Caffeine affects the biological responses of human hematopoietic cells of myeloid lineage via downregulation of the mTOR pathway and xanthine oxidase activity.

Correction of human myeloid cell function is crucial for the prevention of inflammatory and allergic reactions as well as leukaemia progression. Caffeine, a naturally occurring food component, is known to display anti-inflammatory effects which have previously been ascribed largely to its inhibitory actions on phosphodiesterase. However, more recent studies suggest an additional role in affecting the activity of the mammalian target of rapamycin (mTOR), a master regulator of myeloid cell translational pathways, although detailed molecular events underlying its mode of action have not been elucidated. Here, we report the cellular uptake of caffeine, without metabolisation, by healthy and malignant hematopoietic myeloid cells including monocytes, basophils and primary acute myeloid leukaemia mononuclear blasts. Unmodified caffeine downregulated mTOR signalling, which affected glycolysis and the release of pro-inflammatory/pro-angiogenic cytokines as well as other inflammatory mediators. In monocytes, the effects of caffeine were potentiated by its ability to inhibit xanthine oxidase, an enzyme which plays a central role in human purine catabolism by generating uric acid. In basophils, caffeine also increased intracellular cyclic adenosine monophosphate (cAMP) levels which further enhanced its inhibitory action on mTOR. These results demonstrate an important mode of pharmacological action of caffeine with potentially wide-ranging therapeutic impact for treating non-infectious disorders of the human immune system, where it could be applied directly to inflammatory cells.

Vision-based vehicle detection and tracking with a mobile camera using a statistical framework

En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

Seed image analysis and taxonomy of Diplotaxis DC. (Brassicaceae, Brassiceae)

The genus Diplotaxis, comprising 32 or 34 species, plus several additional infraspecific taxa, displays a considerable degree of heterogeneity in the morphology, molecular markers, chromosome numbers and geographical amplitude of the species. The taxonomic relationships within the genus Diplotaxis were investigated by phenetic characterisation of germplasm belonging to 27 taxa of the genus, because there is an increasing interest in Diplotaxis, since some of its species (D. tenuifolia, D. muralis) are gathered or cultivated for human consumption, whereas others are frequent arable weeds (D. erucoides) in many European vineyards. Using a computer-aided vision system, 33 morpho-colorimetric features of seeds were electronically measured. The data were used to implement a statistical classifier, which is able to discriminate the taxa within the genus Diplotaxis, in order to compare the resulting species grouping with the current infrageneric systematics of this genus. Despite the high heterogeneity of the samples, due to the great intra-population variability, the stepwise Linear Discriminant Analysis method, applied to distinguish the groups, was able to reach over 80% correct identification. The results obtained allowed us to confirm the current taxonomic position of most taxa and suggested the taxonomic position of others for reconsideration.

