Multi-Camera very wide baseline feature matching based on view-adaptive junction detection

This paper presents a strategy for solving the feature matching problem in calibrated very wide-baseline camera settings. In this kind of settings, perspective distortion, depth discontinuities and occlusion represent enormous challenges. The proposed strategy addresses them by using geometrical information, specifically by exploiting epipolar-constraints. As a result it provides a sparse number of reliable feature points for which 3D position is accurately recovered. Special features known as junctions are used for robust matching. In particular, a strategy for refinement of junction end-point matching is proposed which enhances usual junction-based approaches. This allows to compute cross-correlation between perfectly aligned plane patches in both images, thus yielding better matching results. Evaluation of experimental results proves the effectiveness of the proposed algorithm in very wide-baseline environments.

Diseño de algoritmos de guerra electrónica y radar para su implementación en sistemas de tiempo real

Esta tesis se centra en el estudio y desarrollo de algoritmos de guerra electrónica {electronic warfare, EW) y radar para su implementación en sistemas de tiempo real. La llegada de los sistemas de radio, radar y navegación al terreno militar llevó al desarrollo de tecnologías para combatirlos. Así, el objetivo de los sistemas de guerra electrónica es el control del espectro electomagnético. Una de la funciones de la guerra electrónica es la inteligencia de señales {signals intelligence, SIGINT), cuya labor es detectar, almacenar, analizar, clasificar y localizar la procedencia de todo tipo de señales presentes en el espectro. El subsistema de inteligencia de señales dedicado a las señales radar es la inteligencia electrónica {electronic intelligence, ELINT). Un sistema de tiempo real es aquel cuyo factor de mérito depende tanto del resultado proporcionado como del tiempo en que se da dicho resultado. Los sistemas radar y de guerra electrónica tienen que proporcionar información lo más rápido posible y de forma continua, por lo que pueden encuadrarse dentro de los sistemas de tiempo real. La introducción de restricciones de tiempo real implica un proceso de realimentación entre el diseño del algoritmo y su implementación en plataformas “hardware”. Las restricciones de tiempo real son dos: latencia y área de la implementación. En esta tesis, todos los algoritmos presentados se han implementado en plataformas del tipo field programmable gate array (FPGA), ya que presentan un buen compromiso entre velocidad, coste total, consumo y reconfigurabilidad. La primera parte de la tesis está centrada en el estudio de diferentes subsistemas de un equipo ELINT: detección de señales mediante un detector canalizado, extracción de los parámetros de pulsos radar, clasificación de modulaciones y localization pasiva. La transformada discreta de Fourier {discrete Fourier transform, DFT) es un detector y estimador de frecuencia quasi-óptimo para señales de banda estrecha en presencia de ruido blanco. El desarrollo de algoritmos eficientes para el cálculo de la DFT, conocidos como fast Fourier transform (FFT), han situado a la FFT como el algoritmo más utilizado para la detección de señales de banda estrecha con requisitos de tiempo real. Así, se ha diseñado e implementado un algoritmo de detección y análisis espectral para su implementación en tiempo real. Los parámetros más característicos de un pulso radar son su tiempo de llegada y anchura de pulso. Se ha diseñado e implementado un algoritmo capaz de extraer dichos parámetros. Este algoritmo se puede utilizar con varios propósitos: realizar un reconocimiento genérico del radar que transmite dicha señal, localizar la posición de dicho radar o bien puede utilizarse como la parte de preprocesado de un clasificador automático de modulaciones. La clasificación automática de modulaciones es extremadamente complicada en entornos no cooperativos. Un clasificador automático de modulaciones se divide en dos partes: preprocesado y el algoritmo de clasificación. Los algoritmos de clasificación basados en parámetros representativos calculan diferentes estadísticos de la señal de entrada y la clasifican procesando dichos estadísticos. Los algoritmos de localization pueden dividirse en dos tipos: triangulación y sistemas cuadráticos. En los algoritmos basados en triangulación, la posición se estima mediante la intersección de las rectas proporcionadas por la dirección de llegada de la señal. En cambio, en los sistemas cuadráticos, la posición se estima mediante la intersección de superficies con igual diferencia en el tiempo de llegada (time difference of arrival, TDOA) o diferencia en la frecuencia de llegada (frequency difference of arrival, FDOA). Aunque sólo se ha implementado la estimación del TDOA y FDOA mediante la diferencia de tiempos de llegada y diferencia de frecuencias, se presentan estudios exhaustivos sobre los diferentes algoritmos para la estimación del TDOA, FDOA y localización pasiva mediante TDOA-FDOA. La segunda parte de la tesis está dedicada al diseño e implementación filtros discretos de respuesta finita (finite impulse response, FIR) para dos aplicaciones radar: phased array de banda ancha mediante filtros retardadores (true-time delay, TTD) y la mejora del alcance de un radar sin modificar el “hardware” existente para que la solución sea de bajo coste. La operación de un phased array de banda ancha mediante desfasadores no es factible ya que el retardo temporal no puede aproximarse mediante un desfase. La solución adoptada e implementada consiste en sustituir los desfasadores por filtros digitales con retardo programable. El máximo alcance de un radar depende de la relación señal a ruido promedio en el receptor. La relación señal a ruido depende a su vez de la energía de señal transmitida, potencia multiplicado por la anchura de pulso. Cualquier cambio hardware que se realice conlleva un alto coste. La solución que se propone es utilizar una técnica de compresión de pulsos, consistente en introducir una modulación interna a la señal, desacoplando alcance y resolución. ABSTRACT This thesis is focused on the study and development of electronic warfare (EW) and radar algorithms for real-time implementation. The arrival of radar, radio and navigation systems to the military sphere led to the development of technologies to fight them. Therefore, the objective of EW systems is the control of the electromagnetic spectrum. Signals Intelligence (SIGINT) is one of the EW functions, whose mission is to detect, collect, analyze, classify and locate all kind of electromagnetic emissions. Electronic intelligence (ELINT) is the SIGINT subsystem that is devoted to radar signals. A real-time system is the one whose correctness depends not only on the provided result but also on the time in which this result is obtained. Radar and EW systems must provide information as fast as possible on a continuous basis and they can be defined as real-time systems. The introduction of real-time constraints implies a feedback process between the design of the algorithms and their hardware implementation. Moreover, a real-time constraint consists of two parameters: Latency and area of the implementation. All the algorithms in this thesis have been implemented on field programmable gate array (FPGAs) platforms, presenting a trade-off among performance, cost, power consumption and reconfigurability. The first part of the thesis is related to the study of different key subsystems of an ELINT equipment: Signal detection with channelized receivers, pulse parameter extraction, modulation classification for radar signals and passive location algorithms. The discrete Fourier transform (DFT) is a nearly optimal detector and frequency estimator for narrow-band signals buried in white noise. The introduction of fast algorithms to calculate the DFT, known as FFT, reduces the complexity and the processing time of the DFT computation. These properties have placed the FFT as one the most conventional methods for narrow-band signal detection for real-time applications. An algorithm for real-time spectral analysis for user-defined bandwidth, instantaneous dynamic range and resolution is presented. The most characteristic parameters of a pulsed signal are its time of arrival (TOA) and the pulse width (PW). The estimation of these basic parameters is a fundamental task in an ELINT equipment. A basic pulse parameter extractor (PPE) that is able to estimate all these parameters is designed and implemented. The PPE may be useful to perform a generic radar recognition process, perform an emitter location technique and can be used as the preprocessing part of an automatic modulation classifier (AMC). Modulation classification is a difficult task in a non-cooperative environment. An AMC consists of two parts: Signal preprocessing and the classification algorithm itself. Featurebased algorithms obtain different characteristics or features of the input signals. Once these features are extracted, the classification is carried out by processing these features. A feature based-AMC for pulsed radar signals with real-time requirements is studied, designed and implemented. Emitter passive location techniques can be divided into two classes: Triangulation systems, in which the emitter location is estimated with the intersection of the different lines of bearing created from the estimated directions of arrival, and quadratic position-fixing systems, in which the position is estimated through the intersection of iso-time difference of arrival (TDOA) or iso-frequency difference of arrival (FDOA) quadratic surfaces. Although TDOA and FDOA are only implemented with time of arrival and frequency differences, different algorithms for TDOA, FDOA and position estimation are studied and analyzed. The second part is dedicated to FIR filter design and implementation for two different radar applications: Wideband phased arrays with true-time delay (TTD) filters and the range improvement of an operative radar with no hardware changes to minimize costs. Wideband operation of phased arrays is unfeasible because time delays cannot be approximated by phase shifts. The presented solution is based on the substitution of the phase shifters by FIR discrete delay filters. The maximum range of a radar depends on the averaged signal to noise ratio (SNR) at the receiver. Among other factors, the SNR depends on the transmitted signal energy that is power times pulse width. Any possible hardware change implies high costs. The proposed solution lies in the use of a signal processing technique known as pulse compression, which consists of introducing an internal modulation within the pulse width, decoupling range and resolution.

