11 resultados para Functional areas

em Universidad Politécnica de Madrid


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El objeto de la investigación es analizar la situación de las plataformas logísticas y caracterizar las mismas, sus áreas funcionales y los parámetros de diseño que se utilizan para su planificación y desarrollo. La investigación se ha realizado sobre las plataformas logísticas existentes en España, si bien se ha contrastado la situación nacional con otras experiencias internacionales. Para ello se ha procedido al estudio del estado del arte a nivel internacional, determinando la terminología, caracterización y clasificación que aporta la comunidad científica al respecto sobre las plataformas logísticas. La investigación se ha centrado en el estudio de un elevado número de plataformas logísticas ubicadas en distintas Comunidades Autónomas, que representan en torno al cuarenta por ciento de las que se encuentran en estos momentos en activo, analizando sus datos básicos, su clasificación en lo que respecta a su grado de centralidad, su intermodalidad, su accesibilidad, y la información urbanística relativa a superficies de áreas funcionales, edificabilidades, usos principales, complementarios y no admitidos, red viaria, zonas verdes, y parámetros máximos y mínimos de ordenación. El análisis, valoración e interpretación de los resultados obtenidos, ha permitido concluir en la heterogeneidad existente sobre el término, proponiéndose por parte del autor un nuevo concepto que englobe y defina de forma genérica pero clara la tipología de plataformas logísticas presentes en el panorama nacional. Del mismo modo, y como consecuencia de la investigación realizada, ha sido posible la caracterización de una “plataforma logística tipo”, estableciendo unos parámetros de diseño estándar para desarrollos posteriores. Finalmente se proponen varias líneas de investigación. En primer lugar, analizar el conjunto del transporte de mercancías, para determinar y valorar su desequilibrio, para de este modo potenciar la intermodalidad e internacionalizar la misma; y, en segundo lugar, establecer una regulación global de las competencias y legislación en materia de planificación de centros logísticos, para racionalizar el desarrollo de estos elementos. The aim of this research is to analyze the situation of logistics platforms and to characterize them, their functional areas and the design parameters that are used in their planning and development. This study was conducted on logistics platforms in Spain, although the situation in Spain has been compared to other international experiences. For this purpose, the international state-of-the-art has been examined, determining the terminology, characterization and classification provided by the scientific community in regard to logistics platforms. The research focuses on the study of a large number of logistics platforms located in different Autonomous Regions, representing approximately 40% of those currently in operation. An analysis has been made of the fundamental data, classification in regard to the degree of centrality, intermodality, accessibility and the urban planning information relating to functional area spaces, as well as buildable potential, main, complementary and prohibited uses, the road network, green zones and maximum and minimum development planning parameters. The analysis, evaluation and interpretation of the results obtained has led to the conclusion of the heterogeneous nature of the term, and the author proposes a new concept that would cover and define, in a generic yet clear way, the typology of logistics platforms present in the national scenario. In a similar manner, and as a result of the research conducted, it has been possible to define a “logistics platform type”, establishing standard design parameters for future developments. Lastly, various lines of research are proposed. In the first place, to analyze overall goods transport to determine and evaluate its imbalances and, in this way, to promote its intermodality and internationalization. In the second place, to establish a global regulation of competencies and legislation with regard to the planning of logistics centers, to rationalize the development of these elements.

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Community development must be accompanied by a social involvement process which creates functional groups of citizens capable of taking responsibility for their own development. It is important that this process promotes the structuring of all population groups and provides the appropriate institutional and technical support. The present paper addresses these issues based on over 25 years of experience by the Association Instituto de Desarrollo Comunitario de Cuenca in revitalizing rural areas of the Spanish province of Cuenca. This paper analyses the social involvement process encouraged by this association, the relationships between public institutions and local associations, the role of these associations and the difficulties encountered in the rural areas. The long-term perspective of this experience provides some keys which can be used to successfully support the process of social involvement ―such as information on its characteristics and methodological tools―, establish local associations and create sustainable partnerships that foster the growth of leadership within the community development process.

