Comparison of the effects of the alpha-2 agonists detomidine, romifidine and xylazine on nociceptive withdrawal reflex and temporal summation in horses

OBJECTIVE: To evaluate and compare the antinociceptive effects of the three alpha-2 agonists, detomidine, romifidine and xylazine at doses considered equipotent for sedation, using the nociceptive withdrawal reflex (NWR) and temporal summation model in standing horses. STUDY DESIGN: Prospective, blinded, randomized cross-over study. ANIMALS: Ten healthy adult horses weighing 527-645 kg and aged 11-21 years old. METHODS: Electrical stimulation was applied to the digital nerves to evoke NWR and temporal summation in the left thoracic limb and pelvic limb of each horse. Electromyographic reflex activity was recorded from the common digital extensor and the cranial tibial muscles. After baseline measurements a single bolus dose of detomidine, 0.02 mg kg(-1), romifidine 0.08 mg kg(-1), or xylazine, 1 mg kg(-1), was administered intravenously (IV). Determinations of NWR and temporal summation thresholds were repeated at 10, 20, 30, 40, 60, 70, 90, 100, 120 and 130 minutes after test-drug administration alternating the thoracic limb and the pelvic limb. Depth of sedation was assessed before measurements at each time point. Behavioural reaction was observed and recorded following each stimulation. RESULTS: The administration of detomidine, romifidine and xylazine significantly increased the current intensities necessary to evoke NWR and temporal summation in thoracic limbs and pelvic limbs of all horses compared with baseline. Xylazine increased NWR thresholds over baseline values for 60 minutes, while detomidine and romifidine increased NWR thresholds over baseline for 100 and 120 minutes, respectively. Temporal summation thresholds were significantly increased for 40, 70 and 130 minutes after xylazine, detomidine and romifidine, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: Detomidine, romifidine and xylazine, administered IV at doses considered equipotent for sedation, significantly increased NWR and temporal summation thresholds, used as a measure of antinociceptive activity. The extent of maximal increase of NWR and temporal summation thresholds was comparable, while the duration of action was drug-specific.

Sink mat for broken glass plate negative

Broken glass plate negative. Goal To design a simple protective enclosure for the two pieces of the glass plate negative, that allows the user to visualize the image as a whole. Treatment A sink mat was created by layering museum board and Volera foam, and "sinks" cut to fit the broken pieces along with thumb notches for ease of lifting. A portfolio of e-flute board, buckram, and cotton ties was built up around the sink mat to provide a protective enclosure that is easily stored on edge.

Artifact exhibit and storage box

Plaster death mask. Goal To design a box that can store and exhibit the death mask without requiring the removal or re-positioning of the mask. Treatment A custom, cloth-covered box with a drop-front was constructed to fit the dimensions of the mask and foam filler. Foam was carved to accommodate the mask and then covered with unbleached muslin.

Static and dynamic characteristics of cerebral blood flow during the resting state in schizophrenia

Background: The cerebral network that is active during rest and is deactivated during goal-oriented activity is called the default mode network (DMN). It appears to be involved in self-referential mental activity. Atypical functional connectivity in the DMN has been observed in schizophrenia. One hypothesis suggests that pathologically increased DMN connectivity in schizophrenia is linked with a main symptom of psychosis, namely, misattribution of thoughts. Methods: A resting-state pseudocontinuous arterial spin labeling (ASL) study was conducted to measure absolute cerebral blood flow (CBF) in 34 schizophrenia patients and 27 healthy controls. Using independent component analysis (ICA), the DMN was extracted from ASL data. Mean CBF and DMN connectivity were compared between groups using a 2-sample t test. Results: Schizophrenia patients showed decreased mean CBF in the frontal and temporal regions (P < .001). ICA demonstrated significantly increased DMN connectivity in the precuneus (x/y/z = -16/-64/38) in patients than in controls (P < .001). CBF was not elevated in the respective regions. DMN connectivity in the precuneus was significantly correlated with the Positive and Negative Syndrome Scale scores (P < .01). Conclusions: In schizophrenia patients, the posterior hub-which is considered the strongest part of the DMN-showed increased DMN connectivity. We hypothesize that this increase hinders the deactivation of the DMN and, thus, the translation of cognitive processes from an internal to an external focus. This might explain symptoms related to defective self-monitoring, such as auditory verbal hallucinations or ego disturbances.

Effectiveness of integrated cognitive remediartion therapy for schizophrenia outpatients: Early versus long-term course of illness – results from an international RCT

