871 resultados para strongly correlated systems


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Dissolved organic matter (DOM) dynamics during storm events has received considerable attention in forested watersheds, but the extent to which storms impart rapid changes in DOM concentration and composition in highly disturbed agricultural watersheds remains poorly understood. In this study, we used identical in situ optical sensors for DOM fluorescence (FDOM) with and without filtration to continuously evaluate surface water DOM dynamics in a 415 km(2) agricultural watershed over a 4 week period containing a short-duration rainfall event. Peak turbidity preceded peak discharge by 4 h and increased by over 2 orders of magnitude, while the peak filtered FDOM lagged behind peak turbidity by 15 h. FDOM values reported using the filtered in situ fluorometer increased nearly fourfold and were highly correlated with dissolved organic carbon (DOC) concentrations (r(2) = 0.97), providing a highly resolved proxy for DOC throughout the study period. Discrete optical properties including specific UV absorbance (SUVA(254)), spectral slope (S(290-350)), and fluorescence index (FI) were also strongly correlated with in situ FDOM and indicate a shift toward aromatic, high molecular weight DOM from terrestrially derived sources during the storm. The lag of the peak in FDOM behind peak discharge presumably reflects the draining of watershed soils from natural and agricultural landscapes. Field and experimental evidence showed that unfiltered FDOM measurements underestimated filtered FDOM concentrations by up to similar to 60% at particle concentrations typical of many riverine systems during hydrologic events. Together, laboratory and in situ data provide insights into the timing and magnitude of changes in DOM quantity and quality during storm events in an agricultural watershed, and indicate the need for sample filtration in systems with moderate to high suspended sediment loads.

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Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

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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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The price formation of the Iberian Energy Derivatives Market-the power futures market-starting in July 2006, is assessed until November 2011, through the evolution of the difference between forward and spot prices in the delivery period (“ex-post forward risk premium”) and the comparison with the forward generation costs from natural gas (“clean spark spread”). The premium tends to be positive in all existing mechanisms (futures, Over-the-Counter and auctions for catering part of the last resort supplies). Since year 2011, the values are smaller due to regulatorily recognized prices for coal power plants. The power futures are strongly correlated with European gas prices. The spreads built with prompt contracts tend also to be positive. The biggest ones are for the month contract, followed by the quarter contract and then by the year contract. Therefore, gas fired generation companies can maximize profits trading with contracts of shorter maturity.

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I. GENERALIDADES 1.1. Introducción Entre los diversos tipos de perturbaciones eléctricas, los huecos de tensión son considerados el problema de calidad de suministro más frecuente en los sistemas eléctricos. Este fenómeno es originado por un aumento extremo de la corriente en el sistema, causado principalmente por cortocircuitos o maniobras inadecuadas en la red. Este tipo de perturbación eléctrica está caracterizado básicamente por dos parámetros: tensión residual y duración. Típicamente, se considera que el hueco se produce cuando la tensión residual alcanza en alguna de las fases un valor entre 0.01 a 0.9 pu y tiene una duración de hasta 60 segundos. Para un usuario final, el efecto más relevante de un hueco de tensión es la interrupción o alteración de la operación de sus equipos, siendo los dispositivos de naturaleza electrónica los principalmente afectados (p. ej. ordenador, variador de velocidad, autómata programable, relé, etc.). Debido al auge tecnológico de las últimas décadas y a la búsqueda constante de automatización de los procesos productivos, el uso de componentes electrónicos resulta indispensable en la actualidad. Este hecho, lleva a que los efectos de los huecos de tensión sean más evidentes para el usuario final, provocando que su nivel de exigencia de la calidad de energía suministrada sea cada vez mayor. De forma general, el estudio de los huecos de tensión suele ser abordado bajo dos enfoques: en la carga o en la red. Desde el punto de vista de la carga, se requiere conocer las características de sensibilidad de los equipos para modelar su respuesta ante variaciones súbitas de la tensión del suministro eléctrico. Desde la perspectiva de la red, se busca estimar u obtener información adecuada que permita caracterizar su comportamiento en términos de huecos de tensión. En esta tesis, el trabajo presentado se encuadra en el segundo aspecto, es decir, en el modelado y estimación de la respuesta de un sistema eléctrico de potencia ante los huecos de tensión. 1.2. Planteamiento del problema A pesar de que los huecos de tensión son el problema de calidad de suministro más frecuente en las redes, hasta la actualidad resulta complejo poder analizar de forma adecuada este tipo de perturbación para muchas compañías del sector eléctrico. Entre las razones más comunes se tienen: - El tiempo de monitorización puede llegar a ser de varios años para conseguir una muestra de registros de huecos estadísticamente válida. - La limitación de recursos económicos para la adquisición e instalación de equipos de monitorización de huecos. - El elevado coste operativo que implica el análisis de los datos de los medidores de huecos de tensión instalados. - La restricción que tienen los datos de calidad de energía de las compañías eléctricas. Es decir, ante la carencia de datos que permitan analizar con mayor detalle los huecos de tensión, es de interés de las compañías eléctricas y la academia poder crear métodos fiables que permitan profundizar en el estudio, estimación y supervisión de este fenómeno electromagnético. Los huecos de tensión, al ser principalmente originados por eventos fortuitos como los cortocircuitos, son el resultado de diversas variables exógenas como: (i) la ubicación de la falta, (ii) la impedancia del material de contacto, (iii) el tipo de fallo, (iv) la localización del fallo en la red, (v) la duración del evento, etc. Es decir, para plantear de forma adecuada cualquier modelo teórico sobre los huecos de tensión, se requeriría representar esta incertidumbre combinada de las variables para proveer métodos realistas y, por ende, fiables para los usuarios. 