Complex tracer mobilities in polymer networks revealed by fluorescence correlation spectroscopy

Gels are elastic porous polymer networks that are accompanied by pronounced mechanical properties. Due to their biocompatibility, ‘responsive hydrogels’ (HG) have many biomedical applications ranging from biosensors and drug delivery to tissue engineering. They respond to external stimuli such as temperature and salt by changing their dimensions. Of paramount importance is the ability to engineer penetrability and diffusion of interacting molecules in the crowded HG environment, as this would enable one to optimize a specific functionality. Even though the conditions under which biomedical devices operate are rather complex, a bottom-up approach could reduce the complexity of mutually coupled parameters influencing tracer mobility. The present thesis focuses on the interaction-induced tracer diffusion in polymer solutions and their homologous gels, probed by means of Fluorescence Correlation Spectroscopy (FCS). This is a single-molecule-sensitive technique having the advantage of optimal performance under ultralow tracer concentrations, typically employed in biosensors. Two different types of hydrogels have been investigated, a conventional one with broad polydispersity in the distance between crosslink points and a so-called ‘ideal’, with uniform mesh size distribution. The former is based on a thermoresponsive polymer, exhibiting phase separation in water at temperatures close to the human body temperature. The latter represents an optimal platform to study tracer diffusion. Mobilities of different tracers have been investigated in each network, varying in size, geometry and in terms of tracer-polymer attractive strength, as perturbed by different stimuli. The thesis constitutes a systematic effort towards elucidating the role of the strength and nature of different tracer-polymer interactions, on tracer mobilities; it outlines that interactions can still be very important even in the simplified case of dilute polymer solutions; it also demonstrates that the presence of permanent crosslinks exerts distinct tracer slowdown, depending on the tracer type and the nature of the tracer-polymer interactions, expressed differently by each tracer with regard to the selected stimulus. In aqueous polymer solutions, the tracer slowdown is found to be system-dependent and no universal trend seems to hold, in contrast to predictions from scaling theory for non-interacting nanoparticle mobility and empirical relations concerning the mesh size in polymer solutions. Complex tracer dynamics in polymer networks may be distinctly expressed by FCS, depending on the specific synergy among-at least some of - the following parameters: nature of interactions, external stimuli employed, tracer size and type, crosslink density and swelling ratio.

COMPARATIVE STUDY OF INFORMAL HEALTH CARE NETWORKS AND ELDERLY HEALTH STATUS IN ARGENTINA AND CUBA

This study will explore familial and friend support networks and living arrangements among elderly individuals in Latin America and the impact that this type of support has on the health of the elderly individuals in the countries of interest. Using data from the Survey on Health and Well-Being of Elders (SABE) from 1999-2000, I will explore which type of support has a larger impact on overall health. I will also measure differences in unmet needs for certain health services. This topic is particularly interesting because it will help to uncover what policies are best for aiding in the healthcare of the elderly in aging population. Lastly, the investigation of this topic will allow me to draw conclusions about the most effective means of social and public policy for the elderly community and provide me with information about the role of both informal provisions of support from family and friends, and formal provisions of support from the government. My primary focus will be on Argentina, using Buenos Aires as the sample city, and Cuba, using Havana as the sample city. These two countries have increasingly aging populations, poorer resources and vast inequalities, but, extremely different political, economic and cultural situations. Comparing the two countries will further allow me to determine correlations between health and the existence of support networks, as well as provide me with information to make more general claims that may be of use in the United States. Argentina is particularly interesting to me because of my abroad experience and homestay experience with an older Argentine woman who lived alone but depended upon her family for many healthcare needs, doctors’ visits and general well-being. In Argentina, I experienced a different form of living than I am used to in the United States, where many older individuals or couples live in nursing homes or assisted living facilities rather than alone or with family. The changing economic climate of the two countries coupled with labor patterns of women returning to work at rapid rates indicates that policies cannot just rely on either the formal or informal sector but require a combination of the two sectors working together.This paper will first give background on the difference in the economies and the health care systems in Argentina and Cuba and will show why it interesting to study and compare these two countries. I will then discuss the health status of the elderly in each population as well as discuss the informal care networks and the role of family in each country. This section will then be followed by a description of the data and methods used. I will end by drawing conclusions about the study and the outcomes, and then I will attempt to make suggestions about effective health care policies for the elderly.

Detecting unknown attacks in wireless sensor networks that contain mobile nodes

As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

Multiple attractors, long chaotic transients, and failure in small-world networks of excitable neurons.