Background Nowadays there is extensive evidence available showing the efficacy of cognitive remediation therapies. Integrative approaches seem superior regarding the maintenance of proximal outcome at follow-up as well as generalization to other areas of functioning. To date, only limited evidence about the efficacy of CRT is available concerning elder schizophrenia patients. The Integrated Neurocognitive Therapy (INT) represents a new developed cognitive remediation approach. It is a manualized group therapy approach targeting all 11 NIMH-MATRICS dimensions within one therapy concept. In this study we compared the effects of INT on an early course group (duration of disease<5 years) to a long-term group of schizophrenia outpatients (duration of disease>15 years). Methods An international multicenter study carried out in Germany, Switzerland and Austria with a total of 90 outpatients diagnosed with Schizophrenia (DSM-IV-TR) were randomly assigned either to an INT-Therapy or to Treatment-As-Usual (TAU). 50 of the 90 Patients were an Early-Course (EC) group, suffering from schizophrenia for less than 5 years (Mean age=29 years, Mean duration of illness=3.3 years). The other 40 were a Long-term Course (LC) group, suffering from schizophrenia longer than 15 years (Mean age= 45 years, Mean duration of illness=22 years). Treatment comprised of 15 biweekly sessions. An extensive assessment battery was conducted before and after treatment and at follow up (1 year). Multivariate General Linear Models (GLM) (duration of illness x treatment x time) examined our hypothesis, if an EC group of schizophrenia outpatients differ in proximal and distal outcome from a LC group. Results Irrespective of the duration of illness, both groups (EC & LC) were able to benefit from the INT. INT was superior compared to TAU in most of the assessed domains. Dropout rate of EC group was much higher (21.4%) than LC group (8%) during therapy phase. However, interaction effects show that the LC group revealed significantly higher effects in the neurocognitive domains of speed of processing (F>3.6) and vigilance (F>2.4). In social cognition the EC group showed significantly higher effects in social schema (F>2.5) and social attribution (blame; F>6.0) compared to the LC group. Regarding more distal outcome, patients treated with INT obtained reduced general symptoms unaffected by the duration of illness during therapy phase and at follow-up (F>4.3). Discussion Results suggest that INT is a valid goal-oriented treatment to improve cognitive functions in schizophrenia outpatients. Irrespective of the duration of illness significant treatment, effects were evident. Against common expectations, long-term, more chronic patients showed higher effects in basal cognitive functions compared to younger patients and patients without any active therapy (TAU). Consequently, more integrated therapy offers are also recommended for long-term course schizophrenia patients.

Habitat characteristics and energy budget of the ocean quahog (Arctica islandica)

We compared lifetime and population energy budgets of the extraordinary long-lived ocean quahog Arctica islandica from 6 different sites - the Norwegian coast, Kattegat, Kiel Bay, White Sea, German Bight, and off northeast Iceland - covering a temperature and salinity gradient of 4-10°C (annual mean) and 25-34, respectively. Based on von Bertalanffy growth models and size-mass relationships, we computed organic matter production of body (PSB) and of shell (PSS), whereas gonad production (PG) was estimated from the seasonal cycle in mass. Respiration (R) was computed by a model driven by body mass, temperature, and site. A. islandica populations differed distinctly in maximum life span (40 y in Kiel Bay to 197 y in Iceland), but less in growth performance (phi' ranged from 2.41 in the White Sea to 2.65 in Kattegat). Individual lifetime energy throughput, as approximated by assimilation, was highest in Iceland (43,730 kJ) and lowest in the White Sea (313 kJ). Net growth efficiency ranged between 0.251 and 0.348, whereas lifetime energy investment distinctly shifted from somatic to gonad production with increasing life span; PS/PG decreased from 0.362 (Kiel Bay, 40 y) to 0.031 (Iceland, 197 y). Population annual energy budgets were derived from individual budgets and estimates of population mortality rate (0.035/y in Iceland to 0.173/y in Kiel Bay). Relationships between budget ratios were similar on the population level, albeit with more emphasis on somatic production; PS/ PG ranged from 0.196 (Iceland) to 2.728 (White Sea), and P/B ranged from 0.203-0.285/y. Life span is the principal determinant of the relationship between budget parameters, whereas temperature affects net growth efficiency only. In the White Sea population, both growth performance and net growth efficiency of A. islandica were lowest. We presume that low temperature combined with low salinity represent a particularly stressful environment for this species.

Fulminant hepatic and multiple organ failure following acute viral tonsillitis: a case report.

BACKGROUND Pyogenic tonsillitis may often be observed in the general Western population. In severe cases, it may require antibiotic treatment or even hospitalization and often a prompt clinical response will be noted. Here we present an unusual case of progressive multiple organ failure including fulminant liver failure following acute tonsillitis initially mistaken for "classic" pyogenic (that is bacterial) tonsillitis. CASE PRESENTATION A 68-year-old previously healthy white man was referred with suspicion of pyogenic angina. After tonsillectomy, he developed acute liver failure and consecutive multiple organ failure including acute hemodynamic, pulmonary and dialysis-dependent renal failure. Immunohistopathological analysis of his tonsils and liver as well as serum polymerase chain reaction analyses revealed herpes simplex virus-2 to be the causative pathogen. Treatment included high-dose acyclovir and multiorgan supportive intensive care therapy. His final outcome was favorable. CONCLUSIONS Fulminant herpes simplex virus-2-induced multiple organ failure is rarely observed in the Western hemisphere and should be considered a potential diagnosis in patients with tonsillitis and multiple organ failure including acute liver failure. From a clinical perspective, it seems important to note that fulminant herpes simplex virus-2 infection may masquerade as "routine" bacterial severe sepsis/septic shock. This persevering condition should be diagnosed early and treated goal-oriented in order to gain control of this life-threatening condition.

Some improvements over the continuation call tabling implementation technique

Tabled evaluation has been proved an effective method to improve several aspeets of goal-oriented query evaluation, including termination and complexity. Several "native" implementations of tabled evaluation have been developed which offer good performance, but many of them need significant changes to the underlying Prolog implementation. More portable approaches, generally using program transformation, have been proposed but they often result in lower efficieney. We explore some techniques aimed at combining the best of these worlds, i.e., developing a portable and extensible implementation, with minimal modifications at the abstract machine level, and with reasonably good performance. Our preliminary results indícate promising results.

