856 resultados para DYNAMICAL-SYSTEMS APPROACH


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We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers.

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The classical theory of intermittency developed for return maps assumes uniform density of points reinjected from the chaotic to laminar region. Though it works fine in some model systems, there exist a number of so-called pathological cases characterized by a significant deviation of main characteristics from the values predicted on the basis of the uniform distribution. Recently, we reported on how the reinjection probability density (RPD) can be generalized. Here, we extend this methodology and apply it to different dynamical systems exhibiting anomalous type-II and type-III intermittencies. Estimation of the universal RPD is based on fitting a linear function to experimental data and requires no a priori knowledge on the dynamical model behind. We provide special fitting procedure that enables robust estimation of the RPD from relatively short data sets (dozens of points). Thus, the method is applicable for a wide variety of data sets including numerical simulations and real-life experiments. Estimated RPD enables analytic evaluation of the length of the laminar phase of intermittent behaviors. We show that the method copes well with dynamical systems exhibiting significantly different statistics reported in the literature. We also derive and classify characteristic relations between the mean laminar length and main controlling parameter in perfect agreement with data provided by numerical simulations

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En esta tesis se aborda el estudio del proceso de isomerización del sistema molecular LiNC/LiCN tanto aislado como en presencia de un pulso láser aplicando la teoría del estado de transición (TST). Esta teoría tiene como pilar fundamental el hecho de que el conocimiento de la dinámica en las proximidades de un punto de silla de la superficie de energía potencial permite determinar los parámetros cinéticos de la reacción objeto de estudio. Históricamente, existen dos formulaciones de la teoría del estado de transición, la versión termodinámica de Eyring (Eyr38) y la visión dinámica de Wigner (Wig38). Ésta última ha sufrido recientemente un amplio desarrollo, paralelo a los avances en sistemas dinámicos que ha dado lugar a una formulación geométrica en el espacio de fases que sirve como base al trabajo desarrollado en esta tesis. Nos hemos centrado en abordar el problema desde una visión fundamentalmente práctica, ya que la teoría del estado de transición presenta una desventaja: su elevado coste computacional y de tiempo de cálculo. Dos han sido los principales objetivos de este trabajo. El primero de ellos ha sido sentar las bases teóricas y computacionales de un algoritmo eficiente que permita obtener las magnitudes fundamentales de la TST. Así, hemos adaptado con éxito un algoritmo computacional desarrollado en el ámbito de la mecánica celeste (Jor99), obteniendo un método rápido y eficiente para la obtención de los objetos geométricos que rigen la dinámica en el espacio de fases y que ha permitido calcular magnitudes cinéticas tales como el flujo reactivo, la densidad de estados de reactivos y productos y en última instancia la constante de velocidad. Dichos cálculos han sido comparados con resultados estadísticos (presentados en (Mül07)) lo cual nos ha permitido demostrar la eficacia del método empleado. El segundo objetivo de esta tesis, ha sido la evaluación de la influencia de los parámetros de un pulso electromagnético sobre la dinámica de reacción. Para ello se ha generalizado la metodología de obtención de la forma normal del hamiltoniano cuando el sistema químico es alterado mediante una perturbación temporal periódica. En este caso el punto fijo inestable en cuya vecindad se calculan los objetos geométricos de interés para la aplicación de la TST, se transforma en una órbita periódica del mismo periodo que la perturbación. Esto ha permitido la simulación de la reactividad en presencia de un pulso láser. Conocer el efecto de esta perturbación posibilita el control de la reactividad química. Además de obtener los objetos geométricos que rigen la dinámica en una cierta vecindad de la órbita periódica y que son la clave de la TST, se ha estudiado el efecto de los parámetros del pulso sobre la reactividad en el espacio de fases global así como sobre el flujo reactivo que atraviesa la superficie divisoria que separa reactivos de productos. Así, se ha puesto de manifiesto, que la amplitud del pulso es el parámetro más influyente sobre la reactividad química, pudiendo producir la aparición de flujos reactivos a energías inferiores a las de aparición del sistema aislado y el aumento del flujo reactivo a valores constantes de energía inicial. ABSTRACT We have studied the isomerization reaction LiNC/LiCN isolated and perturbed by a laser pulse. Transition State theory (TST) is the main tool we have used. The basis of this theory is knowing the dynamics close to a fixed point of the potential energy surface. It is possible to calculate kinetic magnitudes by knowing the dynamics in a neighbourhood of the fixed point. TST was first formulated in the 30's and there were 2 points of view, one thermodynamical by Eyring (Eyr38) and another dynamical one by Wigner (Wig38). The latter one has grown lately due to the growth of the dynamical systems leading to a geometrical view of the TST. This is the basis of the work shown in this thesis. As the TST has one main handicap: the high computational cost, one of the main goals of this work is to find an efficient method. We have adapted a methodology developed in the field of celestial mechanics (Jor99). The result: an efficient, fast and accurate algorithm that allows us to obtain the geometric objects that lead the dynamics close to the fixed point. Flux across the dividing surface, density of states and reaction rate coefficient have been calculated and compared with previous statistical results, (Mül07), leading to the conclusion that the method is accurate and good enough. We have widen the methodology to include a time dependent perturbation. If the perturbation is periodic in time, the fixed point becomes a periodic orbit whose period is the same as the period of the perturbation. This way we have been able to simulate the isomerization reaction when the system has been perturbed by a laser pulse. By knowing the effect of that perturbation we will be able to control the chemical reactivity. We have also studied the effect of the parameters on the global phase space dynamics and on the flux across the dividing surface. It has been prove that amplitude is the most influent parameter on the reaction dynamics. Increasing amplitude leads to greater fluxes and to some flux at energies it would not if the systems would not have been perturbed.

