Sonophone: Desarrollo y evaluación de un sonómetro profesional para iOS

La medida de la presión sonora es un proceso de extrema importancia para la ingeniería acústica, de aplicación en numerosas áreas de esta disciplina, como la acústica arquitectónica o el control de ruido. Sobre todo en esta última, es necesario poder efectuar medidas precisas en condiciones muy diversas. Por otra parte, la ubicuidad de los dispositivos móviles inteligentes (smartphones, tabletas, etc.), dispositivos que integran potencia de procesado, conectividad, interactividad y una interfaz intuitiva en un tamaño reducido, abre la posibilidad de su uso como sistemas de medida de calidad y de coste bajo. En este Proyecto se pretende utilizar las capacidades de entrada y salida, procesado, conectividad inalámbrica y geolocalización de los dispositivos móviles basados en iOS, en concreto el iPhone, para implementar un sistema de medidas acústicas que iguale o supere las prestaciones de los sonómetros existentes en el mercado. SonoPhone permitirá, mediante la conexión de un micrófono de medida adecuado, la realización de medidas de acuerdo a las normas técnicas en vigor, así como la posibilidad de programar, configurar y almacenar o trasmitir las medidas realizadas, que además estarán geolocalizadas con el GPS integrado en el dispositivo móvil. También se permitirá enviar los datos de la medida a un almacenamiento remoto en la nube. La aplicación tiene una estructura modular en la que un módulo de adquisición de datos lee la señal del micrófono, un back-end efectúa el procesado necesario, y otros módulos permiten la calibración del dispositivo y programar y configurar las medidas, así como su almacenamiento y transmisión en red. Una interfaz de usuario (GUI) permite visualizar las medidas y efectuar las configuraciones deseadas por el usuario, todo ello en tiempo real. Además de implementar la aplicación, se ha realizado una prueba de funcionamiento para determinar si el hardware del iPhone es adecuado para la medida de la presión acústica de acuerdo a las normas internacionales. Sound pressure measurement is an extremely important process in the field of acoustic engineering, with applications in numerous subfields, like for instance building acoustics and noise control, where it is necessary to be able to accurately measure sound pressure in very diverse (and sometimes adverse) conditions. On the other hand, the growing ubiquity of mobile devices such as smartphones or tablets, which combine processing power, connectivity, interactivity and an intuitive interface in a small size, makes it possible to use these devices as quality low-cost measurement systems. This Project aims to use the input-output capabilities of iOS-based mobile devices, in particular the iPhone, together with their processing power, wireless connectivity and geolocation features, to implement an acoustic measurement system that rivals the performance of existing devices. SonoPhone allows, with the addition of an adequate measurement microphone, to carry out measurements that comply with current technical regulations, as well as programming, configuring, storing and transmitting the results of the measurement. These measurements will be geolocated using the integrated GPS, and can be transmitted effortlessly to a remote cloud storage. The application is structured in modular fashion. A data acquisition module reads the signal from the microphone, while a back-end module carries out the necessary processing. Other modules permit the device to be calibrated, or control the configuration of the measurement and its storage or transmission. A Graphical User Interface (GUI) allows visual feedback on the measurement in progress, and provides the user with real-time control over the measurement parameters. Not only an application has been developed; a laboratory test was carried out with the goal of determining if the hardware of the iPhone permits the whole system to comply with international regulations regarding sound level meters.