A novel methodology for planning reliable wireless sensor networks

Wireless sensor networks (WSNs) have shown their potentials in various applications, which bring a lot of benefits to users from both research and industrial areas. For many setups, it is envisioned thatWSNs will consist of tens to hundreds of nodes that operate on small batteries. However due to the diversity of the deployed environments and resource constraints on radio communication, sensing ability and energy supply, it is a very challenging issue to plan optimized WSN topology and predict its performance before real deployment. During the network planning phase, the connectivity, coverage, cost, network longevity and service quality should all be considered. Therefore it requires designers coping with comprehensive and interdisciplinary knowledge, including networking, radio engineering, embedded system and so on, in order to efficiently construct a reliable WSN for any specific types of environment. Nowadays there is still a lack of the analysis and experiences to guide WSN designers to efficiently construct WSN topology successfully without many trials. Therefore, simulation is a feasible approach to the quantitative analysis of the performance of wireless sensor networks. However the existing planning algorithms and tools, to some extent, have serious limitations to practically design reliable WSN topology: Only a few of them tackle the 3D deployment issue, and an overwhelming number of works are proposed to place devices in 2D scheme. Without considering the full dimension, the impacts of environment to the performance of WSN are not completely studied, thus the values of evaluated metrics such as connectivity and sensing coverage are not sufficiently accurate to make proper decision. Even fewer planning methods model the sensing coverage and radio propagation by considering the realistic scenario where obstacles exist. Radio signals propagate with multi-path phenomenon in the real world, in which direct paths, reflected paths and diffracted paths contribute to the received signal strength. Besides, obstacles between the path of sensor and objects might block the sensing signals, thus create coverage hole in the application. None of the existing planning algorithms model the network longevity and packet delivery capability properly and practically. They often employ unilateral and unrealistic formulations. The optimization targets are often one-sided in the current works. Without comprehensive evaluation on the important metrics, the performance of planned WSNs can not be reliable and entirely optimized. Modeling of environment is usually time consuming and the cost is very high, while none of the current works figure out any method to model the 3D deployment environment efficiently and accurately. Therefore many researchers are trapped by this issue, and their algorithms can only be evaluated in the same scenario, without the possibility to test the robustness and feasibility for implementations in different environments. In this thesis, we propose a novel planning methodology and an intelligent WSN planning tool to assist WSN designers efficiently planning reliable WSNs. First of all, a new method is proposed to efficiently and automatically model the 3D indoor and outdoor environments. To the best of our knowledge, this is the first time that the advantages of image understanding algorithm are applied to automatically reconstruct 3D outdoor and indoor scenarios for signal propagation and network planning purpose. The experimental results indicate that the proposed methodology is able to accurately recognize different objects from the satellite images of the outdoor target regions and from the scanned floor plan of indoor area. Its mechanism offers users a flexibility to reconstruct different types of environment without any human interaction. Thereby it significantly reduces human efforts, cost and time spent on reconstructing a 3D geographic database and allows WSN designers concentrating on the planning issues. Secondly, an efficient ray-tracing engine is developed to accurately and practically model the radio propagation and sensing signal on the constructed 3D map. The engine contributes on efficiency and accuracy to the estimated results. By using image processing concepts, including the kd-tree space division algorithm and modified polar sweep algorithm, the rays are traced efficiently without detecting all the primitives in the scene. The radio propagation model iv is proposed, which emphasizes not only the materials of obstacles but also their locations along the signal path. The sensing signal of sensor nodes, which is sensitive to the obstacles, is benefit from the ray-tracing algorithm via obstacle detection. The performance of this modelling method is robust and accurate compared with conventional methods, and experimental results imply that this methodology is suitable for both outdoor urban scenes and indoor environments. Moreover, it can be applied to either GSM communication or ZigBee protocol by varying frequency parameter of the radio propagation model. Thirdly, WSN planning method is proposed to tackle the above mentioned challenges and efficiently deploy reliable WSNs. More metrics (connectivity, coverage, cost, lifetime, packet latency and packet drop rate) are modeled more practically compared with other works. Especially 3D ray tracing method is used to model the radio link and sensing signal which are sensitive to the obstruction of obstacles; network routing is constructed by using AODV protocol; the network longevity, packet delay and packet drop rate are obtained via simulating practical events in WSNet simulator, which to the best of our knowledge, is the first time that network simulator is involved in a planning algorithm. Moreover, a multi-objective optimization algorithm is developed to cater for the characteristics of WSNs. The capability of providing multiple optimized solutions simultaneously allows users making their own decisions accordingly, and the results are more comprehensively optimized compared with other state-of-the-art algorithms. iMOST is developed by integrating the introduced algorithms, to assist WSN designers efficiently planning reliable WSNs for different configurations. The abbreviated name iMOST stands for an Intelligent Multi-objective Optimization Sensor network planning Tool. iMOST contributes on: (1) Convenient operation with a user-friendly vision system; (2) Efficient and automatic 3D database reconstruction and fast 3D objects design for both indoor and outdoor environments; (3) It provides multiple multi-objective optimized 3D deployment solutions and allows users to configure the network properties, hence it can adapt to various WSN applications; (4) Deployment solutions in the 3D space and the corresponding evaluated performance are visually presented to users; and (5) The Node Placement Module of iMOST is available online as well as the source code of the other two rebuilt heuristics. Therefore WSN designers will be benefit from v this tool on efficiently constructing environment database, practically and efficiently planning reliable WSNs for both outdoor and indoor applications. With the open source codes, they are also able to compare their developed algorithms with ours to contribute to this academic field. Finally, solid real results are obtained for both indoor and outdoor WSN planning. Deployments have been realized for both indoor and outdoor environments based on the provided planning solutions. The measured results coincide well with the estimated results. The proposed planning algorithm is adaptable according to the WSN designer’s desirability and configuration, and it offers flexibility to plan small and large scale, indoor and outdoor 3D deployments. The thesis is organized in 7 chapters. In Chapter 1, WSN applications and motivations of this work are introduced, the state-of-the-art planning algorithms and tools are reviewed, challenges are stated out and the proposed methodology is briefly introduced. In Chapter 2, the proposed 3D environment reconstruction methodology is introduced and its performance is evaluated for both outdoor and indoor environment. The developed ray-tracing engine and proposed radio propagation modelling method are described in details in Chapter 3, their performances are evaluated in terms of computation efficiency and accuracy. Chapter 4 presents the modelling of important metrics of WSNs and the proposed multi-objective optimization planning algorithm, the performance is compared with the other state-of-the-art planning algorithms. The intelligent WSN planning tool iMOST is described in Chapter 5. RealWSN deployments are prosecuted based on the planned solutions for both indoor and outdoor scenarios, important data are measured and results are analysed in Chapter 6. Chapter 7 concludes the thesis and discusses about future works. vi Resumen en Castellano Las redes de sensores inalámbricas (en inglés Wireless Sensor Networks, WSNs) han demostrado su potencial en diversas aplicaciones que aportan una gran cantidad de beneficios para el campo de la investigación y de la industria. Para muchas configuraciones se prevé que las WSNs consistirán en decenas o cientos de nodos que funcionarán con baterías pequeñas. Sin embargo, debido a la diversidad de los ambientes para desplegar las redes y a las limitaciones de recursos en materia de comunicación de radio, capacidad de detección y suministro de energía, la planificación de la topología de la red y la predicción de su rendimiento es un tema muy difícil de tratar antes de la implementación real. Durante la fase de planificación del despliegue de la red se deben considerar aspectos como la conectividad, la cobertura, el coste, la longevidad de la red y la calidad del servicio. Por lo tanto, requiere de diseñadores