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Los conjuntos bacterianos son sistemas dinámicos difíciles de modelar debido a que las bacterias colaboran e intercambian información entre sí. Estos microorganismos procariotas pueden tomar decisiones por mayoría e intercambiar información genética importante que, por ejemplo, las haga resistentes a un antibiótico. El proceso de conjugación consiste en el intercambio de un plásmido de una bacteria con otra, permitiendo así que se transfieran propiedades. Estudios recientes han demostrado que estos plásmidos pueden ser reprogramados artificialmente para que la bacteria que lo contenga realice una función específica [1]. Entre la multitud de aplicaciones que supone esta idea, el proyecto europeo PLASWIRES está intentando demostrar que es posible usar organismos vivos como computadores distribuidos en paralelo y plásmidos como conexión entre ellos mediante conjugación. Por tanto, mediante una correcta programación de un plásmido, se puede conseguir, por ejemplo, hacer que una colonia de bacterias haga la función de un antibiótico o detecte otros plásmidos peligrosos en bacterias virulentas. El proceso experimental para demostrar esta idea puede llegar a ser algo lento y tedioso, por lo que es necesario el uso de simuladores que predigan su comportamiento. Debido a que el proyecto PLASWIRES se basa en la conjugación bacteriana, surge la necesidad de un simulador que reproduzca esta operación. El presente trabajo surge debido a la deficiencia del simulador GRO para reproducir la conjugación. En este documento se detallan las modificaciones necesarias para que GRO pueda representar este proceso, así como analizar los datos obtenidos e intentar ajustar el modelo a los datos obtenidos por el Instituto de Biomedicina y Biotecnología de Cantabria (IBBTEC). ---ABSTRACT---Bacterial colonies are dynamical systems difficult to model because bacteria collaborate and exchange information with each other. These prokaryotic organisms can make decisions by majority and exchange important genetic information, for example, make them resistant to an antibiotic. The conjugation process is the exchange of a plasmid from one bacterium to another, allowing both to have the same properties. Recent studies have shown that these plasmids can be artificially reprogrammed to make the bacteria that contain it to perform a specific function [1]. Among the multitude of applications involved in this idea, the European project PLASWIRES is attempting to prove that it is possible to use living organisms as parallel and distributed computers with plasmids acting as connectors between them through conjugation. Thus, by properly programming a plasmid, you can get a colony of bacteria that work as an antibiotic or detect hazardous plasmids in virulent bacteria. The experimental process to prove this idea can be slow and tedious, so the use of simulators to predict their behavior is required. Since PLASWIRES project is based on bacterial conjugation, a simulator that can reproduce this operation is required. This work arises due to the absence of the conjugation process in the simulator GRO. This document details the changes made to GRO to represent this process, analyze the data and try to adjust the model to the data obtained by the Institute of Biomedicine and Biotechnology of Cantabria ( IBBTEC ). This project has two main objectives, the first is to add the functionality of intercellular communication by conjugation to the simulator GRO, and the second is to use the experimental data obtained by the IBBTEC. To do this, the following points should be followed: • Study of conjugation biology as a mechanism of intercellular communication. • Design and implementation of the algorithm that simulates conjugation. • Experimental validation and model adjust to the experimental data on rates of conjugation and bacterial growth.