Multi-dimensional classification using Bayesian networks for stationary and evolving streaming data

Hoy en día, con la evolución continua y rápida de las tecnologías de la información y los dispositivos de computación, se recogen y almacenan continuamente grandes volúmenes de datos en distintos dominios y a través de diversas aplicaciones del mundo real. La extracción de conocimiento útil de una cantidad tan enorme de datos no se puede realizar habitualmente de forma manual, y requiere el uso de técnicas adecuadas de aprendizaje automático y de minería de datos. La clasificación es una de las técnicas más importantes que ha sido aplicada con éxito a varias áreas. En general, la clasificación se compone de dos pasos principales: en primer lugar, aprender un modelo de clasificación o clasificador a partir de un conjunto de datos de entrenamiento, y en segundo lugar, clasificar las nuevas instancias de datos utilizando el clasificador aprendido. La clasificación es supervisada cuando todas las etiquetas están presentes en los datos de entrenamiento (es decir, datos completamente etiquetados), semi-supervisada cuando sólo algunas etiquetas son conocidas (es decir, datos parcialmente etiquetados), y no supervisada cuando todas las etiquetas están ausentes en los datos de entrenamiento (es decir, datos no etiquetados). Además, aparte de esta taxonomía, el problema de clasificación se puede categorizar en unidimensional o multidimensional en función del número de variables clase, una o más, respectivamente; o también puede ser categorizado en estacionario o cambiante con el tiempo en función de las características de los datos y de la tasa de cambio subyacente. A lo largo de esta tesis, tratamos el problema de clasificación desde tres perspectivas diferentes, a saber, clasificación supervisada multidimensional estacionaria, clasificación semisupervisada unidimensional cambiante con el tiempo, y clasificación supervisada multidimensional cambiante con el tiempo. Para llevar a cabo esta tarea, hemos usado básicamente los clasificadores Bayesianos como modelos. La primera contribución, dirigiéndose al problema de clasificación supervisada multidimensional estacionaria, se compone de dos nuevos métodos de aprendizaje de clasificadores Bayesianos multidimensionales a partir de datos estacionarios. Los métodos se proponen desde dos puntos de vista diferentes. El primer método, denominado CB-MBC, se basa en una estrategia de envoltura de selección de variables que es voraz y hacia delante, mientras que el segundo, denominado MB-MBC, es una estrategia de filtrado de variables con una aproximación basada en restricciones y en el manto de Markov. Ambos métodos han sido aplicados a dos problemas reales importantes, a saber, la predicción de los inhibidores de la transcriptasa inversa y de la proteasa para el problema de infección por el virus de la inmunodeficiencia humana tipo 1 (HIV-1), y la predicción del European Quality of Life-5 Dimensions (EQ-5D) a partir de los cuestionarios de la enfermedad de Parkinson con 39 ítems (PDQ-39). El estudio experimental incluye comparaciones de CB-MBC y MB-MBC con los métodos del estado del arte de la clasificación multidimensional, así como con métodos comúnmente utilizados para resolver el problema de predicción de la enfermedad de Parkinson, a saber, la regresión logística multinomial, mínimos cuadrados ordinarios, y mínimas desviaciones absolutas censuradas. En ambas aplicaciones, los resultados han sido prometedores con respecto a la precisión de la clasificación, así como en relación al análisis de las estructuras gráficas que identifican interacciones conocidas y novedosas entre las variables. La segunda contribución, referida al problema de clasificación semi-supervisada unidimensional cambiante con el tiempo, consiste en un método nuevo (CPL-DS) para clasificar flujos de datos parcialmente etiquetados. Los flujos de datos difieren de los conjuntos de datos estacionarios en su proceso de generación muy rápido y en su aspecto de cambio de concepto. Es decir, los conceptos aprendidos y/o la distribución subyacente están probablemente cambiando y evolucionando en el tiempo, lo que hace que el modelo de clasificación actual sea obsoleto y deba ser actualizado. CPL-DS utiliza la divergencia de Kullback-Leibler y el método de bootstrapping para cuantificar y detectar tres tipos posibles de cambio: en las predictoras, en la a posteriori de la clase o en ambas. Después, si se detecta cualquier cambio, un nuevo modelo de clasificación se aprende usando el algoritmo EM; si no, el modelo de clasificación actual se mantiene sin modificaciones. CPL-DS es general, ya que puede ser aplicado a varios modelos de clasificación. Usando dos modelos diferentes, el clasificador naive Bayes y la regresión logística, CPL-DS se ha probado con flujos de datos sintéticos y también se ha aplicado al problema real de la detección de código malware, en el cual los nuevos ficheros recibidos deben ser continuamente clasificados en malware o goodware. Los resultados experimentales muestran que nuestro método es efectivo para la detección de diferentes tipos de cambio a partir de los flujos de datos parcialmente etiquetados y también tiene una buena precisión de la clasificación. Finalmente, la tercera contribución, sobre el problema de clasificación supervisada multidimensional cambiante con el tiempo, consiste en dos métodos adaptativos, a saber, Locally Adpative-MB-MBC (LA-MB-MBC) y Globally Adpative-MB-MBC (GA-MB-MBC). Ambos métodos monitorizan el cambio de concepto a lo largo