Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Modelos de elementos finitos explícitos para explosiones en estructuras reticuladas de hormigón armado : aplicaciones al estudio del colapso de edificios

La frecuencia con la que se producen explosiones sobre edificios, ya sean accidentales o intencionadas, es reducida, pero sus efectos pueden ser catastróficos. Es deseable poder predecir de forma suficientemente precisa las consecuencias de estas acciones dinámicas sobre edificaciones civiles, entre las cuales las estructuras reticuladas de hormigón armado son una tipología habitual. En esta tesis doctoral se exploran distintas opciones prácticas para el modelado y cálculo numérico por ordenador de estructuras de hormigón armado sometidas a explosiones. Se emplean modelos numéricos de elementos finitos con integración explícita en el tiempo, que demuestran su capacidad efectiva para simular los fenómenos físicos y estructurales de dinámica rápida y altamente no lineales que suceden, pudiendo predecir los daños ocasionados tanto por la propia explosión como por el posible colapso progresivo de la estructura. El trabajo se ha llevado a cabo empleando el código comercial de elementos finitos LS-DYNA (Hallquist, 2006), desarrollando en el mismo distintos tipos de modelos de cálculo que se pueden clasificar en dos tipos principales: 1) modelos basados en elementos finitos de continuo, en los que se discretiza directamente el medio continuo mediante grados de libertad nodales de desplazamientos; 2) modelos basados en elementos finitos estructurales, mediante vigas y láminas, que incluyen hipótesis cinemáticas para elementos lineales o superficiales. Estos modelos se desarrollan y discuten a varios niveles distintos: 1) a nivel del comportamiento de los materiales, 2) a nivel de la respuesta de elementos estructurales tales como columnas, vigas o losas, y 3) a nivel de la respuesta de edificios completos o de partes significativas de los mismos. Se desarrollan modelos de elementos finitos de continuo 3D muy detallados que modelizan el hormigón en masa y el acero de armado de forma segregada. El hormigón se representa con un modelo constitutivo del hormigón CSCM (Murray et al., 2007), que tiene un comportamiento inelástico, con diferente respuesta a tracción y compresión, endurecimiento, daño por fisuración y compresión, y rotura. El acero se representa con un modelo constitutivo elastoplástico bilineal con rotura. Se modeliza la geometría precisa del hormigón mediante elementos finitos de continuo 3D y cada una de las barras de armado mediante elementos finitos tipo viga, con su posición exacta dentro de la masa de hormigón. La malla del modelo se construye mediante la superposición de los elementos de continuo de hormigón y los elementos tipo viga de las armaduras segregadas, que son obligadas a seguir la deformación del sólido en cada punto mediante un algoritmo de penalización, simulando así el comportamiento del hormigón armado. En este trabajo se denominarán a estos modelos simplificadamente como modelos de EF de continuo. Con estos modelos de EF de continuo se analiza la respuesta estructural de elementos constructivos (columnas, losas y pórticos) frente a acciones explosivas. Asimismo se han comparado con resultados experimentales, de ensayos sobre vigas y losas con distintas cargas de explosivo, verificándose una coincidencia aceptable y permitiendo una calibración de los parámetros de cálculo. Sin embargo estos modelos tan detallados no son recomendables para analizar edificios completos, ya que el elevado número de elementos finitos que serían necesarios eleva su coste computacional hasta hacerlos inviables para los recursos de cálculo actuales. Adicionalmente, se desarrollan modelos de elementos finitos estructurales (vigas y láminas) que, con un coste computacional reducido, son capaces de reproducir el comportamiento global de la estructura con una precisión similar. Se modelizan igualmente el hormigón en masa y el acero de armado de forma segregada. El hormigón se representa con el modelo constitutivo del hormigón EC2 (Hallquist et al., 2013), que también presenta un comportamiento inelástico, con diferente respuesta a tracción y compresión, endurecimiento, daño por fisuración y compresión, y rotura, y se usa en elementos finitos tipo lámina. El acero se representa de nuevo con un modelo constitutivo elastoplástico bilineal con rotura, usando elementos finitos tipo viga. Se modeliza una geometría equivalente del hormigón y del armado, y se tiene en cuenta la posición relativa del acero dentro de la masa de hormigón. Las mallas de ambos se unen mediante nodos comunes, produciendo una respuesta conjunta. En este trabajo se denominarán a estos modelos simplificadamente como modelos de EF estructurales. Con estos modelos de EF estructurales se simulan los mismos elementos constructivos que con los modelos de EF de continuo, y comparando sus respuestas estructurales frente a explosión se realiza la calibración de los primeros, de forma que se obtiene un comportamiento estructural similar con un coste computacional reducido. Se comprueba que estos mismos modelos, tanto los modelos de EF de continuo como los modelos de EF estructurales, son precisos también para el análisis del fenómeno de colapso progresivo en una estructura, y que se pueden utilizar para el estudio simultáneo de los daños de una explosión y el posterior colapso. Para ello se incluyen formulaciones que permiten considerar las fuerzas debidas al peso propio, sobrecargas y los contactos de unas partes de la estructura sobre otras. Se validan ambos modelos con un ensayo a escala real en el que un módulo con seis columnas y dos plantas colapsa al eliminar una de sus columnas. El coste computacional del modelo de EF de continuo para la simulación de este ensayo es