1.3. Objetivo La presente tesis ha tenido como objetivo el desarrollo diversos métodos estocásticos para el estudio, estimación y supervisión de los huecos de tensión en los sistemas eléctricos de potencia. De forma específica, se ha profundizado en los siguientes ámbitos: - En el modelado realista de las variables que influyen en la caracterización de los huecos. Esto es, en esta Tesis se ha propuesto un método que permite representar de forma verosímil su cuantificación y aleatoriedad en el tiempo empleando distribuciones de probabilidad paramétricas. A partir de ello, se ha creado una herramienta informática que permite estimar la severidad de los huecos de tensión en un sistema eléctrico genérico. - Se ha analizado la influencia la influencia de las variables de entrada en la estimación de los huecos de tensión. En este caso, el estudio se ha enfocado en las variables de mayor divergencia en su caracterización de las propuestas existentes. - Se ha desarrollado un método que permite estima el número de huecos de tensión de una zona sin monitorización a través de la información de un conjunto limitado de medidas de un sistema eléctrico. Para ello, se aplican los principios de la estadística Bayesiana, estimando el número de huecos de tensión más probable de un emplazamiento basándose en los registros de huecos de otros nudos de la red. - Plantear una estrategia para optimizar la monitorización de los huecos de tensión en un sistema eléctrico. Es decir, garantizar una supervisión del sistema a través de un número de medidores menor que el número de nudos de la red. II. ESTRUCTURA DE LA TESIS Para plantear las propuestas anteriormente indicadas, la presente Tesis se ha estructurado en seis capítulos. A continuación, se describen brevemente los mismos. A manera de capítulo introductorio, en el capítulo 1, se realiza una descripción del planteamiento y estructura de la presente tesis. Esto es, se da una visión amplia de la problemática a tratar, además de describir el alcance de cada capítulo de la misma. En el capítulo 2, se presenta una breve descripción de los fundamentos y conceptos generales de los huecos de tensión. Los mismos, buscan brindar al lector de una mejor comprensión de los términos e indicadores más empleados en el análisis de severidad de los huecos de tensión en las redes eléctricas. Asimismo, a manera de antecedente, se presenta un resumen de las principales características de las técnicas o métodos existentes aplicados en la predicción y monitorización óptima de los huecos de tensión. En el capítulo 3, se busca fundamentalmente conocer la importancia de las variables que determinen la frecuencia o severidad de los huecos de tensión. Para ello, se ha implementado una herramienta de estimación de huecos de tensión que, a través de un conjunto predeterminado de experimentos mediante la técnica denominada Diseño de experimentos, analiza la importancia de la parametrización de las variables de entrada del modelo. Su análisis, es realizado mediante la técnica de análisis de la varianza (ANOVA), la cual permite establecer con rigor matemático si la caracterización de una determinada variable afecta o no la respuesta del sistema en términos de los huecos de tensión. En el capítulo 4, se propone una metodología que permite predecir la severidad de los huecos de tensión de todo el sistema a partir de los registros de huecos de un conjunto reducido de nudos de dicha red. Para ello, se emplea el teorema de probabilidad condicional de Bayes, el cual calcula las medidas más probables de todo el sistema a partir de la información proporcionada por los medidores de huecos instalados. Asimismo, en este capítulo se revela una importante propiedad de los huecos de tensión, como es la correlación del número de eventos de huecos de tensión en diversas zonas de las redes eléctricas. En el capítulo 5, se desarrollan dos métodos de localización óptima de medidores de huecos de tensión. El primero, que es una evolución metodológica del criterio de observabilidad; aportando en el realismo de la pseudo-monitorización de los huecos de tensión con la que se calcula el conjunto óptimo de medidores y, por ende, en la fiabilidad del método. Como una propuesta alternativa, se emplea la propiedad de correlación de los eventos de huecos de tensión de una red para plantear un método que permita establecer la severidad de los huecos de todo el sistema a partir de una monitorización parcial de dicha red. Finalmente, en el capítulo 6, se realiza una breve descripción de las principales aportaciones de los estudios realizados en esta tesis. Adicionalmente, se describen diversos temas a desarrollar en futuros trabajos. III. RESULTADOS En base a las pruebas realizadas en las tres redes planteadas; dos redes de prueba IEEE de 24 y 118 nudos (IEEE-24 e IEEE-118), además del sistema eléctrico de la República del Ecuador de 357 nudos (EC-357), se describen los siguientes puntos como las observaciones más relevantes: A. Estimación de huecos de tensión en ausencia de medidas: Se implementa un método estocástico de estimación de huecos de tensión denominado PEHT, el cual representa con mayor realismo la simulación de los eventos de huecos de un sistema a largo plazo. Esta primera propuesta de la tesis, es considerada como un paso clave para el desarrollo de futuros métodos del presente trabajo, ya que permite emular de forma fiable los registros de huecos de tensión a largo plazo en una red genérica. Entre las novedades más relevantes del mencionado Programa de Estimación de Huecos de Tensión (PEHT) se tienen: - Considerar el efecto combinado de cinco variables aleatorias de entrada para simular los eventos de huecos de tensión en una pseudo-monitorización a largo plazo. Las variables de entrada modeladas en la caracterización de los huecos de tensión en el PEHT son: (i) coeficiente de fallo, (ii) impedancia de fallo, (iii) tipo de fallo, (iv) localización del fallo y (v) duración. - El modelado estocástico de las variables de entrada impedancia de fallo y duración en la caracterización de los eventos de huecos de tensión. Para la parametrización de las variables mencionadas, se realizó un estudio detallado del comportamiento real de las mismas en los sistemas eléctricos. Asimismo, se define la función estadística que mejor representa la naturaleza aleatoria de cada variable. - Considerar como variables de salida del PEHT a indicadores de severidad de huecos de uso común en las normativas, como es el caso de los índices: SARFI-X, SARFI-Curve, etc. B. Análisis de sensibilidad de los huecos de tensión: Se presenta un estudio causa-efecto (análisis de sensibilidad) de