con un amplio e interdisciplinario nivel de conocimiento que incluye la creación de redes, la ingeniería de radio y los sistemas embebidos entre otros, con el fin de construir de manera eficiente una WSN confiable para cualquier tipo de entorno. Hoy en día todavía hay una falta de análisis y experiencias que orienten a los diseñadores de WSN para construir las topologías WSN de manera eficiente sin realizar muchas pruebas. Por lo tanto, la simulación es un enfoque viable para el análisis cuantitativo del rendimiento de las redes de sensores inalámbricos. Sin embargo, los algoritmos y herramientas de planificación existentes tienen, en cierta medida, serias limitaciones para diseñar en la práctica una topología fiable de WSN: Sólo unos pocos abordan la cuestión del despliegue 3D mientras que existe una gran cantidad de trabajos que colocan los dispositivos en 2D. Si no se analiza la dimensión completa (3D), los efectos del entorno en el desempeño de WSN no se estudian por completo, por lo que los valores de los parámetros evaluados, como la conectividad y la cobertura de detección, no son lo suficientemente precisos para tomar la decisión correcta. Aún en menor medida los métodos de planificación modelan la cobertura de los sensores y la propagación de la señal de radio teniendo en cuenta un escenario realista donde existan obstáculos. Las señales de radio en el mundo real siguen una propagación multicamino, en la que los caminos directos, los caminos reflejados y los caminos difractados contribuyen a la intensidad de la señal recibida. Además, los obstáculos entre el recorrido del sensor y los objetos pueden bloquear las señales de detección y por lo tanto crear áreas sin cobertura en la aplicación. Ninguno de los algoritmos de planificación existentes modelan el tiempo de vida de la red y la capacidad de entrega de paquetes correctamente y prácticamente. A menudo se emplean formulaciones unilaterales y poco realistas. Los objetivos de optimización son a menudo tratados unilateralmente en los trabajos actuales. Sin una evaluación exhaustiva de los parámetros importantes, el rendimiento previsto de las redes inalámbricas de sensores no puede ser fiable y totalmente optimizado. Por lo general, el modelado del entorno conlleva mucho tiempo y tiene un coste muy alto, pero ninguno de los trabajos actuales propone algún método para modelar el entorno de despliegue 3D con eficiencia y precisión. Por lo tanto, muchos investigadores están limitados por este problema y sus algoritmos sólo se pueden evaluar en el mismo escenario, sin la posibilidad de probar la solidez y viabilidad para las implementaciones en diferentes entornos. En esta tesis, se propone una nueva metodología de planificación así como una herramienta inteligente de planificación de redes de sensores inalámbricas para ayudar a los diseñadores a planificar WSNs fiables de una manera eficiente. En primer lugar, se propone un nuevo método para modelar demanera eficiente y automática los ambientes interiores y exteriores en 3D. Según nuestros conocimientos hasta la fecha, esta es la primera vez que las ventajas del algoritmo de _image understanding_se aplican para reconstruir automáticamente los escenarios exteriores e interiores en 3D para analizar la propagación de la señal y viii la planificación de la red. Los resultados experimentales indican que la metodología propuesta es capaz de reconocer con precisión los diferentes objetos presentes en las imágenes satelitales de las regiones objetivo en el exterior y de la planta escaneada en el interior. Su mecanismo ofrece a los usuarios la flexibilidad para reconstruir los diferentes tipos de entornos sin ninguna interacción humana. De este modo se reduce considerablemente el esfuerzo humano, el coste y el tiempo invertido en la reconstrucción de una base de datos geográfica con información 3D, permitiendo así que los diseñadores se concentren en los temas de planificación. En segundo lugar, se ha desarrollado un motor de trazado de rayos (en inglés ray tracing) eficiente para modelar con precisión la propagación de la señal de radio y la señal de los sensores en el mapa 3D construido. El motor contribuye a la eficiencia y la precisión de los resultados estimados. Mediante el uso de los conceptos de procesamiento de imágenes, incluyendo el algoritmo del árbol kd para la división del espacio y el algoritmo _polar sweep_modificado, los rayos se trazan de manera eficiente sin la detección de todas las primitivas en la escena. El modelo de propagación de radio que se propone no sólo considera los materiales de los obstáculos, sino también su ubicación a lo largo de la ruta de señal. La señal de los sensores de los nodos, que es sensible a los obstáculos, se ve beneficiada por la detección de objetos llevada a cabo por el algoritmo de trazado de rayos. El rendimiento de este método de modelado es robusto y preciso en comparación con los métodos convencionales, y los resultados experimentales indican que esta metodología es adecuada tanto para escenas urbanas al aire libre como para ambientes interiores. Por otra parte, se puede aplicar a cualquier comunicación GSM o protocolo ZigBee mediante la variación de la frecuencia del modelo de propagación de radio. En tercer lugar, se propone un método de planificación de WSNs para hacer frente a los desafíos mencionados anteriormente y desplegar redes de sensores fiables de manera eficiente. Se modelan más parámetros (conectividad, cobertura, coste, tiempo de vida, la latencia de paquetes y tasa de caída de paquetes) en comparación con otros trabajos. Especialmente el método de trazado de rayos 3D se utiliza para modelar el enlace de radio y señal de los sensores que son sensibles a la obstrucción de obstáculos; el enrutamiento de la red se construye utilizando el protocolo AODV; la longevidad de la red, retardo de paquetes ix y tasa de abandono de paquetes se obtienen a través de la simulación de eventos prácticos en el simulador WSNet, y según nuestros conocimientos hasta la fecha, es la primera vez que simulador de red está implicado en un algoritmo de planificación. Por otra parte, se ha desarrollado un algoritmo de optimización multi-objetivo para satisfacer las características de las redes inalámbricas de sensores. La capacidad de proporcionar múltiples soluciones optimizadas de forma simultánea permite a los usuarios tomar sus propias decisiones en consecuencia, obteniendo mejores resultados en comparación con otros algoritmos del estado del arte. iMOST se desarrolla mediante la integración de los algoritmos presentados, para ayudar de forma eficiente a los diseñadores en la planificación de WSNs fiables para diferentes configuraciones. El nombre abreviado iMOST (Intelligent Multi-objective Optimization Sensor network planning Tool) representa una herramienta inteligente de planificación de redes de sensores con optimización multi-objetivo. iMOST contribuye en: (1) Operación conveniente con una interfaz de fácil uso, (2) Reconstrucción eficiente y automática de una base de datos con información 3D y diseño rápido de objetos 3D para ambientes interiores y exteriores, (3) Proporciona varias soluciones de despliegue optimizadas para los multi-objetivo en 3D y permite a los usuarios configurar las propiedades de red, por lo que puede adaptarse a diversas aplicaciones de WSN, (4) las soluciones de implementación en el espacio 3D y el correspondiente rendimiento evaluado se presentan visualmente a los usuarios, y (5) El _Node Placement Module_de iMOST está disponible en línea, así como el código fuente de las otras dos heurísticas de planificación. Por lo tanto los diseñadores WSN se beneficiarán de esta herramienta para la construcción eficiente de la base de datos con información del entorno, la planificación práctica y eficiente de WSNs fiables tanto para aplicaciones interiores y exteriores. Con los códigos fuente abiertos, son capaces de comparar sus algoritmos desarrollados con los nuestros para contribuir a este campo académico. Por último, se obtienen resultados reales sólidos tanto para la planificación de WSN en interiores y exteriores. Los despliegues se han realizado tanto para ambientes de interior y como para ambientes de exterior utilizando las soluciones de planificación propuestas. Los resultados medidos coinciden en gran medida con los resultados estimados. El algoritmo de planificación x propuesto se adapta convenientemente al deiseño de redes de sensores inalámbricas, y ofrece flexibilidad para planificar los despliegues 3D a pequeña y gran escala tanto en interiores como en exteriores. La tesis se estructura en 7 capítulos. En el Capítulo 1, se presentan las aplicaciones de WSN y motivaciones de este trabajo, se revisan los algoritmos y herramientas de planificación del estado del arte, se presentan los retos y se describe brevemente la metodología propuesta. En el Capítulo 2, se presenta la metodología de reconstrucción de entornos 3D propuesta y su rendimiento es evaluado tanto para espacios exteriores como para espacios interiores. El motor de trazado de rayos desarrollado y el método de modelado de propagación de radio propuesto se describen en detalle en el Capítulo 3, evaluándose en términos de eficiencia computacional y precisión. En el Capítulo 4 se presenta el modelado de los parámetros importantes de las WSNs y el algoritmo de planificación de optimización multi-objetivo propuesto, el rendimiento se compara con los otros algoritmos de planificación descritos en el estado del arte. La herramienta inteligente de planificación de redes de sensores inalámbricas, iMOST, se describe en el Capítulo 5. En el Capítulo 6 se llevan a cabo despliegues reales de acuerdo a las soluciones previstas para los escenarios interiores y exteriores, se miden los datos importantes y se analizan los resultados. En el Capítulo 7 se concluye la tesis y se discute acerca de los trabajos futuros.