mucho mayor que el del modelo de EF estructurales, lo cual hace inviable su aplicación en edificios completos, mientras que el modelo de EF estructurales presenta una respuesta global suficientemente precisa con un coste asumible. Por último se utilizan los modelos de EF estructurales para analizar explosiones sobre edificios de varias plantas, y se simulan dos escenarios con cargas explosivas para un edificio completo, con un coste computacional moderado. The frequency of explosions on buildings whether they are intended or accidental is small, but they can have catastrophic effects. Being able to predict in a accurate enough manner the consequences of these dynamic actions on civil buildings, among which frame-type reinforced concrete buildings are a frequent typology is desirable. In this doctoral thesis different practical options for the modeling and computer assisted numerical calculation of reinforced concrete structures submitted to explosions are explored. Numerical finite elements models with explicit time-based integration are employed, demonstrating their effective capacity in the simulation of the occurring fast dynamic and highly nonlinear physical and structural phenomena, allowing to predict the damage caused by the explosion itself as well as by the possible progressive collapse of the structure. The work has been carried out with the commercial finite elements code LS-DYNA (Hallquist, 2006), developing several types of calculation model classified in two main types: 1) Models based in continuum finite elements in which the continuous medium is discretized directly by means of nodal displacement degrees of freedom; 2) Models based on structural finite elements, with beams and shells, including kinematic hypothesis for linear and superficial elements. These models are developed and discussed at different levels: 1) material behaviour, 2) response of structural elements such as columns, beams and slabs, and 3) response of complete buildings or significative parts of them. Very detailed 3D continuum finite element models are developed, modeling mass concrete and reinforcement steel in a segregated manner. Concrete is represented with a constitutive concrete model CSCM (Murray et al., 2007), that has an inelastic behaviour, with different tension and compression response, hardening, cracking and compression damage and failure. The steel is represented with an elastic-plastic bilinear model with failure. The actual geometry of the concrete is modeled with 3D continuum finite elements and every and each of the reinforcing bars with beam-type finite elements, with their exact position in the concrete mass. The mesh of the model is generated by the superposition of the concrete continuum elements and the beam-type elements of the segregated reinforcement, which are made to follow the deformation of the solid in each point by means of a penalty algorithm, reproducing the behaviour of reinforced concrete. In this work these models will be called continuum FE models as a simplification. With these continuum FE models the response of construction elements (columns, slabs and frames) under explosive actions are analysed. They have also been compared with experimental results of tests on beams and slabs with various explosive charges, verifying an acceptable coincidence and allowing a calibration of the calculation parameters. These detailed models are however not advised for the analysis of complete buildings, as the high number of finite elements necessary raises its computational cost, making them unreliable for the current calculation resources. In addition to that, structural finite elements (beams and shells) models are developed, which, while having a reduced computational cost, are able to reproduce the global behaviour of the structure with a similar accuracy. Mass concrete and reinforcing steel are also modeled segregated. Concrete is represented with the concrete constitutive model EC2 (Hallquist et al., 2013), which also presents an inelastic behaviour, with a different tension and compression response, hardening, compression and cracking damage and failure, and is used in shell-type finite elements. Steel is represented once again with an elastic-plastic bilineal with failure constitutive model, using beam-type finite elements. An equivalent geometry of the concrete and the steel is modeled, considering the relative position of the steel inside the concrete mass. The meshes of both sets of elements are bound with common nodes, therefore producing a joint response. These models will be called structural FE models as a simplification. With these structural FE models the same construction elements as with the continuum FE models are simulated, and by comparing their response under explosive actions a calibration of the former is carried out, resulting in a similar response with a reduced computational cost. It is verified that both the continuum FE models and the structural FE models are also accurate for the analysis of the phenomenon of progressive collapse of a structure, and that they can be employed for the simultaneous study of an explosion damage and the resulting collapse. Both models are validated with an experimental full-scale test in which a six column, two floors module collapses after the removal of one of its columns. The computational cost of the continuum FE model for the simulation of this test is a lot higher than that of the structural FE model, making it non-viable for its application to full buildings, while the structural FE model presents a global response accurate enough with an admissible cost. Finally, structural FE models are used to analyze explosions on several story buildings, and two scenarios are simulated with explosive charges for a full building, with a moderate computational cost.