Cancelación activa del ruido utilizando el KIT TMS320C5515 EZDSP

El control, o cancelación activa de ruido, consiste en la atenuación del ruido presente en un entorno acústico mediante la emisión de una señal igual y en oposición de fase al ruido que se desea atenuar. La suma de ambas señales en el medio acústico produce una cancelación mutua, de forma que el nivel de ruido resultante es mucho menor al inicial. El funcionamiento de estos sistemas se basa en los principios de comportamiento de los fenómenos ondulatorios descubiertos por Augustin-Jean Fresnel, Christiaan Huygens y Thomas Young entre otros. Desde la década de 1930, se han desarrollado prototipos de sistemas de control activo de ruido, aunque estas primeras ideas eran irrealizables en la práctica o requerían de ajustes manuales cada poco tiempo que hacían inviable su uso. En la década de 1970, el investigador estadounidense Bernard Widrow desarrolla la teoría de procesado adaptativo de señales y el algoritmo de mínimos cuadrados LMS. De este modo, es posible implementar filtros digitales cuya respuesta se adapte de forma dinámica a las condiciones variables del entorno. Con la aparición de los procesadores digitales de señal en la década de 1980 y su evolución posterior, se abre la puerta para el desarrollo de sistemas de cancelación activa de ruido basados en procesado de señal digital adaptativo. Hoy en día, existen sistemas de control activo de ruido implementados en automóviles, aviones, auriculares o racks de equipamiento profesional. El control activo de ruido se basa en el algoritmo fxlms, una versión modificada del algoritmo LMS de filtrado adaptativo que permite compensar la respuesta acústica del entorno. De este modo, se puede filtrar una señal de referencia de ruido de forma dinámica para emitir la señal adecuada que produzca la cancelación. Como el espacio de cancelación acústica está limitado a unas dimensiones de la décima parte de la longitud de onda, sólo es viable la reducción de ruido en baja frecuencia. Generalmente se acepta que el límite está en torno a 500 Hz. En frecuencias medias y altas deben emplearse métodos pasivos de acondicionamiento y aislamiento, que ofrecen muy buenos resultados. Este proyecto tiene como objetivo el desarrollo de un sistema de cancelación activa de ruidos de carácter periódico, empleando para ello electrónica de consumo y un kit de desarrollo DSP basado en un procesador de muy bajo coste. Se han desarrollado una serie de módulos de código para el DSP escritos en lenguaje C, que realizan el procesado de señal adecuado a la referencia de ruido. Esta señal procesada, una vez emitida, produce la cancelación acústica. Empleando el código implementado, se han realizado pruebas que generan la señal de ruido que se desea eliminar dentro del propio DSP. Esta señal se emite mediante un altavoz que simula la fuente de ruido a cancelar, y mediante otro altavoz se emite una versión filtrada de la misma empleando el algoritmo fxlms. Se han realizado pruebas con distintas versiones del algoritmo, y se han obtenido atenuaciones de entre 20 y 35 dB medidas en márgenes de frecuencia estrechos alrededor de la frecuencia del generador, y de entre 8 y 15 dB medidas en banda ancha. ABSTRACT. Active noise control consists on attenuating the noise in an acoustic environment by emitting a signal equal but phase opposed to the undesired noise. The sum of both signals results in mutual cancellation, so that the residual noise is much lower than the original. The operation of these systems is based on the behavior principles of wave phenomena discovered by Augustin-Jean Fresnel, Christiaan Huygens and Thomas Young. Since the 1930’s, active noise control system prototypes have been developed, though these first ideas were practically unrealizable or required manual adjustments very often, therefore they were unusable. In the 1970’s, American researcher Bernard Widrow develops the adaptive signal processing theory and the Least Mean Squares algorithm (LMS). Thereby, implementing digital filters whose response adapts dynamically to the variable environment conditions, becomes possible. With the emergence of digital signal processors in the 1980’s and their later evolution, active noise cancellation systems based on adaptive signal processing are attained. Nowadays active noise control systems have been successfully implemented on automobiles, planes, headphones or racks for professional equipment. Active noise control is based on the fxlms algorithm, which is actually a modified version of the LMS adaptive filtering algorithm that allows compensation for the acoustic response of the environment. Therefore it is possible to dynamically filter a noise reference signal to obtain the appropriate cancelling signal. As the noise cancellation space is limited to approximately one tenth of the wavelength, noise attenuation is only viable for low frequencies. It is commonly accepted the limit of 500 Hz. For mid and high frequencies, conditioning and isolating passive techniques must be used, as they produce very good results. The objective of this project is to develop a noise cancellation system for periodic noise, by using consumer electronics and a DSP development kit based on a very-low-cost processor. Several C coded modules have been developed for the DSP, implementing the appropriate signal processing to the noise reference. This processed signal, once emitted, results in noise cancellation. The developed code has been tested by generating the undesired noise signal in the DSP. This signal is emitted through a speaker simulating the noise source to be removed, and another speaker emits an fxlms filtered version of the same signal. Several versions of the algorithm have been tested, obtaining attenuation levels around 20 – 35 dB measured in a tight bandwidth around the generator frequency, or around 8 – 15 dB measured in broadband.