Vibration reduction for vision systems on board unmanned aerial vehicles using a neuro-fuzzy controller

In this paper, an intelligent control approach based on neuro-fuzzy systems performance is presented, with the objective of counteracting the vibrations that affect the low-cost vision platform onboard an unmanned aerial system of rotating nature. A scaled dynamical model of a helicopter is used to simulate vibrations on its fuselage. The impact of these vibrations on the low-cost vision system will be assessed and an intelligent control approach will be derived in order to reduce its detrimental influence. Different trials that consider a neuro-fuzzy approach as a fundamental part of an intelligent semi-active control strategy have been carried out. Satisfactory results have been achieved compared to those obtained by means of vibration reduction passive techniques.

Feature integration in pattern perception

The human visual system is able to effortlessly integrate local features to form our rich perception of patterns, despite the fact that visual information is discretely sampled by the retina and cortex. By using a novel perturbation technique, we show that the mechanisms by which features are integrated into coherent percepts are scale-invariant and nonlinear (phase and contrast polarity independent). They appear to operate by assigning position labels or “place tags” to each feature. Specifically, in the first series of experiments, we show that the positional tolerance of these place tags in foveal, and peripheral vision is about half the separation of the features, suggesting that the neural mechanisms that bind features into forms are quite robust to topographical jitter. In the second series of experiment, we asked how many stimulus samples are required for pattern identification by human and ideal observers. In human foveal vision, only about half the features are needed for reliable pattern interpolation. In this regard, human vision is quite efficient (ratio of ideal to real ≈ 0.75). Peripheral vision, on the other hand is rather inefficient, requiring more features, suggesting that the stimulus may be relatively underrepresented at the stage of feature integration.