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Si no tenemos en cuenta posibles procesos subyacentes con significado físico, químico, económico, etc., podemos considerar una serie temporal como un mero conjunto ordenado de valores y jugar con él algún inocente juego matemático como transformar dicho conjunto en otro objeto con la ayuda de una operación matemática para ver qué sucede: qué propiedades del conjunto original se conservan, cuáles se transforman y cómo, qué podemos decir de alguna de las dos representaciones matemáticas del objeto con sólo atender a la otra... Este ejercicio sería de cierto interés matemático por sí solo. Ocurre, además, que las series temporales son un método universal de extraer información de sistemas dinámicos en cualquier campo de la ciencia. Esto hace ganar un inesperado interés práctico al juego matemático anteriormente descrito, ya que abre la posibilidad de analizar las series temporales (vistas ahora como evolución temporal de procesos dinámicos) desde una nueva perspectiva. Hemos para esto de asumir la hipótesis de que la información codificada en la serie original se conserva de algún modo en la transformación (al menos una parte de ella). El interés resulta completo cuando la nueva representación del objeto pertencece a un campo de la matemáticas relativamente maduro, en el cual la información codificada en dicha representación puede ser descodificada y procesada de manera efectiva. ABSTRACT Disregarding any underlying process (and therefore any physical, chemical, economical or whichever meaning of its mere numeric values), we can consider a time series just as an ordered set of values and play the naive mathematical game of turning this set into a different mathematical object with the aids of an abstract mapping, and see what happens: which properties of the original set are conserved, which are transformed and how, what can we say about one of the mathematical representations just by looking at the other... This exercise is of mathematical interest by itself. In addition, it turns out that time series or signals is a universal method of extracting information from dynamical systems in any field of science. Therefore, the preceding mathematical game gains some unexpected practical interest as it opens the possibility of analyzing a time series (i.e. the outcome of a dynamical process) from an alternative angle. Of course, the information stored in the original time series should be somehow conserved in the mapping. The motivation is completed when the new representation belongs to a relatively mature mathematical field, where information encoded in such a representation can be effectively disentangled and processed. This is, in a nutshell, a first motivation to map time series into networks.

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We characterize the chaos in a fractional Duffing’s equation computing the Lyapunov exponents and the dimension of the strange attractor in the effective phase space of the system. We develop a specific analytical method to estimate all Lyapunov exponents and check the results with the fiduciary orbit technique and a time series estimation method.

