Correlation of the Physicochemical and Structural Properties of pDNA/Cationic Liposome Complexes with Their in Vitro Transfection

In this study, we characterized the conventional physicochemical properties of the complexes formed by plasmid DNA (pDNA) and cationic liposomes (CL) composed of egg phosphatidylcholine (EPC), 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), and 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) (50/25/25% molar ratio). We found that these properties are nearly unaffected at the studied ranges when the molar charge ratio (R-+/-) between the positive charge from the CL and negative charge from pDNA is not close to the isoneutrality region (R-+/- = 1). However, the results from in vitro transfection of HeLa cells showed important differences when R-+/- is varied, indicating that the relationships between the physicochemical and biological characteristics were not completely elucidated. To obtain information regarding possible liposome structural modifications, small-angle X-ray scattering (SAXS) experiments were performed as a function of R-+/- to obtain correlations between structural, physicochemical, and transfection properties. The SAXS results revealed that pDNA/CL complexes can be described as being composed of single bilayers, double bilayers, and multiple bilayers, depending on the R-+/- value. Interestingly, for R-+/- = 9, 6, and 3, the system is composed of single and double bilayers, and the fraction of the latter increases with the amount of DNA (or a decreasing R-+/-) in the system. This information is used to explain the transfection differences observed at an R-+/- = 9 as compared to R-+/- = 3 and 6. Close to the isoneutrality region (R-+/- = 1.8), there was an excess of pDNA, which induced the formation of a fraction of aggregates with multiple bilayers. These aggregates likely provide additional resistance against the release of pDNA during the transfection phenomenon, reflected as a decrease in the transfection level. The obtained results permitted proper correlation of the physicochemical and structural properties of pDNA/CL complexes with the in vitro transfection of HeLa cells by these complexes, contributing to a better understanding of the gene delivery process.

Influence of the relative amounts of crystalline and amorphous phases on the mechanical properties of polyamide-6 nanocomposites

The relative amounts of amorphous and crystalline ?- and a-phases in polyamide-6 nanocomposites, estimated from the deconvolution of X-ray diffraction peaks using Gaussian functions, correlates with their mechanical, thermomechanical, and barrier properties. The incorporation of organoclay platelets (Cloisite 15A and 30B) induced the crystallization of the polymer in the ? form at expense of the amorphous phase, such that 12 wt % of Cloisite is enough to enhance the mechanical and the thermomechanical properties. However, higher nanofiller loads were necessary to achieve good barrier effects, because this property is mainly dependent on the tortuous path permeation mechanism of the gas molecules through the nanocomposite films. (C) 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Effect of the vanadium(V) concentration on the spectroscopic properties of nanosized europium-doped yttrium phosphates

Nanosized rare earth phosphovanadate phosphors (Y(P,V)O-4:Eu3+) have been prepared by applying the organic-inorganic polymeric precursors methodology. Luminescent powders with tetragonal structure and different vanadate concentrations (0%, 1%, 5%, 10%, 20%, 50%, and 100%, with regard to the phosphate content) were then obtained for evaluation of their structural and spectroscopic properties. The solids were characterized by scanning electron microscopy, X-ray diffractometry, vibrational spectroscopy (Raman and infrared), and electronic spectroscopy (emission, excitation, luminescence lifetimes, chromaticity, quantum efficiencies, and Judd-Ofelt intensity parameters). The solids exhibited very intense D-5(0) -> F-7(J) Eu3+ transitions, and it was possible to control the luminescent characteristics, such as excitation maximum, lifetime and emission colour, through the vanadium(V) concentration. The observed luminescent properties correlated to the characteristics of the chemical environments around the Eu3+ ions with respect to the composition of the phosphovanadates. The Eu3+ luminescence spectroscopy results indicated that the presence of larger vanadium(V) amounts in the phosphate host lattice led to more covalent and polarizable chemical environments. So, besides allowing for control of the luminescent properties of the solids, the variation in the vanadate concentration in the obtained YPO4:Eu3+ phosphors enabled the establishment of a strict correlation between the observable spectroscopic features and the chemical characteristics of the powders.

