanomedicine

Electrochemical sensor for simultaneous determination of herbicide MCPA and its metabolite 4-chloro-2-methylphenol. Application to photodegradation environmental monitoring

The development and application of a polyaniline/carbon nanotube (CNT) cyclodextrin matrix (PANI-β-CD/MWCNT)-based electrochemical sensor for the quantitative determination of the herbicide 4-chloro-2-methylphenoxyacetic acid (MCPA) and its main transformation product 4-chloro-2-methylphenol in natural waters are described. A simple cyclic voltammetry-based electrochemical methodology, in phosphate buffer solution at pH 6.0, was used to develop a method to determine both MCPA and 4-chloro-2-methylphenol, without any previous extraction or derivatization steps. A linear concentration range (10 to 50 μmol L−1) and detection limits of 1.1 and 1.9 μmol L−1, respectively, were achieved using optimized cyclic voltammetric parameters. The proposed method was successfully applied to the determination of MCPA and 4-chloro-2-methylphenol in natural water samples with satisfactory recoveries (94 to 107 %) and in good agreement with the results obtained by an established high-performance liquid chromatography technique, no significant differences being found between the methods. Interferences from ionic species and other herbicides used for broad-leaf weed control were shown to be small. The newly developed methodology was also successfully applied to MCPA photodegradation environmental studies.

ezGo: A voice operated wheelchair with biosignal monitoring for home environments

In this paper we present ezGo, an electric powered wheelchair with a speech based interface and biosignal monitoring instrumentation. The user can use the voice, a natural communication method, for controlling the chair movement and obtain information about his health. Additionally a set of semi-autonomous modes with macro recording enable the execution of navigation tasks with little effort and improved precision. The main purpose of the system is to provide severely disabled persons with an assistive device that can improve their confidence and daily independence. The obtained results on usability tests showed that users consider ezGo a valuable help on their daily tasks and a very desirable addition to standard wheelchairs.

Biomarkers of Nitrosative Stress: Development and validation of a new analytical method for 3-Nitrotyrosine quantification

Background: The nitration of tyrosine residues in proteins is associated with nitrosative stress, resulting in the formation of 3-nitrotyrosine (3-NT). 3-NT levels in biological samples have been associated with numerous physiological and pathological conditions. For this reason, several attempts have been made in order to develop methods that accurately quantify 3-NT in biological samples. Regarding chromatographic methods, they seem to be very accurate, showing very good sensibility and specificity. However, accurate quantification of this molecule, which is present at very low concentrations both at physiological and pathological states, is always a complex task and a target of intense research. Objectives: We aimed to develop a simple, rapid, low-cost and sensitive 3-NT quantification method for use in medical laboratories as an additional tool for diagnosis and/or treatment monitoring of a wide range of pathologies. We also aimed to evaluate the performance of the HPLC-based method developed here in a wide range of biological matrices. Material and methods: All experiments were performed on a Hitachi LaChrom Elite® HPLC system and separation was carried out using a Lichrocart® 250-4 Lichrospher 100 RP-18 (5μm) column. The method was further validated according to ICH guidelines. The biological matrices tested were serum, whole blood, urine, B16 F-10 melanoma cell line, growth medium conditioned with the same cell line, bacterial and yeast suspensions. Results: From all the protocols tested, the best results were obtained using 0.5% CH3COOH:MeOH:H2O (15:15:70) as the mobile phase, with detection at wavelengths 215, 276 and 356 nm, at 25ºC, and using a flow rate of 1 mL/min. By using this protocol, it was possible to obtain a linear calibration curve (correlation coefficient = 1), limits of detection and quantification in the order of ng/mL, and a short analysis time (<15 minutes per sample). Additionally, the developed protocol allowed the successful detection and quantification of 3-NT in all biological matrices tested, with detection at 356 nm. Conclusion: The method described in this study, which was successfully developed and validated for 3-NT quantification, is simple, cheap and fast, rendering it suitable for analysis in a wide range of biological matrices.