Roofscapes and the spatiality of the common

The relationship between forms of delimitation and expropriation of the commons through the management of the "public" have led to a world of enclosures and exact division lines. But this is not how the individual perceives and experiences space, this is how bureaucracy builds it. The body’s individual spatiality is understood as the complex topological extension configured by the sensible world at every turn, reflecting while allowing the crossings, junctions, intensities, densities, proximities, etc., which weave together the experiential fabric wherein he lives. This individual spatiality, when it resonates with others, produces a form of common spatiality, the understanding of which can and should act as a new frame of reference for intervention strategies and spatial politics in the contemporary world. The roofscape, as a space not fitting within the canonical division of public/private, is a unique study case to frame these new concepts.

Functional validation of MB-OFDM system using HW-in the loop

Functional validation of complex digital systems is a hard and critical task in the design flow. In particular, when dealing with communication systems, like Multiband Orthogonal Frequency Division Multiplexing Ultra Wideband (MB-OFDM UWB), the design decisions taken during the process have to be validated at different levels in an easy way. In this work, a unified algorithm-architecture-circuit co-design environment for this type of systems, to be implemented in FPGA, is presented. The main objective is to find an efficient methodology for designing a configurable optimized MB-OFDM UWB system by using as few efforts as possible in verification stage, so as to speed up the development period. Although this efficient design methodology is tested and considered to be suitable for almost all types of complex FPGA designs, we propose a solution where both the circuit and the communication channel are tested at different levels (algorithmic, RTL, hardware device) using a common testbench.