Effects of low-salinity and high-turbidity waters one mpirical ocean colour algorithms: an example for Southwestern Atlantic waters

The spectral reflectance of the sea surface recorded using ocean colour satellite sensors has been used to estimate chlorophyll-a concentrations for decades. However, in bio-optically complex coastal waters, these estimates are compromised by the presence of several other coloured components besides chlorophyll, especially in regions affected by low-salinity waters. The present work aims to (a) describe the influence of the freshwater plume from the La Plata River on the variability of in situ remote sensing reflectance and (b) evaluate the performance of operational ocean colour chlorophyll algorithms applied to Southwestern Atlantic waters, which receive a remarkable seasonal contribution from La Plata River discharges. Data from three oceanographic cruises are used, in addition to a historical regional bio-optical dataset. Deviations found between measured and estimated concentrations of chlorophyll-a are examined in relation to surface water salinity and turbidity gradients to investigate the source of errors in satellite estimates of pigment concentrations. We observed significant seasonal variability in surface reflectance properties that are strongly driven by La Plata River plume dynamics and arise from the presence of high levels of inorganic suspended solids and coloured dissolved materials. As expected, existing operational algorithms overestimate the concentration of chlorophyll-a, especially in waters of low salinity (S<33.5) and high turbidity (Rrs(670)>0.0012 sr−1). Additionally, an updated version of the regional algorithm is presented, which clearly improves the chlorophyll estimation in those types of coastal environment. In general, the techniques presented here allow us to directly distinguish the bio-optical types of waters to be considered in algorithm studies by the ocean colour community.

Empirical and fundamental mechanical tests in the evaluation of dough and bread rheological properties

Bread dough and particularly wheat dough, due to its viscoelastic behaviour, is probably the most dynamic and complicated rheological system and its characteristics are very important since they highly affect final products’ textural and sensorial properties. The study of dough rheology has been a very challenging task for many researchers since it can provide numerous information about dough formulation, structure and processing. This explains why dough rheology has been a matter of investigation for several decades. In this research rheological assessment of doughs and breads was performed by using empirical and fundamental methods at both small and large deformation, in order to characterize different types of doughs and final products such as bread. In order to study the structural aspects of food products, image analysis techniques was used for the integration of the information coming from empirical and fundamental rheological measurements. Evaluation of dough properties was carried out by texture profile analysis (TPA), dough stickiness (Chen and Hoseney cell) and uniaxial extensibility determination (Kieffer test) by using a Texture Analyser; small deformation rheological measurements, were performed on a controlled stress–strain rheometer; moreover the structure of different doughs was observed by using the image analysis; while bread characteristics were studied by using texture profile analysis (TPA) and image analysis. The objective of this research was to understand if the different rheological measurements were able to characterize and differentiate the different samples analysed. This in order to investigate the effect of different formulation and processing conditions on dough and final product from a structural point of view. For this aim the following different materials were performed and analysed: - frozen dough realized without yeast; - frozen dough and bread made with frozen dough; - doughs obtained by using different fermentation method; - doughs made by Kamut® flour; - dough and bread realized with the addition of ginger powder; - final products coming from different bakeries. The influence of sub-zero storage time on non-fermented and fermented dough viscoelastic performance and on final product (bread) was evaluated by using small deformation and large deformation methods. In general, the longer the sub-zero storage time the lower the positive viscoelastic attributes. The effect of fermentation time and of different type of fermentation (straight-dough method; sponge-and-dough procedure and poolish method) on rheological properties of doughs were investigated using empirical and fundamental analysis and image analysis was used to integrate this information throughout the evaluation of the dough’s structure. The results of fundamental rheological test showed that the incorporation of sourdough (poolish method) provoked changes that were different from those seen in the others type of fermentation. The affirmative action of some ingredients (extra-virgin olive oil and a liposomic lecithin emulsifier) to improve rheological characteristics of Kamut® dough has been confirmed also when subjected to low temperatures (24 hours and 48 hours at 4°C). Small deformation oscillatory measurements and large deformation mechanical tests performed provided useful information on the rheological properties of samples realized by using different amounts of ginger powder, showing that the sample with the highest amount of ginger powder (6%) had worse rheological characteristics compared to the other samples. Moisture content, specific volume, texture and crumb grain characteristics are the major quality attributes of bread products. The different sample analyzed, “Coppia Ferrarese”, “Pane Comune Romagnolo” and “Filone Terra di San Marino”, showed a decrease of crumb moisture and an increase in hardness over the storage time. Parameters such as cohesiveness and springiness, evaluated by TPA that are indicator of quality of fresh bread, decreased during the storage. By using empirical rheological tests we found several differences among the samples, due to the different ingredients used in formulation and the different process adopted to prepare the sample, but since these products are handmade, the differences could be account as a surplus value. In conclusion small deformation (in fundamental units) and large deformation methods showed a significant role in monitoring the influence of different ingredients used in formulation, different processing and storage conditions on dough viscoelastic performance and on final product. Finally the knowledge of formulation, processing and storage conditions together with the evaluation of structural and rheological characteristics is fundamental for the study of complex matrices like bakery products, where numerous variable can influence their final quality (e.g. raw material, bread-making procedure, time and temperature of the fermentation and baking).