On a common circle: Natural scenes and Gestalt rules

To understand how the human visual system analyzes images, it is essential to know the structure of the visual environment. In particular, natural images display consistent statistical properties that distinguish them from random luminance distributions. We have studied the geometric regularities of oriented elements (edges or line segments) present in an ensemble of visual scenes, asking how much information the presence of a segment in a particular location of the visual scene carries about the presence of a second segment at different relative positions and orientations. We observed strong long-range correlations in the distribution of oriented segments that extend over the whole visual field. We further show that a very simple geometric rule, cocircularity, predicts the arrangement of segments in natural scenes, and that different geometrical arrangements show relevant differences in their scaling properties. Our results show similarities to geometric features of previous physiological and psychophysical studies. We discuss the implications of these findings for theories of early vision.

Expression of protein encoded by varicella-zoster virus open reading frame 63 in latently infected human ganglionic neurons.

The ganglionic cell type in which varicella-zoster virus (VZV) is latent in humans was analyzed by using antibodies raised against in vitro-expressed VZV open reading frame 63 protein. VZV open reading frame 63 protein was detected exclusively in the cytoplasm of neurons of latently infected human trigeminal and thoracic ganglia. This is, to our knowledge, the first identification of a herpesvirus protein expressed during latency in the human nervous system.

Pleasant sweeping grooming touch in rhesus monkey: effects on autonomic nervous system and its codification in posterior insular and secondary somatosensory cortex