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An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50–100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

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Fixation-off sensitivity (FOS) denotes the forms of EEG abnormalities, which are elicited by elimination of central vision or fixation. The phenomenon seems to depend on variables that modulate the alpha rhythm, however, the cerebral mechanisms underlying FOS remain unclear [1]. The scarce previous fMRI findings related to FOS have shown activation in extrastriate cortex [2] and also in frontal areas [3][4]. On the other hand, simultaneous EEG-fMRI technique has been used to assess the relationship between spontaneous power fluctuations of electrical rhythms and associated fMRI signal modulations. These studies have identified that lateral frontoparietal networks show a negative correlation with alpha band in healthy subjects. This neuroanatomical pattern is related to attentional processes and cognitive resources. Moreover, a sub-beta band (17-23 Hz) has been identified with posterior cingulate, temporoparietal junction and dorso-medial prefrontal cortex activations, which correspond to the DMN [5][6].

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Objective: To show the results of a device that generates automated olfactory stimuli suitable for functional magnetic resonance imaging (fMRI) experiments. Material and methods: Te n normal volunteers, 5 women and 5 men, were studied. The system allows the programming of several sequences, providing the capability to synchronise the onset of odour presentation with acquisition by a trigger signal of the MRI scanner. The olfactometer is a device that allows selection of the odour, the event paradigm, the time of stimuli and the odour concentration. The paradigm used during fMRI scanning consisted of 15-s blocks. The odorant event took 2 s with butanol, mint and coffee. Results: We observed olfactory activity in the olfactory bulb, entorhinal cortex (4%), amygdala (2.5%) and temporo-parietal cortex, especially in the areas related to emotional integration. Conclusions: The device has demonstrated its effectiveness in stimulating olfactory areas and its capacity to adapt to fMRI equipment.RESUMEN Objetivo: Mostrar los resultados del olfatómetro capaz de generar tareas olfativas en un equipo de resonancia magnética funcional (fMRI). Material y métodos: Estudiamos 10 sujetos normales: 5 varones y 5 mujeres. El olfatómetro está dise ̃ nado para que el estímulo que produce se sincronice con el equipo de fMRI mediante la se ̃ nal desencadenante que suministra el propio equipo. El olfatómetro es capaz de: selec- cionar el olor, secuenciar los distintos olores, programar la frecuencia y duración de los olores y controlar la intensidad del olor. El paradigma utilizado responde a un dise ̃ no de activación asociada a eventos, en el que la duración del bloque de activación y de reposo es de 15 s. La duración del estímulo olfativo (butanol, menta o café) es de 2 segundos, durante toda la serie que consta de 9 ciclos. Resultados: Se ha observado reactividad (contraste BOLD) en las diferentes áreas cerebrales involucradas en las tareas olfativas: bulbo olfatorio, córtex entorrinal (4%), amigdala (2,5%) y córtex temporoparietal. Las áreas relacionadas con integración de las emociones tienen una reactividad mayor. Conclusiones: El dispositivo propuesto nos permite controlar de forma automática y sincronizada los olores necesarios para estudiar la actividad de las áreas olfatorias cerebrales mediante fMRI.

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Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.

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Although progressive functional brain network disruption has been one of the hallmarks of Alzheimer?s Dis- ease, little is known about the origin of this functional impairment that underlies cognitive symptoms. We in- vestigated how the loss of white matter (WM) integrity disrupts the organization of the functional networks at different frequency bands. The analyses were performed in a sample of healthy elders and mild cognitive im- pairment (MCI) subjects. Spontaneous brain magnetic activity (measured with magnetoencephalography) was characterized with phase synchronization analysis, and graph theory was applied to the functional networks. We identified WM areas (using diffusion weighted magnetic resonance imaging) that showed a statistical de- pendence between the fractional anisotropy and the graph metrics. These regions are part of an episodic mem- ory network and were also related to cognitive functions. Our data support the hypothesis that disruption of the anatomical networks influences the organization at the functional level resulting in the prodromal dementia syndrome of MCI.