Adaptive Multi-Camera System for Real Time Object Detection

In this paper we present an adaptive multi-camera system for real time object detection able to efficiently adjust the computational requirements of video processing blocks to the available processing power and the activity of the scene. The system is based on a two level adaptation strategy that works at local and at global level. Object detection is based on a Gaussian mixtures model background subtraction algorithm. Results show that the system can efficiently adapt the algorithm parameters without a significant loss in the detection accuracy.

Edge Detection by Adaptive Splitting II. The Three-Dimensional Case

In Llanas and Lantarón, J. Sci. Comput. 46, 485–518 (2011) we proposed an algorithm (EDAS-d) to approximate the jump discontinuity set of functions defined on subsets of ℝ d . This procedure is based on adaptive splitting of the domain of the function guided by the value of an average integral. The above study was limited to the 1D and 2D versions of the algorithm. In this paper we address the three-dimensional problem. We prove an integral inequality (in the case d=3) which constitutes the basis of EDAS-3. We have performed detailed computational experiments demonstrating effective edge detection in 3D function models with different interface topologies. EDAS-1 and EDAS-2 appealing properties are extensible to the 3D case

A new ultrasonic signal amplification method for detection bacteria

A new method is presented that increases the sensitivity of ultrasound-based techniques for detection of bacteria. The technique was developed for the detection of catalase-positive microorganisms. It uses a bubble trapping medium containing hydrogen peroxide that is mixed with the sample for microbiological evaluation. The enzyme catalase is present in catalase-positive bacteria, which induces a rapid hydrolysis of hydrogen peroxide, forming bubbles which remain in the medium. This reaction results in the amplification of the mechanical changes that the microorganisms produce in the medium. The effect can be detected by means of ultrasonic wave amplitude continuous measurement since the bubbles increase the ultrasonic attenuation significantly. It is shown that microorganism concentrations of the order of 105 cells ml−1 can be detected using this method. This allows an improvement of three orders of magnitude in the ultrasonic detection threshold of microorganisms in conventional culture media, and is competitive with modern rapid microbiological methods. It can also be used for the characterization of the enzymatic activity.