Il tatto assume un'importanza fondamentale nella vita quotidiana, in quanto ci permette di discriminare le caratteristiche fisiche di un oggetto specifico, di identificarlo e di eventualmente integrare le suddette informazioni tattili con informazioni provenienti da altri canali sensoriali. Questa è la componente sensoriale-discriminativa del tatto. Tuttavia quotidianamente il tatto assume un ruolo fondamentale durante le diverse interazioni sociali, positive, come quando abbracciamo o accarezziamo una persona con cui abbiamo un rapporto affettivo e negative, per esempio quando allontaniamo una persona estranea dal nostro spazio peri-personale. Questa componente è la cosiddetta dimensione affettiva-motivazionale, la quale determina la codifica della valenza emotiva che l'interazione assume. Questa componente ci permette di creare, mantenere o distruggere i legami sociali in relazione al significato che il tocco assume durante l'interazione. Se per esempio riceviamo una carezza da un familiare, questa verrà percepita come piacevole e assumerà un significato affiliativo. Questo tipo di tocco è comunente definito come Tocco Sociale (Social Touch). Gli aspetti discriminativi del tatto sono stati ben caratterizzati, in quanto storicamente, il ruolo del tatto è stato considerato quello di discriminare le caratteristiche di ciò che viene toccato, mentre gli aspetti affettivi sono stati solo recentemente indagati considerando la loro importanza nelle interazioni sociali. Il tocco statico responsabile dell'aspetto discriminante attiva a livello della pelle le grandi fibre mieliniche (Aβ), modulando a livello del sistema nervoso centrale le cortecce sensoriali, sia primarie che secondarie. Questo permette la codifica a livello del sistema nervoso centrale delle caratteristiche fisiche oggettive degli oggetti toccati. Studi riguardanti le caratteristiche del tocco affiliativo sociale hanno messo in evidenza che suddetta stimolazione tattile 1) è un particolare tocco dinamico che avviene sul lato peloso delle pelle con una velocità di 1-10 cm/sec; 2) attiva le fibre amieliniche (fibre CT o C-LTMRs); 3) induce positivi effetti autonomici, ad esempio la diminuzione della frequenza cardiaca e l'aumento della variabilità della frequenza cardiaca; e 4) determina la modulazione di regioni cerebrali coinvolte nella codifica del significato affiliativo dello stimolo sensoriale periferico, in particolare la corteccia insulare. Il senso del tatto, con le sue due dimensioni discriminativa e affiliativa, è quotidianamente usato non solo negli esseri umani, ma anche tra i primati non umani. Infatti, tutti i primati non umani utilizzano la componente discriminativa del tatto per identificare gli oggetti e il cibo e l'aspetto emotivo durante le interazioni sociali, sia negative come durante un combattimento, che positive, come durante i comportamenti affiliativi tra cui il grooming. I meccanismi di codifica della componente discriminativa dei primati non umani sono simili a quelli umani. Tuttavia, si conosce ben poco dei meccanismi alla base della codifica del tocco piacevole affiliativo. Pur essendo ben noto che i meccanorecettori amilienici C-LTMRs sono presenti anche sul lato peloso della pelle dei primati non umani, attualmente non ci sono studi riguardanti la correlazione tra il tocco piacevole e la loro modulazione, come invece è stato ampiamente dimostrato nell'uomo. Recentemente è stato ipotizzato (Dunbar, 2010) il ruolo delle fibre C-LTMRs durante il grooming, in particolare durante il cosiddetto swepping. Il grooming è costituito da due azioni motorie, lo sweeping e il picking che vengono eseguite in modo ritmico. Durante lo sweeping la scimmia agente muove il pelo della scimmia ricevente con un movimento a mano aperta, per poter vedere il preciso punto della pelle dove eseguire il picking, ovvero dove prendere la pelle a livello della radice del pelo con le unghie dell'indice e del pollice e tirare per rimuovere parassiti o uova di parassiti e ciò che è rimasto incastrato nel pelo. Oltre il noto ruolo igenico, il grooming sembra avere anche una importante funzione sociale affiliativa. Come la carezza nella società umana, cosi il grooming tra i primati non umani è considerato un comportamento. Secondo l'ipotesi di Dunbar l'attivazione delle C-LTMRs avverrebbe durante lo sweeping e questo porta a supporre che lo sweeping, come la carezza umana, costituisca una componente affiliativa del grooming, determinando quindi a contribuire alla sua codifica come comportamento sociale. Fino ad ora non vi è però alcuna prova diretta a sostegno di questa ipotesi. In particolare, 1) la velocità cui viene eseguito lo sweeping è compatibile con la velocità di attivazione delle fibre CT nell'uomo e quindi con la velocità tipica della carezza piacevole di carattere sociale affiliativo (1-10 cm/sec)?; 2) lo sweeping induce la stessa modulazione del sistema nervoso autonomo in direzione della modulazione del sistema vagale, come il tocco piacevole nell'uomo, attraverso l'attivazione delle fibre CT?; 3) lo sweeping modula la corteccia insulare, cosi come il tocco piacevole viene codificato come affiliativo nell'uomo mediante le proiezioni delle fibre CT a livello dell'insula posteriore? Lo scopo del presente lavoro è quella di testare l'ipotesi di Dunbar sopra citata, cercando quindi di rispondere alle suddette domande. Le risposte potrebbero consentire di ipotizzare la somiglianza tra lo sweeping, caratteristico del comportamento affiliativo di grooming tra i primati non umani e la carezza. In particolare, abbiamo eseguito 4 studi pilota. Nello Studio 1 abbiamo valutato la velocità con cui viene eseguito lo sweeping tra scimmie Rhesus, mediante una analisi cinematica di video registrati tra un gruppo di scimmie Rhesus. Negli Studi 2 e 3 abbiamo valutato gli effetti sul sistema nervoso autonomo dello sweeping eseguito dallo sperimentatore su una scimmia Rhesus di sesso maschile in una tipica situazione sperimentale. La stimolazione tattile è stata eseguita a diverse velocità, in accordo con i risultati dello Studio 1 e degli studi umani che hanno dimostrato la velocità ottimale e non ottimale per l'attivazione delle C-LTMRs. In particolare, nello Studio 2 abbiamo misurato la frequenza cardiaca e la variabilità di questa, come indice della modulatione vagale, mentre nello Studio 3 abbiamo valutato gli effetti dello sweeping sul sistema nervoso autonomo in termini di variazioni di temperatura del corpo, nello specifico a livello del muso della scimmia. Infine, nello Studio 4 abbiamo studiato il ruolo della corteccia somatosensoriale secondaria e insulare nella codifica dello sweeping. A questo scopo abbiamo eseguito registrazioni di singoli neuroni mentre la medesima scimmia soggetto sperimentale dello Studio 2 e 3, riceveva lo sweeping a due velocità, una ottimale per l'attivazione delle C-LTMRs secondo gli studi umani e i risultati dei tre studi sopra citati, ed una non ottimale. I dati preliminari ottenuti, dimostrano che 1) (Studio 1) lo sweeping tra scimmie Rhesus viene eseguito con una velocità media di 9.31 cm/sec, all'interno dell'intervallo di attivazione delle fibre CT nell'uomo; 2) (Studio 2) lo sweeping eseguito dallo sperimentatore sulla schiena di una scimmia Rhesus di sesso maschile in una situazione sperimentale determina una diminuzione della frequenza cardiaca e l'aumento della variabilità della frequenza cardiaca se eseguito alla velocità di 5 e 10 cm/sec. Al contrario, lo sweeping eseguito ad una velocità minore di 1 cm/sec o maggiore di 10 cm/sec, determina l'aumento della frequenza cardiaca e la diminuzione della variabilità di questa, quindi il decremento dell'attivazione del sistema nervoso parasimpatico; 3) (Studio 3) lo sweeping eseguito dallo sperimentatore sulla schiena di una scimmia Rhesus di sesso maschile in una situazione sperimentale determina l'aumento della temperatura corporea a livello del muso della scimmia se eseguito alla velocità di 5-10 cm/sec. Al contrario, lo sweeping eseguito ad una velocità minore di 5 cm/sec o maggiore di 10 cm/sec, determina la diminuzione della temperatura del muso; 4) (Studio 4) la corteccia somatosensoriale secondaria e la corteccia insulare posteriore presentano neuroni selettivamente modulati durante lo sweeping eseguito ad una velocità di 5-13 cm/sec ma non neuroni selettivi per la codifica della velocità dello sweeping minore di 5 cm/sec. Questi risultati supportano l'ipotesi di Dunbar relativa al coinvolgimento delle fibre CT durante lo sweeping. Infatti i dati mettono in luce che lo sweeping viene eseguito con una velocità (9.31 cm/sec), simile a quella di attivazione delle fibre CT nell'uomo (1-10 cm/sec), determina gli stessi effetti fisiologici positivi in termini di frequenza cardiaca (diminuzione) e variabilità della frequenza cardiaca (incremento) e la modulazione delle medesime aree a livello del sistema nervoso centrale (in particolare la corteccia insulare). Inoltre, abbiamo dimostrato per la prima volta che suddetta stimolazione tattile determina l'aumento della temperatura del muso della scimmia. Il presente studio rappresenta la prima prova indiretta dell'ipotesi relativa alla modulazione del sistema delle fibre C-LTMRs durante lo sweeping e quindi della codifica della stimolazione tattile piacevole affiliativa a livello del sistema nervoso centrale ed autonomo, nei primati non umani. I dati preliminari qui presentati evidenziano la somiglianza tra il sistema delle fibre CT dell'uomo e del sistema C-LTMRs nei primati non umano, riguardanti il Social Touch. Nonostante ciò abbiamo riscontrato alcune discrepanze tra i risultati da noi ottenuti e quelli invece ottenuti dagli studi umani. La velocità media dello sweeping è di 9.31 cm / sec, rasente il limite superiore dell’intervallo di velocità che attiva le fibre CT nell'uomo. Inoltre, gli effetti autonomici positivi, in termini di battito cardiaco, variabilità della frequenza cardiaca e temperatura a livello del muso, sono stati evidenziati durante lo sweeping eseguito con una velocità di 5 e 10 cm/sec, quindi al limite superiore dell’intervallo ottimale che attiva le fibre CT nell’uomo. Al contrario, lo sweeping eseguito con una velocità inferiore a 5 cm/sec e superiore a 10 cm/sec determina effetti fisiologici negativo. Infine, la corteccia insula sembra essere selettivamente modulata dallo stimolazione eseguita alla velocità di 5-13 cm/sec, ma non 1-5 cm/sec. Quindi, gli studi sul sistema delle fibre CT nell’uomo hanno dimostrato che la velocità ottimale è 1-10 cm/sec, mentre dai nostri risultati la velocità ottimale sembra essere 5-13 cm / sec. Quindi, nonostante l'omologia tra il sistema delle fibre CT nell'umano deputato alla codifica del tocco piacevole affiliativo ed il sistema delle fibre C-LTMRs nei primati non umani, ulteriori studi saranno necessari per definire con maggiore precisione la velocità ottimale di attivazione delle fibre C-LTMR e per dimostrare direttamente la loro attivazione durante lo sweeping, mediante la misurazione diretta della loro modulazione. Studi in questa direzione potranno confermare l'omologia tra lo sweeping in qualità di tocco affiliativo piacevole tra i primati non umani e la carezza tra gli uomini. Infine, il presente studio potrebbe essere un importante punto di partenza per esplorare il meccanismo evolutivo dietro la trasformazione dello sweeping tra primati non umani, azione utilitaria eseguita durante il grooming, a carezza, gesto puramente affiliativo tra gli uomini.

