4 resultados para 670200 Fibre Processing and Textiles

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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Las proteínas son biopolímeros con potenciales propiedades para aplicaciones en el campo de envases por su capacidad para formar films con buenas propiedades barrera en condiciones secas. Además, al ser biodegradables y provenir de recursos renovables, ofrecen importantes ventajas desde el punto de vista medioambiental y económico. Sin embargo, los films basados en proteínas son frágiles y presentan una baja resistencia a la humedad, por lo que se requiere su modificación para fabricar materiales útiles en las condiciones de servicio.El objetivo de esta tesis es reducir la absorción de humedad y simultáneamente mejorar las propiedades mecánicas de los materiales fabricados con proteína de soja. Para ello es necesaria la adición de sustancias que puedan interaccionar con los grupos polares de la proteína, reduciendo así su carácter hidrofílico y la absorción de humedad, y que a la vez puedan actuar como plastificantes, reduciendo la fragilidad del material fabricado. Además, las condiciones de procesado también influyen en las propiedades del material, por tanto, la optimización del procesado es otro de los objetivos de la tesis.Para poder conseguir la mejora de las propiedades del material y, en concreto, aquellas requeridas por el sector del envase, como son las propiedades mecánicas y la resistencia a la humedad, la tesis se ha centrado en tres áreas: plastificación por adición de glicerol; mezclado con sustancias naturales como gelatinas, ácidos, aceites y azúcares; y procesado por los métodos húmedo y seco.

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Although many optical fibre applications are based on their capacity to transmit optical signals with low losses, it can also be desirable for the optical fibre to be strongly affected by a certain physical parameter in the environment. In this way, it can be used as a sensor for this parameter. There are many strong arguments for the use of POFs as sensors. In addition to being easy to handle and low cost, they demonstrate advantages common to all multimode optical fibres. These specifically include flexibility, small size, good electromagnetic compatibility behaviour, and in general, the possibility of measuring any phenomenon without physically interacting with it. In this paper, a sensor based on POF is designed and analysed with the aim of measuring the volume and turbidity of a low viscosity fluid, in this case water, as it passes through a pipe. A comparative study with a commercial sensor is provided to validate the proven flow measurement. Likewise, turbidity is measured using different colour dyes. Finally, this paper will present the most significant results and conclusions from all the tests which are carried out.

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The objective of the work was to develop a non-invasive methodology for image acquisition, processing and nonlinear trajectory analysis of the collective fish response to a stochastic event. Object detection and motion estimation were performed by an optical flow algorithm in order to detect moving fish and simultaneously eliminate background, noise and artifacts. The Entropy and the Fractal Dimension (FD) of the trajectory followed by the centroids of the groups of fish were calculated using Shannon and permutation Entropy and the Katz, Higuchi and Katz-Castiglioni's FD algorithms respectively. The methodology was tested on three case groups of European sea bass (Dicentrarchus labrax), two of which were similar (C1 control and C2 tagged fish) and very different from the third (C3, tagged fish submerged in methylmercury contaminated water). The results indicate that Shannon entropy and Katz-Castiglioni were the most sensitive algorithms and proved to be promising tools for the non-invasive identification and quantification of differences in fish responses. In conclusion, we believe that this methodology has the potential to be embedded in online/real time architecture for contaminant monitoring programs in the aquaculture industry.