Contributions to Bayesian network learning with applications to neuroscience

Neuronal morphology is a key feature in the study of brain circuits, as it is highly related to information processing and functional identification. Neuronal morphology affects the process of integration of inputs from other neurons and determines the neurons which receive the output of the neurons. Different parts of the neurons can operate semi-independently according to the spatial location of the synaptic connections. As a result, there is considerable interest in the analysis of the microanatomy of nervous cells since it constitutes an excellent tool for better understanding cortical function. However, the morphologies, molecular features and electrophysiological properties of neuronal cells are extremely variable. Except for some special cases, this variability makes it hard to find a set of features that unambiguously define a neuronal type. In addition, there are distinct types of neurons in particular regions of the brain. This morphological variability makes the analysis and modeling of neuronal morphology a challenge. Uncertainty is a key feature in many complex real-world problems. Probability theory provides a framework for modeling and reasoning with uncertainty. Probabilistic graphical models combine statistical theory and graph theory to provide a tool for managing domains with uncertainty. In particular, we focus on Bayesian networks, the most commonly used probabilistic graphical model. In this dissertation, we design new methods for learning Bayesian networks and apply them to the problem of modeling and analyzing morphological data from neurons. The morphology of a neuron can be quantified using a number of measurements, e.g., the length of the dendrites and the axon, the number of bifurcations, the direction of the dendrites and the axon, etc. These measurements can be modeled as discrete or continuous data. The continuous data can be linear (e.g., the length or the width of a dendrite) or directional (e.g., the direction of the axon). These data may follow complex probability distributions and may not fit any known parametric distribution. Modeling this kind of problems using hybrid Bayesian networks with discrete, linear and directional variables poses a number of challenges regarding learning from data, inference, etc. In this dissertation, we propose a method for modeling and simulating basal dendritic trees from pyramidal neurons using Bayesian networks to capture the interactions between the variables in the problem domain. A complete set of variables is measured from the dendrites, and a learning algorithm is applied to find the structure and estimate the parameters of the probability distributions included in the Bayesian networks. Then, a simulation algorithm is used to build the virtual dendrites by sampling values from the Bayesian networks, and a thorough evaluation is performed to show the model’s ability to generate realistic dendrites. In this first approach, the variables are discretized so that discrete Bayesian networks can be learned and simulated. Then, we address the problem of learning hybrid Bayesian networks with different kinds of variables. Mixtures of polynomials have been proposed as a way of representing probability densities in hybrid Bayesian networks. We present a method for learning mixtures of polynomials approximations of one-dimensional, multidimensional and conditional probability densities from data. The method is based on basis spline interpolation, where a density is approximated as a linear combination of basis splines. The proposed algorithms are evaluated using artificial datasets. We also use the proposed methods as a non-parametric density estimation technique in Bayesian network classifiers. Next, we address the problem of including directional data in Bayesian networks. These data have some special properties that rule out the use of classical statistics. Therefore, different distributions and statistics, such as the univariate von Mises and the multivariate von Mises–Fisher distributions, should be used to deal with this kind of information. In particular, we extend the naive Bayes classifier to the case where the conditional probability distributions of the predictive variables given the class follow either of these distributions. We consider the simple scenario, where only directional predictive variables are used, and the hybrid case, where discrete, Gaussian and directional distributions are mixed. The classifier decision functions and their decision surfaces are studied at length. Artificial examples are used to illustrate the behavior of the classifiers. The proposed classifiers are empirically evaluated over real datasets. We also study the problem of interneuron classification. An extensive group of experts is asked to classify a set of neurons according to their most prominent anatomical features. A web application is developed to retrieve the experts’ classifications. We compute agreement measures to analyze the consensus between the experts when classifying the neurons. Using Bayesian networks and clustering algorithms on the resulting data, we investigate the suitability of the anatomical terms and neuron types commonly used in the literature. Additionally, we apply supervised learning approaches to automatically classify interneurons using the values of their morphological measurements. Then, a methodology for building a model which captures the opinions of all the experts is presented. First, one Bayesian network is learned for each expert, and we propose an algorithm for clustering Bayesian networks corresponding to experts with similar behaviors. Then, a Bayesian network which represents the opinions of each group of experts is induced. Finally, a consensus Bayesian multinet which models the opinions of the whole group of experts is built. A thorough analysis of the consensus model identifies different behaviors between the experts when classifying the interneurons in the experiment. A set of characterizing morphological traits for the neuronal types can be defined by performing inference in the Bayesian multinet. These findings are used to validate the model and to gain some insights into neuron morphology. Finally, we study a classification problem where the true class label of the training instances is not known. Instead, a set of class labels is available for each instance. This is inspired by the neuron classification problem, where a group of experts is asked to individually provide a class label for each instance. We propose a novel approach for learning Bayesian networks using count vectors which represent the number of experts who selected each class label for each instance. These Bayesian networks are evaluated using artificial datasets from supervised learning problems. Resumen La morfología neuronal es una característica clave en el estudio de los circuitos cerebrales, ya que está altamente relacionada con el procesado de información y con los roles funcionales. La morfología neuronal afecta al proceso de integración de las señales de entrada y determina las neuronas que reciben las salidas de otras neuronas. Las diferentes partes de la neurona pueden operar de forma semi-independiente