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El cerebro humano es probablemente uno de los sistemas más complejos a los que nos enfrentamos en la actualidad, si bien es también uno de los más fascinantes. Sin embargo, la compresión de cómo el cerebro organiza su actividad para llevar a cabo tareas complejas es un problema plagado de restos y obstáculos. En sus inicios la neuroimagen y la electrofisiología tenían como objetivo la identificación de regiones asociadas a activaciones relacionadas con tareas especificas, o con patrones locales que variaban en el tiempo dada cierta actividad. Sin embargo, actualmente existe un consenso acerca de que la actividad cerebral tiene un carácter temporal multiescala y espacialmente extendido, lo que lleva a considerar el cerebro como una gran red de áreas cerebrales coordinadas, cuyas conexiones funcionales son continuamente creadas y destruidas. Hasta hace poco, el énfasis de los estudios de la actividad cerebral funcional se han centrado en la identidad de los nodos particulares que forman estas redes, y en la caracterización de métricas de conectividad entre ellos: la hipótesis subyacente es que cada nodo, que es una representación mas bien aproximada de una región cerebral dada, ofrece a una única contribución al total de la red. Por tanto, la neuroimagen funcional integra los dos ingredientes básicos de la neuropsicología: la localización de la función cognitiva en módulos cerebrales especializados y el rol de las fibras de conexión en la integración de dichos módulos. Sin embargo, recientemente, la estructura y la función cerebral han empezado a ser investigadas mediante la Ciencia de la Redes, una interpretación mecánico-estadística de una antigua rama de las matemáticas: La teoría de grafos. La Ciencia de las Redes permite dotar a las redes funcionales de una gran cantidad de propiedades cuantitativas (robustez, centralidad, eficiencia, ...), y así enriquecer el conjunto de elementos que describen objetivamente la estructura y la función cerebral a disposición de los neurocientíficos. La conexión entre la Ciencia de las Redes y la Neurociencia ha aportado nuevos puntos de vista en la comprensión de la intrincada anatomía del cerebro, y de cómo las patrones de actividad cerebral se pueden sincronizar para generar las denominadas redes funcionales cerebrales, el principal objeto de estudio de esta Tesis Doctoral. Dentro de este contexto, la complejidad emerge como el puente entre las propiedades topológicas y dinámicas de los sistemas biológicos y, específicamente, en la relación entre la organización y la dinámica de las redes funcionales cerebrales. Esta Tesis Doctoral es, en términos generales, un estudio de cómo la actividad cerebral puede ser entendida como el resultado de una red de un sistema dinámico íntimamente relacionado con los procesos que ocurren en el cerebro. Con este fin, he realizado cinco estudios que tienen en cuenta ambos aspectos de dichas redes funcionales: el topológico y el dinámico. De esta manera, la Tesis está dividida en tres grandes partes: Introducción, Resultados y Discusión. En la primera parte, que comprende los Capítulos 1, 2 y 3, se hace un resumen de los conceptos más importantes de la Ciencia de las Redes relacionados al análisis de imágenes cerebrales. Concretamente, el Capitulo 1 está dedicado a introducir al lector en el mundo de la complejidad, en especial, a la complejidad topológica y dinámica de sistemas acoplados en red. El Capítulo 2 tiene como objetivo desarrollar los fundamentos biológicos, estructurales y funcionales del cerebro, cuando éste es interpretado como una red compleja. En el Capítulo 3, se resumen los objetivos esenciales y tareas que serán desarrolladas a lo largo de la segunda parte de la Tesis. La segunda parte es el núcleo de la Tesis, ya que contiene los resultados obtenidos a lo largo de los últimos cuatro años. Esta parte está dividida en cinco Capítulos, que contienen una versión detallada de las publicaciones llevadas a cabo durante esta Tesis. El Capítulo 4 está relacionado con la topología de las redes funcionales y, específicamente, con la detección y cuantificación de los nodos mas importantes: aquellos denominados “hubs” de la red. En el Capítulo 5 se muestra como las redes funcionales cerebrales pueden ser vistas no como una única red, sino más bien como una red-de-redes donde sus componentes tienen que coexistir en una situación de balance funcional. De esta forma, se investiga cómo los hemisferios cerebrales compiten para adquirir centralidad en la red-de-redes, y cómo esta interacción se mantiene (o no) cuando se introducen fallos deliberadamente en la red funcional. El Capítulo 6 va un paso mas allá al considerar las redes funcionales como sistemas vivos. En este Capítulo se muestra cómo al analizar la evolución de la topología de las redes, en vez de tratarlas como si estas fueran un sistema estático, podemos caracterizar mejor su estructura. Este hecho es especialmente relevante cuando se quiere tratar de encontrar diferencias entre grupos que desempeñan una tarea de memoria, en la que las redes funcionales tienen fuertes fluctuaciones. En el Capítulo 7 defino cómo crear redes parenclíticas a partir de bases de datos de actividad cerebral. Este nuevo tipo de redes, recientemente introducido para estudiar las anormalidades entre grupos de control y grupos anómalos, no ha sido implementado nunca en datos cerebrales y, en este Capítulo explico cómo hacerlo cuando se quiere evaluar la consistencia de la dinámica cerebral. Para concluir esta parte de la Tesis, el Capítulo 8 se centra en la relación entre las propiedades topológicas de los nodos dentro de una red y sus características dinámicas. Como mostraré más adelante, existe una relación entre ellas que revela que la posición de un nodo dentro una