las variables de entrada de mayor divergencia en su parametrización entre las referencias relacionadas a la estimación de los huecos de tensión en redes eléctricas. De forma específica, se profundiza en el estudio de la influencia de la parametrización de las variables coeficiente de fallo e impedancia de fallo en la predicción de los huecos de tensión. A continuación un resumen de las conclusiones más destacables: - La precisión de la variable de entrada coeficiente de fallo se muestra como un parámetro no influyente en la estimación del número de huecos de tensión (SARFI-90 y SARFI-70) a largo plazo. Es decir, no se requiere de una alta precisión del dato tasa de fallo de los elementos del sistema para obtener una adecuada estimación de los huecos de tensión. - La parametrización de la variable impedancia de fallo se muestra como un factor muy sensible en la estimación de la severidad de los huecos de tensión. Por ejemplo, al aumentar el valor medio de esta variable aleatoria, se disminuye considerablemente la severidad reportada de los huecos en la red. Por otra parte, al evaluar el parámetro desviación típica de la impedancia de fallo, se observa una relación directamente proporcional de este parámetro con la severidad de los huecos de tensión de la red. Esto es, al aumentar la desviación típica de la impedancia de fallo, se evidencia un aumento de la media y de la variación interanual de los eventos SARFI-90 y SARFI-70. - En base al análisis de sensibilidad desarrollado en la variable impedancia de fallo, se considera muy cuestionable la fiabilidad de los métodos de estimación de huecos de tensión que omiten su efecto en el modelo planteado. C. Estimación de huecos de tensión en base a la información de una monitorización parcial de la red: Se desarrolla un método que emplea los registros de una red parcialmente monitorizada para determinar la severidad de los huecos de todo el sistema eléctrico. A partir de los casos de estudio realizados, se observa que el método implementado (PEHT+MP) posee las siguientes características: - La metodología propuesta en el PEHT+MP combina la teoría clásica de cortocircuitos con diversas técnicas estadísticas para estimar, a partir de los datos de los medidores de huecos instalados, las medidas de huecos de los nudos sin monitorización de una red genérica. - El proceso de estimación de los huecos de tensión de la zona no monitorizada de la red se fundamenta en la aplicación del teorema de probabilidad condicional de Bayes. Es decir, en base a los datos observados (los registros de los nudos monitorizados), el PEHT+MP calcula de forma probabilística la severidad de los huecos de los nudos sin monitorización del sistema. Entre las partes claves del procedimiento propuesto se tienen los siguientes puntos: (i) la creación de una base de datos realista de huecos de tensión a través del Programa de Estimación de Huecos de Tensión (PEHT) propuesto en el capítulo anterior; y, (ii) el criterio de máxima verosimilitud empleado para estimar las medidas de huecos de los nudos sin monitorización de la red evaluada. - Las predicciones de medidas de huecos de tensión del PEHT+MP se ven potenciadas por la propiedad de correlación de los huecos de tensión en diversas zonas de un sistema eléctrico. Esta característica intrínseca de las redes eléctricas limita de forma significativa la respuesta de las zonas fuertemente correlacionadas del sistema ante un eventual hueco de tensión. Como el PEHT+MP está basado en principios probabilísticos, la reducción del rango de las posibles medidas de huecos se ve reflejado en una mejor predicción de las medidas de huecos de la zona no monitorizada. - Con los datos de un conjunto de medidores relativamente pequeño del sistema, es posible obtener estimaciones precisas (error nulo) de la severidad de los huecos de la zona sin monitorizar en las tres redes estudiadas. - El PEHT+MP se puede aplicar a diversos tipos de indicadores de severidad de los huecos de tensión, como es el caso de los índices: SARFI-X, SARFI-Curve, SEI, etc. D. Localización óptima de medidores de huecos de tensión: Se plantean dos métodos para ubicar de forma estratégica al sistema de monitorización de huecos en una red genérica. La primera propuesta, que es una evolución metodológica de la localización óptima de medidores de huecos basada en el criterio de observabilidad (LOM+OBS); y, como segunda propuesta, un método que determina la localización de los medidores de huecos según el criterio del área de correlación (LOM+COR). Cada método de localización óptima de medidores propuesto tiene un objetivo concreto. En el caso del LOM+OBS, la finalidad del método es determinar el conjunto óptimo de medidores que permita registrar todos los fallos que originen huecos de tensión en la red. Por otro lado, en el método LOM+COR se persigue definir un sistema óptimo de medidores que, mediante la aplicación del PEHT+MP (implementado en el capítulo anterior), sea posible estimar de forma precisa las medidas de huecos de tensión de todo el sistema evaluado. A partir del desarrollo de los casos de estudio de los citados métodos de localización óptima de medidores en las tres redes planteadas, se describen a continuación las observaciones más relevantes: - Como la generación de pseudo-medidas de huecos de tensión de los métodos de localización óptima de medidores (LOM+OBS y LOM+COR) se obtienen mediante la aplicación del algoritmo PEHT, la formulación del criterio de optimización se realiza en base a una pseudo-monitorización realista, la cual considera la naturaleza aleatoria de los huecos de tensión a través de las cinco variables estocásticas modeladas en el PEHT. Esta característica de la base de datos de pseudo-medidas de huecos de los métodos LOM+OBS y LOM+COR brinda una mayor fiabilidad del conjunto óptimo de medidores calculado respecto a otros métodos similares en la bibliografía. - El conjunto óptimo de medidores se determina según la necesidad del operador de la red. Esto es, si el objetivo es registrar todos los fallos que originen huecos de tensión en el sistema, se emplea el criterio de observabilidad en la localización óptima de medidores de huecos. Por otra parte, si se plantea definir un sistema de monitorización que permita establecer la severidad de los huecos de tensión de todo el sistema en base a los datos de un conjunto reducido de medidores de huecos, el criterio de correlación resultaría el adecuado. De forma específica, en el caso del método LOM+OBS, basado en el criterio de observabilidad, se evidenciaron las siguientes propiedades en los casos de estudio realizados: - Al aumentar el tamaño de la red, se observa la tendencia de disminuir el porcentaje de nudos monitorizados de dicho sistema. Por ejemplo, para monitorizar los fallos