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El projecte és el disseny d’una solució a un problema industrial en el sector de l’automòbil. Per garantir la qualitat del producte s’ha de poder trobar i determinar els defectes i els seus causants a la pintura de les carrosseries. L’objectiu era estudiar la viabilitat d’automatitzar el procés de reconeixement de dos dels principals defectes i contaminants que provoquen aquestes irregularitats a la pintura. En tres apartats es descriu: el disseny del μVisió, l’aparell que fa l’adquisició de la imatge amb diferents il·luminats (visible, infraroig i ultraviolat); el disseny del tractament de les imatges adquirides i el disseny de l’estació a l’empresa on s’establiria aquest prototip. Mitjançant aquests dissenys s’ha determinat que és necessari només un tipus d’il·luminació per veure els dos tipus de defectes, que amb l’algoritme assolit, es poden detectar un dels dos defectes i que l’establiment del prototip a la línia per fer-ne les proves sense repercutir a la línia és viable. Finalment, s’ha presentat el projecte a l’empresa per continuar amb el desenvolupament del prototip amb diferents línies de millora entre les quals està el tractament de la imatge amb intel·ligència artificial un cop hi hagi suficients imatges per entrenar-la. El proyecto es el diseño de una solución a un problema industrial en el sector del automóvil. Para garantizar la calidad del producto se tiene que poder encontrar y determinar los defectos y sus causantes en la pintura de las carrocerías. El objetivo era estudiar la viabilidad de automatizar el proceso de reconocimiento de dos de los principales defectos y contaminantes que provocan estas irregularidades a la pintura. En tres apartados se describe: el diseño del μVisió, el aparato que hace la adquisición de la imagen con diferentes iluminados (visible, infrarrojo y ultravioleta); el diseño del tratamiento de las imágenes adquiridas y el diseño de la estación en la empresa donde se establecería este prototipo. Mediante estos diseños se ha determinado que es necesario solo un tipo de iluminación para ver los dos tipos de defectos, que, con el algoritmo logrado, es pueden detectar uno de los dos defectos y que el establecimiento del prototipo a la línea para hacer las pruebas sin repercutir a la línea es viable. Finalmente, se ha presentado el proyecto a la empresa para continuar con el desarrollo del prototipo con diferentes líneas de mejora, entre las cuales está el tratamiento de la imagen con inteligencia artificial una vez haya suficientes imágenes por entrenarla. The project is the design of a solution to an industrial problem in the automobile sector. To guarantee the quality of the product, it is necessary to be able to find and determine the defects and their causes in the painting of the bodywork. The main goal was to study the feasibility of automating the process of recognizing two of the main defects and pollutesthat cause these irregularities in the paint. In three sections it describes:the design of the μVisió, the device that acquires the image with different illuminations (visible, infrared, and ultraviolet); the design of the processing of the acquired images and the design of the station to the company where this prototype would be established. Thanks to these designs, it has been determined that only one type of lighting is necessary to see the two types of defects, that with the algorithm achieved, it is possible to detect one of the two defects and that the establishment of the prototype on the line to carry out the tests without affecting the line is viable. Finally, the project has been presented to the company to continue with the development of the prototype with different lines of improvement, among which there is the processing of the image with artificial intelligence once there are enough images to train it.

The unintentional discovery of cirrhosis in a patient with prostate cancer lead us to enquire if some of the indexes/scored designed for the evaluation of liver fi brosis/cirrhosis, in Chronic Hepatitis C patients, could have helped us in the detection of incipient liver fi brosis, and its follow up, in this patient.