Learning with Kernels on Graphs: DAG-based kernels, data streams and RNA function prediction.

In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.

Influence of V5/6-His Tag on the Properties of Gap Junction Channels Composed of Connexin43, Connexin40 or Connexin45

HeLa cells expressing wild-type connexin43, connexin40 or connexin45 and connexins fused with a V5/6-His tag to the carboxyl terminus (CT) domain (Cx43-tag, Cx40-tag, Cx45-tag) were used to study connexin expression and the electrical properties of gap junction channels. Immunoblots and immunolabeling indicated that tagged connexins are synthesized and targeted to gap junctions in a similar manner to their wild-type counterparts. Voltage-clamp experiments on cell pairs revealed that tagged connexins form functional channels. Comparison of multichannel and single-channel conductances indicates that tagging reduces the number of operational channels, implying interference with hemichannel trafficking, docking and/or channel opening. Tagging provoked connexin-specific effects on multichannel and single-channel properties. The Cx43-tag was most affected and the Cx45-tag, least. The modifications included (1) V j-sensitive gating of I j (V j, gap junction voltage; I j, gap junction current), (2) contribution and (3) kinetics of I j deactivation and (4) single-channel conductance. The first three reflect alterations of fast V j gating. Hence, they may be caused by structural and/or electrical changes on the CT that interact with domains of the amino terminus and cytoplasmic loop. The fourth reflects alterations of the ion-conducting pathway. Conceivably, mutations at sites remote from the channel pore, e.g., 6-His-tagged CT, affect protein conformation and thus modify channel properties indirectly. Hence, V5/6-His tagging of connexins is a useful tool for expression studies in vivo. However, it should not be ignored that it introduces connexin-dependent changes in both expression level and electrophysiological properties.

Computational prediction of the influence of crosslink distribution on the thermo-mechanical properties of epoxies

Experimental studies on epoxies report that the microstructure consists of highly crosslinked localized regions connected with a dispersed phase of low crosslink density. The various thermo-mechanical properties of epoxies might be affected by the crosslink distribution. But as experiments cannot report the exact number of crosslinked covalent bonds present in the structure, molecular dynamics is thus being used in this work to determine the influence of crosslink distribution on thermo-mechanical properties. Molecular dynamics and molecular mechanics simulations are used to establish wellequilibrated molecular models of EPON 862-DETDA epoxy system with a range of crosslink densities and various crosslink distributions. Crosslink distributions are being varied by forming differently crosslinked localized clusters and then by forming different number of crosslinks interconnecting the clusters. Simulations are subsequently used to predict the volume shrinkage, thermal expansion coefficients, and elastic properties of each of the crosslinked systems. The results indicate that elastic properties increase with increasing levels of overall crosslink density and the thermal expansion coefficient decreases with overall crosslink density, both above and below the glass transition temperature. Elastic moduli and coefficients of linear thermal expansion values were found to be different for systems with same overall crosslink density but having different crosslink distributions, thus indicating an effect of the epoxy nanostructure on physical properties. The values of thermo-mechanical properties for all the crosslinked systems are within the range of values reported in literature.