que originan huecos en la red IEEE-24, se requiere monitorizar el 100\% de los nudos del sistema. En el caso de las redes IEEE-118 y EC-357, el método LOM+OBS determina que con la monitorización de un 89.5% y 65.3% del sistema, respectivamente, se cumpliría con el criterio de observabilidad del método. - El método LOM+OBS permite calcular la probabilidad de utilización del conjunto óptimo de medidores a largo plazo, estableciendo así un criterio de la relevancia que tiene cada medidor considerado como óptimo en la red. Con ello, se puede determinar el nivel de precisión u observabilidad (100%, 95%, etc.) con el cual se detectarían los fallos que generan huecos en la red estudiada. Esto es, al aumentar el nivel de precisión de detección de los fallos que originan huecos, se espera que aumente el número de medidores requeridos en el conjunto óptimo de medidores calculado. - El método LOM+OBS se evidencia como una técnica aplicable a todo tipo de sistema eléctrico (radial o mallado), el cual garantiza la detección de los fallos que originan huecos de tensión en un sistema según el nivel de observabilidad planteado. En el caso del método de localización óptima de medidores basado en el criterio del área de correlación (LOM+COR), las diversas pruebas realizadas evidenciaron las siguientes conclusiones: - El procedimiento del método LOM+COR combina los métodos de estimación de huecos de tensión de capítulos anteriores (PEHT y PEHT+MP) con técnicas de optimización lineal para definir la localización óptima de los medidores de huecos de tensión de una red. Esto es, se emplea el PEHT para generar los pseudo-registros de huecos de tensión, y, en base al criterio planteado de optimización (área de correlación), el LOM+COR formula y calcula analíticamente el conjunto óptimo de medidores de la red a largo plazo. A partir de la información registrada por este conjunto óptimo de medidores de huecos, se garantizaría una predicción precisa de la severidad de los huecos de tensión de todos los nudos del sistema con el PEHT+MP. - El método LOM+COR requiere un porcentaje relativamente reducido de nudos del sistema para cumplir con las condiciones de optimización establecidas en el criterio del área de correlación. Por ejemplo, en el caso del número total de huecos (SARFI-90) de las redes IEEE-24, IEEE-118 y EC-357, se calculó un conjunto óptimo de 9, 12 y 17 medidores de huecos, respectivamente. Es decir, solamente se requeriría monitorizar el 38\%, 10\% y 5\% de los sistemas indicados para supervisar los eventos SARFI-90 en toda la red. - El método LOM+COR se muestra como un procedimiento de optimización versátil, el cual permite reducir la dimensión del sistema de monitorización de huecos de redes eléctricas tanto radiales como malladas. Por sus características, este método de localización óptima permite emular una monitorización integral del sistema a través de los registros de un conjunto pequeño de monitores. Por ello, este nuevo método de optimización de medidores sería aplicable a operadores de redes que busquen disminuir los costes de instalación y operación del sistema de monitorización de los huecos de tensión. ABSTRACT I. GENERALITIES 1.1. Introduction Among the various types of electrical disturbances, voltage sags are considered the most common quality problem in power systems. This phenomenon is caused by an extreme increase of the current in the network, primarily caused by short-circuits or inadequate maneuvers in the system. This type of electrical disturbance is basically characterized by two parameters: residual voltage and duration. Typically, voltage sags occur when the residual voltage, in some phases, reaches a value between 0.01 to 0.9 pu and lasts up to 60 seconds. To an end user, the most important effect of a voltage sags is the interruption or alteration of their equipment operation, with electronic devices the most affected (e.g. computer, drive controller, PLC, relay, etc.). Due to the technology boom of recent decades and the constant search for automating production processes, the use of electronic components is essential today. This fact makes the effects of voltage sags more noticeable to the end user, causing the level of demand for a quality energy supply to be increased. In general, the study of voltage sags is usually approached from one of two aspects: the load or the network. From the point of view of the load, it is necessary to know the sensitivity characteristics of the equipment to model their response to sudden changes in power supply voltage. From the perspective of the network, the goal is to estimate or obtain adequate information to characterize the network behavior in terms of voltage sags. In this thesis, the work presented fits into the second aspect; that is, in the modeling and estimation of the response of a power system to voltage sag events. 1.2. Problem Statement Although voltage sags are the most frequent quality supply problem in electrical networks, thistype of disturbance remains complex and challenging to analyze properly. Among the most common reasons for this difficulty are: - The sag monitoring time, because it can take up to several years to get a statistically valid sample. - The limitation of funds for the acquisition and installation of sag monitoring equipment. - The high operating costs involved in the analysis of the voltage sag data from the installed monitors. - The restrictions that electrical companies have with the registered power quality data. That is, given the lack of data to further voltage sag analysis, it is of interest to electrical utilities and researchers to create reliable methods to deepen the study, estimation and monitoring of this electromagnetic phenomenon. Voltage sags, being mainly caused by random events such as short-circuits, are the result of various exogenous variables such as: (i) the number of faults of a system element, (ii) the impedance of the contact material, (iii) the fault type, (iv) the fault location, (v) the duration of the event, etc. That is, to properly raise any theoretical model of voltage sags, it is necessary to represent the combined uncertainty of variables to provide realistic methods that are reliable for users. 