An ICT-based closed-loop model to improve care for heart failure patients

Durante las últimas décadas se ha producido un fenómeno global de envejecimiento en la población. Esta tendencia se puede observar prácticamente en todos los países del mundo y se debe principalmente a los avances en la medicina, y a los descensos en las tasas de fertilidad y mortalidad. El envejecimiento de la población tiene un gran impacto en la salud de los ciudadanos, y a menudo es la causa de aparición de enfermedades crónicas. Este tipo de enfermedades supone una amenaza y una carga importantes para la sociedad, especialmente en aspectos como la mortalidad o los gastos en los sistemas sanitarios. Entre las enfermedades cardiovasculares, la insuficiencia cardíaca es probablemente la condición con mayor prevalencia y afecta a 23-26 millones de personas en todo el mundo. Normalmente, la insuficiencia cardíaca presenta un mal pronóstico y una tasa de supervivencia bajas, en algunos casos peores que algún tipo de cáncer. Además, suele ser la causa de hospitalizaciones frecuentes y es una de las enfermedades más costosas para los sistemas sanitarios. La tendencia al envejecimiento de la población y la creciente incidencia de las enfermedades crónicas están llevando a una situación en la que los sistemas de salud no son capaces de hacer frente a la demanda de la sociedad. Los servicios de salud existentes tendrán que adaptarse para ser efectivos y sostenibles en el futuro. Es necesario identificar nuevos paradigmas de cuidado de pacientes, así como mecanismos para la provisión de servicios que ayuden a transformar estos sistemas sanitarios. En este contexto, esta tesis se plantea la búsqueda de soluciones, basadas en las Tecnologías de la Información y la Comunicación (TIC), que contribuyan a realizar la transformación en los sistemas sanitarios. En concreto, la tesis se centra en abordar los problemas de una de las enfermedades con mayor impacto en estos sistemas: la insuficiencia cardíaca. Las siguientes hipótesis constituyen la base para la realización de este trabajo de investigación: 1. Es posible definir un modelo basado en el paradigma de lazo cerrado y herramientas TIC que formalice el diseño de mejores servicios para pacientes con insuficiencia cardíaca. 2. El modelo de lazo cerrado definido se puede utilizar para definir un servicio real que ayude a gestionar la insuficiencia cardíaca crónica. 3. La introducción, la adopción y el uso de un servicio basado en el modelo definido se traducirá en mejoras en el estado de salud de los pacientes que sufren insuficiencia cardíaca. a. La utilización de un sistema basado en el modelo de lazo cerrado definido mejorará la experiencia del usuario de los pacientes. La definición del modelo planteado se ha basado en el estándar ISO / EN 13940- Sistema de conceptos para dar soporte a la continuidad de la asistencia. Comprende un conjunto de conceptos, procesos, flujos de trabajo, y servicios como componentes principales, y representa una formalización de los servicios para los pacientes con insuficiencia cardíaca. Para evaluar el modelo definido se ha definido un servicio real basado en el mismo, además de la implementación de un sistema de apoyo a dicho servicio. El diseño e implementación de dicho sistema se realizó siguiendo la metodología de Diseño Orientado a Objetivos. El objetivo de la evaluación consistía en investigar el efecto que tiene un servicio basado en el modelo de lazo cerrado sobre el estado de salud de los pacientes con insuficiencia cardíaca. La evaluación se realizó en el marco de un estudio clínico observacional. El análisis de los resultados ha comprendido métodos de análisis cuantitativos y cualitativos. El análisis cuantitativo se ha centrado en determinar el estado de salud de los pacientes en base a datos objetivos (obtenidos en pruebas de laboratorio o exámenes médicos). Para realizar este análisis se definieron dos índices específicos: el índice de estabilidad y el índice de la evolución del estado de salud. El análisis cualitativo ha evaluado la autopercepción del estado de salud de los pacientes en términos de calidad de vida, auto-cuidado, el conocimiento, la ansiedad y la depresión, así como niveles de conocimiento. Se ha basado en los datos recogidos mediante varios cuestionarios o instrumentos estándar (i.e. EQ-5D, la Escala de Ansiedad y Depresión (HADS), el Cuestionario de Cardiomiopatía de Kansas City (KCCQ), la Escala Holandesa de Conocimiento de Insuficiencia Cardíaca (DHFKS), y la Escala Europea de Autocuidado en Insuficiencia Cardíaca (EHFScBS), así como cuestionarios dedicados no estandarizados de experiencia de usuario. Los resultados obtenidos en ambos análisis, cuantitativo y cualitativo, se compararon con el fin de evaluar la correlación entre el estado de salud objetivo y subjetivo