Método computacional para la aceleración de análisis paramétricos de modificaciones locales en estructuras complejas sometidas a cargas dinámicas

Dentro del análisis y diseño estructural surgen frecuentemente problemas de ingeniería donde se requiere el análisis dinámico de grandes modelos de elementos finitos que llegan a millones de grados de libertad y emplean volúmenes de datos de gran tamaño. La complejidad y dimensión de los análisis se dispara cuando se requiere realizar análisis paramétricos. Este problema se ha abordado tradicionalmente desde diversas perspectivas: en primer lugar, aumentando la capacidad tanto de cálculo como de memoria de los sistemas informáticos empleados en los análisis. En segundo lugar, se pueden simplificar los análisis paramétricos reduciendo su número o detalle y por último se puede recurrir a métodos complementarios a los elementos .nitos para la reducción de sus variables y la simplificación de su ejecución manteniendo los resultados obtenidos próximos al comportamiento real de la estructura. Se propone el empleo de un método de reducción que encaja en la tercera de las opciones y consiste en un análisis simplificado que proporciona una solución para la respuesta dinámica de una estructura en el subespacio modal complejo empleando un volumen de datos muy reducido. De este modo se pueden realizar análisis paramétricos variando múltiples parámetros, para obtener una solución muy aproximada al objetivo buscado. Se propone no solo la variación de propiedades locales de masa, rigidez y amortiguamiento sino la adición de grados de libertad a la estructura original para el cálculo de la respuesta tanto permanente como transitoria. Adicionalmente, su facilidad de implementación permite un control exhaustivo sobre las variables del problema y la implementación de mejoras como diferentes formas de obtención de los autovalores o la eliminación de las limitaciones de amortiguamiento en la estructura original. El objetivo del método se puede considerar similar a los que se obtienen al aplicar el método de Guyan u otras técnicas de reducción de modelos empleados en dinámica estructural. Sin embargo, aunque el método permite ser empleado en conjunción con otros para obtener las ventajas de ambos, el presente procedimiento no realiza la condensación del sistema de ecuaciones, sino que emplea la información del sistema de ecuaciones completa estudiando tan solo la respuesta en las variables apropiadas de los puntos de interés para el analista. Dicho interés puede surgir de la necesidad de obtener la respuesta de las grandes estructuras en unos puntos determinados o de la necesidad de modificar la estructura en zonas determinadas para cambiar su comportamiento (respuesta en aceleraciones, velocidades o desplazamientos) ante cargas dinámicas. Por lo tanto, el procedimiento está particularmente indicado para la selección del valor óptimo de varios parámetros en grandes estructuras (del orden de cientos de miles de modos) como pueden ser la localización de elementos introducidos, rigideces, masas o valores de amortiguamientos viscosos en estudios previos en los que diversas soluciones son planteadas y optimizadas, y que en el caso de grandes estructuras, pueden conllevar un número de simulaciones extremadamente elevado para alcanzar la solución óptima. Tras plantear las herramientas necesarias y desarrollar el procedimiento, se propone un caso de estudio para su aplicación al modelo de elementos .nitos del UAV MILANO desarrollado por el Instituto Nacional de Técnica Aeroespacial. A dicha estructura se le imponen ciertos requisitos al incorporar un equipo en aceleraciones en punta de ala izquierda y desplazamientos en punta de ala derecha en presencia de la sustentación producida por una ráfaga continua de viento de forma sinusoidal. La modificación propuesta consiste en la adición de un equipo en la punta de ala izquierda, bien mediante un anclaje rígido, bien unido mediante un sistema de reducción de la respuesta dinámica con propiedades de masa, rigidez y amortiguamiento variables. El estudio de los resultados obtenidos permite determinar la optimización de los parámetros del sistema de atenuación por medio de múltiples análisis dinámicos de forma que se cumplan de la mejor forma posible los requisitos impuestos con la modificación. Se comparan los resultados con los obtenidos mediante el uso de un programa comercial de análisis por el método de los elementos .nitos lográndose soluciones muy aproximadas entre el modelo completo y el reducido. La influencia de diversos factores como son el amortiguamiento modal de la estructura original, el número de modos retenidos en la