del tiempo utilizando la log-verosimilitud media como métrica y el test de Page-Hinkley. Luego, si se detecta un cambio de concepto, LA-MB-MBC adapta el actual clasificador Bayesiano multidimensional localmente alrededor de cada nodo cambiado, mientras que GA-MB-MBC aprende un nuevo clasificador Bayesiano multidimensional. El estudio experimental realizado usando flujos de datos sintéticos multidimensionales indica los méritos de los métodos adaptativos propuestos. ABSTRACT Nowadays, with the ongoing and rapid evolution of information technology and computing devices, large volumes of data are continuously collected and stored in different domains and through various real-world applications. Extracting useful knowledge from such a huge amount of data usually cannot be performed manually, and requires the use of adequate machine learning and data mining techniques. Classification is one of the most important techniques that has been successfully applied to several areas. Roughly speaking, classification consists of two main steps: first, learn a classification model or classifier from an available training data, and secondly, classify the new incoming unseen data instances using the learned classifier. Classification is supervised when the whole class values are present in the training data (i.e., fully labeled data), semi-supervised when only some class values are known (i.e., partially labeled data), and unsupervised when the whole class values are missing in the training data (i.e., unlabeled data). In addition, besides this taxonomy, the classification problem can be categorized into uni-dimensional or multi-dimensional depending on the number of class variables, one or more, respectively; or can be also categorized into stationary or streaming depending on the characteristics of the data and the rate of change underlying it. Through this thesis, we deal with the classification problem under three different settings, namely, supervised multi-dimensional stationary classification, semi-supervised unidimensional streaming classification, and supervised multi-dimensional streaming classification. To accomplish this task, we basically used Bayesian network classifiers as models. The first contribution, addressing the supervised multi-dimensional stationary classification problem, consists of two new methods for learning multi-dimensional Bayesian network classifiers from stationary data. They are proposed from two different points of view. The first method, named CB-MBC, is based on a wrapper greedy forward selection approach, while the second one, named MB-MBC, is a filter constraint-based approach based on Markov blankets. Both methods are applied to two important real-world problems, namely, the prediction of the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors, and the prediction of the European Quality of Life-5 Dimensions (EQ-5D) from 39-item Parkinson’s Disease Questionnaire (PDQ-39). The experimental study includes comparisons of CB-MBC and MB-MBC against state-of-the-art multi-dimensional classification methods, as well as against commonly used methods for solving the Parkinson’s disease prediction problem, namely, multinomial logistic regression, ordinary least squares, and censored least absolute deviations. For both considered case studies, results are promising in terms of classification accuracy as well as regarding the analysis of the learned MBC graphical structures identifying known and novel interactions among variables. The second contribution, addressing the semi-supervised uni-dimensional streaming classification problem, consists of a novel method (CPL-DS) for classifying partially labeled data streams. Data streams differ from the stationary data sets by their highly rapid generation process and their concept-drifting aspect. That is, the learned concepts and/or the underlying distribution are likely changing and evolving over time, which makes the current classification model out-of-date requiring to be updated. CPL-DS uses the Kullback-Leibler divergence and bootstrapping method to quantify and detect three possible kinds of drift: feature, conditional or dual. Then, if any occurs, a new classification model is learned using the expectation-maximization algorithm; otherwise, the current classification model is kept unchanged. CPL-DS is general as it can be applied to several classification models. Using two different models, namely, naive Bayes classifier and logistic regression, CPL-DS is tested with synthetic data streams and applied to the real-world problem of malware detection, where the new received files should be continuously classified into malware or goodware. Experimental results show that our approach is effective for detecting different kinds of drift from partially labeled data streams, as well as having a good classification performance. Finally, the third contribution, addressing the supervised multi-dimensional streaming classification problem, consists of two adaptive methods, namely, Locally Adaptive-MB-MBC (LA-MB-MBC) and Globally Adaptive-MB-MBC (GA-MB-MBC). Both methods monitor the concept drift over time using the average log-likelihood score and the Page-Hinkley test. Then, if a drift is detected, LA-MB-MBC adapts the current multi-dimensional Bayesian network classifier locally around each changed node, whereas GA-MB-MBC learns a new multi-dimensional Bayesian network classifier from scratch. Experimental study carried out using synthetic multi-dimensional data streams shows the merits of both proposed adaptive methods.