de acuerdo a la localización espacial de las conexiones sinápticas. Por tanto, existe un interés considerable en el análisis de la microanatomía de las células nerviosas, ya que constituye una excelente herramienta para comprender mejor el funcionamiento de la corteza cerebral. Sin embargo, las propiedades morfológicas, moleculares y electrofisiológicas de las células neuronales son extremadamente variables. Excepto en algunos casos especiales, esta variabilidad morfológica dificulta la definición de un conjunto de características que distingan claramente un tipo neuronal. Además, existen diferentes tipos de neuronas en regiones particulares del cerebro. La variabilidad neuronal hace que el análisis y el modelado de la morfología neuronal sean un importante reto científico. La incertidumbre es una propiedad clave en muchos problemas reales. La teoría de la probabilidad proporciona un marco para modelar y razonar bajo incertidumbre. Los modelos gráficos probabilísticos combinan la teoría estadística y la teoría de grafos con el objetivo de proporcionar una herramienta con la que trabajar bajo incertidumbre. En particular, nos centraremos en las redes bayesianas, el modelo más utilizado dentro de los modelos gráficos probabilísticos. En esta tesis hemos diseñado nuevos métodos para aprender redes bayesianas, inspirados por y aplicados al problema del modelado y análisis de datos morfológicos de neuronas. La morfología de una neurona puede ser cuantificada usando una serie de medidas, por ejemplo, la longitud de las dendritas y el axón, el número de bifurcaciones, la dirección de las dendritas y el axón, etc. Estas medidas pueden ser modeladas como datos continuos o discretos. A su vez, los datos continuos pueden ser lineales (por ejemplo, la longitud o la anchura de una dendrita) o direccionales (por ejemplo, la dirección del axón). Estos datos pueden llegar a seguir distribuciones de probabilidad muy complejas y pueden no ajustarse a ninguna distribución paramétrica conocida. El modelado de este tipo de problemas con redes bayesianas híbridas incluyendo variables discretas, lineales y direccionales presenta una serie de retos en relación al aprendizaje a partir de datos, la inferencia, etc. En esta tesis se propone un método para modelar y simular árboles dendríticos basales de neuronas piramidales usando redes bayesianas para capturar las interacciones entre las variables del problema. Para ello, se mide un amplio conjunto de variables de las dendritas y se aplica un algoritmo de aprendizaje con el que se aprende la estructura y se estiman los parámetros de las distribuciones de probabilidad que constituyen las redes bayesianas. Después, se usa un algoritmo de simulación para construir dendritas virtuales mediante el muestreo de valores de las redes bayesianas. Finalmente, se lleva a cabo una profunda evaluaci ón para verificar la capacidad del modelo a la hora de generar dendritas realistas. En esta primera aproximación, las variables fueron discretizadas para poder aprender y muestrear las redes bayesianas. A continuación, se aborda el problema del aprendizaje de redes bayesianas con diferentes tipos de variables. Las mixturas de polinomios constituyen un método para representar densidades de probabilidad en redes bayesianas híbridas. Presentamos un método para aprender aproximaciones de densidades unidimensionales, multidimensionales y condicionales a partir de datos utilizando mixturas de polinomios. El método se basa en interpolación con splines, que aproxima una densidad como una combinación lineal de splines. Los algoritmos propuestos se evalúan utilizando bases de datos artificiales. Además, las mixturas de polinomios son utilizadas como un método no paramétrico de estimación de densidades para clasificadores basados en redes bayesianas. Después, se estudia el problema de incluir información direccional en redes bayesianas. Este tipo de datos presenta una serie de características especiales que impiden el uso de las técnicas estadísticas clásicas. Por ello, para manejar este tipo de información se deben usar estadísticos y distribuciones de probabilidad específicos, como la distribución univariante von Mises y la distribución multivariante von Mises–Fisher. En concreto, en esta tesis extendemos el clasificador naive Bayes al caso en el que las distribuciones de probabilidad condicionada de las variables predictoras dada la clase siguen alguna de estas distribuciones. Se estudia el caso base, en el que sólo se utilizan variables direccionales, y el caso híbrido, en el que variables discretas, lineales y direccionales aparecen mezcladas. También se estudian los clasificadores desde un punto de vista teórico, derivando sus funciones de decisión y las superficies de decisión asociadas. El comportamiento de los clasificadores se ilustra utilizando bases de datos artificiales. Además, los clasificadores son evaluados empíricamente utilizando bases de datos reales. También se estudia el problema de la clasificación de interneuronas. Desarrollamos una aplicación web que permite a un grupo de expertos clasificar un conjunto de neuronas de acuerdo a sus características morfológicas más destacadas. Se utilizan medidas de concordancia para analizar el consenso entre los expertos a la hora de clasificar las neuronas. Se investiga la idoneidad de los términos anatómicos y de los tipos neuronales utilizados frecuentemente en la literatura a través del análisis de redes bayesianas y la aplicación de algoritmos de clustering. Además, se aplican técnicas de aprendizaje supervisado con el objetivo de clasificar de forma automática las interneuronas a partir de sus valores morfológicos. A continuación, se presenta una metodología para construir un modelo que captura las opiniones de todos los expertos. Primero, se genera una red bayesiana para cada experto y se propone un algoritmo para agrupar las redes bayesianas que se corresponden con expertos con comportamientos similares. Después, se induce una red bayesiana que modela la opinión de cada grupo de expertos. Por último, se construye una multired bayesiana que modela las opiniones del conjunto completo de expertos. El análisis del modelo consensuado permite identificar diferentes comportamientos entre los expertos a la hora de clasificar las neuronas. Además, permite extraer un conjunto de características morfológicas relevantes para cada uno de los tipos neuronales mediante inferencia con la multired bayesiana. Estos descubrimientos se utilizan para validar el modelo y constituyen información relevante acerca de la morfología neuronal. Por último, se estudia un problema de clasificación en el que la etiqueta de clase de los datos de entrenamiento es incierta. En cambio, disponemos de un conjunto de etiquetas para cada instancia. Este problema está inspirado en el problema de la clasificación de neuronas, en el que un grupo de expertos proporciona una etiqueta de clase para cada instancia de manera individual. Se propone un método para aprender redes bayesianas utilizando vectores de cuentas, que representan el número de expertos que seleccionan cada etiqueta de clase para cada instancia. Estas redes bayesianas se evalúan utilizando bases de datos artificiales de problemas de aprendizaje supervisado.