red está íntimamente correlacionada con sus propiedades dinámicas. Finalmente, la última parte de esta Tesis Doctoral está compuesta únicamente por el Capítulo 9, el cual contiene las conclusiones y perspectivas futuras que pueden surgir de los trabajos expuestos. En vista de todo lo anterior, espero que esta Tesis aporte una perspectiva complementaria sobre uno de los más extraordinarios sistemas complejos frente a los que nos encontramos: El cerebro humano. ABSTRACT The human brain is probably one of the most complex systems we are facing, thus being a timely and fascinating object of study. Characterizing how the brain organizes its activity to carry out complex tasks is highly non-trivial. While early neuroimaging and electrophysiological studies typically aimed at identifying patches of task-specific activations or local time-varying patterns of activity, there has now been consensus that task-related brain activity has a temporally multiscale, spatially extended character, as networks of coordinated brain areas are continuously formed and destroyed. Up until recently, though, the emphasis of functional brain activity studies has been on the identity of the particular nodes forming these networks, and on the characterization of connectivity metrics between them, the underlying covert hypothesis being that each node, constituting a coarse-grained representation of a given brain region, provides a unique contribution to the whole. Thus, functional neuroimaging initially integrated the two basic ingredients of early neuropsychology: localization of cognitive function into specialized brain modules and the role of connection fibres in the integration of various modules. Lately, brain structure and function have started being investigated using Network Science, a statistical mechanics understanding of an old branch of pure mathematics: graph theory. Network Science allows endowing networks with a great number of quantitative properties, thus vastly enriching the set of objective descriptors of brain structure and function at neuroscientists’ disposal. The link between Network Science and Neuroscience has shed light about how the entangled anatomy of the brain is, and how cortical activations may synchronize to generate the so-called functional brain networks, the principal object under study along this PhD Thesis. Within this context, complexity appears to be the bridge between the topological and dynamical properties of biological systems and, more specifically, the interplay between the organization and dynamics of functional brain networks. This PhD Thesis is, in general terms, a study of how cortical activations can be understood as the output of a network of dynamical systems that are intimately related with the processes occurring in the brain. In order to do that, I performed five studies that encompass both the topological and the dynamical aspects of such functional brain networks. In this way, the Thesis is divided into three major parts: Introduction, Results and Discussion. In the first part, comprising Chapters 1, 2 and 3, I make an overview of the main concepts of Network Science related to the analysis of brain imaging. More specifically, Chapter 1 is devoted to introducing the reader to the world of complexity, specially to the topological and dynamical complexity of networked systems. Chapter 2 aims to develop the biological, topological and functional fundamentals of the brain when it is seen as a complex network. Next, Chapter 3 summarizes the main objectives and tasks that will be developed along the forthcoming Chapters. The second part of the Thesis is, in turn, its core, since it contains the results obtained along these last four years. This part is divided into five Chapters, containing a detailed version of the publications carried out during the Thesis. Chapter 4 is related to the topology of functional networks and, more specifically, to the detection and quantification of the leading nodes of the network: the hubs. In Chapter 5 I will show that functional brain networks can be viewed not as a single network, but as a network-of-networks, where its components have to co-exist in a trade-off situation. In this way, I investigate how the brain hemispheres compete for acquiring the centrality of the network-of-networks and how this interplay is maintained (or not) when failures are introduced in the functional network. Chapter 6 goes one step beyond by considering functional networks as living systems. In this Chapter I show how analyzing the evolution of the network topology instead of treating it as a static system allows to better characterize functional networks. This fact is especially relevant when trying to find differences between groups performing certain memory tasks, where functional networks have strong fluctuations. In Chapter 7 I define how to create parenclitic networks from brain imaging datasets. This new kind of networks, recently introduced to study abnormalities between control and anomalous groups, have not been implemented with brain datasets and I explain in this Chapter how to do it when evaluating the consistency of brain dynamics. To conclude with this part of the Thesis, Chapter 8 is devoted to the interplay between the topological properties of the nodes within a network and their dynamical features. As I will show, there is an interplay between them which reveals that the position of a node in a network is intimately related with its dynamical properties. Finally, the last part of this PhD Thesis is composed only by Chapter 9, which contains the conclusions and future perspectives that may arise from the exposed results. In view of all, I hope that reading this Thesis will give a complementary perspective of one of the most extraordinary complex systems: The human brain.

