987 resultados para Hybrid imprinted membrane
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Toxic amides, such as acrylamide, are potentially harmful to Human health, so there is great interest in the fabrication of compact and economical devices to measure their concentration in food products and effluents. The CHEmically Modified Field Effect Transistor (CHEMFET) based onamorphous silicon technology is a candidate for this type of application due to its low fabrication cost. In this article we have used a semi-empirical modelof the device to predict its performance in a solution of interfering ions. The actual semiconductor unit of the sensor was fabricated by the PECVD technique in the top gate configuration. The CHEMFET simulation was performed based on the experimental current voltage curves of the semiconductor unit and on an empirical model of the polymeric membrane. Results presented here are useful for selection and design of CHEMFET membranes and provide an idea of the limitations of the amorphous CHEMFET device. In addition to the economical advantage, the small size of this prototype means it is appropriate for in situ operation and integration in a sensor array.
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In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.
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This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.
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In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.
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This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.
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This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.
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Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.
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The relentless discovery of cancer biomarkers demands improved methods for their detection. In this work, we developed protein imprinted polymer on three-dimensional gold nanoelectrode ensemble (GNEE) to detect epithelial ovarian cancer antigen-125 (CA 125), a protein biomarker associated with ovarian cancer. CA 125 is the standard tumor marker used to follow women during or after treatment for epithelial ovarian cancer. The template protein CA 125 was initially incorporated into the thin-film coating and, upon extraction of protein from the accessible surfaces on the thin film, imprints for CA 125 were formed. The fabrication and analysis of the CA 125 imprinted GNEE was done by using cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) techniques. The surfaces of the very thin, protein imprinted sites on GNEE are utilized for immunospecific capture of CA 125 molecules, and the mass of bound on the electrode surface can be detected as a reduction in the faradic current from the redox marker. Under optimal conditions, the developed sensor showed good increments at the studied concentration range of 0.5–400 U mL−1. The lowest detection limit was found to be 0.5 U mL−1. Spiked human blood serum and unknown real serum samples were analyzed. The presence of non-specific proteins in the serum did not significantly affect the sensitivity of our assay. Molecular imprinting using synthetic polymers and nanomaterials provides an alternative approach to the trace detection of biomarker proteins.
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The measurement of room impulse response (RIR) when there are high background noise levels frequently means one must deal with very low signal-to-noise ratios (SNR). if such is the case, the measurement might yield unreliable results, even when synchronous averaging techniques are used. Furthermore, if there are non-linearities in the apparatus or system time variances, the final SNR can be severely degraded. The test signals used in RIR measurement are often disturbed by non-stationary ambient noise components. A novel approach based on the energy analysis of ambient noise - both in the time and in frequency - was considered. A modified maximum length sequence (MLS) measurement technique. referred to herein as the hybrid MLS technique, was developed for use in room acoustics. The technique consists of reducing the noise energy of the captured sequences before applying the averaging technique in order to improve the overall SNRs and frequency response accuracy. Experiments were conducted under real conditions with different types of underlying ambient noises. Results are shown and discussed. Advantages and disadvantages of the hybrid MLS technique over standard MLS technique are evaluated and discussed. Our findings show that the new technique leads to a significant increase in the overall SNR. (C) 2008 Elsevier Ltd. All rights reserved.
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PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.
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The evolution of hybrid polyploid vertebrates, their viability and their perpetuation over evolutionary time have always been questions of great interest. However, little is known about the impact of hybridization and polyploidization on the regulatory networks that guarantee the appropriate quantitative and qualitative gene expression programme. The Squalius alburnoides complex of hybrid fish is an attractive system to address these questions, as it includes a wide variety of diploid and polyploid forms, and intricate systems of genetic exchange. Through the study of genome-specific allele expression of seven housekeeping and tissue-specific genes, we found that a gene copy silencing mechanism of dosage compensation exists throughout the distribution range of the complex. Here we show that the allele-specific patterns of silencing vary within the complex, according to the geographical origin and the type of genome involved in the hybridization process. In southern populations, triploids of S. alburnoides show an overall tendency for silencing the allele from the minority genome, while northern population polyploids exhibit preferential biallelic gene expression patterns, irrespective of genomic composition. The present findings further suggest that gene copy silencing and variable expression of specific allele combinations may be important processes in vertebrate polyploid evolution.