1.3. Objective This Thesis has been aimed at developing various stochastic methods for the study, estimation and monitoring of voltage sags in electrical power systems. Specifically, it has deepened the research in the following areas: - This research furthers knowledge in the realistic modeling of the variables that influence sag characterization. This thesis proposes a method to credibly represent the quantification and randomness of the sags in time by using parametric probability distributions. From this, a software tool was created to estimate the severity of voltage sags in a generic power system. - This research also analyzes the influence of the input variables in the estimation of voltage sags. In this case, the study has focused on the variables of greatest divergence in their characterization of the existing proposals. - A method was developed to estimate the number of voltage sags of an area without monitoring through the information of a limited set of sag monitors in an electrical system. To this end, the principles of Bayesian statistics are applied, estimating the number of sags most likely to happen in a system busbar based in records of other sag network busbars. - A strategy was developed to optimize the monitorization of voltage sags on a power system. Its purpose is to ensure the monitoring of the system through a number of monitors lower than the number of busbars of the network assessed. II. THESIS STRUCTURE To describe in detail the aforementioned proposals, this Thesis has been structured into six chapters. Below is are brief descriptions of them: As an introductory chapter, Chapter 1, provides a description of the approach and structure of this thesis. It presents a wide view of the problem to be treated, in addition to the description of the scope of each chapter. In Chapter 2, a brief description of the fundamental and general concepts of voltage sags is presented to provide to the reader a better understanding of the terms and indicators used in the severity analysis of voltage sags in power networks. Also, by way of background, a summary of the main features of existing techniques or methods used in the prediction and optimal monitoring of voltage sags is also presented. Chapter 3 essentially seeks to know the importance of the variables that determine the frequency or severity of voltage sags. To do this, a tool to estimate voltage sags is implemented that, through a predetermined set of experiments using the technique called Design of Experiments, discusses the importance of the parameters of the input variables of the model. Its analysis is interpreted by using the technique of analysis of variance (ANOVA), which provides mathematical rigor to establish whether the characterization of a particular variable affects the system response in terms of voltage sags or not. In Chapter 4, a methodology to predict the severity of voltage sags of an entire system through the sag logs of a reduced set of monitored busbars is proposed. For this, the Bayes conditional probability theorem is used, which calculates the most likely sag severity of the entire system from the information provided by the installed monitors. Also, in this chapter an important property of voltage sags is revealed, as is the correlation of the voltage sags events in several zones of a power system. In Chapter 5, two methods of optimal location of voltage sag monitors are developed. The first one is a methodological development of the observability criteria; it contributes to the realism of the sag pseudo-monitoring with which the optimal set of sag monitors is calculated and, therefore, to the reliability of the proposed method. As an alternative proposal, the correlation property of the sag events of a network is used to raise a method that establishes the sag severity of the entire system from a partial monitoring of the network. Finally, in Chapter 6, a brief description of the main contributions of the studies in this Thesis is detailed. Additionally, various themes to be developed in future works are described. III. RESULTS. Based on tests on the three networks presented, two IEEE test networks of 24 and 118 busbars (IEEE-24 and IEEE-118) and the electrical system of the Republic of Ecuador (EC-357), the following points present the most important observations: A. Estimation of voltage sags in the absence of measures: A stochastic estimation method of voltage sags, called PEHT, is implemented to represent with greater realism the long-term simulation of voltage sags events in a system. This first proposal of this thesis is considered a key step for the development of future methods of this work, as it emulates in a reliable manner the voltage sag long-term records in a generic network. Among the main innovations of this voltage sag estimation method are the following: - Consideration of the combined effect of five random input variables to simulate the events of voltage sags in long-term monitoring is included. The input variables modeled in the characterization of voltage sags on the PEHT are as follows: (i) fault coefficient, (ii) fault impedance, (iii) type of fault, (iv) location of the fault, and (v) fault duration. - Also included is the stochastic modeling of the input variables of fault impedance and duration in the characterization of the events of voltage sags. For the parameterization of these variables, a detailed study of the real behavior in power systems is developed. Also, the statistical function best suited to the random nature of each variable is defined. - Consideration of sag severity indicators used in standards as PEHT output variables, including such as indices as SARFI-X, SARFI-Curve, etc. B. Sensitivity analysis of voltage sags: A cause-effect study (sensitivity analysis) of the input variables of greatest divergence between reference parameterization related to the estimation of voltage sags in electrical networks is presented. Specifically, it delves into the study of the influence of the parameterization of the variables fault coefficient and fault impedance in the voltage sag estimation. Below is a summary of the most notable observations: - The accuracy of the input variable fault coefficient is shown as a non-influential parameter in the long-term estimation of the number of voltage sags (SARFI-90 and SARFI-70). That is, it does not require a high accuracy of the fault rate data of system elements for a proper voltage sag estimation. - The parameterization of the variable fault impedance is shown to be a very sensitive factor in the estimation of the voltage sag severity. For example, by increasing the average value of this random variable, the reported sag severity in the network significantly decreases. Moreover, in assessing the standard deviation of the fault impedance parameter, a direct relationship of this parameter with the voltage sag severity of the network is observed. That is, by increasing the fault impedance standard deviation, an increase of the average and the interannual variation of the SARFI-90 and SARFI-70 events is evidenced. - Based on the sensitivity analysis developed in the variable fault impedance, the omission of this variable in the voltage sag estimation would significantly call into question the reliability of the responses obtained. C. Voltage sag estimation