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Most large dynamical systems are thought to have ergodic dynamics, whereas small systems may not have free interchange of energy between degrees of freedom. This assumption is made in many areas of chemistry and physics, ranging from nuclei to reacting molecules and on to quantum dots. We examine the transition to facile vibrational energy flow in a large set of organic molecules as molecular size is increased. Both analytical and computational results based on local random matrix models describe the transition to unrestricted vibrational energy flow in these molecules. In particular, the models connect the number of states participating in intramolecular energy flow to simple molecular properties such as the molecular size and the distribution of vibrational frequencies. The transition itself is governed by a local anharmonic coupling strength and a local state density. The theoretical results for the transition characteristics compare well with those implied by experimental measurements using IR fluorescence spectroscopy of dilution factors reported by Stewart and McDonald [Stewart, G. M. & McDonald, J. D. (1983) J. Chem. Phys. 78, 3907–3915].

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Complexity originates from the tendency of large dynamical systems to organize themselves into a critical state, with avalanches or "punctuations" of all sizes. In the critical state, events which would otherwise be uncoupled become correlated. The apparent, historical contingency in many sciences, including geology, biology, and economics, finds a natural interpretation as a self-organized critical phenomenon. These ideas are discussed in the context of simple mathematical models of sandpiles and biological evolution. Insights are gained not only from numerical simulations but also from rigorous mathematical analysis.

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Mapas simpléticos têm sido amplamente utilizados para modelar o transporte caótico em plasmas e fluidos. Neste trabalho, propomos três tipos de mapas simpléticos que descrevem o movimento de deriva elétrica em plasmas magnetizados. Efeitos de raio de Larmor finito são incluídos em cada um dos mapas. No limite do raio de Larmor tendendo a zero, o mapa com frequência monotônica se reduz ao mapa de Chirikov-Taylor, e, nos casos com frequência não-monotônica, os mapas se reduzem ao mapa padrão não-twist. Mostramos como o raio de Larmor finito pode levar à supressão de caos, modificar a topologia do espaço de fases e a robustez de barreiras de transporte. Um método baseado na contagem dos tempos de recorrência é proposto para analisar a influência do raio de Larmor sobre os parâmetros críticos que definem a quebra de barreiras de transporte. Também estudamos um modelo para um sistema de partículas onde a deriva elétrica é descrita pelo mapa de frequência monotônica, e o raio de Larmor é uma variável aleatória que assume valores específicos para cada partícula do sistema. A função densidade de probabilidade para o raio de Larmor é obtida a partir da distribuição de Maxwell-Boltzmann, que caracteriza plasmas na condição de equilíbrio térmico. Um importante parâmetro neste modelo é a variável aleatória gama, definida pelo valor da função de Bessel de ordem zero avaliada no raio de Larmor da partícula. Resultados analíticos e numéricos descrevendo as principais propriedades estatísticas do parâmetro gama são apresentados. Tais resultados são então aplicados no estudo de duas medidas de transporte: a taxa de escape e a taxa de aprisionamento por ilhas de período um.