Bovine mastitis: the diagnostic properties of a PCR-based assay to monitor the Staphylococcus aureus genotype B status of a herd, using bulk tank milk

Staphylococcus aureus genotype B (GTB) is a contagious mastitis pathogen in cattle, occurring in up to 87% of individuals. Because treatment is generally insufficient, culling is often required, leading to large economic loss in the Swiss dairy industry. As the detection of this pathogen in bulk tank milk (BTM) would greatly facilitate its control, a novel real-time quantitative PCR-based assay for BTM has previously been developed and is now being evaluated for its diagnostic properties at the herd level. Herds were initially classified as to their Staph. aureus GTB status by a reference method. Using BTM and herd pools of single-quarter and 4-quarter milk, the herds were then grouped by the novel assay, and the resulting classifications were compared. A total of 54 dairy herds were evaluated. Using the reference method, 21 herds were found to be GTB positive, whereas 33 were found to be negative. Considering the novel assay using both herd pools, all herds were grouped correctly, resulting in maximal diagnostic sensitivities (100%) and specificities (100%). For BTM samples, diagnostic sensitivities and specificities were 90 and 100%, respectively. Two herds were false negative in BTM, because cows with clinical signs of mastitis were not milked into the tank. Besides its excellent diagnostic properties, the assay is characterized by its low detection level, high efficiency, and its suitability for automation. Using the novel knowledge and assay, eradication of Staph. aureus GTB from a dairy herd may be considered as a realistic goal.

Optical properties of rabbit brain in the red and near-infrared: changes observed under in vivo, postmortem, frozen, and formalin-fixated conditions.

The outcome of light-based therapeutic approaches depends on light propagation in biological tissues, which is governed by their optical properties. The objective of this study was to quantify optical properties of brain tissue in vivo and postmortem and assess changes due to tissue handling postmortem. The study was carried out on eight female New Zealand white rabbits. The local fluence rate was measured in the VIS/NIR range in the brain in vivo, just postmortem, and after six weeks’ storage of the head at −20∘C or in 10% formaldehyde solution. Only minimal changes in the effective attenuation coefficient μeff were observed for two methods of sacrifice, exsanguination or injection of KCl. Under all tissue conditions, μeff decreased with increasing wavelengths. After long-term storage for six weeks at −20∘C, μeff decreased, on average, by 15 to 25% at all wavelengths, while it increased by 5 to 15% at all wavelengths after storage in formaldehyde. We demonstrated that μeff was not very sensitive to the method of animal sacrifice, that tissue freezing significantly altered tissue optical properties, and that formalin fixation might affect the tissue’s optical properties.

On the Statistical Distribution of Object-Oriented System Properties

The statistical distributions of different software properties have been thoroughly studied in the past, including software size, complexity and the number of defects. In the case of object-oriented systems, these distributions have been found to obey a power law, a common statistical distribution also found in many other fields. However, we have found that for some statistical properties, the behavior does not entirely follow a power law, but a mixture between a lognormal and a power law distribution. Our study is based on the Qualitas Corpus, a large compendium of diverse Java-based software projects. We have measured the Chidamber and Kemerer metrics suite for every file of every Java project in the corpus. Our results show that the range of high values for the different metrics follows a power law distribution, whereas the rest of the range follows a lognormal distribution. This is a pattern typical of so-called double Pareto distributions, also found in empirical studies for other software properties.

Electronic, structural, and optical properties of the host and Cr-doped cadmium thioindate

The cadmium thioindate spinel CdIn2S4 semiconductor has potential applications for optoelectronic devices. We present a theoretical study of the structural and optoelectronic properties of the host and of the Cr-doped ternary spinel. For the host spinel, we analyze the direct or indirect character of the energy bandgap, the change of the energy bandgap with the anion displacement parameter and with the site cation distribution, and the optical properties. The main effect of the Cr doping is the creation of an intermediate band within the energy bandgap. The character and the occupation of this band are analyzed for two substitutions: Cr by In and Cr by Cd. This band permits more channels for the photon absorption. The optical properties are obtained and analyzed. The absorption coefficients are decomposed into contributions from the different absorption channels and from the inter-and intra-atomic components.