Comportamiento estructural de elementos de fábrica reforzados con materiales compuestos avanzados solicitados a flexión y flexocompresión

El refuerzo de estructuras existentes mediante el encolado exterior de láminas de polímeros reforzados con fibras (FRP) se ha convertido en la aplicación más común de los materiales compuestos avanzados en construcción. Estos materiales presentan muchas ventajas frente a los materiales convencionales (sin corrosión, ligeros, de fácil aplicación, etc.). Pero a pesar de las numerosas investigaciones realizadas, aún persisten ciertas dudas sobre algunos aspectos de su comportamiento y las aplicaciones prácticas se llevan a cabo sólo con la ayuda de guías, sin que haya una normativa oficial. El objetivo de este trabajo es incrementar el conocimiento sobre esta técnica de refuerzo, y más concretamente, sobre el refuerzo a flexión de estructuras de fábrica. Con frecuencia el elemento reforzado es de hormigón armado y las láminas de FRP encoladas al exterior sirven para mejorar su resistencia a flexión, cortante o compresión (encamisados). Sin embargo su empleo en otros materiales como las estructuras de fábrica resulta muy prometedor. Las fábricas se caracterizan por soportar muy bien los esfuerzos de compresión pero bastante mal los de tracción. Adherir láminas de materiales compuestos puede servir para mejorar la capacidad resistente de elementos de fábrica sometidos a esfuerzos de flexión. Pero para ello, debe quedar garantizada una correcta adherencia entre el FRP y la fábrica, especialmente en edificios antiguos cuya superficie puede estar deteriorada por encontrarse a la intemperie o por el propio paso del tiempo. En el capítulo II se describen los objetivos fundamentales del trabajo y el método seguido. En el capítulo III se hace una amplia revisión del estado de conocimiento sobre el tema. En el apartado III.1 se detallan las principales características y propiedades mecánicas de fibras, matrices y materiales compuestos así como sus principales aplicaciones, haciendo especial hincapié en aspectos relativos a su durabilidad. En el apartado III.2 se incluye una revisión histórica de las líneas de investigación, tanto teóricas como empíricas, publicadas sobre estructuras de hormigón reforzadas a flexión encolando materiales compuestos. El apartado III.3 se centra en el aspecto fundamental de la adherencia refuerzo-soporte. Se hace un repaso a distintos modelos propuestos para prevenir el despegue distinguiendo si éste se inicia en la zona de anclaje o si está inducido por fisuras en la zona interior del elemento. Se observa falta de consenso en las propuestas. Además en este punto se relatan las campañas experimentales publicadas acerca de la adherencia entre materiales compuestos y fábricas. En el apartado III.4 se analizan las particularidades de las estructuras de fábrica. Además, se revisan algunas de las investigaciones relativas a la mejora de su comportamiento a flexión mediante láminas de FRP. El comportamiento mecánico de muros reforzados solicitados a flexión pura (sin compresión) ha sido documentado por varios autores, si bien es una situación poco frecuente en fábricas reales. Ni el comportamiento mecánico de muros reforzados solicitados a flexocompresión ni la incidencia que el nivel de compresión soportado por la fábrica tiene sobre la capacidad resistente del elemento reforzado han sido suficientemente tratados. En cuanto a los trabajos teóricos, las diferentes propuestas se basan en los métodos utilizados para hormigón armado y comparten los principios habituales de cálculo. Sin embargo, presentan diferencias relativas, sobre todo, a tres aspectos: 1) la forma de modelar el comportamiento de la fábrica, 2) el valor de deformación de cálculo del refuerzo, y 3) el modo de fallo que se considera recomendable buscar con el diseño. A pesar de ello, el ajuste con la parte experimental de cada trabajo suele ser bueno debido a una enorme disparidad en las variables consideradas. Cada campaña presenta un modo de fallo característico y la formulación que se propone resulta apropiada para él. Parece necesario desarrollar un método de cálculo para fábricas flexocomprimidas reforzadas con FRP que pueda ser utilizado para todos los posibles fallos, tanto atribuibles a la lámina como a la fábrica. En el apartado III.4 se repasan algunas lesiones habituales en fábricas solicitadas a flexión y se recogen ejemplos de refuerzos con FRP para reparar o prevenir estos daños. Para mejorar el conocimiento sobre el tema, se llevan a cabo dos pequeñas campañas experimentales realizadas en el Instituto de Ciencias de la Construcción Eduardo Torroja. La primera acerca de la adherencia de materiales compuestos encolados a fábricas deterioradas (apartado IV.1) y la segunda sobre el comportamiento estructural a flexocompresión de probetas de fábrica reforzadas con estos materiales (apartado IV.2). En el capítulo V se analizan algunos de los modelos de adherencia propuestos para prevenir el despegue del extremo del refuerzo. Se confirma que las predicciones obtenidas con ellos resultan muy dispares. Se recopila una base de datos con los resultados experimentales de campañas sobre adherencia de FRP a fábricas extraídas de la literatura y de los resultados propios de la campaña descrita en el punto IV.1. Esta base de datos permite conocer cual de los métodos analizados resulta más adecuado para dimensionar el anclaje de láminas de FRP adheridas a fábricas. En el capítulo VI se propone un método para la comprobación en agotamiento de secciones de fábrica reforzadas con materiales compuestos sometidas a esfuerzos combinados de flexión y compresión. Está basado en el procedimiento de cálculo de la capacidad resistente de secciones de hormigón armado pero adaptado a las fábricas reforzadas. Para ello, se utiliza un diagrama de cálculo tensión deformación de la fábrica de tipo bilineal (acorde con el CTE DB SE-F) cuya simplicidad facilita el desarrollo de toda la formulación al tiempo que resulta adecuado para predecir la capacidad resistente a flexión tanto para fallos debidos al refuerzo como a la fábrica. Además se limita la deformación de cálculo del refuerzo teniendo en consideración ciertos aspectos que provocan que la lámina adherida no pueda desarrollar toda su resistencia, como el desprendimiento inducido por fisuras en el interior del elemento o el deterioro medioambiental. En concreto, se propone un “coeficiente reductor por adherencia” que se determina a partir de una base de datos con 68 resultados experimentales procedentes de publicaciones de varios autores y de los ensayos propios de la campaña descrita en el punto IV.2. También se revisa la formulación propuesta con ayuda de la base de datos. En el capítulo VII se estudia la incidencia de las principales variables, como el axil, la deformación de cálculo del refuerzo o su rigidez, en la capacidad final del elemento. Las conclusiones del trabajo realizado y las posibles líneas futuras de investigación se exponen en el capítulo VIII. ABSTRACT Strengthening of existing structures with externally bonded fiber reinforced polymers (FRP) has become the most common application of advanced composite materials in construction. These materials exhibit many advantages in comparison with traditional ones (corrosion resistance, light weight, easy to apply, etc.). But despite countless researches have been done, there are still doubts about some aspects of their behaviour and applications are carried out only with the help of guidelines, without official regulations. The aim of this work is to improve the knowledge on this retrofitting technique, particularly in regard to flexural strengthening of masonry structures. Reinforced concrete is often the strengthened material and external glued FRP plates are used to improve its flexural, shear or compressive (by wrapping) capacity. However the use of this technique on other materials like masonry structures looks promising. Unreinforced masonry is characterized for being a good material to support compressive stresses but really bad to withstand tensile ones. Glue composite plates can improve the flexural capacity of masonry elements subject to bending. But a proper bond between FRP sheet and masonry must be ensured to do that, especially in old buildings whose surface can be damaged due to being outside or ageing. The main objectives of the work and the methodology carried out are described In Chapter II. An extensive overview of the state of art is done in Chapter III. In Section III.1 physical and mechanical properties of fibers, matrix and composites and their main applications are related. Durability aspects are especially emphasized. Section III.2 includes an historical overview of theoretical and empirical researches on concrete structures strengthened gluing FRP plates to improve their flexural behaviour. Section III.3 focuses on the critical point of bonding between FRP and substrate. Some theoretical models to prevent debonding of FRP laminate are reviewed, it has made a distinction between models for detachment at the end of the plate or debonding in the intermediate zones due to the effects of cracks. It is observed a lack of agreement in the proposals. Some experimental studies on bonding between masonry and FRP are also related in this chapter. The particular characteristics of masonry structures are analyzed in Section III.4. Besides some empirical and theoretical investigations relative to improve their flexural capacity with FRP sheets are reviewed. The mechanical behaviour of strengthened walls subject to pure bending (without compression) has been established by several authors, but this is an unusual situation for real masonry. Neither mechanical behaviour of walls subject to bending and compression nor influence of axial load in the final capacity of the strengthened element are adequately studied. In regard to theoretical studies, the different proposals are based on reinforced concrete analytical methods and share common design principles. However, they present differences, especially, about three aspects: 1) the constitutive law of masonry, 2) the value of ultimate FRP strain and 3) the desirable failure mode that must be looked for. In spite of them, a good agreement between each experimental program and its theoretical study is often exhibited due to enormous disparity in considered test parameters. Each experimental program usually presents a characteristic failure mode and the proposed formulation results appropriate for this one. It seems necessary to develop a method for FRP strengthened walls subject to bending and compression enable for all failure modes (due to FRP or masonry). Some common damages in masonry subject to bending are explained in Section III.4. Examples of FRP strengthening to repair or prevent these damages are also written. Two small experimental programs are carried out in Eduardo Torroja Institute to improve the knowledge on this topic. The first one is concerned about the bond between FRP plates and damaged masonry (section IV.1) and the second one is related to the mechanical behaviour of the strengthened masonry specimens subject to out of plane bending combined with axial force (section IV.2). In the Chapter V some bond models to prevent the debonding at the FRP plate end are checked. It is confirmed that their predictions are so different. A pure-shear test database is compiled with results from the existing literature and others from the experimental program described in section IV.1. This database lets know which of the considered model is more suitable to design anchorage lengths of glued FRP to masonry. In the Chapter VI a method to check unreinforced masonry sections with external FRP strengthening subject to bending and compression to the ultimate limit state is proposed. This method is based on concrete reinforced one, but it is adapted to strengthened masonry. A bilinear constitutive law is used for masonry (according to CTE DB SE-F). Its simplicity helps to develop the model formulation and it has proven to be suitable to predict bending capacity either for FRP failures or masonry crushing. With regard to FRP, the design strain is limited. It is taken into account different aspects which cause the plate can’t reach its ultimate strength, like intermediate FRP debonding induced by opening cracking or environmental damage. A “bond factor” is proposed. It is obtained by means of an experimental bending test database that includes 68 results from the existing literature and from the experimental program described in section IV.2. The proposed formulation has also been checked with the help of bending database. The effects of the main parameters, like axial load, FRP design effective strain or FRP stiffness, on the bending capacity of the strengthened element are studied in Chapter VII. Finally, the main conclusions from the work carried out are summarized in Chapter VIII. Future lines of research to be explored are suggested as well.