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Author: Jeanice Kerr Swift Title: REALIZING SUSTAINED SCHOOL IMPROVEMENT Advisor: Dr. Kent Seidel and Dr. Linda Brookhart Degree Date: June, 2011 Developing effective methods for improving America's schools is dependent upon coordinated work of practitioners and researchers. School improvement proves a complicated, confusing and most often troubled process; one characterized by the unprecedented challenges of dramatic societal shift, increasing levels of student need, and ongoing involvement from political and governmental influences. The drive to discover better ways to consistently improve schools is fueled by urgency for dramatic results. This research examines both the macro and the micro levels of the school improvement process and illuminates the need for an intentional new way of thinking and leading. At the macro level, the study examined the need for implementing a systems approach to improve America's schools. The study explored a single school's improvement journey. This work aligned individual and group perceptions of staff members alongside student achievement outcome data framed against the findings in the literature. The study rendered themes from within the reflected experiences of participant educators; the work pointed to the need for an improved social technology, the importance of teams, and shared leadership in the orchestrating of successful school improvement processes, particularly the essential roles of collective listening, learning, and leading to realize transformed outcomes for schools.

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"U.S. Atomic Energy Commission Contract AT(29-1)-1106."

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A method is proposed for determining the optimal placement and controller design for multiple distributed actuators to reduce the vibrations of flexible structures. In particular, application of piezoceramic patches to a horizontally-slewing single-link flexible manipulator modeled using the assumed modes method is investigated. The optimization method uses simulated annealing and allows placement of any number of distributed actuators of unequal length, although piezoceramics of fixed equal lengths are used in the example. It also designs an linear-quadratic-regulator controller as part of the optimization procedure. The measures of performance used in the investigation to determine optimality are the total mass of the system and the time integral of the absolute value of the hub and tip position error. This study also varies the relative weightings for each of these performance measures to observe the effects on the controller designs and piezoceramic patch positions in the optimized solutions.

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Adaptive management is the pathway to effective conservation, use and management of Australia’s coastal catchments and waterways. While the concepts of adaptive management are not new, applications involving both assessment and management responses are indeed limited at the national and regional scales. This paper outlines the components of a systematic framework for linking scientific knowledge, existing tools, planning approaches and participatory processes to achieve healthy regional partnerships between community, industry, government agencies and science providers to overcome institutional barriers and uncoordinated monitoring. The framework developed by the Coastal CRC (www.coastal.crc.org.au/amf/amf_index.htm) is hierarchical in the way it displays information to allow associated frameworks to be integrated, and represents a construct in which processes, information, decision tools and outcomes are brought together in a structured and transparent way for adaptive catchment and coastal management. This paper proposes how an adaptive management approach could be used to benefit the implementation of the Reef Water Quality Protection Plan (RWQPP).

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An algorithm for suppressing the chaotic oscillations in non-linear dynamical systems with singular Jacobian matrices is developed using a linear feedback control law based upon the Lyapunov-Krasovskii (LK) method. It appears that the LK method can serve effectively as a generalised method for the suppression of chaotic oscillations for a wide range of systems. Based on this method, the resulting conditions for undisturbed motions to be locally or globally stable are sufficient and conservative. The generalized Lorenz system and disturbed gyrostat equations are exemplified for the validation of the proposed feedback control rule. (c) 2005 Elsevier Ltd. All rights reserved.