We study the dynamical states of a small-world network of recurrently coupled excitable neurons, through both numerical and analytical methods. The dynamics of this system depend mostly on both the number of long-range connections or ?shortcuts?, and the delay associated with neuronal interactions. We find that persistent activity emerges at low density of shortcuts, and that the system undergoes a transition to failure as their density reaches a critical value. The state of persistent activity below this transition consists of multiple stable periodic attractors, whose number increases at least as fast as the number of neurons in the network. At large shortcut density and for long enough delays the network dynamics exhibit exceedingly long chaotic transients, whose failure times follow a stretched exponential distribution. We show that this functional form arises for the ensemble-averaged activity if the failure time for each individual network realization is exponen- tially distributed

Collective Organization of Complex Networks: Emergent Scales, Vulnerability, and Targeting of Desired Dynamics

Cuando una colectividad de sistemas dinámicos acoplados mediante una estructura irregular de interacciones evoluciona, se observan dinámicas de gran complejidad y fenómenos emergentes imposibles de predecir a partir de las propiedades de los sistemas individuales. El objetivo principal de esta tesis es precisamente avanzar en nuestra comprensión de la relación existente entre la topología de interacciones y las dinámicas colectivas que una red compleja es capaz de mantener. Siendo este un tema amplio que se puede abordar desde distintos puntos de vista, en esta tesis se han estudiado tres problemas importantes dentro del mismo que están relacionados entre sí. Por un lado, en numerosos sistemas naturales y artificiales que se pueden describir mediante una red compleja la topología no es estática, sino que depende de la dinámica que se desarrolla en la red: un ejemplo son las redes de neuronas del cerebro. En estas redes adaptativas la propia topología emerge como consecuencia de una autoorganización del sistema. Para conocer mejor cómo pueden emerger espontáneamente las propiedades comúnmente observadas en redes reales, hemos estudiado el comportamiento de sistemas que evolucionan según reglas adaptativas locales con base empírica. Nuestros resultados numéricos y analíticos muestran que la autoorganización del sistema da lugar a dos de las propiedades más universales de las redes complejas: a escala mesoscópica, la aparición de una estructura de comunidades, y, a escala macroscópica, la existencia de una ley de potencias en la distribución de las interacciones en la red. El hecho de que estas propiedades aparecen en dos modelos con leyes de evolución cuantitativamente distintas que siguen unos mismos principios adaptativos sugiere que estamos ante un fenómeno que puede ser muy general, y estar en el origen de estas propiedades en sistemas reales. En segundo lugar, proponemos una medida que permite clasificar los elementos de una red compleja en función de su relevancia para el mantenimiento de dinámicas colectivas. En concreto, estudiamos la vulnerabilidad de los distintos elementos de una red frente a perturbaciones o grandes fluctuaciones, entendida como una medida del impacto que estos acontecimientos externos tienen en la interrupción de una dinámica colectiva. Los resultados que se obtienen indican que la vulnerabilidad dinámica es sobre todo dependiente de propiedades locales, por tanto nuestras conclusiones abarcan diferentes topologías, y muestran la existencia de una dependencia no trivial entre la vulnerabilidad y la conectividad de los elementos de una red. Finalmente, proponemos una estrategia de imposición de una dinámica objetivo genérica en una red dada e investigamos su validez en redes con diversas topologías que mantienen regímenes dinámicos turbulentos. Se obtiene como resultado que las redes heterogéneas (y la amplia mayora de las redes reales estudiadas lo son) son las más adecuadas para nuestra estrategia de targeting de dinámicas deseadas, siendo la estrategia muy efectiva incluso en caso de disponer de un conocimiento muy imperfecto de la topología de la red. Aparte de la relevancia teórica para la comprensión de fenómenos colectivos en sistemas complejos, los métodos y resultados propuestos podrán dar lugar a aplicaciones en sistemas experimentales y tecnológicos, como por ejemplo los sistemas neuronales in vitro, el sistema nervioso central (en el estudio de actividades síncronas de carácter patológico), las redes eléctricas o los sistemas de comunicaciones. ABSTRACT The time evolution of an ensemble of dynamical systems coupled through an irregular interaction scheme gives rise to dynamics of great of complexity and emergent phenomena that cannot be predicted from the properties of the individual systems. The main objective of this thesis is precisely to increase our understanding of the interplay between the interaction topology and the collective dynamics that a complex network can support. This is a very broad subject, so in this thesis we will limit ourselves to the study of three relevant problems that have strong connections among them. First, it is a well-known fact that in many natural and manmade systems that can be represented as complex networks the topology is not static; rather, it depends on the dynamics taking place on the network (as it happens, for instance, in the neuronal networks in the brain). In these adaptive networks the topology itself emerges from the self-organization in the system. To better understand how the properties that are commonly observed in real networks spontaneously emerge, we have studied the behavior of systems that evolve according to local adaptive rules that are empirically motivated. Our numerical and analytical results show that self-organization brings about two of the most universally found properties in complex networks: at the mesoscopic scale, the appearance of a community structure, and, at the macroscopic scale, the existence of a power law in the weight distribution of the network interactions. The fact that these properties show up in two models with quantitatively different mechanisms that follow the same general adaptive principles suggests that our results may be generalized to other systems as well, and they may be behind the origin of these properties in some real systems. We also propose a new measure that provides a ranking of the elements in a network in terms of their relevance for the maintenance of collective dynamics. Specifically, we study the vulnerability of the elements under perturbations or large fluctuations, interpreted as a measure of the impact these external events have on the disruption of collective motion. Our results suggest that the dynamic vulnerability measure depends largely on local properties (our conclusions thus being valid for different topologies) and they show a non-trivial dependence of the vulnerability on the connectivity of the network elements. Finally, we propose a strategy for the imposition of generic goal dynamics on a given network, and we explore its performance in networks with different topologies that support turbulent dynamical regimes. It turns out that heterogeneous networks (and most real networks that have been studied belong in this category) are the most suitable for our strategy for the targeting of desired dynamics, the strategy being very effective even when the knowledge on the network topology is far from accurate. Aside from their theoretical relevance for the understanding of collective phenomena in complex systems, the methods and results here discussed might lead to applications in experimental and technological systems, such as in vitro neuronal systems, the central nervous system (where pathological synchronous activity sometimes occurs), communication systems or power grids.