from the information of a network partially monitored: A method that uses the voltage sag records of a partially monitored network for the sag estimation of all the power system is developed. From the case studies performed, it is observed that the method implemented (PEHT+MP) has the following characteristics: - The methodology proposed in the PEHT+MP combines the classical short-circuit theory with several statistical techniques to estimate, from data the of the installed sag meters, the sag measurements of unmonitored busbars of a generic power network. - The estimation process of voltage sags of the unmonitored zone of the network is based on the application of the conditional probability theorem of Bayes. That is, based on the observed data (monitored busbars records), the PEHT+MP calculates probabilistically the sag severity at unmonitored system busbars. Among the key parts of the proposed procedure are the following: (i) the creation of a realistic data base of voltage sags through of the sag estimation program (PEHT); and, (ii) the maximum likelihood criterion used to estimate the sag indices of system busbars without monitoring. - The voltage sag measurement estimations of PEHT+MP are potentiated by the correlation property of the sag events in power systems. This inherent characteristic of networks significantly limits the response of strongly correlated system zones to a possible voltage sag. As the PEHT+MP is based on probabilistic principles, a reduction of the range of possible sag measurements is reflected in a better sag estimation of the unmonitored area of the power system. - From the data of a set of monitors representing a relatively small portion of the system, to obtain accurate estimations (null error) of the sag severity zones without monitoring is feasible in the three networks studied. - The PEHT+MP can be applied to several types of sag indices, such as: SARFI-X, SARFI-Curve, SEI, etc. D. Optimal location of voltage sag monitors in power systems: Two methods for strategically locating the sag monitoring system are implemented for a generic network. The first proposal is a methodological development of the optimal location of sag monitors based on the observability criterion (LOM + OBS); the second proposal is a method that determines the sag monitor location according to the correlation area criterion (LOM+COR). Each proposed method of optimal location of sag monitors has a specific goal. In the case of LOM+OBS, the purpose of the method is to determine the optimal set of sag monitors to record all faults that originate voltage sags in the network. On the other hand, the LOM+COR method attempts to define the optimal location of sag monitors to estimate the sag indices in all the assessed network with the PEHT+MP application. From the development of the case studies of these methods of optimal location of sag monitors in the three networks raised, the most relevant observations are described below: - As the generation of voltage sag pseudo-measurements of the optimal location methods (LOM+OBS and LOM+COR) are obtained by applying the algorithm PEHT, the formulation of the optimization criterion is performed based on a realistic sag pseudo-monitoring, which considers the random nature of voltage sags through the five stochastic variables modeled in PEHT. This feature of the database of sag pseudo-measurements of the LOM+OBS and LOM+COR methods provides a greater reliability of the optimal set of monitors calculated when compared to similar methods in the bibliography. - The optimal set of sag monitors is determined by the network operator need. That is, if the goal is to record all faults that originate from voltage sags in the system, the observability criterion is used to determine the optimal location of sag monitors (LOM+OBS). Moreover, if the objective is to define a monitoring system that allows establishing the sag severity of the system from taken from information based on a limited set of sag monitors, the correlation area criterion would be appropriate (LOM+COR). Specifically, in the case of the LOM+OBS method (based on the observability criterion), the following properties were observed in the case studies: - By increasing the size of the network, there was observed a reduction in the percentage of monitored system busbars required. For example, to monitor all the faults which cause sags in the IEEE-24 network, then 100% of the system busbars are required for monitoring. In the case of the IEEE-118 and EC-357 networks, the method LOM+OBS determines that with monitoring 89.5 % and 65.3 % of the system, respectively, the observability criterion of the method would be fulfilled. - The LOM+OBS method calculates the probability of using the optimal set of sag monitors in the long term, establishing a relevance criterion of each sag monitor considered as optimal in the network. With this, the level of accuracy or observability (100%, 95%, etc.) can be determined, with which the faults that caused sags in the studied network are detected. That is, when the accuracy level for detecting faults that cause sags in the system is increased, a larger number of sag monitors is expected when calculating the optimal set of monitors. - The LOM + OBS method is demonstrated to be a technique applicable to any type of electrical system (radial or mesh), ensuring the detection of faults that cause voltage sags in a system according to the observability level raised. In the case of the optimal localization of sag monitors based on the criterion of correlation area (LOM+COR), several tests showed the following conclusions: - The procedure of LOM+COR method combines the implemented algorithms of voltage sag estimation (PEHT and PEHT+MP) with linear optimization techniques to define the optimal location of the sag monitors in a network. That is, the PEHT is used to generate the voltage sag pseudo-records, and, from the proposed optimization criterion (correlation area), the LOM+COR formulates and analytically calculates the optimal set of sag monitors of the network in the long term. From the information recorded by the optimal set of sag monitors, an accurate prediction of the voltage sag severity at all the busbars of the system is guaranteed with the PEHT+MP. - The LOM + COR method is shown to be a versatile optimization procedure, which reduces the size of the sag monitoring system both at radial as meshed grids. Due to its characteristics, this optimal location method allows emulation of complete system sag monitoring through the records of a small optimal set of sag monitors. Therefore, this new optimization method would be applicable to network operators that looks to reduce the installation and operation costs of the voltage sag monitoring system.