Debonding detection of FRP strengthened concrete beams by using impedance measurements and an ensemble PSO adaptive spectral model

An impedance-based midspan debonding identification method for RC beams strengthened with FRP strips is presented in this paper using piezoelectric ceramic (PZT) sensor?actuators. To reach this purpose, firstly, a two-dimensional electromechanical impedance model is proposed to predict the electrical admittance of the PZT transducer bonded to the FRP strips of an RC beam. Considering the impedance is measured in high frequencies, a spectral element model of the bonded-PZT?FRP strengthened beam is developed. This model, in conjunction with experimental measurements of PZT transducers, is used to present an updating methodology to quantitatively detect interfacial debonding of these kinds of structures. To improve the performance and accuracy of the detection algorithm in a challenging problem such as ours, the structural health monitoring approach is solved with an ensemble process based on particle of swarm. An adaptive mesh scheme has also been developed to increase the reliability in locating the area in which debonding initiates. Predictions carried out with experimental results have showed the effectiveness and potential of the proposed method to detect prematurely at its earliest stages a critical failure mode such as that due to midspan debonding of the FRP strip.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Enhancing Activity Recognition by Fusing Inertial and Biometric Information

Activity recognition is an active research field nowadays, as it enables the development of highly adaptive applications, e.g. in the field of personal health. In this paper, a light high-level fusion algorithm to detect the activity that an individual is performing is presented. The algorithm relies on data gathered from accelerometers placed on different parts of the body, and on biometric sensors. Inertial sensors allow detecting activity by analyzing signal features such as amplitude or peaks. In addition, there is a relationship between the activity intensity and biometric response, which can be considered together with acceleration data to improve the accuracy of activity detection. The proposed algorithm is designed to work with minimum computational cost, being ready to run in a mobile device as part of a context-aware application. In order to enable different user scenarios, the algorithm offers best-effort activity estimation: its quality of estimation depends on the position and number of the available inertial sensors, and also on the presence of biometric information.

Detection and Tracking of Traffic Signs Using a Recursive Bayesian Decision Framework

In this paper we propose a new method for the automatic detection and tracking of road traffic signs using an on-board single camera. This method aims to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. The proposed approach exploits a combination of different features, such as color, appearance, and tracking information. This information is introduced into a recursive Bayesian decision framework, in which prior probabilities are dynamically adapted to tracking results. This decision scheme obtains a number of candidate regions in the image, according to their HS (Hue-Saturation). Finally, a Kalman filter with an adaptive noise tuning provides the required time and spatial coherence to the estimates. Results have shown that the proposed method achieves high detection rates in challenging scenarios, including illumination changes, rapid motion and significant perspective distortion

Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks

A new method for detecting microcalcifications in regions of interest (ROIs) extracted from digitized mammograms is proposed. The top-hat transform is a technique based on mathematical morphology operations and, in this paper, is used to perform contrast enhancement of the mi-crocalcifications. To improve microcalcification detection, a novel image sub-segmentation approach based on the possibilistic fuzzy c-means algorithm is used. From the original ROIs, window-based features, such as the mean and standard deviation, were extracted; these features were used as an input vector in a classifier. The classifier is based on an artificial neural network to identify patterns belonging to microcalcifications and healthy tissue. Our results show that the proposed method is a good alternative for automatically detecting microcalcifications, because this stage is an important part of early breast cancer detection

A new feature extraction method for signal classification applied to cat spinal cord signals