Avaliação da influência de emoções na tomada de decisão de sistemas computacionais.

Este trabalho avalia a influência das emoções humanas expressas pela mímica da face na tomada de decisão de sistemas computacionais, com o objetivo de melhorar a experiência do usuário. Para isso, foram desenvolvidos três módulos: o primeiro trata-se de um sistema de computação assistiva - uma prancha de comunicação alternativa e ampliada em versão digital. O segundo módulo, aqui denominado Módulo Afetivo, trata-se de um sistema de computação afetiva que, por meio de Visão Computacional, capta a mímica da face do usuário e classifica seu estado emocional. Este segundo módulo foi implementado em duas etapas, as duas inspiradas no Sistema de Codificação de Ações Faciais (FACS), que identifica expressões faciais com base no sistema cognitivo humano. Na primeira etapa, o Módulo Afetivo realiza a inferência dos estados emocionais básicos: felicidade, surpresa, raiva, medo, tristeza, aversão e, ainda, o estado neutro. Segundo a maioria dos pesquisadores da área, as emoções básicas são inatas e universais, o que torna o módulo afetivo generalizável a qualquer população. Os testes realizados com o modelo proposto apresentaram resultados 10,9% acima dos resultados que usam metodologias semelhantes. Também foram realizadas análises de emoções espontâneas, e os resultados computacionais aproximam-se da taxa de acerto dos seres humanos. Na segunda etapa do desenvolvimento do Módulo Afetivo, o objetivo foi identificar expressões faciais que refletem a insatisfação ou a dificuldade de uma pessoa durante o uso de sistemas computacionais. Assim, o primeiro modelo do Módulo Afetivo foi ajustado para este fim. Por fim, foi desenvolvido um Módulo de Tomada de Decisão que recebe informações do Módulo Afetivo e faz intervenções no Sistema Computacional. Parâmetros como tamanho do ícone, arraste convertido em clique e velocidade de varredura são alterados em tempo real pelo Módulo de Tomada de Decisão no sistema computacional assistivo, de acordo com as informações geradas pelo Módulo Afetivo. Como o Módulo Afetivo não possui uma etapa de treinamento para inferência do estado emocional, foi proposto um algoritmo de face neutra para resolver o problema da inicialização com faces contendo emoções. Também foi proposto, neste trabalho, a divisão dos sinais faciais rápidos entre sinais de linha base (tique e outros ruídos na movimentação da face que não se tratam de sinais emocionais) e sinais emocionais. Os resultados dos Estudos de Caso realizados com os alunos da APAE de Presidente Prudente demonstraram que é possível melhorar a experiência do usuário, configurando um sistema computacional com informações emocionais expressas pela mímica da face.