Gear dynamics monitoring using discrete wavelet transformation and multi-layer perceptron neural networks

This paper presents a multi-stage algorithm for the dynamic condition monitoring of a gear. The algorithm provides information referred to the gear status (fault or normal condition) and estimates the mesh stiffness per shaft revolution in case that any abnormality is detected. In the first stage, the analysis of coefficients generated through discrete wavelet transformation (DWT) is proposed as a fault detection and localization tool. The second stage consists in establishing the mesh stiffness reduction associated with local failures by applying a supervised learning mode and coupled with analytical models. To do this, a multi-layer perceptron neural network has been configured using as input features statistical parameters sensitive to torsional stiffness decrease and derived from wavelet transforms of the response signal. The proposed method is applied to the gear condition monitoring and results show that it can update the mesh dynamic properties of the gear on line.

Design and optimization of optical, fiber based PSK demodulators for high-bit-rate optical networks

El objetivo principal de esta tesis ha sido el diseño y la optimización de receptores implementados con fibra óptica, para ser usados en redes ópticas de alta velocidad que empleen formatos de modulación de fase. En los últimos años, los formatos de modulación de fase (Phase Shift keying, PSK) han captado gran atención debido a la mejora de sus prestaciones respecto a los formatos de modulación convencionales. Principalmente, presentan una mejora de la eficiencia espectral y una mayor tolerancia a la degradación de la señal causada por la dispersión cromática, la dispersión por modo de polarización y los efectos no-lineales en la fibra óptica. En este trabajo, se analizan en detalle los formatos PSK, incluyendo sus variantes de modulación de fase diferencial (Differential Phase Shift Keying, DPSK), en cuadratura (Differential Quadrature Phase Shift Keying, DQPSK) y multiplexación en polarización (Polarization Multiplexing Differential Quadrature Phase Shift Keying, PM-DQPSK), con la finalidad de diseñar y optimizar los receptores que permita su demodulación. Para ello, se han analizado y desarrollado nuevas estructuras que ofrecen una mejora en las prestaciones del receptor y una reducción de coste comparadas con las actualmente disponibles. Para la demodulación de señales DPSK, en esta tesis, se proponen dos nuevos receptores basados en un interferómetro en línea Mach-Zehnder (MZI) implementado con tecnología todo-fibra. El principio de funcionamiento de los MZI todo-fibra propuestos se asienta en la interferencia modal que se produce en una fibra multimodo (MMF) cuando se situada entre dos monomodo (SMF). Este tipo de configuración (monomodo-multimodo-monomodo, SMS) presenta un buen ratio de extinción interferente si la potencia acoplada en la fibra multimodo se reparte, principal y equitativamente, entre dos modos dominantes. Con este objetivo, se han estudiado y demostrado tanto teórica como experimentalmente dos nuevas estructuras SMS que mejoran el ratio de extinción. Una de las propuestas se basa en emplear una fibra multimodo de índice gradual cuyo perfil del índice de refracción presenta un hundimiento en su zona central. La otra consiste en una estructura SMS con las fibras desalineadas y donde la fibra multimodo es una fibra de índice gradual convencional. Para las dos estructuras, mediante el análisis teórico desarrollado, se ha demostrado que el 80 – 90% de la potencia de entrada se acopla a los dos modos dominantes de la fibra multimodo y se consigue una diferencia inferior al 10% entre ellos. También se ha demostrado experimentalmente que se puede obtener un ratio de extinción de al menos 12 dB. Con el objeto de demostrar la capacidad de estas estructuras para ser empleadas como demoduladores de señales DPSK, se han realizado numerosas simulaciones de un sistema de transmisión óptico completo y se ha analizado la calidad del receptor bajo diferentes perspectivas, tales como la sensibilidad, la tolerancia a un filtrado óptico severo o la tolerancia a las dispersiones cromática y por modo de polarización. En todos los casos se ha concluido que los receptores propuestos presentan rendimientos comparables a los obtenidos con receptores convencionales. En esta tesis, también se presenta un diseño alternativo para la implementación de un receptor DQPSK, basado en el uso de una fibra mantenedora de la polarización (PMF). A través del análisi teórico y del desarrollo de simulaciones numéricas, se ha demostrado que el receptor DQPSK propuesto presenta prestaciones similares a los convencionales. Para complementar el trabajo realizado sobre el receptor DQPSK basado en PMF, se ha extendido el estudio de su principio de demodulación con el objeto de demodular señales PM-DQPSK, obteniendo como resultado la propuesta de una nueva estructura de demodulación. El receptor PM-DQPSK propuesto se basa en la estructura conjunta de una única línea de retardo junto con un rotador de polarización. Se ha analizado la calidad de los receptores DQPSK y PM-DQPSK bajo diferentes perspectivas, tales como la sensibilidad, la tolerancia a un filtrado óptico severo, la tolerancia a las dispersiones cromática y por modo de polarización o su comportamiento bajo condiciones no-ideales. En comparación con los receptores convencionales, nuestra propuesta exhibe prestaciones similares y además permite un diseño más simple que redunda en un coste potencialmente menor. En las redes de