In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

Permutation tests for nonparametric detection

In this paper, the authors provide a methodology to design nonparametric permutation tests and, in particular, nonparametric rank tests for applications in detection. In the first part of the paper, the authors develop the optimization theory of both permutation and rank tests in the Neyman?Pearson sense; in the second part of the paper, they carry out a comparative performance analysis of the permutation and rank tests (detectors) against the parametric ones in radar applications. First, a brief review of some contributions on nonparametric tests is realized. Then, the optimum permutation and rank tests are derived. Finally, a performance analysis is realized by Monte-Carlo simulations for the corresponding detectors, and the results are shown in curves of detection probability versus signal-to-noise ratio

Influence of delay time on regularity estimation for voice pathology detection

The employment of nonlinear analysis techniques for automatic voice pathology detection systems has gained popularity due to the ability of such techniques for dealing with the underlying nonlinear phenomena. On this respect, characterization using nonlinear analysis typically employs the classical Correlation Dimension and the largest Lyapunov Exponent, as well as some regularity quantifiers computing the system predictability. Mostly, regularity features highly depend on a correct choosing of some parameters. One of those, the delay time �, is usually fixed to be 1. Nonetheless, it has been stated that a unity � can not avoid linear correlation of the time series and hence, may not correctly capture system nonlinearities. Therefore, present work studies the influence of the � parameter on the estimation of regularity features. Three � estimations are considered: the baseline value 1; a � based on the Average Automutual Information criterion; and � chosen from the embedding window. Testing results obtained for pathological voice suggest that an improved accuracy might be obtained by using a � value different from 1, as it accounts for the underlying nonlinearities of the voice signal.

Análisis genómico y funcional de los sistemas de Quorum Sensing en Rhizobium leguminosarum

