5 resultados para Redes de sensores sem fios

em Repositório da Produção Científica e Intelectual da Unicamp


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The behaviour of Nafion® polymeric membranes containing acid-base dyes, bromothymol blue (BB) and methyl violet (MV), were studied aiming at constructing an optical sensor for pH measurement. BB revealed to be inadequate for developing sensing phases due to the electrostatic repulsion between negative groups of their molecules and the negative charge of the sulfonate group of the Nafion®, which causes leaching of the dye from the membrane. On the other hand, MV showed to be suitable due to the presence of positive groups in its structure. The membrane prepared from a methanolic solution whose Nafion®/dye molar ratio was 20 presented the best analytical properties, changing its color from green to violet in the pH range from 0.6 to 3.0. The membrane can be prepared with good reproducibility, presenting durability of ca. 6 months and response time of 22 s, making possible its use for pH determination in flow analysis systems.

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The aim of this paper is the description of the strategies and advances in the use of MIP in the development of chemical sensors. MIP has been considered an emerging technology, which allows the synthesis of materials that can mimic some highly specific natural receptors such as antibodies and enzymes. In recent years a great number of publications have demonstrated a growth in their use as sensing phases in the construction of sensors . Thus, the MIP technology became very attractive as a promising analytical tool for the development of sensors.

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Optical chemical sensors with detection in the near and mid infrared region are reviewed. Fundamental concepts of infrared spectroscopy and optical chemical sensors are briefly described, before presenting some aspects on optical chemical sensors, such as synthesis of NIR and IR reagents, preparation of new materials as well as application in determinations of species of biological, industrial and environmental importance.

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Animal welfare has been an important research topic in animal production mainly in its ways of assessment. Vocalization is found to be an interesting tool for evaluating welfare as it provides data in a non-invasive way as well as it allows easy automation of process. The present research had as objective the implementation of an algorithm based on artificial neural network that had the potential of identifying vocalization related to welfare pattern indicatives. The research was done in two parts, the first was the development of the algorithm, and the second its validation with data from the field. Previous records allowed the development of the algorithm from behaviors observed in sows housed in farrowing cages. Matlab® software was used for implementing the network. It was selected a retropropagation gradient algorithm for training the network with the following stop criteria: maximum of 5,000 interactions or error quadratic addition smaller than 0.1. Validation was done with sows and piglets housed in commercial farm. Among the usual behaviors the ones that deserved enhancement were: the feed dispute at farrowing and the eventual risk of involuntary aggression between the piglets or between those and the sow. The algorithm was able to identify through the noise intensity the inherent risk situation of piglets welfare reduction.

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Universidade Estadual de Campinas . Faculdade de Educação Física