comunicaciones ópticas actuales se utiliza la tecnología de multimplexación en longitud de onda (WDM) que obliga al uso de filtros ópticos con bandas de paso lo más estrechas posibles y a emplear una serie de dispositivos que incorporan filtros en su arquitectura, tales como los multiplexores, demultiplexores, ROADMs, conmutadores y OXCs. Todos estos dispositivos conectados entre sí son equivalentes a una cadena de filtros cuyo ancho de banda se va haciendo cada vez más estrecho, llegando a distorsionar la forma de onda de las señales. Por esto, además de analizar el impacto del filtrado óptico en las señales de 40 Gbps DQPSK y 100 Gbps PM-DQPSK, este trabajo de tesis se completa estudiando qué tipo de filtro óptico minimiza las degradaciones causadas en la señal y analizando el número máximo de filtros concatenados que permiten mantener la calidad requerida al sistema. Se han estudiado y simulado cuatro tipos de filtros ópticos;Butterworth, Bessel, FBG y F-P. ABSTRACT The objective of this thesis is the design and optimization of optical fiber-based phase shift keying (PSK) demodulators for high-bit-rate optical networks. PSK modulation formats have attracted significant attention in recent years, because of the better performance with respect to conventional modulation formats. Principally, PSK signals can improve spectrum efficiency and tolerate more signal degradation caused by chromatic dispersion, polarization mode dispersion and nonlinearities in the fiber. In this work, many PSK formats were analyzed in detail, including the variants of differential phase modulation (Differential Phase Shift Keying, DPSK), in quadrature (Differential Quadrature Phase Shift Keying, DQPSK) and polarization multiplexing (Polarization Multiplexing Differential Quadrature Phase Shift Keying, PM-DQPSK), in order to design and optimize receivers enabling demodulations. Therefore, novel structures, which offer good receiver performances and a reduction in cost compared to the current structures, have been analyzed and developed. Two novel receivers based on an all-fiber in-line Mach-Zehnder interferometer (MZI) were proposed for DPSK signal demodulation in this thesis. The operating principle of the all-fiber MZI is based on the modal interference that occurs in a multimode fiber (MMF) when it is located between two single-mode fibers (SMFs). This type of configuration (Single-mode-multimode-single-mode, SMS) can provide a good extinction ratio if the incoming power from the SMF could be coupled equally into two dominant modes excited in the MMF. In order to improve the interference extinction ratio, two novel SMS structures have been studied and demonstrated, theoretically and experimentally. One of the two proposed MZIs is based on a graded-index multimode fiber (MMF) with a central dip in the index profile, located between two single-mode fibers (SMFs). The other one is based on a conventional graded-index MMF mismatch spliced between two SMFs. Theoretical analysis has shown that, in these two schemes, 80 – 90% of the incoming power can be coupled into the two dominant modes exited in the MMF, and the power difference between them is only ~10%. Experimental results show that interference extinction ratio of 12 dB could be obtained. In order to demonstrate the capacity of these two structures for use as DPSK signal demodulators, numerical simulations in a completed optical transmission system have been carried out, and the receiver quality has been analyzed under different perspectives, such as sensitivity, tolerance to severe optical filtering or tolerance to chromatic and polarization mode dispersion. In all cases, from the simulation results we can conclude that the two proposed receivers can provide performances comparable to conventional ones. In this thesis, an alternative design for the implementation of a DQPSK receiver, which is based on a polarization maintaining fiber (PMF), was also presented. To complement the work made for the PMF-based DQPSK receiver, the study of the demodulation principle has been extended to demodulate PM-DQPSK signals, resulting in the proposal of a novel demodulation structure. The proposed PM-DQPSK receiver is based on only one delay line and a polarization rotator. The quality of the proposed DQPSK and PM-DQPSK receivers under different perspectives, such as sensitivity, tolerance to severe optical filtering, tolerance to chromatic dispersion and polarization mode dispersion, or behavior under non-ideal conditions. Compared with the conventional receivers, our proposals exhibit similar performances but allow a simpler design which can potentially reduce the cost. The wavelength division multiplexing (WDM) technology used in current optical communications networks requires the use of optical filters with a passband as narrow as possible, and the use of a series of devices that incorporate filters in their architecture, such as multiplexers, demultiplexers, switches, reconfigurable add-drop multiplexers (ROADMs) and optical cross-connects (OXCs). All these devices connected together are equivalent to a chain of filters whose bandwidth becomes increasingly narrow, resulting in distortion to the waveform of the signals. Therefore, in addition to analyzing the impact of optical filtering on signal of 40 Gbps DQPSK and 100 Gbps PM-DQPSK, we study which kind of optical filter minimizes the signal degradation and analyze the maximum number of concatenated filters for maintaining the required quality of the system. Four types of optical filters, including Butterworth, Bessel, FBG and FP, have studied and simulated.