Rhizobium leguminosarum (Rl) es una alfa-proteobacteria capaz de establecer una simbiosis diazotrófica con distintas leguminosas. A pesar de la importancia de esta simbiosis en el balance global del ciclo del nitrógeno, muy pocos genomas de rhizobios han sido secuenciados, que aporten nuevos conocimientos relacionados con las características genéticas que contribuyen a importantes procesos simbióticos. Únicamente tres secuencias completas de Rl han sido publicadas: Rl bv. viciae 3841 y dos genomas de Rl bv. trifolii (WSM1325 y WSM2304), ambos simbiontes de trébol. La secuencia genómica de Rlv UPM791 se ha determinado por medio de secuenciación 454. Este genoma tiene un tamaño aproximado de 7.8 Mb, organizado en un cromosoma y 5 replicones extracromosómicos, que incluyen un plásmido simbiótico de 405 kb. Este nuevo genoma se ha analizado en relación a las funciones simbióticas y adaptativas en comparación con los genomas completos de Rlv 3841 y Rl bv. trifolii WSM1325 y WSM2304. Mientras que los plásmidos pUPM791a y b se encuentran conservados, el plásmido simbiótico pUPM791c exhibe un grado de conservación muy bajo comparado con aquellos descritos en las otras cepas de Rl. Uno de los factores implicados en el establecimiento de la simbiosis es el sistema de comunicación intercelular conocido como Quorum Sensing (QS). El análisis del genoma de Rlv UPM791 ha permitido la identificación de dos sistemas tipo LuxRI mediados por señales de tipo N-acyl-homoserina lactonas (AHLs). El análisis mediante HPLC-MS ha permitido asociar las señales C6-HSL, C7-HSL y C8-HSL al sistema rhiRI, codificado en el plásmido simbiótico; mientras que el sistema cinRI, localizado en el cromosoma, produce 3OH-C14:1-HSL. Se ha identificado una tercera sintasa (TraI) codificada en el plásmido simbiótico, pero su regulador correspondiente se encuentra truncado debido a un salto de fase. Adicionalmente, se han encontrado tres reguladores de tipo LuxR-orphan que no presentan una sintasa LuxI asociada. El efecto potencial de las señales tipo AHL se ha estudiado mediante una estrategia de quorum quenching, la cual interfiere con los sistemas de QS de la bacteria. Esta estrategia está basada en la introducción del gen aiiA de Bacillus subtilis, que expresa constitutivamente una enzima lactonasa degradadora de AHLs. Para llevar a cabo el análisis en condiciones simbióticas, se ha desarrollado un sistema de doble marcaje que permite la identificación basado en los marcadores gusA y celB, que codifican para una enzima β–glucuronidasa y una β–galactosidasa termoestable, respectivamente. Los resultados obtenidos indican que Rlv UPM791 predomina sobre la cepa Rlv 3841 para la formación de nódulos en plantas de guisante. La baja estabilidad del plásmido que codifica para aiiA, no ha permitido obtener una conclusión definitiva sobre el efecto de la lactonasa AiiA en competitividad. Con el fin de analizar el significado y la regulación de la producción de moléculas señal tipo AHL, se han generado mutantes defectivos en cada uno de los dos sistemas de QS. Se ha llevado a cabo un análisis detallado sobre la producción de AHLs, formación de biofilm y simbiosis con plantas de guisante, veza y lenteja. El efecto de las deleciones de los genes rhiI y rhiR en Rlv UPM791 es más drástico en ausencia del plásmido pUPM791d. Mutaciones en cinI o cinRIS muestran tanto ausencia de señales, como producción exclusivamente de las de bajo peso molecular, respectivamente, producidas por el sistema rhiRI. Estas mutaciones mostraron un efecto importante en simbiosis. El sistema rhiRI se necesita para un comportamiento simbiótico normal. Además, mutantes cinRIS generaron nódulos blancos e ineficientes, mientras que el mutante cinI fue incapaz de producir nódulos en ninguna de las leguminosas utilizadas. Dicha mutación resultó en la inestabilización del plasmido simbiótico por un mecanismo dependiente de cinI que no ha sido aclarado. En general, los resultados obtenidos indican la existencia de un modelo de regulación dependiente de QS significativamente distinto a los que se han descrito previamente en otras cepas de R. leguminosarum, en las cuales no se había observado ningún fenotipo relevante en simbiosis. La regulación de la producción de AHLs Rlv UPM791 es un proceso complejo que implica genes situados en los plásmidos UPM791c y UPM791d, además de la señal 3-OH-C14:1-HSL. Finalmente, se ha identificado un transportador de tipo RND, homologo a mexAB-oprM de P. aeruginosa e implicado en la extrusión de AHLs de cadena larga. La mutación he dicho transportador no tuvo efectos apreciables sobre la simbiosis. ABSTRACT Rhizobium leguminosarum (Rl) is a soil alpha-proteobacterium that establishes a diazotrophic symbiosis with different legumes. Despite the importance of this symbiosis to the global nitrogen cycling balance, very few rhizobial genomes have been sequenced so far which provide new insights into the genetic features contributing to symbiotically relevant processes. Only three complete sequences of Rl strains have been published: Rl bv. viciae 3841, harboring six plasmids (7.75 Mb) and two Rl bv. trifolii (WSM1325 and WSM2304), both clover symbionts, harboring 5 and 4 plasmids, respectively (7.41 and 6.87 Mb). The genomic sequence of Rlv UPM791 was undertaken by means of 454 sequencing. Illumina and Sanger reads were used