truncatura o la precisión proporcionada por el barrido en frecuencia se analiza en detalle para, por último, señalar la eficiencia en términos de tiempo y volumen de datos de computación que ofrece el método propuesto en comparación con otras aproximaciones. Por lo tanto, puede concluirse que el método propuesto se considera una opción útil y eficiente para el análisis paramétrico de modificaciones locales en grandes estructuras. ABSTRACT When developing structural design and analysis some projects require dynamic analysis of large finite element models with millions of degrees of freedom which use large size data .les. The analysis complexity and size grow if a parametric analysis is required. This problem has been approached traditionally in several ways: one way is increasing the power and the storage capacity of computer systems involved in the analysis. Other obvious way is reducing the total amount of analyses and their details. Finally, complementary methods to finite element analysis can also be employed in order to limit the number of variables and to reduce the execution time keeping the results as close as possible to the actual behaviour of the structure. Following this third option, we propose a model reduction method that is based in a simplified analysis that supplies a solution for the dynamic response of the structure in the complex modal space using few data. Thereby, parametric analysis can be done varying multiple parameters so as to obtain a solution which complies with the desired objetive. We propose not only mass, stiffness and damping variations, but also addition of degrees of freedom to the original structure in order to calculate the transient and steady-state response. Additionally, the simple implementation of the procedure allows an in-depth control of the problem variables. Furthermore, improvements such as different ways to obtain eigenvectors or to remove damping limitations of the original structure are also possible. The purpose of the procedure is similar to that of using the Guyan or similar model order reduction techniques. However, in our method we do not perform a true model order reduction in the traditional sense. Furthermore, additional gains, which we do not explore herein, can be obtained through the combination of this method with traditional model-order reduction procedures. In our procedure we use the information of the whole system of equations is used but only those nodes of interest to the analyst are processed. That interest comes from the need to obtain the response of the structure at specific locations or from the need to modify the structure at some suitable positions in order to change its behaviour (acceleration, velocity or displacement response) under dynamic loads. Therefore, the procedure is particularly suitable for parametric optimization in large structures with >100000 normal modes such as position of new elements, stiffness, mass and viscous dampings in previous studies where different solutions are devised and optimized, and in the case of large structures, can carry an extremely high number of simulations to get the optimum solution. After the introduction of the required tools and the development of the procedure, a study case is proposed with use the finite element model (FEM) of the MILANO UAV developed by Instituto Nacional de Técnica Aeroespacial. Due to an equipment addition, certain acceleration and displacement requirements on left wing tip and right wing tip, respectively, are imposed. The structure is under a continuous sinusoidal wind gust which produces lift. The proposed modification consists of the addition of an equipment in left wing tip clamped through a rigid attachment or through a dynamic response reduction system with variable properties of mass, stiffness and damping. The analysis of the obtained results allows us to determine the optimized parametric by means of multiple dynamic analyses in a way such that the imposed requirements have been accomplished in the best possible way. The results achieved are compared with results from a commercial finite element analysis software, showing a good correlation. Influence of several factors such as the modal damping of the original structure, the number of modes kept in the modal truncation or the precission given by the frequency sweep is analyzed. Finally, the efficiency of the proposed method is addressed in tems of computational time and data size compared with other approaches. From the analyses performed, we can conclude that the proposed method is a useful and efficient option to perform parametric analysis of possible local modifications in large structures.