de los pacientes. Los resultados de la validación demostraron que el modelo propuesto tiene efectos positivos en el cuidado de los pacientes con insuficiencia cardíaca y contribuye a mejorar su estado de salud. Asimismo, ratificaron al modelo como instrumento válido para la definición de servicios mejorados para la gestión de esta enfermedad. ABSTRACT During the last decades we have witnessed a global aging phenomenon in the population. This can be observed in practically every country in the world, and it is mainly caused by the advances in medicine, and the decrease of mortality and fertility rates. Population aging has an important impact on citizens’ health and it is often the cause for chronic diseases, which constitute global burden and threat to the society in terms of mortality and healthcare expenditure. Among chronic diseases, Chronic Heart Failure (CHF) or Heart Failure (HF) is probably the one with highest prevalence, affecting between 23 and 26 million people worldwide. Heart failure is a chronic, long-term and serious condition with very poor prognosis and worse survival rates than some type of cancers. Additionally, it is often the cause of frequent hospitalizations and one of the most expensive conditions for the healthcare systems. The aging trends in the population and the increasing incidence of chronic diseases are leading to a situation where healthcare systems are not able to cope with the society demand. Current healthcare services will have to be adapted and redefined in order to be effective and sustainable in the future. There is a need to find new paradigms for patients’ care, and to identify new mechanisms for services’ provision that help to transform the healthcare systems. In this context, this thesis aims to explore new solutions, based on ICT, that contribute to achieve the needed transformation within the healthcare systems. In particular, it focuses on addressing the problems of one of the diseases with higher impact within these systems: Heart Failure. The following hypotheses represent the basis to the elaboration of this research: 1. It is possible to define a model based on a closed-loop paradigm and ICT tools that formalises the design of enhanced healthcare services for chronic heart failure patients. 2. The described closed-loop model can be exemplified in a real service that supports the management of chronic heart failure disease. 3. The introduction, adoption and use of a service based on the outlined model will result in improvements in the health status of patients suffering heart failure. 4. The user experience of patients when utilizing a system based on the defined closed-loop model will be enhanced. The definition of the closed-loop model for health care support of heart failure patients have been based on the standard ISO/EN 13940 System of concepts to support continuity of care. It includes a set of concept, processes and workflows, and services as main components, and it represent a formalization of services for heart failure patients. In order to be validated, the proposed closed-loop model has been instantiated into a real service and a supporting IT system. The design and implementation of the system followed the user centred design methodology Goal Oriented Design. The validation, that included an observational clinical study, aimed to investigate the effect that a service based on the closed-loop model had on heart failure patients’ health status. The analysis of results comprised quantitative and qualitative analysis methods. The quantitative analysis was focused on determining the health status of patients based on objective data (obtained in lab tests or physical examinations). Two specific indexes where defined and considered in this analysis: the stability index and the health status evolution index. The qualitative analysis assessed the self-perception of patients’ health status in terms of quality of life, self-care, knowledge, anxiety and depression, as well as knowledge levels. It was based on the data gathered through several standard instruments (i.e. EQ-5D, the Hospital Anxiety and Depression Scale, the Kansas City Cardiomyopathy Questionnaire, the Dutch Heart Failure Knowledge Scale, and the European Heart Failure Self-care Behaviour Scale) as well as dedicated non-standardized user experience questionnaires. The results obtained in both analyses, quantitative and qualitative, were compared in order to assess the correlation between the objective and subjective health status of patients. The results of the validation showed that the proposed model contributed to improve the health status of the patients and had a positive effect on the patients’ care. It also proved that the model is a valid instrument for designing enhanced healthcare services for heart failure patients.