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Detailed electronic structure calculations of picene clusters doped by potassium modeling the crystalline K3picene structure show that while two electrons are completely transferred from potassium atoms to the lowest-energy unoccupied molecular orbital of pristine picene, the third one remains closely attached to both material components. Multiconfigurational analysis is necessary to show that many structures of almost degenerate total energies compete to define the cluster ground state. Our results prove that the 4s orbital of potassium should be included in any interaction model describing the material. We propose a quarter-filled two-orbital model as the most simple model capable of describing the electronic structure of K-intercalated picene. Precise solutions obtained by a development of the Lanczos method show low-energy electronic excitations involving orbitals located at different positions. Consequently, metallic transport is possible in spite of the clear dominance of interaction over hopping.

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For many strongly correlated metals with layered crystal structure the temperature dependence of the interlayer resistance is different to that of the intralayer resistance. We consider a small polaron model which exhibits this behavior, illustrating how the interlayer transport is related to the coherence of quasiparticles within the layers. Explicit results are also given for the electron spectral function, interlayer optical conductivity, and the interlayer magnetoresistance. All these quantities have two contributions: one coherent (dominant at low temperatures) and the other incoherent (dominant at high temperatures).

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Layered systems show anisotropic transport properties. The interlayer conductivity shows a general temperature dependence for a wide class of materials. This can be understood if conduction occurs in two different channels activated at different temperatures. We show that the characteristic temperature dependence can be explained using a polaron model for the transport. The results show an intuitive interpretation in terms of coherent and incoherent quasi-particles within the layers. Further, we extract results for the magnetoresistance, thermopower, spectral function and optical conductivity for the model and discuss application to experiments.

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The problem of strongly correlated electrons in one dimension attracted attention of condensed matter physicists since early 50’s. After the seminal paper of Tomonaga [1] who suggested the first soluble model in 1950, there were essential achievements reflected in papers by Luttinger [2] (1963) and Mattis and Lieb [3] (1963). A considerable contribution to the understanding of generic properties of the 1D electron liquid has been made by Dzyaloshinskii and Larkin [4] (1973) and Efetov and Larkin [5] (1976). Despite the fact that the main features of the 1D electron liquid were captured and described by the end of 70’s, the investigators felt dissatisfied with the rigour of the theoretical description. The most famous example is the paper by Haldane [6] (1981) where the author developed the fundamentals of a modern bosonisation technique, known as the operator approach. This paper became famous because the author has rigourously shown how to construct the Fermi creation/anihilation operators out of the Bose ones. The most recent example of such a dissatisfaction is the review by von Delft and Schoeller [7] (1998) who revised the approach to the bosonisation and came up with what they called constructive bosonisation.

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Iridium nanoparticles deposited on a variety of surfaces exhibited thermal sintering characteristics that were very strongly correlated with the lability of lattice oxygen in the supporting oxide materials. Specifically, the higher the lability of oxygen ions in the support, the greater the resistance of the nanoparticles to sintering in an oxidative environment. Thus with γ-Al2O3 as the support, rapid and extensive sintering occurred. In striking contrast, when supported on gadolinia-ceria and alumina-ceria-zirconia composite, the Ir nanoparticles underwent negligible sintering. In keeping with this trend, the behavior found with yttria-stabilized zirconia was an intermediate between the two extremes. This resistance, or lack of resistance, to sintering is considered in terms of oxygen spillover from support to nanoparticles and discussed with respect to the alternative mechanisms of Ostwald ripening versus nanoparticle diffusion. Activity towards the decomposition of N2O, a reaction that displays pronounced sensitivity to catalyst particle size (large particles more active than small particles), was used to confirm that catalytic behavior was consistent with the independently measured sintering characteristics. It was found that the nanoparticle active phase was Ir oxide, which is metallic, possibly present as a capping layer. Moreover, observed turnover frequencies indicated that catalyst-support interactions were important in the cases of the sinter-resistant systems, an effect that may itself be linked to the phenomena that gave rise to materials with a strong resistance to nanoparticle sintering.