Secure optical networks based on quantum key distribution and weakly trusted repeaters

Abstract—In this paper we explore how recent technologies can improve the security of optical networks. In particular, we study how to use quantum key distribution(QKD) in common optical network infrastructures and propose a method to overcome its distance limitations. QKD is the first technology offering information theoretic secretkey distribution that relies only on the fundamental principles of quantum physics. Point-to-point QKDdevices have reached a mature industrial state; however, these devices are severely limited in distance, since signals at the quantum level (e.g., single photons) are highly affected by the losses in the communication channel and intermediate devices. To overcome this limitation, intermediate nodes (i.e., repeaters) are used. Both quantum-regime and trusted, classical repeaters have been proposed in the QKD literature, but only the latter can be implemented in practice. As a novelty, we propose here a new QKD network model based on the use of not fully trusted intermediate nodes, referred to as weakly trusted repeaters. This approach forces the attacker to simultaneously break several paths to get access to the exchanged key, thus improving significantly the security of the network. We formalize the model using network codes and provide real scenarios that allow users to exchange secure keys over metropolitan optical networks using only passive components. Moreover, the theoretical framework allows one to extend these scenarios not only to accommodate more complex trust constraints, but also to consider robustness and resiliency constraints on the network.

Grasp Mapping Between a 3-Finger Haptic Device and a Robotic Hand

This paper presents the implementation of a robust grasp mapping between a 3-finger haptic device (master) and a robotic hand (slave). Mapping is based on a grasp equivalence defined considering the manipulation capabilities of the master and slave devices. The metrics that translate the human hand gesture to the robotic hand workspace are obtained through an analytical user study. This allows a natural control of the robotic hand. The grasp mapping is accomplished defining 4 control modes that encapsulate all the grasps gestures considered.

Networks based on QKD and weakly trusted repeaters

We study how to use quantum key distribution (QKD) in common optical network infrastructures and propose a method to overcome its distance limitations. QKD is the first technology offering information theoretic secret-key distribution that relies only on the fundamental principles of quantum physics. Point-to-point QKD devices have reached a mature industrial state; however, these devices are severely limited in distance, since signals at the quantum level (e.g. single photons) are highly affected by the losses in the communication channel and intermediate devices. To overcome this limitation, intermediate nodes (i.e. repeaters) are used. Both, quantum-regime and trusted, classical, repeaters have been proposed in the QKD literature, but only the latter can be implemented in practice. As a novelty, we propose here a new QKD network model based on the use of not fully trusted intermediate nodes, referred as weakly trusted repeaters. This approach forces the attacker to simultaneously break several paths to get access to the exchanged key, thus improving significantly the security of the network. We formalize the model using network codes and provide real scenarios that allow users to exchange secure keys over metropolitan optical networks using only passive components.