Aplicación de técnicas de inteligencia artificial a la predicción de contaminantes atmosféricos

Abstract Air pollution is a big threat and a phenomenon that has a specific impact on human health, in addition, changes that occur in the chemical composition of the atmosphere can change the weather and cause acid rain or ozone destruction. Those are phenomena of global importance. The World Health Organization (WHO) considerates air pollution as one of the most important global priorities. Salamanca, Gto., Mexico has been ranked as one of the most polluted cities in this country. The industry of the area led to a major economic development and rapid population growth in the second half of the twentieth century. The impact in the air quality is important and significant efforts have been made to measure the concentrations of pollutants. The main pollution sources are locally based plants in the chemical and power generation sectors. The registered concerning pollutants are Sulphur Dioxide (SO2) and particles on the order of ∼10 micrometers or less (PM10). The prediction in the concentration of those pollutants can be a powerful tool in order to take preventive measures such as the reduction of emissions and alerting the affected population. In this PhD thesis we propose a model to predict concentrations of pollutants SO2 and PM10 for each monitoring booth in the Atmospheric Monitoring Network Salamanca (REDMAS - for its spanish acronym). The proposed models consider the use of meteorological variables as factors influencing the concentration of pollutants. The information used along this work is the current real data from REDMAS. In the proposed model, Artificial Neural Networks (ANN) combined with clustering algorithms are used. The type of ANN used is the Multilayer Perceptron with a hidden layer, using separate structures for the prediction of each pollutant. The meteorological variables used for prediction were: Wind Direction (WD), wind speed (WS), Temperature (T) and relative humidity (RH). Clustering algorithms, K-means and Fuzzy C-means, are used to find relationships between air pollutants and weather variables under consideration, which are added as input of the RNA. Those relationships provide information to the ANN in order to obtain the prediction of the pollutants. The results of the model proposed in this work are compared with the results of a multivariate linear regression and multilayer perceptron neural network. The evaluation of the prediction is calculated with the mean absolute error, the root mean square error, the correlation coefficient and the index of agreement. The results show the importance of meteorological variables in the prediction of the concentration of the pollutants SO2 and PM10 in the city of Salamanca, Gto., Mexico. The results show that the proposed model perform better than multivariate linear regression and multilayer perceptron neural network. The models implemented for each monitoring booth have the ability to make predictions of air quality that can be used in a system of real-time forecasting and human health impact analysis. Among the main results of the development of this thesis we can cite: A model based on artificial neural network combined with clustering algorithms for prediction with a hour ahead of the concentration of each pollutant (SO2 and PM10) is proposed. A different model was designed for each pollutant and for each of the three monitoring booths of the REDMAS. A model to predict the average of pollutant concentration in the next 24 hours of pollutants SO2 and PM10 is proposed, based on artificial neural network combined with clustering algorithms. Model was designed for each booth of the REDMAS and each pollutant separately. Resumen La contaminación atmosférica es una amenaza aguda, constituye un fenómeno que tiene particular incidencia sobre la salud del hombre. Los cambios que se producen en la composición química de la atmósfera pueden cambiar el clima, producir lluvia ácida o destruir el ozono, fenómenos todos ellos de una gran importancia global. La Organización Mundial de la Salud (OMS) considera la contaminación atmosférica como una de las más importantes prioridades mundiales. Salamanca, Gto., México; ha sido catalogada como una de las ciudades más contaminadas en este país. La industria de la zona propició un importante desarrollo económico y un crecimiento acelerado de la población en la segunda mitad del siglo XX. Las afectaciones en el aire son graves y se han hecho importantes esfuerzos por medir las concentraciones de los contaminantes. Las principales fuentes de contaminación son fuentes fijas como industrias químicas y de generación eléctrica. Los contaminantes que se han registrado como preocupantes son el Bióxido de Azufre (SO2) y las Partículas Menores a 10 micrómetros (PM10). La predicción de las concentraciones de estos contaminantes puede ser una potente herramienta que permita tomar medidas preventivas como reducción de emisiones a la atmósfera y alertar a la población afectada. En la presente tesis doctoral se propone un modelo de predicción de concentraci ón de los contaminantes más críticos SO2 y PM10 para cada caseta de monitorización de la Red de Monitorización Atmosférica de Salamanca (REDMAS). Los modelos propuestos plantean el uso de las variables meteorol ógicas como factores que influyen en la concentración de los contaminantes. La información utilizada durante el desarrollo de este trabajo corresponde a datos reales obtenidos de la REDMAS. En el Modelo Propuesto (MP) se aplican Redes Neuronales Artificiales (RNA) combinadas con algoritmos de agrupamiento. La RNA utilizada es el Perceptrón Multicapa con una capa oculta, utilizando estructuras independientes para la predicción de cada contaminante. Las variables meteorológicas disponibles para realizar la predicción fueron: Dirección de Viento (DV), Velocidad de Viento (VV), Temperatura (T) y Humedad Relativa (HR). Los algoritmos de agrupamiento K-means y Fuzzy C-means son utilizados para encontrar relaciones existentes entre los contaminantes atmosféricos en estudio y las variables meteorológicas. Dichas relaciones aportan información a las RNA para obtener la predicción de los contaminantes, la cual es agregada como entrada de las RNA. Los resultados del modelo propuesto en este trabajo son comparados con los resultados de una Regresión Lineal Multivariable (RLM) y un Perceptrón Multicapa (MLP). La evaluación de la predicción se realiza con el Error Medio Absoluto, la Raíz del Error Cuadrático Medio, el coeficiente de correlación y el índice de acuerdo. Los resultados obtenidos muestran la importancia de las variables meteorológicas en la predicción de la concentración de los contaminantes SO2 y PM10 en la ciudad de Salamanca, Gto., México. Los resultados muestran que el MP predice mejor la concentración de los contaminantes SO2 y PM10 que los modelos RLM y MLP. Los modelos implementados para cada caseta de monitorizaci ón tienen la capacidad para realizar predicciones de calidad del aire, estos modelos pueden ser implementados en un sistema que permita realizar la predicción en tiempo real y analizar el impacto en la salud de la población. Entre los principales resultados obtenidos del desarrollo de esta tesis podemos citar: Se propone un modelo basado en una red neuronal artificial combinado con algoritmos de agrupamiento para la predicción con una hora de anticipaci ón de la concentración de cada contaminante (SO2 y PM10). Se diseñó un modelo diferente para cada contaminante y para cada una de las tres casetas de monitorización de la REDMAS. Se propone un modelo de predicción del promedio de la concentración de las próximas 24 horas de los contaminantes SO2 y PM10, basado en una red neuronal artificial combinado con algoritmos de agrupamiento. Se diseñó un modelo para cada caseta de monitorización de la REDMAS y para cada contaminante por separado.