Nepfix: on-demand cloud elastic simulation of networks of evolutionary processors

Una Red de Procesadores Evolutivos o NEP (por sus siglas en ingles), es un modelo computacional inspirado por el modelo evolutivo de las celulas, específicamente por las reglas de multiplicación de las mismas. Esta inspiración hace que el modelo sea una abstracción sintactica de la manipulation de information de las celulas. En particu¬lar, una NEP define una maquina de cómputo teorica capaz de resolver problemas NP completos de manera eficiente en tóerminos de tiempo. En la praóctica, se espera que las NEP simuladas en móaquinas computacionales convencionales puedan resolver prob¬lemas reales complejos (que requieran ser altamente escalables) a cambio de una alta complejidad espacial. En el modelo NEP, las cóelulas estóan representadas por palabras que codifican sus secuencias de ADN. Informalmente, en cualquier momento de cómputo del sistema, su estado evolutivo se describe como un coleccion de palabras, donde cada una de ellas representa una celula. Estos momentos fijos de evolucion se denominan configuraciones. De manera similar al modelo biologico, las palabras (celulas) mutan y se dividen en base a bio-operaciones sencillas, pero solo aquellas palabras aptas (como ocurre de forma parecida en proceso de selection natural) seran conservadas para la siguiente configuracióon. Una NEP como herramienta de computation, define una arquitectura paralela y distribuida de procesamiento simbolico, en otras palabras, una red de procesadores de lenguajes. Desde el momento en que el modelo fue propuesto a la comunidad científica en el año 2001, múltiples variantes se han desarrollado y sus propiedades respecto a la completitud computacional, eficiencia y universalidad han sido ampliamente estudiadas y demostradas. En la actualidad, por tanto, podemos considerar que el modelo teórico NEP se encuentra en el estadio de la madurez. La motivación principal de este Proyecto de Fin de Grado, es proponer una aproxi-mación práctica que permita dar un salto del modelo teórico NEP a una implantación real que permita su ejecucion en plataformas computacionales de alto rendimiento, con el fin de solucionar problemas complejos que demanda la sociedad actual. Hasta el momento, las herramientas desarrolladas para la simulation del modelo NEP, si bien correctas y con resultados satisfactorios, normalmente estón atadas a su entorno de ejecucion, ya sea el uso de hardware específico o implementaciones particulares de un problema. En este contexto, el propósito fundamental de este trabajo es el desarrollo de Nepfix, una herramienta generica y extensible para la ejecucion de cualquier algo¬ritmo de un modelo NEP (o alguna de sus variantes), ya sea de forma local, como una aplicación tradicional, o distribuida utilizando los servicios de la nube. Nepfix es una aplicacion software desarrollada durante 7 meses y que actualmente se encuentra en su segunda iteration, una vez abandonada la fase de prototipo. Nepfix ha sido disenada como una aplicacion modular escrita en Java 8 y autocontenida, es decir, no requiere de un entorno de ejecucion específico (cualquier maquina virtual de Java es un contenedor vólido). Nepfix contiene dos componentes o móodulos. El primer móodulo corresponde a la ejecución de una NEP y es por lo tanto, el simulador. Para su desarrollo, se ha tenido en cuenta el estado actual del modelo, es decir, las definiciones de los procesadores y filtros mas comunes que conforman la familia del modelo NEP. Adicionalmente, este componente ofrece flexibilidad en la ejecucion, pudiendo ampliar las capacidades del simulador sin modificar Nepfix, usando para ello un lenguaje de scripting. Dentro del desarrollo de este componente, tambióen se ha definido un estóandar de representacióon del modelo NEP basado en el formato JSON y se propone una forma de representation y codificación de las palabras, necesaria para la comunicación entre servidores. Adicional-mente, una característica importante de este componente, es que se puede considerar una aplicacion aislada y por tanto, la estrategia de distribution y ejecución son total-mente independientes. El segundo moódulo, corresponde a la distribucióon de Nepfix en la nube. Este de-sarrollo es el resultado de un proceso de i+D, que tiene una componente científica considerable. Vale la pena resaltar el