Automated characterisation of intergrowth textures in mineral particles. A case study

The characterisation of mineral texture has been a major concern for process mineralogists, as liberation characteristics of the ores are intimately related to the mineralogical texture. While a great effort has been done to automatically characterise texture in unbroken ores, the characterisation of textural attributes in mineral particles is usually descriptive. However, the quantitative characterisation of texture in mineral particles is essential to improve and predict the performance of minerallurgical processes (i.e. all the processes involved in the liberation and separation of the mineral of interest) and to achieve a more accurate geometallurgical model. Driven by this necessity of achieving a more complete characterisation of textural attributes in mineral particles, a methodology has been recently developed to automatically characterise the type of intergrowth between mineral phases within particles by means of digital image analysis. In this methodology, a set ofminerallurgical indices has been developed to quantify different mineralogical features and to identify the intergrowth pattern by discriminant analysis. The paper shows the application of the methodology to the textural characterisation of chalcopyrite in the rougher concentrate of the Kansanshi copper mine (Zambia). In this sample, the variety of intergrowth patterns of chalcopyrite with the other minerals has been used to illustrate the methodology. The results obtained show that the method identifies the intergrowth type and provides quantitative information to achieve a complete and detailed mineralogical characterisation. Therefore, the use of this methodology as a routinely tool in automated mineralogy would contribute to a better understanding of the ore behaviour during liberation and separation processes.

Digital libraries for the preservation of research methods and associated artifacts

New digital artifacts are emerging in data-intensive science. For example, scientific workflows are executable descriptions of scientific procedures that define the sequence of computational steps in an automated data analysis, supporting reproducible research and the sharing and replication of best-practice and know-how through reuse. Workflows are specified at design time and interpreted through their execution in a variety of situations, environments, and domains. Hence it is essential to preserve both their static and dynamic aspects, along with the research context in which they are used. To achieve this, we propose the use of multidimensional digital objects (Research Objects) that aggregate the resources used and/or produced in scientific investigations, including workflow models, provenance of their executions, and links to the relevant associated resources, along with the provision of technological support for their preservation and efficient retrieval and reuse. In this direction, we specified a software architecture for the design and implementation of a Research Object preservation system, and realized this architecture with a set of services and clients, drawing together practices in digital libraries, preservation systems, workflow management, social networking and Semantic Web technologies. In this paper, we describe the backbone system of this realization, a digital library system built on top of dLibra.