Adaptive fuzzy knowledge-based systems for control metabots' mobility on virtual environments

The confluence of three-dimensional (3D) virtual worlds with social networks imposes on software agents, in addition to conversational functions, the same behaviours as those common to human-driven avatars. In this paper, we explore the possibilities of the use of metabots (metaverse robots) with motion capabilities in complex virtual 3D worlds and we put forward a learning model based on the techniques used in evolutionary computation for optimizing the fuzzy controllers which will subsequently be used by metabots for moving around a virtual environment.

Legal Aspects which Implement Good Practice Measures in the Management of Construction and Demolition Waste

The construction industry, one of the most important ones in the development of a country, generates unavoidable impacts on the environment. The social demand towards greater respect for the environment is a high and general outcry. Therefore, the construction industry needs to reduce the impact it produces. Proper waste management is not enough; we must take a further step in environmental management, where new measures need to be introduced for the prevention at source, such as good practices to promote recycling. Following the amendment of the legal frame applicable to Construction and Demolition Waste (C&D waste), important developments have been incorporated in European and International laws, aiming to promote the culture of reusing and recycling. This change of mindset, that is progressively taking place in society, is allowing for the consideration of C&D waste no longer as an unusable waste, but as a reusable material. The main objective of the work presented in this paper is to enhance C&D waste management systems through the development of preventive measures during the construction process. These measures concern all the agents intervening in the construction process as only the personal implication of all of them can ensure an efficient management of the C&D waste generated. Finally, a model based on preventive measures achieves organizational cohesion between the different stages of the construction process, as well as promoting the conservation of raw materials through the use and waste minimization. All of these in order to achieve a C&D waste management system, whose primary goal is zero waste generation

Extended Triple-Junction Solar Cell 3D Distributed Model: Application to Chromatic Aberration-Related Losses

An extended 3D distributed model based on distributed circuit units for the simulation of triple‐junction solar cells under realistic conditions for the light distribution has been developed. A special emphasis has been put in the capability of the model to accurately account for current mismatch and chromatic aberration effects. This model has been validated, as shown by the good agreement between experimental and simulation results, for different light spot characteristics including spectral mismatch and irradiance non‐uniformities. This model is then used for the prediction of the performance of a triple‐junction solar cell for a light spot corresponding to a real optical architecture in order to illustrate its suitability in assisting concentrator system analysis and design process.