desarrollo de este modulo no solo por los resul-tados prócticos esperados, sino por el proceso de investigation que se se debe abordar con esta nueva perspectiva para la ejecución de sistemas de computación natural. La principal característica de las aplicaciones que se ejecutan en la nube es que son gestionadas por la plataforma y normalmente se encapsulan en un contenedor. En el caso de Nepfix, este contenedor es una aplicacion Spring que utiliza el protocolo HTTP o AMQP para comunicarse con el resto de instancias. Como valor añadido, Nepfix aborda dos perspectivas de implementation distintas (que han sido desarrolladas en dos iteraciones diferentes) del modelo de distribution y ejecucion, que tienen un impacto muy significativo en las capacidades y restricciones del simulador. En concreto, la primera iteration utiliza un modelo de ejecucion asincrono. En esta perspectiva asincrona, los componentes de la red NEP (procesadores y filtros) son considerados como elementos reactivos a la necesidad de procesar una palabra. Esta implementation es una optimization de una topologia comun en el modelo NEP que permite utilizar herramientas de la nube para lograr un escalado transparente (en lo ref¬erente al balance de carga entre procesadores) pero produce efectos no deseados como indeterminacion en el orden de los resultados o imposibilidad de distribuir eficiente-mente redes fuertemente interconectadas. Por otro lado, la segunda iteration corresponde al modelo de ejecucion sincrono. Los elementos de una red NEP siguen un ciclo inicio-computo-sincronizacion hasta que el problema se ha resuelto. Esta perspectiva sincrona representa fielmente al modelo teórico NEP pero el proceso de sincronizacion es costoso y requiere de infraestructura adicional. En concreto, se requiere un servidor de colas de mensajes RabbitMQ. Sin embargo, en esta perspectiva los beneficios para problemas suficientemente grandes superan a los inconvenientes, ya que la distribuciín es inmediata (no hay restricciones), aunque el proceso de escalado no es trivial. En definitiva, el concepto de Nepfix como marco computacional se puede considerar satisfactorio: la tecnología es viable y los primeros resultados confirman que las carac-terísticas que se buscaban originalmente se han conseguido. Muchos frentes quedan abiertos para futuras investigaciones. En este documento se proponen algunas aproxi-maciones a la solucion de los problemas identificados como la recuperacion de errores y la division dinamica de una NEP en diferentes subdominios. Por otra parte, otros prob-lemas, lejos del alcance de este proyecto, quedan abiertos a un futuro desarrollo como por ejemplo, la estandarización de la representación de las palabras y optimizaciones en la ejecucion del modelo síncrono. Finalmente, algunos resultados preliminares de este Proyecto de Fin de Grado han sido presentados recientemente en formato de artículo científico en la "International Work-Conference on Artificial Neural Networks (IWANN)-2015" y publicados en "Ad-vances in Computational Intelligence" volumen 9094 de "Lecture Notes in Computer Science" de Springer International Publishing. Lo anterior, es una confirmation de que este trabajo mas que un Proyecto de Fin de Grado, es solo el inicio de un trabajo que puede tener mayor repercusion en la comunidad científica. Abstract Network of Evolutionary Processors -NEP is a computational model inspired by the evolution of cell populations, which might model some properties of evolving cell communities at the syntactical level. NEP defines theoretical computing devices able to solve NP complete problems in an efficient manner. In this model, cells are represented by words which encode their DNA sequences. Informally, at any moment of time, the evolutionary system is described by a collection of words, where each word represents one cell. Cells belong to species and their community evolves according to mutations and division which are defined by operations on words. Only those cells are accepted as surviving (correct) ones which are represented by a word in a given set of words, called the genotype space of the species. This feature is analogous with the natural process of evolution. Formally, NEP is based on an architecture for parallel and distributed processing, in other words, a network of language processors. Since the date when NEP was