Sensing Aeropolis. Urban air monitoring devices in Madrid, 2006-2010

Esta tesis examina las implicaciones técnicas, políticas y espaciales del aire urbano, y en concreto, de la calidad del aire, para tenerlo en cuenta desde una perspectiva arquitectónica. En oposición a formas de entender el aire como un vacío o como una metáfora, este proyecto propone abordarlo desde un acercamiento material y tecnológico, trayendo el entorno al primer plano y reconociendo sus múltiples agencias. Debido a la escasa bibliografía detectada en el campo de la arquitectura, el objetivo es construir un marco teórico-analítico para considerar el aire urbano. Para ello el trabajo construye Aeropolis, una metáfora heurística que describe el ensamblaje sociotecnico de la ciudad. Situada en la intersección de determinadas ramas de la filosofía de la cultura, los estudios sobre ciencia y tecnología y estudios feministas de la ciencia este nuevo paisaje conceptual ofrece una metodología y herramientas para abordar el objeto de estudio desde distintos ángulos. Estas herramientas metodológicas han sido desarrolladas en el contexto específico de Madrid, ciudad muy contaminada cuyo aire ha sido objeto de controversias políticas y sociales, y donde las políticas y tecnologías para reducir sus niveles no han sido exitosas. Para encontrar una implicación alternativa con el aire esta tesis propone un método de investigación de agentes invisibles a partir del análisis de sus dispositivos epistémicos. Se centra, en concreto, en los instrumentos que miden, visualizan y comunican la calidad del aire, proponiendo que no sólo lo representan, sino que son también instrumentos que diseñan el aire y la ciudad. La noción de “sensing” (en castellano medir y sentir) es expandida, reconociendo distintas prácticas que reconstruyen el aire de Madrid. El resultado de esta estrategia no es sólo la ampliación de los espacios desde los que relacionarnos con el aire, sino también la legitimación de prácticas existentes fuera de contextos científicos y administrativos, como por ejemplo prácticas relacionadas con el cuerpo, así como la redistribución de agencias entre más actores. Así, esta tesis trata sobre toxicidad, la Unión Europea, producción colaborativa, modelos de computación, dolores de cabeza, kits DIY, gases, cuerpos humanos, salas de control, sangre o políticos, entre otros. Los dispositivos que sirven de datos empíricos sirven como un ejemplo excepcional para investigar infraestructuras digitales, permitiendo desafiar nociones sobre Ciudades Inteligentes. La tesis pone especial atención en los efectos del aire en el espacio público, reconociendo los procesos de invisibilización que han sufrido sus infraestructuras de monitorización. Para terminar se exponen líneas de trabajo y oportunidades para la arquitectura y el diseño urbano a través de nuevas relaciones entre infraestructuras urbanas, el medio construido, espacios domésticos y públicos y humanos y no humanos, para crear nuevas ecologías políticas urbanas (queer). ABSTRACT This thesis examines the technical, political and spatial implications of urban air, and more specifically "air quality", in order to consider it from an architectural perspective. In opposition to understandings of the air either as a void or as a metaphor, this project proposes to inspect it from a material and technical approach, bringing the background to the fore and acknowledging its multiple agencies. Due to the scarce bibliography within the architectural field, its first aim is to construct a theoretical and analytical framework from which to consider urban air. For this purpose, the work attempts the construction of Aeropolis, a heuristic metaphor that describes the city's aero socio-material assemblage. Located at the intersection of certain currents in cultural philosophy, science and technology studies as well as feminist studies in technoscience, this framework enables a methodology and toolset to be extracted in order to approach the subject matter from different angles. The methodological tools stemming from this purpose-built framework were put to the test in a specific case study: Madrid, a highly polluted city whose air has been subject to political and social controversies, and where no effective policies or technologies have been successful in reducing its levels of pollution. In order to engage with the air, the thesis suggests a method for researching invisible agents by examining the epistemic devices involved. It locates and focuses on the instruments that sense, visualise and communicate urban air, claiming that they do not only represent it, but are also instruments that design the air and the city. The notion of "sensing" is then expanded by recognising different practices which enact the air in Madrid. The work claims that the result of this is not only the opening up of spaces for engagement but also the legitimisation of existing practices outside science and policymaking environments, such as embodied practices, as well as the redistribution of agency among more actors. So this is a thesis about toxicity, the European Union, collaborative production, scientific computational models, headaches, DIY kits, gases, human bodies, control rooms, blood, or politicians, among many others. The devices found throughout the work serve as an exceptional substrate for an investigation of digital infrastructures, enabling to challenge Smart City tropes. There is special attention paid to the effects of the air on the public space, acknowledging the silencing processes these infrastructures have been subjected to. Finally there is an outline of the opportunities arising for architecture and urban design when taking the air into account, to create new (queer) urban political ecologies between the air, urban infrastructures, the built environment, public and domestic spaces, and humans and more than humans.