Estudio acústico del auditorio Rafael Frühbeck, Burgos

El presente proyecto desarrolla un estudio acústico del recinto: Auditorio Rafael Frühbeck de Burgos, cumpliendo con las indicaciones exigidas por la norma UNE-EN ISO 3382-1: 2010, “Medición de parámetros acústicos en recintos, Parte 1: Salas de Espectáculos”. Se desarrollan dos estudios acústicos sobre el mismo recinto. En el primero de ellos, el recinto está configurado para la realización de eventos tales como conferencias o congresos, donde la inteligibilidad de la palabra es un factor determinante. En el segundo estudio, el recinto se configura para espectáculos musicales como conciertos de orquesta sinfónica o música de cámara. En esta configuración, la palabra ya no es tan determinante como la correcta interpretación y disfrute de la música por parte de la audiencia. Para ambas configuraciones del recinto se ha realizado un procesado estadístico de los datos con el fin de obtener un valor único de cada parámetro acústico estudiado. De esta forma, se comparan los resultados para ambas configuraciones, y se evalúan los valores obtenidos de cada uno de los parámetros acústicos con el fin de conocer si se adecuan a las necesidades acústicas exigidas por el tipo de evento desarrollado. Además, se ha construido un modelo geométrico del recinto por ordenador, para ambas configuraciones acústicas, haciendo uso del software profesional de predicción y simulación acústica EASE. Se realiza un estudio acústico sobre el modelo geométrico mediante simulación, siguiendo las pautas llevadas a cabo durante la medición “in situ”. Los resultados obtenidos por simulación se comparan con los obtenidos de las mediciones “in situ”, para estudiar la validación del modelo geométrico. El parámetro acústico elegido para validar el modelo, en un primer momento, será el tiempo de reverberación. Si se consigue una buena validación del modelo geométrico, este puede ser utilizado para realizar predicciones acústicas mediante simulación, cuando un sistema de refuerzo sonoro sea utilizado dentro del recinto. El sistema de refuerzo sonoro ubicado en el recinto sometido a estudio, no ha sido utilizado en el presente proyecto. ABSTRACT. The present projects carry out an acoustic study of enclosure: Rafael Frühbeck Concert Hall, in Burgos, fulfilling the indications demanded by the standard UNE-EN ISO 3382-1:2010 “Measurement of room acoustic parameters – Part 1: Performance spaces. Two acoustics studies are developed on the same enclosure. In first of them, the enclosure is formed for the accomplishment of events such as conferences or congresses, where speech intelligibility is a determining factor. In the second study, the enclosure forms for musical performances like concerts of symphony orchestra or chamber music. In this acoustic configuration, speech intelligibility is not as determining as the correct interpretation and enjoyment of music in audience areas. For both configurations of the enclosure, a statistical processing of the data has been realised with the purpose of obtaining a unique value of each studied acoustic parameter. In this way, the results for both configurations are compared, and the obtained values of each one of the acoustic parameters are evaluated with the purpose of knowing if they are adapted to the acoustic needs demanded by the type of developed event. In addition, a geometric model of the enclosure has been constructed by computer, for both acoustic configurations; making use of the professional software of prediction and acoustical simulation, EASE. An acoustic study is developed on the geometric model by means of simulation, following the rules carried out during the measurement “in situ”. The results obtained by simulation are compared with the obtained ones from the measurement “in situ”, to study the validation of the geometric model. Initially the acoustic parameter chosen to validate the model is Reverberation Time. If a good validation of the geometric model is reached, it can be used to realize acoustic predictions by simulation, when a sound reinforcement system is used within the enclosure. The sound reinforcement system located in the enclosure under study has not been used in the present project.