pro¬posed, several extensions and variants have appeared engendering a new set of models named Networks of Bio-inspired Processors (NBP). During this time, several works have proved the computational power of NBP. Specifically, their efficiency, universality, and computational completeness have been thoroughly investigated. Therefore, we can say that the NEP model has reached its maturity. The main motivation for this End of Grade project (EOG project in short) is to propose a practical approximation that allows to close the gap between theoretical NEP model and a practical implementation in high performing computational platforms in order to solve some of high the high complexity problems society requires today. Up until now tools developed to simulate NEPs, while correct and successful, are usu¬ally tightly coupled to the execution environment, using specific software frameworks (Hadoop) or direct hardware usage (GPUs). Within this context the main purpose of this work is the development of Nepfix, a generic and extensible tool that aims to execute algorithms based on NEP model and compatible variants in a local way, similar to a traditional application or in a distributed cloud environment. Nepfix as an application was developed during a 7 month cycle and is undergoing its second iteration once the prototype period was abandoned. Nepfix is designed as a modular self-contained application written in Java 8, that is, no additional external dependencies are required and it does not rely on an specific execution environment, any JVM is a valid container. Nepfix is made of two components or modules. The first module corresponds to the NEP execution and therefore simulation. During the development the current state of the theoretical model was used as a reference including most common filters and processors. Additionally extensibility is provided by the use of Python as a scripting language to run custom logic. Along with the simulation a definition language for NEP has been defined based on JSON as well as a mechanisms to represent words and their possible manipulations. NEP simulator is isolated from distribution and as mentioned before different applications that include it as a dependency are possible, the distribution of NEPs is an example of this. The second module corresponds to executing Nepfix in the cloud. The development carried a heavy R&D process since this front was not explored by other research groups until now. It's important to point out that the development of this module is not focused on results at this point in time, instead we focus on feasibility and discovery of this new perspective to execute natural computing systems and NEPs specifically. The main properties of cloud applications is that they are managed by the platform and are encapsulated in a container. For Nepfix a Spring application becomes the container and the HTTP or AMQP protocols are used for communication with the rest of the instances. Different execution perspectives were studied, namely asynchronous and synchronous models were developed for solving different kind of problems using NEPs. Different limitations and restrictions manifest in both models and are explored in detail in the respective chapters. In conclusion we can consider that Nepfix as a computational framework is suc-cessful: Cloud technology is ready for the challenge and the first results reassure that the properties Nepfix project pursued were met. Many investigation branches are left open for future investigations. In this EOG implementation guidelines are proposed for some of them like error recovery or dynamic NEP splitting. On the other hand other interesting problems that were not in the scope of this project were identified during development like word representation standardization or NEP model optimizations. As a confirmation that the results of this work can be useful to the scientific com-munity a preliminary version of this project was published in The International Work- Conference on Artificial Neural Networks (IWANN) in May 2015. Development has not stopped since that point and while Nepfix in it's current state can not be consid¬ered a final product the most relevant ideas, possible problems and solutions that were produced during the seven months development cycle are worthy to be gathered and presented giving a meaning to this EOG work.