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The fatty acid profile of erythrocyte membranes has been considered a good biomarker for several pathologic situations. Dietary intake, digestion, absorption, metabolism, storage and exchange amongst compartments, greatly influence the fatty acids composition of different cells and tissues. Lipoprotein and hepatic lipases were also involved in fatty acid availability. In the present work we examined the correlations between fatty acid in Red Blood Cells (RBCs) membranes, the fatty acid desaturase and elongase activities, glycaemia, blood lipids, lipoproteins and apoproteins, and the endothelial lipase (EL) mass in plasma. Twenty one individuals were considered in the present study, with age >18 y. RBCs membranes were obtained and analysed for fatty acid composition by gas chromatography. The amount of fatty acids (as percentage) were analysed, and the ratios between fatty acid 16:1/16:0; 18:1/18:0; 18:0/16:0; 22:6 n-3/20:5 n-3 and 20:4 n-6/18:2 n-6 were calculated. Bivariate analysis (rs) and partial correlations were determined. SCD16 estimation activity correlated positively with BMI (rs=0.466, p=0.043) and triacylglycerols (TAG) (rs=0.483, p=0.026), and negatively with the ratio ApoA1/ApoB (rs=-0.566, p=0.007). Endothelial lipase (EL) correlated positively with the EPA/AA ratio in RBCs membranes (rs=0.524, p=0.045). After multi-adjustment for BMI, age, hs-CRP and dietary n3/n6 ratio, the correlations remained significant between EL and EPA/AA ratio. At the best of our knowledge this is the first report that correlated EL with the fatty acid profile of RBCs plasma membranes. The association found here can suggest that the enzyme may be involved in the bioavailability and distribution of n-3/n-6 fatty acids, suggesting a major role for EL in the pathophysiological mechanisms involving biomembranes’ fatty acids, such as in inflammatory response and eicosanoids metabolites pathways.
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A presente dissertação descreve o desenvolvimento e a caracterização de sensores potenciométricos com base em polímeros de impressão molecular e de sensores ópticos com base em membranas de poli(cloreto de vinilo), PVC, para a determinação de cobre em vinhos verdes. Os sensores potenciométricos foram preparados a partir de diferentes solventes (metanol e clorofórmio), tendo o seu crescimento decorrido na presença ou ausência da molécula molde (cobre). Os sistemas sensores selectivos ao cobre continham partículas de polímeros com ou sem impressão molecular como material electroactivo, dispersas em solvente plastificante, PVC e, em alguns casos, aditivo aniónico. A avaliação dos vários sistemas baseou-se na comparação das características operacionais dos diversos eléctrodos onde foram aplicados. Estas características foram obtidas a partir de curvas de calibração, cujos declives e limites de detecção variaram entre -39,9 – 37,0 mV decada-1 e 4,2 – 29,1 μg mL-1, respectivamente. Os sensores não são independentes do pH uma vez que o complexo formado entre o cobre e a difenilcarbazida é favorecido por valores de pH próximos de 5. Assim, obtiveram-se melhores resultados usando água desionizada ou solução tampão de HEPES revelando-se um método rápido e relativamente eficaz nestas condições. Os sensores ópticos basearam-se na reacção colorimétrica entre o cobre e um complexante. Os reagentes complexantes escolhidos foram a neocuproína, a difenilcarbazida e o dietilditiocarbamato de sódio. Avaliou-se o efeito de vários parâmetros experimentais na resposta destes sensores, tais como o pH (avaliado para os valores 3,00 e 5,00), a concentração de cobre (que variou entre 0,06 e 317,7 mg L- 1) e as próprias características da membrana. Os melhores resultados foram obtidos a pH 3, numa gama de concentrações de 0,06 e 31,8 mg L-1 usando a difenilcarbazida como reagente complexante. A aplicação destes sensores a vinhos requer ainda estudos adicionais, especialmente no que diz respeito à necessidade de implementar algum procedimento de pré-tratamento de amostra.
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We present a study of the effects of nanoconfinement on a system of hard Gaussian overlap particles interacting with planar substrates through the hard-needle-wall potential, extending earlier work by two of us [D. J. Cleaver and P. I. C. Teixeira, Chem. Phys. Lett. 338, 1 (2001)]. Here, we consider the case of hybrid films, where one of the substrates induces strongly homeotropic anchoring, while the other favors either weakly homeotropic or planar anchoring. These systems are investigated using both Monte Carlo simulation and density-functional theory, the latter implemented at the level of Onsager's second-virial approximation with Parsons-Lee rescaling. The orientational structure is found to change either continuously or discontinuously depending on substrate separation, in agreement with earlier predictions by others. The theory is seen to perform well in spite of its simplicity, predicting the positional and orientational structure seen in simulations even for small particle elongations.
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A biomimetic sensor for norfloxacin is presented that is based on host-guest interactions and potentiometric transduction. The artificial host was imprinted into polymers made from methacrylic acid and/or 2-vinyl pyridine. The resulting particles were entrapped in a plasticized poly(vinyl chloride) (PVC) matrix. The sensors exhibit near-Nernstian response in steady state evaluations, and detection limits range from 0.40 to 1.0 μgmL−1, respectively, and are independent of pH values at between 2 and 6, and 8 and 11, respectively. Good selectivity was observed over several potential interferents. In flowing media, the sensors exhibit fast response, a sensitivity of 68.2 mV per decade, a linear range from 79 μM to 2.5 mM, a detection limit of 20 μgmL−1, and a stable baseline. The sensors were successfully applied to field monitoring of norfloxacin in fish samples, biological samples, and pharmaceutical products