A real case of a cognitive multiplayer game: design and development of the iOS client in Swift and its cloud architecture

as tecnologías emergentes como el cloud computing y los dispositivos móviles están creando una oportunidad sin precedentes para mejorar el sistema educativo, permitiendo tanto a los educadores personalizar y mejorar la experiencia de aprendizaje, como facilitar a los estudiantes que adquieran conocimientos sin importar dónde estén. Por otra parte, a través de técnicas de gamificacion será posible promover y motivar a los estudiantes a que aprendan materias arduas haciendo que la experiencia sea más motivadora. Los juegos móviles pueden ser el camino correcto para dar soporte a esta experiencia de aprendizaje mejorada. Este proyecto integra el diseño y desarrollo de una arquitectura en la nube altamente escalable y con alto rendimiento, así como el propio cliente de iOS, para dar soporte a una nueva version de Temporis, un juego móvil multijugador orientado a reordenar eventos históricos en una línea temporal (e.j. historia, arte, deportes, entretenimiento y literatura). Temporis actualmente está disponible en Google Play. Esta memoria describe el desarrollo de la nueva versión de Temporis (Temporis v.2.0) proporcionando detalles acerca de la mejora y adaptación basados en el Temporis original. En particular se describe el nuevo backend hecho en Go sobre Google App Engine creado para soportar miles de usuarios, asó como otras características por ejemplo como conseguir enviar noticaciones push desde la propia plataforma. Por último, el cliente de iOS en Temporis v.2.0 se ha desarrollado utilizando las últimas y más relevantes tecnologías, prestando especial atención a Swift (el lenguaje de programación nuevo de Apple, que es seguro y rápido), el Paradigma Funcional Reactivo (que ayuda a construir aplicaciones altamente interactivas además de a minimizar errores) y la arquitectura VIPER (una arquitectura que sigue los principios SOLID, se centra en la separación de asuntos y favorece la reutilización de código en otras plataformas). ABSTRACT Emerging technologies such as cloud computing and mobile devices are creating an unprecedented opportunity for enhancing the educational system, letting both educators customize and improve the learning experience, and students acquire knowledge regardless of where they are. Moreover, through gamification techniques it would be possible to encourage and motivate students to learn arduous subjects by making the experience more motivating. Mobile games can be a perfect vehicle to support this enhanced learning experience. This project integrates the design and development of a highly scalable and performant cloud architecture, as well as the iOS client that uses it, in order to provide support to a new version of Temporis, a mobile multiplayer game focused on ordering time-based (e.g. history, art, sports, entertainment and literature) in a timeline that currently is available on Google Play. This work describes the development of the new Temporis version (Temporis v.2.0), providing details about improvements and details on the adaptation of the original Temporis. In particular, the new Google App Engine backend is described, which was created to support thousand of users developed in Go language are provided, in addition to other features like how to achieve push notications in this platform. Finally, the mobile iOS client developed using the latest and more relevant technologies is explained paying special attention to Swift (Apple's new programming language, that is safe and fast), the Functional Reactive Paradigm (that helps building highly interactive apps while minimizing bugs) and the VIPER architecture (a SOLID architecture that enforces separation of concerns and makes it easy to reuse code for other platforms).

Processing of speech signals for physical and sensory disabilities.

Assistive technology involving voice communication is used primarily by people who are deaf, hard of hearing, or who have speech and/or language disabilities. It is also used to a lesser extent by people with visual or motor disabilities. A very wide range of devices has been developed for people with hearing loss. These devices can be categorized not only by the modality of stimulation [i.e., auditory, visual, tactile, or direct electrical stimulation of the auditory nerve (auditory-neural)] but also in terms of the degree of speech processing that is used. At least four such categories can be distinguished: assistive devices (a) that are not designed specifically for speech, (b) that take the average characteristics of speech into account, (c) that process articulatory or phonetic characteristics of speech, and (d) that embody some degree of automatic speech recognition. Assistive devices for people with speech and/or language disabilities typically involve some form of speech synthesis or symbol generation for severe forms of language disability. Speech synthesis is also used in text-to-speech systems for sightless persons. Other applications of assistive technology involving voice communication include voice control of wheelchairs and other devices for people with mobility disabilities.