Detecting periodicity with horizontal visibility graphs

The horizontal visibility algorithm was recently introduced as a mapping between time series and networks. The challenge lies in characterizing the structure of time series (and the processes that generated those series) using the powerful tools of graph theory. Recent works have shown that the visibility graphs inherit several degrees of correlations from their associated series, and therefore such graph theoretical characterization is in principle possible. However, both the mathematical grounding of this promising theory and its applications are in its infancy. Following this line, here we address the question of detecting hidden periodicity in series polluted with a certain amount of noise. We first put forward some generic properties of horizontal visibility graphs which allow us to define a (graph theoretical) noise reduction filter. Accordingly, we evaluate its performance for the task of calculating the period of noisy periodic signals, and compare our results with standard time domain (autocorrelation) methods. Finally, potentials, limitations and applications are discussed.

Distributed Estimation of Distribution Algorithms for continuous optimization: how does the exchanged information influence their behavior?

One of the most promising areas in which probabilistic graphical models have shown an incipient activity is the field of heuristic optimization and, in particular, in Estimation of Distribution Algorithms. Due to their inherent parallelism, different research lines have been studied trying to improve Estimation of Distribution Algorithms from the point of view of execution time and/or accuracy. Among these proposals, we focus on the so-called distributed or island-based models. This approach defines several islands (algorithms instances) running independently and exchanging information with a given frequency. The information sent by the islands can be either a set of individuals or a probabilistic model. This paper presents a comparative study for a distributed univariate Estimation of Distribution Algorithm and a multivariate version, paying special attention to the comparison of two alternative methods for exchanging information, over a wide set of parameters and problems ? the standard benchmark developed for the IEEE Workshop on Evolutionary Algorithms and other Metaheuristics for Continuous Optimization Problems of the ISDA 2009 Conference. Several analyses from different points of view have been conducted to analyze both the influence of the parameters and the relationships between them including a characterization of the configurations according to their behavior on the proposed benchmark.