Engineering an Ontology for Autonomous Systems - The OASys Ontology

This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programe on autonomous systems’ engineering within a model-based control approach. The ontology aims at providing a unified conceptual framework for the autonomous systems’ stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-specific concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous system’s conceptual models. The objective is to obtain and to use these models as main input for the autonomous system’s model-based control system.

How has Spain become a leader in the wind energy industry during the last decade?

During the last decade, wind energy has been the fastest growing renewable source of energy worldwide. Limited sources of fossil fuel in addition to the negative effects of greenhouse gas emissions on the environment have led many countries to support development of renewable energies such as wind energy. Spain as the fourth biggest producer of wind energy plays an important global role in wind industry. In this paper, some important factors in the rapid growth of wind energy in Spain such as policy design, industry and technology, economic environment and social acceptance have been studied. The objective of this study is to introduce a model based on the successful development of wind energy in Spain which can be implemented by other countries

Contribution of re-regulation reservoirs considering pumping capability to environmentally friendly hydropower operation

Environmental constraints imposed on hydropoweroperation are usually given in the form of minimum environmental flows and maximum and minimum rates of change of flows, or ramp rates. One solution proposed to mitigate the environmental impact caused by the flows discharged by a hydropower plant while reducing the economic impact of the above-mentioned constraints consists in building a re-regulationreservoir, or afterbay, downstream of the power plant. Adding pumpingcapability between the re-regulationreservoir and the main one could contribute both to reducing the size of the re-regulationreservoir, with the consequent environmental improvement, and to improving the economic feasibility of the project, always fulfilling the environmental constraints imposed to hydropoweroperation. The objective of this paper is studying the contribution of a re-regulationreservoir to fulfilling the environmental constraints while reducing the economic impact of said constraints. For that purpose, a revenue-driven optimization model based on mixed integer linear programming is used. Additionally, the advantages of adding pumpingcapability are analysed. In order to illustrate the applicability of the methodology, a case study based on a real hydropower plant is presented

Simulation of a mechanical thrombectomy device based in the use of self-expandable stents for the blood clots extraction

Recently, we have presented some studies concerning the analysis, design and optimization of one experimental device developed in the UK - GPTAD - which has been designed to remove blood clots without the need to make contact with the clot itself, thereby potentially reducing the risk of problems such as downstream embolisation. Based on the idea of a modification of the previous device, in this work, we present a model based in the use of stents like the SolitaireTM FR, which is in contact with the clot itself. In the case of such devices, the stent is self-expandable and the extraction of the blood clot is faciliatated by the stent, which must be inside the clot. Such stents are generally inserted in position by using the guidewire inserted into the catheter. This type of modeling could potentially be useful in showing how the blood clot is moved by the various different forces involved. The modelling has been undertaken by analyzing the resistances, compliances and inertances effects. We model an artery and blood clot for range of forces for the guidewire. In each case we determine the interaction between blood clot, stent and artery.

Definición de un nuevo modelo de negocio sostenible y aplicable a la nueva realidad de negocios y social para la convergencia de operadores de telecomunicación e Internet