Study of interaction between Si(O,C) nanowires and the biological system

Nanomedicine is a new branch of medicine, based on the potentiality and intrinsic properties of nanomaterials. Indeed, the nanomaterials ( i.e. the materials with nano and under micron size) can be suitable to different applications in biomedicine. The nanostructures can be used by taking advantage of their properties (for example superparamagnetic nanoparticles) or functionalized to deliver the drug in a specific target, thanks the ability to cross biological barriers. The size and the shape of 1D-nanostructures (nanotubes and nanowires) have an important role on the cell fate: their morphology plays a key role on the interaction between nanostructure and the biological system. For this reason the 1D nanostructure are interesting for their ability to mime the biological system. An implantable material or device must therefore integrate with the surrounding extracellular matrix (ECM), a complex network of proteins with structural and signaling properties. Innovative techniques allow the generation of complex surface patterns that can resemble the structure of the ECM, such as 1D nanostructures. NWs based on cubic silicon carbide (3C-SiC), either bare (3C-SiC NWs) or surrounded by an amorphous shell (3C-SiC/SiO2 core/shell NWs), and silicon oxycarbide nanowires (SiOxCy NWs) can meet the chemical, mechanical and electrical requirements for tissue engineering and have a strong potential to pave the way for the development of a novel generation of implantable nano-devices. Silicon oxycarbide shows promising physical and chemical properties as elastic modulus, bending strength and hardness, chemical durability superior to conventional silicate glasses in aggressive environments and high temperature stability up to 1300 °C. Moreover, it can easily be engineered through functionalization and decoration with macro-molecules and nanoparticles. Silicon carbide has been extensively studied for applications in harsh conditions, as chemical environment, high electric field and high and low temperature, owing to its high hardness, high thermal conductivity, chemical inertness and high electron mobility. Also, its cubic polytype (3C) is highly biocompatible and hemocompatible, and some prototypes of biomedical applications and biomedical devices have been already realized starting from 3C-SiC thin films. Cubic SiC-based NWs can be used as a biomimetic biomaterial, providing a robust and novel biocompatible biological interface . We cultured in vitro A549 human lung adenocarcinoma epithelial cells and L929 murine fibroblast cells over core/shell SiC/SiO2, SiOxCy and bare 3C-SiC nanowire platforms, and analysed the cytotoxicity, by indirect and direct contact tests, the cell adhesion, and the cell proliferation. These studies showed that all the nanowires are biocompatible according to ISO 10993 standards. We evaluated the blood compatibility through the interaction of the nanowires with platelet rich plasma. The adhesion and activation of platelets on the nanowire bundles, assessed via SEM imaging and soluble P-selectin quantification, indicated that a higher platelet activation is induced by the core/shell structures compared to the bare ones. Further, platelet activation is higher with 3C-SiC/SiO2 NWs and SiOxCyNWs, which therefore appear suitable in view of possible tissue regeneration. On the contrary, bare 3C-SiC NWs show a lower platelet activation and are therefore promising in view of implantable bioelectronics devices, as cardiovascular implantable devices. The NWs properties are suitable to allow the design of a novel subretinal Micro Device (MD). This devices is based on Si NWs and PEDOT:PSS, though the well know principle of the hybrid ordered bulk heterojunction (OBHJ). The aim is to develop a device based on a well-established photovoltaic technology and to adapt this know-how to the prosthetic field. The hybrid OBHJ allows to form a radial p–n junction on a nanowire/organic structure. In addition, the nanowires increase the light absorption by means of light scattering effects: a nanowires based p-n junction increases the light absorption up to the 80%, as previously demonstrated, overcoming the Shockley-Queisser limit of 30 % of a bulk p-n junction. Another interesting employment of these NWs is to design of a SiC based epicardial-interacting patch based on teflon that include SiC nanowires. . Such contact patch can bridge the electric conduction across the cardiac infarct as nanowires can ‘sense’ the direction of the wavefront propagation on the survival cardiac tissue and transmit it to the downstream surivived regions without discontinuity. The SiC NWs are tested in terms of toxicology, biocompatibility and conductance among cardiomyocytes and myofibroblasts.