Contributions to the Resilience Management in the Internet of Things

El auge del "Internet de las Cosas" (IoT, "Internet of Things") y sus tecnologías asociadas han permitido su aplicación en diversos dominios de la aplicación, entre los que se encuentran la monitorización de ecosistemas forestales, la gestión de catástrofes y emergencias, la domótica, la automatización industrial, los servicios para ciudades inteligentes, la eficiencia energética de edificios, la detección de intrusos, la gestión de desastres y emergencias o la monitorización de señales corporales, entre muchas otras. La desventaja de una red IoT es que una vez desplegada, ésta queda desatendida, es decir queda sujeta, entre otras cosas, a condiciones climáticas cambiantes y expuestas a catástrofes naturales, fallos de software o hardware, o ataques maliciosos de terceros, por lo que se puede considerar que dichas redes son propensas a fallos. El principal requisito de los nodos constituyentes de una red IoT es que estos deben ser capaces de seguir funcionando a pesar de sufrir errores en el propio sistema. La capacidad de la red para recuperarse ante fallos internos y externos inesperados es lo que se conoce actualmente como "Resiliencia" de la red. Por tanto, a la hora de diseñar y desplegar aplicaciones o servicios para IoT, se espera que la red sea tolerante a fallos, que sea auto-configurable, auto-adaptable, auto-optimizable con respecto a nuevas condiciones que puedan aparecer durante su ejecución. Esto lleva al análisis de un problema fundamental en el estudio de las redes IoT, el problema de la "Conectividad". Se dice que una red está conectada si todo par de nodos en la red son capaces de encontrar al menos un camino de comunicación entre ambos. Sin embargo, la red puede desconectarse debido a varias razones, como que se agote la batería, que un nodo sea destruido, etc. Por tanto, se hace necesario gestionar la resiliencia de la red con el objeto de mantener la conectividad entre sus nodos, de tal manera que cada nodo IoT sea capaz de proveer servicios continuos, a otros nodos, a otras redes o, a otros servicios y aplicaciones. En este contexto, el objetivo principal de esta tesis doctoral se centra en el estudio del problema de conectividad IoT, más concretamente en el desarrollo de modelos para el análisis y gestión de la Resiliencia, llevado a la práctica a través de las redes WSN, con el fin de mejorar la capacidad la tolerancia a fallos de los nodos que componen la red. Este reto se aborda teniendo en cuenta dos enfoques distintos, por una parte, a diferencia de otro tipo de redes de dispositivos convencionales, los nodos en una red IoT son propensos a perder la conexión, debido a que se despliegan en entornos aislados, o en entornos con condiciones extremas; por otra parte, los nodos suelen ser recursos con bajas capacidades en términos de procesamiento, almacenamiento y batería, entre otros, por lo que requiere que el diseño de la gestión de su resiliencia sea ligero, distribuido y energéticamente eficiente. En este sentido, esta tesis desarrolla técnicas auto-adaptativas que permiten a una red IoT, desde la perspectiva del control de su topología, ser resiliente ante fallos en sus nodos. Para ello, se utilizan técnicas basadas en lógica difusa y técnicas de control proporcional, integral y derivativa (PID - "proportional-integral-derivative"), con el objeto de mejorar la conectividad de la red, teniendo en cuenta que el consumo de energía debe preservarse tanto como sea posible. De igual manera, se ha tenido en cuenta que el algoritmo de control debe ser distribuido debido a que, en general, los enfoques centralizados no suelen ser factibles a despliegues a gran escala. El presente trabajo de tesis implica varios retos que conciernen a la conectividad de red, entre los que se incluyen: la creación y el análisis de modelos matemáticos que describan la red, una propuesta de sistema de control auto-adaptativo en respuesta a fallos en los nodos, la optimización de los parámetros del sistema de control, la validación mediante una implementación siguiendo un enfoque de ingeniería del software y finalmente la evaluación en una aplicación real. Atendiendo a los retos anteriormente mencionados, el presente trabajo justifica, mediante una análisis matemático, la relación existente entre el "grado de un nodo" (definido como el número de nodos en la vecindad del nodo en cuestión) y la conectividad de la red, y prueba la eficacia de varios tipos de controladores que permiten ajustar la potencia de trasmisión de los nodos de red en respuesta a eventuales fallos, teniendo en cuenta el consumo de energía como parte de los objetivos de control. Así mismo, este trabajo realiza una evaluación y comparación con otros algoritmos representativos; en donde se demuestra que el enfoque desarrollado es más tolerante a fallos aleatorios en los nodos de la red, así como en su eficiencia energética. Adicionalmente, el uso de algoritmos bioinspirados ha permitido la optimización de los parámetros de control de redes dinámicas de gran tamaño. Con respecto a la implementación en un sistema real, se han integrado las propuestas de esta tesis en un modelo de programación OSGi ("Open Services Gateway Initiative") con el objeto de crear un middleware auto-adaptativo que mejore la gestión de la resiliencia, especialmente la reconfiguración en tiempo de ejecución de componentes software cuando se ha producido un fallo. Como conclusión, los resultados de esta tesis doctoral contribuyen a la investigación teórica y, a la aplicación práctica del control resiliente de la topología en redes distribuidas de gran tamaño. Los diseños y algoritmos presentados pueden ser vistos como una prueba novedosa de algunas técnicas para la próxima era de IoT. A continuación, se enuncian de forma resumida las principales contribuciones de esta tesis: (1) Se han analizado matemáticamente propiedades relacionadas con la conectividad de la red. Se estudia, por ejemplo, cómo varía la probabilidad de conexión de la red al modificar el alcance de comunicación de los nodos, así como cuál es el mínimo número de nodos que hay que añadir al sistema desconectado para su re-conexión. (2) Se han propuesto sistemas de control basados en lógica difusa para alcanzar el grado de los nodos deseado, manteniendo la conectividad completa de la red. Se han