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Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical con- nections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 dif- ferent brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very- large-scale integration circuits analyses, shows that func- tional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrange- ments for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal?ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organi- zations that can only be identified when the physical locations of the nodes are included in the analysis.

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Unraveling pyramidal cell structure is crucial to understanding cortical circuit computations. Although it is well known that pyramidal cell branching structure differs in the various cortical areas, the principles that determine the geometric shapes of these cells are not fully understood. Here we analyzed and modeled with a von Mises distribution the branching angles in 3D reconstructed basal dendritic arbors of hundreds of intracellularly injected cortical pyramidal cells in seven different cortical regions of the frontal, parietal, and occipital cortex of the mouse. We found that, despite the differences in the structure of the pyramidal cells in these distinct functional and cytoarchitectonic cortical areas, there are common design principles that govern the geometry of dendritic branching angles of pyramidal cells in all cortical areas.

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The paper describes some relevant results of an on-going research aiming to elaborate a methodology to help the mobility management in natural parks, compatible with their protection missions: it has been developed a procedure to reproduce the mobility-environment relationships in various operational conditions. The final purpose is the identification of: a) the effects of various choices in transport planning, both at long term and strategic level; b) the most effective policies of mobility management. The work is articulated in the following steps: 1) definition of protected area on the basis of ecological and socio-economic criteria and legislative constraints; 2) analysis of mobility needs in the protected areas; 3) reconstruction of the state of the art of mobility management in natural parks at European level; 4) analysis of used traffic flows measurement methods; 5) analysis of environmental impacts due to transport systems modelling (air pollution and noise only); 6) identification of mitigation measures to be potentially applied. The whole methodology has been tested and validated on Italian case studies: i) the concerned area has been zoned according to the land-use peculiarities; ii) the local situations of transport infrastructure (roads and parking), services (public transport systems) and rules (traffic regulations) have been mapped with references to physical and functional attributes; iii) the mobility, both systematic and touristic, has been represented in an origin-destination matrix. By means of an assignment model the flows have been distributed and the corresponding average speeds to quantify gaseous and noise emissions was calculated, the criticalities in the reference scenario have been highlighted, as well as some alternative scenarios, including both operational and infrastructural measures have been identified. The comparison between projects and reference scenario allowed the quantification of effects (variation of emissions) for each scenario and a selection of the most effective management actions to be taken.

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The final purpose is the identification of: a) the effects of various choices in transport planning, both at long term and strategic level; b) the most effective policies of mobility management. The preliminary work was articulated in the following steps: 1) definition of protected area on the basis of ecological and socio-economic criteria and legislative constraints; 2) analysis of mobility needs in the protected areas; 3) reconstruction of the state of the art of mobility management in natural parks at European level; 4) analysis of used traffic flows measurement methods; 5) analysis of environmental impacts due to transport systems modelling (limited to air pollution and noise); 6) identification of mitigation measures to the potentially applied. The whole methodology has been firstly tested on the case study of the National Park of ?Gran Sasso and Monti della Laga? and further validated on the National Park of ?Gargano?, both located Italy: i) the concerned area has been zoned according to the land-use peculiarities; ii) the local situations of transport infrastructure (roads and parking), services (public transport systems) and rules (traffic regulations) have been mapped with references to physical and functional attributes; iii) the mobility, both systematic and touristic, has been synthetically represented in an origin-destination matrix. By means of an assignment model it has been determined the distribution of flows and the corresponding average speeds to quantify gaseous and noise emissions. On this basis the environmental criticalities in the reference scenario have been highlighted, as well as some alternative scenarios including both operational and infrastructural measures have been identified. The comparison between the projects and the reference scenario allowed the quantification of the effects (variation of emissions) for each scenario and a selection of the most effective management actions to be taken.