Multi-agent system for control of robots inspired on the distributed activity and hormonal regulation of humans

Robotics is an emerging field with great activity. Robotics is a field that presents several problems because it depends on a large number of disciplines, technologies, devices and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges. New uses are, for example, household robots or professional robots. To facilitate the low cost, rapid development of robotic systems, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems. Specifically, we model the decentralized activity and hormonal variation.

Chronic smoking and alcoholism change expression of selective genes in the human prefrontal cortex

Background: Alcoholism is commonly associated with chronic smoking. A number of gene expression profiles of regions within the human mesocorticolimbic system have identified potential alcohol-sensitive genes; however, the influence of smoking on these changes was not taken into account. This study addressed the impact of alcohol and smoking on the expression of 4 genes, previously identified as alcoholism-sensitive. in the human prefrontal cortex (PFC). Methods: mRNA expression of apolipoprotein D, tissue inhibitor of the metalloproteinase 3, high-affinity glial glutamate transporter and midkine, was measured in the PFC of alcoholic Subjects and controls with and without smoking comorbidity using real-time polymerase chain reaction. Results: The results show that alcohol affects transcription of some of these genes. Additionally, smoking has a marked influence on gene expression. Conclusion: This study emphasizes the need for careful case selection in future gene expression studies to delineate the adaptive molecular process associated with smoking and alcohol.

Biological polarized light reflectors in stomatopod crustaceans

Body parts that can reflect highly polarized light have been found in several species of stomatopod crustaceans (mantis shrimps). These polarized light reflectors can be grossly divided into two major types. The first type, usually red or pink in color to the human visual system, is located within an animal’s cuticle. Reflectors of the second type, showing iridescent blue, are located beneath the exoskeleton and thus are unaffected by the molt cycle. We used reflection spectropolarimetry and transmission electron microscopy (TEM) to study the reflective properties and the structures that reflect highly polarized light in stomatopods. For the first type of reflector, the degree of polarization usually changes dramatically, from less than 20% to over 70%, with a change in viewing angle. TEM examination indicates that the polarization reflection is generated by multilayer thin-film interference. The second type of reflector, the blue colored ones, reflects highly polarized light to all viewing angles. However, these reflectors show a slight chromatic change with different viewing angles. TEM sections have revealed that streams of oval-shaped vesicles might be responsible for the production of the polarized light reflection. In all the reflectors we have examined so far, the reflected light is always maximally polarized at around 500 nm, which is close to the wavelength best transmitted by sea water. This suggests that the polarized light reflectors found in stomatopods are well adapted to the underwater environment. We also found that most reflectors produce polarized light with a horizontal e-vector. How these polarized light reflectors are used in stomatopod signaling remains unknown.

Helicopter automation using a low-cost sensing system

This paper details the design of an autonomous helicopter control system using a low cost sensor suite. Control is maintained using simple nested PID loops. Aircraft attitude, velocity, and height is estimated using an in-house designed IMU and vision system. Information is combined using complimentary filtering. The aircraft is shown to be stabilised and responding to high level demands on all axes, including heading, height, lateral velocity and longitudinal velocity.

Natural images dominate in binocular rivalry

Ecological approaches to perception have demonstrated that information encoding by the visual system is informed by the natural environment, both in terms of simple image attributes like luminance and contrast, and more complex relationships corresponding to Gestalt principles of perceptual organization. Here, we ask if this optimization biases perception of visual inputs that are perceptually bistable. Using the binocular rivalry paradigm, we designed stimuli that varied in either their spatiotemporal amplitude spectra or their phase spectra. We found that noise stimuli with “natural” amplitude spectra (i.e., amplitude content proportional to 1/f, where f is spatial or temporal frequency) dominate over those with any other systematic spectral slope, along both spatial and temporal dimensions. This could not be explained by perceived contrast measurements, and occurred even though all stimuli had equal energy. Calculating the effective contrast following attenuation by a model contrast sensitivity function suggested that the strong contrast dependency of rivalry provides the mechanism by which binocular vision is optimized for viewing natural images. We also compared rivalry between natural and phase-scrambled images and found a strong preference for natural phase spectra that could not be accounted for by observer biases in a control task. We propose that this phase specificity relates to contour information, and arises either from the activity of V1 complex cells, or from later visual areas, consistent with recent neuroimaging and single-cell work. Our findings demonstrate that human vision integrates information across space, time, and phase to select the input most likely to hold behavioral relevance.