evaluado diferentes tipos de controladores basados en lógica difusa mediante simulaciones, y los resultados se han comparado con otros algoritmos representativos. (3) Se ha investigado más a fondo, dando un enfoque más simple y aplicable, el sistema de control de doble bucle, y sus parámetros de control se han optimizado empleando algoritmos heurísticos como el método de la entropía cruzada (CE, "Cross Entropy"), la optimización por enjambre de partículas (PSO, "Particle Swarm Optimization"), y la evolución diferencial (DE, "Differential Evolution"). (4) Se han evaluado mediante simulación, la mayoría de los diseños aquí presentados; además, parte de los trabajos se han implementado y validado en una aplicación real combinando técnicas de software auto-adaptativo, como por ejemplo las de una arquitectura orientada a servicios (SOA, "Service-Oriented Architecture"). ABSTRACT The advent of the Internet of Things (IoT) enables a tremendous number of applications, such as forest monitoring, disaster management, home automation, factory automation, smart city, etc. However, various kinds of unexpected disturbances may cause node failure in the IoT, for example battery depletion, software/hardware malfunction issues and malicious attacks. So, it can be considered that the IoT is prone to failure. The ability of the network to recover from unexpected internal and external failures is known as "resilience" of the network. Resilience usually serves as an important non-functional requirement when designing IoT, which can further be broken down into "self-*" properties, such as self-adaptive, self-healing, self-configuring, self-optimization, etc. One of the consequences that node failure brings to the IoT is that some nodes may be disconnected from others, such that they are not capable of providing continuous services for other nodes, networks, and applications. In this sense, the main objective of this dissertation focuses on the IoT connectivity problem. A network is regarded as connected if any pair of different nodes can communicate with each other either directly or via a limited number of intermediate nodes. More specifically, this thesis focuses on the development of models for analysis and management of resilience, implemented through the Wireless Sensor Networks (WSNs), which is a challenging task. On the one hand, unlike other conventional network devices, nodes in the IoT are more likely to be disconnected from each other due to their deployment in a hostile or isolated environment. On the other hand, nodes are resource-constrained in terms of limited processing capability, storage and battery capacity, which requires that the design of the resilience management for IoT has to be lightweight, distributed and energy-efficient. In this context, the thesis presents self-adaptive techniques for IoT, with the aim of making the IoT resilient against node failures from the network topology control point of view. The fuzzy-logic and proportional-integral-derivative (PID) control techniques are leveraged to improve the network connectivity of the IoT in response to node failures, meanwhile taking into consideration that energy consumption must be preserved as much as possible. The control algorithm itself is designed to be distributed, because the centralized approaches are usually not feasible in large scale IoT deployments. The thesis involves various aspects concerning network connectivity, including: creation and analysis of mathematical models describing the network, proposing self-adaptive control systems in response to node failures, control system parameter optimization, implementation using the software engineering approach, and evaluation in a real application. This thesis also justifies the relations between the "node degree" (the number of neighbor(s) of a node) and network connectivity through mathematic analysis, and proves the effectiveness of various types of controllers that can adjust power transmission of the IoT nodes in response to node failures. The controllers also take into consideration the energy consumption as part of the control goals. The evaluation is performed and comparison is made with other representative algorithms. The simulation results show that the proposals in this thesis can tolerate more random node failures and save more energy when compared with those representative algorithms. Additionally, the simulations demonstrate that the use of the bio-inspired algorithms allows optimizing the parameters of the controller. With respect to the implementation in a real system, the programming model called OSGi (Open Service Gateway Initiative) is integrated with the proposals in order to create a self-adaptive middleware, especially reconfiguring the software components at runtime when failures occur. The outcomes of this thesis contribute to theoretic research and practical applications of resilient topology control for large and distributed networks. The presented controller designs and optimization algorithms can be viewed as novel trials of the control and optimization techniques for the coming era of the IoT. The contributions of this thesis can be summarized as follows: (1) Mathematically, the fault-tolerant probability of a large-scale stochastic network is analyzed. It is studied how the probability of network connectivity depends on the communication range of the nodes, and what is the minimum number of neighbors to be added for network re-connection. (2) A fuzzy-logic control system is proposed, which obtains the desired node degree and in turn maintains the network connectivity when it is subject to node failures. There are different types of fuzzy-logic controllers evaluated by simulations, and the results demonstrate the improvement of fault-tolerant capability as compared to some other representative algorithms. (3) A simpler but more applicable approach, the two-loop control system is further investigated, and its control parameters are optimized by using some heuristic algorithms such as Cross Entropy (CE), Particle Swarm Optimization (PSO), and Differential Evolution (DE). (4) Most of the designs are evaluated by means of simulations, but part of the proposals are implemented and tested in a real-world application by combining the self-adaptive software technique and the control algorithms which are presented in this thesis.