Continuous and lurching traveling pulses in neuronal networks with delay and spatially decaying connectivity

Propagation of discharges in cortical and thalamic systems, which is used as a probe for examining network circuitry, is studied by constructing a one-dimensional model of integrate-and-fire neurons that are coupled by excitatory synapses with delay. Each neuron fires only one spike. The velocity and stability of propagating continuous pulses are calculated analytically. Above a certain critical value of the constant delay, these pulses lose stability. Instead, lurching pulses propagate with discontinuous and periodic spatio-temporal characteristics. The parameter regime for which lurching occurs is strongly affected by the footprint (connectivity) shape; bistability may occur with a square footprint shape but not with an exponential footprint shape. For strong synaptic coupling, the velocity of both continuous and lurching pulses increases logarithmically with the synaptic coupling strength gsyn for an exponential footprint shape, and it is bounded for a step footprint shape. We conclude that the differences in velocity and shape between the front of thalamic spindle waves in vitro and cortical paroxysmal discharges stem from their different effective delay; in thalamic networks, large effective delay between inhibitory neurons arises from their effective interaction via the excitatory cells which display postinhibitory rebound.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.

Industrial networks of the future:review of research and practice

Academic researchers have followed closely the interest of companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? Firstly, it appears that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example in assembly operations. Secondly, the increased tendency towards specialization has forced other, upstream, parts of industrial networks to introduce advanced manufacturing technologies to supply niche markets. Thirdly, the capital market for investments in capacity, and the trade in manufacturing as a commodity, dominates resource allocation to a larger extent than previously was the case. Fourthly, there is a continuous move towards more loosely connected entities that comprise manufacturing networks. More traditional concepts, such as the “keiretsu” and “chaibol” networks of some Asian economies, do not sufficiently support the demands now being placed on networks. Research should address these four fundamental challenges to prepare for the industrial networks of 2020 and beyond.

Modelling data and voice traffic over IP networks using continuous-time Markov models

Common approaches to IP-traffic modelling have featured the use of stochastic models, based on the Markov property, which can be classified into black box and white box models based on the approach used for modelling traffic. White box models, are simple to understand, transparent and have a physical meaning attributed to each of the associated parameters. To exploit this key advantage, this thesis explores the use of simple classic continuous-time Markov models based on a white box approach, to model, not only the network traffic statistics but also the source behaviour with respect to the network and application. The thesis is divided into two parts: The first part focuses on the use of simple Markov and Semi-Markov traffic models, starting from the simplest two-state model moving upwards to n-state models with Poisson and non-Poisson statistics. The thesis then introduces the convenient to use, mathematically derived, Gaussian Markov models which are used to model the measured network IP traffic statistics. As one of the most significant contributions, the thesis establishes the significance of the second-order density statistics as it reveals that, in contrast to first-order density, they carry much more unique information on traffic sources and behaviour. The thesis then exploits the use of Gaussian Markov models to model these unique features and finally shows how the use of simple classic Markov models coupled with use of second-order density statistics provides an excellent tool for capturing maximum traffic detail, which in itself is the essence of good traffic modelling. The second part of the thesis, studies the ON-OFF characteristics of VoIP traffic with reference to accurate measurements of the ON and OFF periods, made from a large multi-lingual database of over 100 hours worth of VoIP call recordings. The impact of the language, prosodic structure and speech rate of the speaker on the statistics of the ON-OFF periods is analysed and relevant conclusions are presented. Finally, an ON-OFF VoIP source model with log-normal transitions is contributed as an ideal candidate to model VoIP traffic and the results of this model are compared with those of previously published work.

Time resolved bit error rate analysis of a fast switching tunable laser for use in optically switched networks

We investigate the use of different direct detection modulation formats in a wavelength switched optical network. We find the minimum time it takes a tunable sampled grating distributed Bragg reflector laser to recover after switching from one wavelength channel to another for different modulation formats. The recovery time is investigated utilizing a field programmable gate array which operates as a time resolved bit error rate detector. The detector offers 93 ps resolution operating at 10.7 Gb/s and allows for all the data received to contribute to the measurement, allowing low bit error rates to be measured at high speed. The recovery times for 10.7 Gb/s non-return-to-zero on–off keyed modulation, 10.7 Gb/s differentially phase shift keyed signal and 21.4 Gb/s differentially quadrature phase shift keyed formats can be as low as 4 ns, 7 ns and 40 ns, respectively. The time resolved phase noise associated with laser settling is simultaneously measured for 21.4 Gb/s differentially quadrature phase shift keyed data and it shows that the phase noise coupled with frequency error is the primary limitation on transmitting immediately after a laser switching event.