Use of subpixel techniques in pocket cameras to measure vibrations and displacements

Presentación oral SPIE Photonics Europe, Brussels, 16-19 April 2012.

Measurement of wide frequency range structural microvibrations with a pocket digital camera and sub-pixel techniques

Analysis of vibrations and displacements is a hot topic in structural engineering. Although there is a wide variety of methods for vibration analysis, direct measurement of displacements in the mid and high frequency range is not well solved and accurate devices tend to be very expensive. Low-cost systems can be achieved by applying adequate image processing algorithms. In this paper, we propose the use of a commercial pocket digital camera, which is able to register more than 420 frames per second (fps) at low resolution, for accurate measuring of small vibrations and displacements. The method is based on tracking elliptical targets with sub-pixel accuracy. Our proposal is demonstrated at a 10 m distance with a spatial resolution of 0.15 mm. A practical application over a simple structure is given, and the main parameters of an attenuated movement of a steel column after an impulsive impact are determined with a spatial accuracy of 4 µm.

Crystallographic orientation and electrode nature are key factors for electric current generation by Geobacter sulfurreducens

We have investigated the influence of electrode material and crystallographic structure on electron transfer and biofilm formation of Geobacter sulfurreducens. Single-crystal gold - Au(110), Au(111), Au(210) - and platinum - Pt(100), Pt(110), Pt(111), Pt(210) - electrodes were tested and compared to graphite rods. G. sulfurreducens electrochemically interacts with all these materials with different attachment kinetics and final current production, although redox species involved in the electron transfer to the anode are virtually the same in all cases. Initial bacterial colonization was fastest on graphite up to the monolayer level, whereas gold electrodes led to higher final current densities. Crystal geometry showed to have an important influence, with Au(210) sustaining a current density of up to 1442 (± 101) μA cm- 2 at the steady state, over Au(111) with 961 (± 94) μA cm- 2 and Au(110) with 944 (± 89) μA cm- 2. On the other hand, the platinum electrodes displayed the lowest performances, including Pt(210). Our results indicate that both crystal geometry and electrode material are key parameters for the efficient interaction of bacteria with the substrate and should be considered for the design of novel materials and microbial devices to optimize energy production.

Measurement of wide frequency range structural microvibrations with a pocket digital camera and sub-pixel techniques

Analysis of vibrations and displacements is a hot topic in structural engineering. Although there is a wide variety of methods for vibration analysis, direct measurement of displacements in the mid and high frequency range is not well solved and accurate devices tend to be very expensive. Low-cost systems can be achieved by applying adequate image processing algorithms. In this paper, we propose the use of a commercial pocket digital camera, which is able to register more than 420 frames per second (fps) at low resolution, for accurate measuring of small vibrations and displacements. The method is based on tracking elliptical targets with sub-pixel accuracy. Our proposal is demonstrated at a 10 m distance with a spatial resolution of 0.15 mm. A practical application over a simple structure is given, and the main parameters of an attenuated movement of a steel column after an impulsive impact are determined with a spatial accuracy of 4 µm.

Proceedings of the Institution of Electrical Engineers.

Vols.1-87,1872-1940 also called no.1-258.

Transforming Health: Emerging technology, the built environment and health behaviors

Thesis (Master's)--University of Washington, 2016-06