Quantitative high performance liquid chromatography/tandem mass spectrometric analysis of the four classes of F2-isoprostanes in human urine

Isoprostanes (iPs) are free radical catalyzed prostaglandin isomers. Analysis of individual isomers of PGF2α—F2-iPs—in urine has reflected lipid peroxidation in humans. However, up to 64 F2-iPs may be formed, and it is unknown whether coordinate generation, disposition, and excretion of F2-iPs occurs in humans. To address this issue, we developed methods to measure individual members of the four structural classes of F2-iPs, using liquid chromatography/tandem mass spectrometry (LC/MS/MS), in which sample preparation is minimized. Authentic standards of F2-iPs of classes III, IV, V, and VI were used to identify class-specific ions for multiple reaction monitoring. Using iPF2α-VI as a model compound, we demonstrated the reproducibility of the assay in human urine. Urinary levels of all F2-iPs measured were elevated in patients with familial hypercholesterolemia. However, only three of eight F2-iPs were elevated in patients with congestive heart failure, compared with controls. Paired analyses by GC/MS and LC/MS/MS of iPF2α-VI in hypercholesterolemia and of 8,12-iso-iPF2α-VI in congestive heart failure were highly correlated. This approach will permit high throughput analysis of multiple iPs in human disease.

Origin and evolution of circular waves and spirals in Dictyostelium discoideum territories.

Randomly distributed Dictyostelium discoideum cells form cooperative territories by signaling to each other with cAMP. Cells initiate the process by sending out pulsatile signals, which propagate as waves. With time, circular and spiral patterns form. We show that by adding spatial and temporal noise to the levels of an important regulator of external cAMP levels, the cAMP phosphodiesterase inhibitor, we can explain the natural progression of the system from randomly firing cells to circular waves whose symmetries break to form double- and single- or multi-armed spirals. When phosphodiesterase inhibitor is increased with time, mimicking experimental data, the wavelength of the spirals shortens, and a proportion of them evolve into pairs of connected spirals. We compare these results to recent experiments, finding that the temporal and spatial correspondence between experiment and model is very close.

Alternativas de análise para experimentos G × E multiatributo

Geralmente, nos experimentos genótipo por ambiente (G × E) é comum observar o comportamento dos genótipos em relação a distintos atributos nos ambientes considerados. A análise deste tipo de experimentos tem sido abordada amplamente para o caso de um único atributo. Nesta tese são apresentadas algumas alternativas de análise considerando genótipos, ambientes e atributos simultaneamente. A primeira, é baseada no método de mistura de máxima verossimilhança de agrupamento - Mixclus e a análise de componentes principais de 3 modos - 3MPCA, que permitem a análise de tabelas de tripla entrada, estes dois métodos têm sido muito usados na área da psicologia e da química, mas pouco na agricultura. A segunda, é uma metodologia que combina, o modelo de efeitos aditivos com interação multiplicativa - AMMI, modelo eficiente para a análise de experimentos (G × E) com um atributo e a análise de procrustes generalizada, que permite comparar configurações de pontos e proporcionar uma medida numérica de quanto elas diferem. Finalmente, é apresentada uma alternativa para realizar imputação de dados nos experimentos (G × E), pois, uma situação muito frequente nestes experimentos, é a presença de dados faltantes. Conclui-se que as metodologias propostas constituem ferramentas úteis para a análise de experimentos (G × E) multiatributo.

