Relationship between fibre orientation and tensile strength of natural collagen membranes for heart valve leaflets

Heart valve prostheses are used to replace native heart valves which that are damaged because of congenital diseases or due to ageing. Biological prostheses made of bovine pericardium are similar to native valves and do not require any anticoagulation treatment, but are less durable than mechanical prostheses and usually fail by tearing. Researches are oriented in improving the resistance and durability of biological heart valve prostheses in order to increase their life expectancy. To understand the mechanical behaviour of bovine pericardium and relate it to its microstructure (mainly collagen fibres concentration and orientation) uniaxial tensile tests have been performed on a model material made of collagen fibres. Small Angle Light Scattering (SALS) has been also used to characterize the microstructure without damaging the material. Results with the model material allowed us to obtain the orientation of the fibres, relating the microstructure to mechanical performance

Construcción automática de grafos RDF a partir de frases en lenguaje natural para la integración de bases de datos heterogéneas

El presente trabajo desarrolla un servicio REST que transforma frases en lenguaje natural a grafos RDF. Los grafos generados son grafos dirigidos, donde los nodos se forman con los sustantivos o adjetivos de las frases, y los arcos se forman con los verbos. Se utiliza dentro del proyecto p-medicine para dar soporte a las siguientes funcionalidades: Búsquedas en lenguaje natural: actualmente la plataforma p-medicine proporciona un interfaz programático para realizar consultas en SPARQL. El servicio desarrollado permitiría generar esas consultas automáticamente a partir de frases en lenguaje natural. Anotaciones de bases de datos mediante lenguaje natural: la plataforma pmedicine incorpora una herramienta, desarrollada por el Grupo de Ingeniería Biomédica de la Universidad Politécnica de Madrid, para la anotación de bases de datos RDF. Estas anotaciones son necesarias para la posterior traducción de las bases de datos a un esquema central. El proceso de anotación requiere que el usuario construya de forma manual las vistas RDF que desea anotar, lo que requiere mostrar gráficamente el esquema RDF y que el usuario construya vistas RDF seleccionando las clases y relaciones necesarias. Este proceso es a menudo complejo y demasiado difícil para un usuario sin perfil técnico. El sistema se incorporará para permitir que la construcción de estas vistas se realice con lenguaje natural. ---ABSTRACT---The present work develops a REST service that transforms natural language sentences to RDF degrees. Generated graphs are directed graphs where nodes are formed with nouns or adjectives of phrases, and the arcs are formed with verbs. Used within the p-medicine project to support the following functionality: Natural language queries: currently the p-medicine platform provides a programmatic interface to query SPARQL. The developed service would automatically generate those queries from natural language sentences. Memos databases using natural language: the p-medicine platform incorporates a tool, developed by the Group of Biomedical Engineering at the Polytechnic University of Madrid, for the annotation of RDF data bases. Such annotations are necessary for the subsequent translation of databases to a central scheme. The annotation process requires the user to manually construct the RDF views that he wants annotate, requiring graphically display the RDF schema and the user to build RDF views by selecting classes and relationships. This process is often complex and too difficult for a user with no technical background. The system is incorporated to allow the construction of these views to be performed with natural language.

Context modelling for natural Human Computer Interaction applications in e-health

The conception of IoT (Internet of Things) is accepted as the future tendency of Internet among academia and industry. It will enable people and things to be connected at anytime and anyplace, with anything and anyone. IoT has been proposed to be applied into many areas such as Healthcare, Transportation，Logistics, and Smart environment etc. However, this thesis emphasizes on the home healthcare area as it is the potential healthcare model to solve many problems such as the limited medical resources, the increasing demands for healthcare from elderly and chronic patients which the traditional model is not capable of. A remarkable change in IoT in semantic oriented vision is that vast sensors or devices are involved which could generate enormous data. Methods to manage the data including acquiring, interpreting, processing and storing data need to be implemented. Apart from this, other abilities that IoT is not capable of are concluded, namely, interoperation, context awareness and security & privacy. Context awareness is an emerging technology to manage and take advantage of context to enable any type of system to provide personalized services. The aim of this thesis is to explore ways to facilitate context awareness in IoT. In order to realize this objective, a preliminary research is carried out in this thesis. The most basic premise to realize context awareness is to collect, model, understand, reason and make use of context. A complete literature review for the existing context modelling and context reasoning techniques is conducted. The conclusion is that the ontology-based context modelling and ontology-based context reasoning are the most promising and efficient techniques to manage context. In order to fuse ontology into IoT, a specific ontology-based context awareness framework is proposed for IoT applications. In general, the framework is composed of eight components which are hardware, UI (User Interface), Context modelling, Context fusion, Context reasoning, Context repository, Security unit and Context dissemination. Moreover, on the basis of TOVE (Toronto Virtual Enterprise), a formal ontology developing methodology is proposed and illustrated which consists of four stages: Specification & Conceptualization, Competency Formulation, Implementation and Validation & Documentation. In addition, a home healthcare scenario is elaborated by listing its well-defined functionalities. Aiming at representing this specific scenario, the proposed ontology developing methodology is applied and the ontology-based model is developed in a free and open-source ontology editor called Protégé. Finally, the accuracy and completeness of the proposed ontology are validated to show that this proposed ontology is able to accurately represent the scenario of interest.