to improve the assembly, leading to 17 final contigs. This genome has an estimated size of 7.8 Mb organized in one chromosome and five extrachromosomal replicons, including a 405 kb symbiotic plasmid. Four of these plasmids are already closed, whereas there are still gaps in the smallest one (pUPM791d) due to the presence of insertion elements and repeated sequences, which difficult the assembly. The annotation has been carried out thanks to the Manatee pipeline. This new genome has been analyzed as regarding symbiotic and adaptive functions in comparison to the Rlv 3841 complete genome, and to those from Rl bv. trifolii strains WSM1325 and WSM2304. While plasmids pUPM791a and b are conserved, the symbiotic plasmid pUPM791c exhibited the lowest degree of conservation as compared to those from the other Rl strains. One of the factors involved in the symbiotic process is the intercellular communication system known as Quorum Sensing (QS). This mechanism allows bacteria to carry out diverse biological processes in a coordinate way through the production and detection of extracellular signals that regulate the transcription of different target genes. Analysis of the Rlv UPM791 genome allowed the identification of two LuxRI-like systems mediated by N-acyl-homoserine lactones (AHLs). HPLC-MS analysis allowed the adscription of C6-HSL, C7-HSL and C8-HSL signals to the rhiRI system, encoded in the symbiotic plasmid, whereas the cinRI system, located in the chromosome, produces 3OH-C14:1-HSL, previously described as “bacteriocin small”. A third synthase (TraI) is encoded also in the symbiotic plasmid, but its cognate regulator TraR is not functional due to a fameshift mutation. Three additional LuxR orphans were also found which no associated LuxI-type synthase. The potential effect of AHLs has been studied by means of a quorum quenching approach to interfere with the QS systems of the bacteria. This approach is based upon the introduction into the strains Rl UPM791 and Rl 3841 of the Bacillus subtilis gene aiiA expressing constitutively an AHL-degrading lactonase enzyme which led to virtual absence of AHL even when AiiA-expressing cells were a fraction of the total population. No significant effect of AiiA-mediated AHL removal on competitiveness for growth in solid surface was observed. For analysis under symbiotic conditions we have set up a two-label system to identify nodules produced by two different strains in pea roots, based on the markers gusA and celB, encoding a β–glucuronidase and a thermostable β–galactosidase enzymes, respectively. The results obtained show that Rlv UPM791 outcompetes Rlv 3841 for nodule formation in pea plants, and that the presence of the AiiA plasmid does not significantly affect the relative competitiveness of the two Rlv strains. However, the low stability of the pME6863 plasmid, encoding aiiA, did not lead to a clear conclusion about the AiiA lactonase effect on competitiveness. In order to further analyze the significance and regulation of the production of AHL signal molecules, mutants deficient in each of the two QS systems were constructed. A detailed analysis of the effect of these mutations on AHL production, biofilm formation and symbiosis with pea, vetch and lentil plants has been carried out. The effect of deletions on Rlv UPM791 rhiI and rhiR genes is more pronounced in the absence of plasmid pUPM791d, as no signal is detected in UPM791.1, lacking this plasmid. Mutations in cinI or cinRIS show either no signals, or only the small ones produced by the rhiRI system, suggesting that cinR might be regulating the rhiRI system. These mutations had a strong effect on symbiosis. Analysis of rhi mutants revealed that rhiRI system is required for normal symbiotic performance, as a drastic reduction of symbiotic fitness is observed when rhiI is deleted, and rhiR is essential for nitrogen fixation in the absence of plasmid pUPM791d. Furthermore, cinRIS mutants resulted in white and inefficient nodules, whereas cinI mutant was unable to form nodules on any legume tested. The latter mutation is associated to the instabilization of the symbiotic plasmid through a mechanism still uncovered. Overall, the results obtained indicate the existence of a model of QS-dependent regulation significantly different to that previously described in other R. leguminosarum strains, where no relevant symbiotic phenotype had been observed. The regulation of AHL production in Rlv UPM791 is a complex process involving the symbiotic plasmid (pUPM791c) and the smallest plasmid (pUPM791d), with a key role for the 3-OH-C14:1-HSL signal. Finally, we made a search for potential AHL transporters in Rlv UPM791 genome. These signals diffuse freely across membranes, but in the case of the long-chain AHLs an active efflux system might be required, as it has been described for C12-HSL in the case of Pseudomonas aeruginosa. We have identified a putative AHL transporter of the RND family homologous to P. aeruginosa mexAB-oprM. A mutant strain deficient in this transporter has been generated, and TLC analysis shows absence of 3OH-C14:1-HSL in its supernatant. This deficiency was complemented by the reintroduction of an intact copy of the genes via plasmid transfer. The mutation in mexAB genes had no significant effects on the symbiotic performance of R. leguminosarum bv. viciae.