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The distribution of dissolved zinc (Zn) was investigated in the Atlantic sector of the Southern Ocean in the austral autumn of 2008 as part of the IPY GEOTRACES expedition ZERO & DRAKE. Research focused on transects across the major frontal systems along the Zero Meridian and across the Drake Passage. There was a strong gradient in surface zinc concentrations observed across the Antarctic Polar Front along both transects and high zinc levels were found in surface waters throughout the Southern Ocean. Vertical profiles for dissolved Zinc showed the presence of local minima and maxima in the upper 200 m consistent with significant uptake by phytoplankton and release by zooplankton grazing, respectively. Highest deep water zinc concentrations were found in the centre of the Weddell Gyre associated with Central Intermediate Water (CIW), a water mass which is depleted in O2, elevated in CO2 and is regionally a CFC minimum. Our data suggests that the remineralization of sinking particles is a key control on the distribution of Zn in the Southern Ocean. Disappearance ratios of zinc to phosphate (Zn:P) in the upper water column increased southwards along both transects and based on laboratory studies they suggest slower growth rates of phytoplankton due to iron or light limitation. Zinc and silicate were strongly correlated throughout the study region but the disappearance ratio (Zn:Si) was relatively uniform overall except for the region close to the ice edge on the Zero Meridian.

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Since the end of the Cold War, recurring civil conflicts have been the dominant form of violent armed conflict in the world, accounting for 70% of conflicts active between 2000-2013. Duration and intensity of episodes within recurring conflicts in Africa exhibit four behaviors characteristic of archetypal dynamic system structures. The overarching questions asked in this study are whether these patterns are robustly correlated with fundamental concepts of resiliency in dynamic systems that scale from micro-to macro levels; are they consistent with theoretical risk factors and causal mechanisms; and what are the policy implications. Econometric analysis and dynamic systems modeling of 36 conflicts in Africa between 1989 -2014 are combined with process tracing in a case study of Somalia to evaluate correlations between state characteristics, peace operations and foreign aid on the likelihood of observed conflict patterns, test hypothesized causal mechanisms across scales, and develop policy recommendations for increasing human security while decreasing resiliency of belligerents. Findings are that observed conflict patterns scale from micro to macro levels; are strongly correlated with state characteristics that proxy a mix of cooperative (e.g., gender equality) and coercive (e.g., security forces) conflict-balancing mechanisms; and are weakly correlated with UN and regional peace operations and humanitarian aid. Interactions between peace operations and aid interventions that effect conflict persistence at micro levels are not seen in macro level analysis, due to interdependent, micro-level feedback mechanisms, sequencing, and lagged effects. This study finds that the dynamic system structures associated with observed conflict patterns contain tipping points between balancing mechanisms at the interface of micro-macro level interactions that are determined as much by factors related to how intervention policies are designed and implemented, as what they are. Policy implications are that reducing risk of conflict persistence requires that peace operations and aid interventions (1) simultaneously increase transparency, promote inclusivity (with emphasis on gender equality), and empower local civilian involvement in accountability measures at the local levels; (2) build bridges to horizontally and vertically integrate across levels; and (3) pave pathways towards conflict transformation mechanisms and justice that scale from the individual, to community, regional, and national levels.

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Studies of non-equilibrium current fluctuations enable assessing correlations involved in quantum transport through nanoscale conductors. They provide additional information to the mean current on charge statistics and the presence of coherence, dissipation, disorder, or entanglement. Shot noise, being a temporal integral of the current autocorrelation function, reveals dynamical information. In particular, it detects presence of non-Markovian dynamics, i.e., memory, within open systems, which has been subject of many current theoretical studies. We report on low-temperature shot noise measurements of electronic transport through InAs quantum dots in the Fermi-edge singularity regime and show that it exhibits strong memory effects caused by quantum correlations between the dot and fermionic reservoirs. Our work, apart from addressing noise in archetypical strongly correlated system of prime interest, discloses generic quantum dynamical mechanism occurring at interacting resonant Fermi edges.

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Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous ecological functions, some of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field-validated, landscape-scale approaches for classifying wetlands based on their expected degree of connectivity with stream networks. During the 2015 water year, flow duration was recorded in non-perennial streams (n = 23) connecting forested wetlands and nearby perennial streams on the Delmarva Peninsula (Maryland, USA). Field and GIS-derived landscape metrics (indicators of catchment, wetland, non-perennial stream, and soil characteristics) were assessed as predictors of wetland-stream connectivity (duration, seasonal onset and offset dates). Connection duration was most strongly correlated with non-perennial stream geomorphology and wetland characteristics. A final GIS-based stepwise regression model (adj-R2 = 0.74, p < 0.0001) described wetland-stream connection duration as a function of catchment area, wetland area and number, and soil available water storage.

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Ionic liquids (ILs) have attracted great attention, from both industry and academia, as alternative fluids for very different types of applications. The large number of cations and anions allow a wide range of physical and chemical characteristics to be designed. However, the exhaustive measurement of all these systems is impractical, thus requiring the use of a predictive model for their study. In this work, the predictive capability of the conductor-like screening model for real solvents (COSMO-RS), a model based on unimolecular quantum chemistry calculations, was evaluated for the prediction water activity coefficient at infinite dilution, gamma(infinity)(w), in several classes of ILs. A critical evaluation of the experimental and predicted data using COSMO-RS was carried out. The global average relative deviation was found to be 27.2%, indicating that the model presents a satisfactory prediction ability to estimate gamma(infinity)(w) in a broad range of ILs. The results also showed that the basicity of the ILs anions plays an important role in their interaction with water, and it considerably determines the enthalpic behavior of the binary mixtures composed by Its and water. Concerning the cation effect, it is possible to state that generally gamma(infinity)(w) increases with the cation size, but it is shown that the cation-anion interaction strength is also important and is strongly correlated to the anion ability to interact with water. The results here reported are relevant in the understanding of ILs-water interactions and the impact of the various structural features of its on the gamma(infinity)(w) as these allow the development of guidelines for the choice of the most suitable lLs with enhanced interaction with water.