Imputação de dados em experimentos multiambientais: novos algoritmos utilizando a decomposição por valores singulares

As análises biplot que utilizam os modelos de efeitos principais aditivos com inter- ação multiplicativa (AMMI) requerem matrizes de dados completas, mas, frequentemente os ensaios multiambientais apresentam dados faltantes. Nesta tese são propostas novas metodologias de imputação simples e múltipla que podem ser usadas para analisar da- dos desbalanceados em experimentos com interação genótipo por ambiente (G×E). A primeira, é uma nova extensão do método de validação cruzada por autovetor (Bro et al, 2008). A segunda, corresponde a um novo algoritmo não-paramétrico obtido por meio de modificações no método de imputação simples desenvolvido por Yan (2013). Também é incluído um estudo que considera sistemas de imputação recentemente relatados na literatura e os compara com o procedimento clássico recomendado para imputação em ensaios (G×E), ou seja, a combinação do algoritmo de Esperança-Maximização com os modelos AMMI ou EM-AMMI. Por último, são fornecidas generalizações da imputação simples descrita por Arciniegas-Alarcón et al. (2010) que mistura regressão com aproximação de posto inferior de uma matriz. Todas as metodologias têm como base a decomposição por valores singulares (DVS), portanto, são livres de pressuposições distribucionais ou estruturais. Para determinar o desempenho dos novos esquemas de imputação foram realizadas simulações baseadas em conjuntos de dados reais de diferentes espécies, com valores re- tirados aleatoriamente em diferentes porcentagens e a qualidade das imputações avaliada com distintas estatísticas. Concluiu-se que a DVS constitui uma ferramenta útil e flexível na construção de técnicas eficientes que contornem o problema de perda de informação em matrizes experimentais.

Uma nova arquitetura para Internet das Coisas com análise e reconhecimento de padrões e processamento com Big Data.

A Internet das Coisas é um novo paradigma de comunicação que estende o mundo virtual (Internet) para o mundo real com a interface e interação entre objetos. Ela possuirá um grande número de dispositivos heteregôneos interconectados, que deverá gerar um grande volume de dados. Um dos importantes desafios para seu desenvolvimento é se guardar e processar esse grande volume de dados em aceitáveis intervalos de tempo. Esta pesquisa endereça esse desafio, com a introdução de serviços de análise e reconhecimento de padrões nas camadas inferiores do modelo de para Internet das Coisas, que procura reduzir o processamento nas camadas superiores. Na pesquisa foram analisados os modelos de referência para Internet das Coisas e plataformas para desenvolvimento de aplicações nesse contexto. A nova arquitetura de implementada estende o LinkSmart Middeware pela introdução de um módulo para reconhecimento de padrões, implementa algoritmos para estimação de valores, detecção de outliers e descoberta de grupos nos dados brutos, oriundos de origens de dados. O novo módulo foi integrado à plataforma para Big Data Hadoop e usa as implementações algorítmicas do framework Mahout. Este trabalho destaca a importância da comunicação cross layer integrada à essa nova arquitetura. Nos experimentos desenvolvidos na pesquisa foram utilizadas bases de dados reais, provenientes do projeto Smart Santander, de modo a validar da nova arquitetura de IoT integrada aos serviços de análise e reconhecimento de padrões e a comunicação cross-layer.

Australian water mass variations from GRACE data linked to Indo-Pacific climate variability

Time-variable gravity data from the Gravity Recovery And Climate Experiment (GRACE) mission are used to study total water content over Australia for the period 2002–2010. A time-varying annual signal explains 61% of the variance of the data, in good agreement with two independent estimates of the same quantity from hydrological models. Water mass content variations across Australia are linked to Pacific and Indian Ocean variability, associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), respectively. From 1989, positive (negative) IOD phases were related to anomalously low (high) precipitation in southeastern Australia, associated with a reduced (enhanced) tropical moisture flux. In particular, the sustained water mass content reduction over central and southern regions of Australia during the period 2006–2008 is associated with three consecutive positive IOD events.