La presente tesis analiza la integración del sector de las telecomunicaciones con los de TI y medios que conforman el actual hiper-sector de las TIC, para abordar una propuesta de valor que se plantea a dos niveles. Se expone de un lado, la iniciativa WIMS 2.0, que aborda los aspectos tecnológicos y estratégicos de la convergencia telco e Internet para, posteriormente, definir un nuevo modelo de negocio, que adaptado al nuevo sector integrado y siguiendo paradigmas inéditos como los que plantea la innovación abierta, permita generar nuevos flujos de ingresos en áreas no habituales para los operadores de telecomunicaciones. A lo largo del capítulo 2, el lector encontrará la contextualización del entorno de las comunicaciones de banda ancha desde tres vertientes: los aspectos tecnológicos, los económicos y el mercado actual, todo ello enfocado en una dimensión nacional, europea y mundial. Se establece de esta manera las bases para el desarrollo de los siguientes capítulos al demostrar cómo la penetración de la banda ancha ha potenciado el desarrollo de un nuevo sistema de valor en el sector integrado de las TIC, alrededor del cual surgen propuestas de modelos de negocio originales que se catalogan en una taxonomía propia. En el tercer capítulo se detalla la propuesta de valor de la iniciativa WIMS 2.0, fundada y liderada por el autor de esta tesis. WIMS 2.0, como iniciativa abierta, se dirige a la comunidad como una propuesta de un nuevo ecosistema y como un modelo de referencia integrado sobre el que desplegar servicios convergentes. Adicionalmente, sobre el planteamiento teórico definido se aporta el enfoque práctico que supone el despliegue del modelo de referencia dentro de la arquitectura de un operador como Telefónica. El capítulo 4 muestra el modelo de negocio Innovación 2.0, basado en la innovación abierta con el objetivo de capturar nuevos flujos de ingresos incrementando el portfolio de servicios innovadores gracias a las ideas frescas y brillantes de start-ups. Innovación 2.0 lejos de quedarse en una mera propuesta teórica, muestra sus bondades en el éxito práctico en el mercado que ha validado las hipótesis planteadas. El último capítulo plantea las líneas futuras de investigación tanto en el ámbito de la iniciativa WIMS 2.0 como en el modelo de Innovación 2.0, algunas de las cuales se están comenzando a abordar. 3 Abstract This thesis examines the integration of telecommunications sector with IT and media that make up the current hyper-ICT sector, to address a value proposition that arises at two levels. On one side, WIMS 2.0 initiative, which addresses the technological and strategic aspects of the telco and Internet convergence to later define a new business model, adapted to the new integrated sector and following original paradigms such as those posed by open innovation, which generates new revenue streams in areas not typical for telecom operators. Throughout Chapter 2, the reader will find the contextualization of the broadband communications environment from three aspects: technological, economic and the current market all focused on a national, European and world scale. Thus it establishes the basis for the development of the following chapters by demonstrating how the penetration of broadband has led to the development of a new value system in the integrated sector of the ICT, around which arise proposals of originals business models, which are categorized in a own taxonomy. The third chapter outlines the value proposition of the WIMS 2.0 initiative, founded and led by the author of this thesis. WIMS 2.0, as open initiative, presents to the community a proposal for a new ecosystem and an integrated reference model on which to deploy converged services. Additionally, above the theoretical approach defined, WIMS 2.0 provides the practical approach is provided which is the deployment of the reference model into the architecture of an operator such as Telefónica. Chapter 4 shows the Innovation 2.0 business model, based on open innovation with the goal of capturing new revenue streams by increasing the portfolio of innovative services thanks to the fresh and brilliant ideas from start-ups. Innovation 2.0, far from being a mere theoretical proposition, shows its benefits in the successful deployment in the market, which has validated the hypotheses. The last chapter sets out the future research at both the WIMS 2.0 initiative and Innovation 2.0 model, some of which are beginning to be addressed.

Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

Understanding phosphorus diffusion into silicon in a MOVPE environment for III-V on silicon solar cells

Dual-junction solar cells formed by a GaAsP or GaInP top cell and a silicon bottom cell seem to be attractive candidates to materialize the long sought-for integration of III?V materials on silicon for photovoltaic applications. When manufacturing a multi-junction solar cell on silicon, one of the first processes to be addressed is the development of the bottom subcell and, in particular, the formation of its emitter. In this study, we analyze, both experimentally and by simulations, the formation of the emitter as a result of phosphorus diffusion that takes place during the first stages of the epitaxial growth of the solar cell. Different conditions for the Metal-Organic Vapor Phase Epitaxy (MOVPE) process have been evaluated to understand the impact of each parameter, namely, temperature, phosphine partial pressure, time exposure and memory effects in the final diffusion profiles obtained. A model based on SSupremIV process simulator has been developed and validated against experimental profiles measured by ECV and SIMS to calculate P diffusion profiles in silicon formed in a MOVPE environment taking in consideration all these factors.

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro.

Towards a lightweight mobile semantic-based approach for enhancing interaction with smart objects

This work describes a semantic extension for a user-smart object interaction model based on the ECA paradigm (Event-Condition-Action). In this approach, smart objects publish their sensing (event) and action capabilities in the cloud and mobile devices are prepared to retrieve them and act as mediators to configure personalized behaviours for the objects. In this paper, the information handled by this interaction system has been shaped according several semantic models that, together with the integration of an embedded ontological and rule-based reasoner, are exploited in order to (i) automatically detect incompatible ECA rules configurations and to (ii) support complex ECA rules definitions and execution. This semantic extension may significantly improve the management of smart spaces populated with numerous smart objects from mobile personal devices, as it facilitates the configuration of coherent ECA rules.