The morphology of statice, Limonium sinuatum (Midnigbt Blue), was studied in San José, Costa Rica, under greenhouse conditions, and in tite field. The germination rate was determined for husked seeds placed in petri dishes 011 mom papero The germination was rapid; epigeal, phanerocotylar or CJYPfOCOtYlar, the latter being tite most frequenL Morphological variations were maracteristic of earo Ptysiological state. There is a deep main root of woody consistency, witht many secondaly roots, chiefly in tite upper 10 cm of soíl. The floral stem is a polytelic synflores cence, bracteate, open type, similar lO an open panicle corymbose. The diameter and vigor of tite roseUe varied considerably, as did tite sbape of tite planto sbape of leaf, color, ahape and number of bracts, and.tlte morphology, size, weigbt and number of floral stems, both within a plant and amoog plants. The vegetative period was 105-120 days and the pre-flowering period lasted 30 days; flowering (anthe The morphology of statice, Limonium sinuatum (Midnigbt Blue), was studied in San José, Costa Rica, under greenhouse conditions, and in tite field. The germination rate was determined for husked seeds placed in petri dishes 011 mom papero The germination was rapid; epigeal, phanerocotylar or CJYPfOCOtYlar, the latter being tite most frequent Morphological variations were maracteristic of earo Ptysiological state. There is a deep main root of woody consistency, witlt many seconda¡y roots, chiefly in tite upper 10 cm of soíl. The floral stem is a polytelic synflores cence, bracteate, open type, similar lO an open panicle corymbose. The diameter and vigor of tite roseUe varied considerably, as did tite sbape of tite planto sbape of leaf, color, ahape and number of bracts, and.tlte morphology, size, weigbt and number of floral stems, both within a plant and amoog plants. The vegetative period was 105-120 days and the pre-flowering period lasted 30 days; flowering (anthe

Tilapia is one of the most important species in aquaculture; however, there is no available index to show the performance of a production unit. It is desirable to assess the productivity using indexes, such as the production and management index for shrimps and the European production efficacy factor for broilers. These indexes are based on data production: growth, survival, and feed conversion of a full production cycle. Taking into account these parameters, we propose a production and management index (PMI) for tilapia that is applicable for a specific period of the production cycle. For the construction and validation of the PMI we have used production data from 8, 614 monthly records of 2 tilapia farms in Huila Department (Colombia), and because of the complexity of tilapia management, different anomalous situations have been detected and then defined as exceptions. As a result, 419 records were considered extreme values because 1 or more exceptions were met. The value of the PMI varies from 0 (the worst situation) to 3.55, which reflects high variability. We have constructed a PMI for tilapia as the product of 3 elements to obtain a positive value index. Instead of classic parameters, we had to calculate an adapted version of them: the relative average daily growth, the survival (as a complementary value of the estimated monthly mortality), and a feed conversion ratio index. To assess the utility of the PMI, some comparisons were performed using records from black and red tilapia. We observed significant differences depending on tilapia strain (PMIblack = 1.0248 vs. PMIred = 1.1661; P < 0.001), age (better values for small fish), and season (PMIrainy = 1.0847 vs. PMIdry = 1.1011; P = 0.026). According to these results, we can conclude that the PMI could be a useful tool for tilapia farmers, despite the complexity of the calculation.

WinEpi Tasas 2.0 is a new, globally accessible computer program, which has been developed as a research tool for the epidemiological study of the pathological processes which affect animal populations. This new version of the program, based on the experimental version, WinEpi Tasas 1.0, enables users to study the distribution and evolution of diseases in affected populations, over time. This information, combined with data on spatial distribution, is of fundamental importance for the establishment of appropriate control strategies and health policies. Such disease control measures are of particular significance in the current context of emerging and re-emerging diseases. The program can be run in either English or Spanish.

Diseases are among the greatest threats affecting the sustainability of shrimp aquaculture. In Ecuador, diseases of cultured shrimp have been quickly transmitted from one region to another. Therefore, an early detection system of impending epidemics could serve as an important management tool for the aquaculture sector. We developed a system for the early detection of shrimp epidemics for the largest shrimp zone of Ecuador based on production surveillance. The system, called Epidemiological Alert System and Aquaculture Management (SAEMA), uses a geographical information system (GIS) with an imaginary grid cartography (12,860 ha per grid) dividing the study area. A production and management index is calculated with the harvest data of each pond. A standardized deviation around the historical averages and an alert level is calculated per grid and month. Normal conditions of production and therefore the absence of disease are depicted in green and yellow. While, orange and red colours express a disease warning manifested through suboptimal production levels. As a result, a map of the study area with grid divisions is displayed, with a specific alert colour for each grid where information is available. SAEMA was developed as a Web application (http://www.saema.espol.edu.ec) that enables producers to record data via a worksheet format using any web browser. Instantaneously, the applications perform a calculation of the alert index and provide feedback to the alert levels displayed in an interactive map. A feedback process was initiated in May 2006 with 19 participating shrimp farms. The objective of this research is to develop a platform for an early detection of shrimp epidemics on a regional scale. The detection of an epidemic, expressed as suboptimal production in a specific region, can provide producers from other zones and government authorities to engage in time preventive and control measures in order to reduce the spread of diseases.