On the steric and mass-induced contributions to the annual sea level variations in the Mediterranean Sea

The sea level variation (SLVtotal) is the sum of two major contributions: steric and mass-induced. The steric SLVsteric is that resulting from the thermal and salinity changes in a given water column. It only involves volume change, hence has no gravitational effect. The mass-induced SLVmass, on the other hand, arises from adding or subtracting water mass to or from the water column and has direct gravitational signature. We examine the closure of the seasonal SLV budget and estimate the relative importance of the two contributions in the Mediterranean Sea as a function of time. We use ocean altimetry data (from TOPEX/Poseidon, Jason 1, ERS, and ENVISAT missions) to estimate SLVtotal, temperature, and salinity data (from the Estimating the Circulation and Climate of the Ocean ocean model) to estimate SLVsteric, and time variable gravity data (from Gravity Recovery and Climate Experiment (GRACE) Project, April 2002 to July 2004) to estimate SLVmass. We find that the annual cycle of SLVtotal in the Mediterranean is mainly driven by SLVsteric but moderately offset by SLVmass. The agreement between the seasonal SLVmass estimations from SLVtotal – SLVsteric and from GRACE is quite remarkable; the annual cycle reaches the maximum value in mid-February, almost half a cycle later than SLVtotal or SLVsteric, which peak by mid-October and mid-September, respectively. Thus, when sea level is rising (falling), the Mediterranean Sea is actually losing (gaining) mass. Furthermore, as SLVmass is balanced by vertical (precipitation minus evaporation, P–E) and horizontal (exchange of water with the Atlantic, Black Sea, and river runoff) mass fluxes, we compared it with the P–E determined from meteorological data to estimate the annual cycle of the horizontal flux.

Pulse phase-coherent timing and spectroscopy of CXOU J164710.2−45521 outbursts

We present a long-term phase-coherent timing analysis and pulse-phase resolved spectroscopy for the two outbursts observed from the transient anomalous X-ray pulsar CXOU J164710.2−455216. For the first outburst we used 11 Chandra and XMM–Newton observations between 2006 September and 2009 August, the longest baseline yet for this source. We obtain a coherent timing solution with P = 10.61065583(4) s, Ṗ = 9.72(1) × 10−13 s s−1 and P̈ = –1.05(5) × 10−20 s s−2. Under the standard assumptions this implies a surface dipolar magnetic field of ∼1014 G, confirming this source as a standard B magnetar. We also study the evolution of the pulse profile (shape, intensity and pulsed fraction) as a function of time and energy. Using the phase-coherent timing solution we perform a phase-resolved spectroscopy analysis, following the spectral evolution of pulse-phase features, which hints at the physical processes taking place on the star. The results are discussed from the perspective of magnetothermal evolution models and the untwisting magnetosphere model. Finally, we present similar analysis for the second, less intense, 2011 outburst. For the timing analysis we used Swift data together with 2 XMM–Newton and Chandra pointings. The results inferred for both outbursts are compared and briefly discussed in a more general framework.

Explaining transactions in time banks in economic crisis

This article studies the services exchanged in a particular Spanish time bank. Using data from users and transactions, we analyse the users’ profile as well as the determinants of providing and receiving different services. Our results show that the representative user is a Spanish female, not married, middle aged, highly educated and unemployed. We also find differences in the personal characteristics driving the supply and demand of services.

Filling the gap: open economy considerations for more reliable potential output estimates. Bruegel Working Paper 2015/11, October 2015

This paper argues that the Phillips curve relationship is not sufficient to trace back the output gap, because the effect of excess demand is not symmetric across tradeable and non-tradeable sectors. In the non-tradeable sector, excess demand creates excess employment and inflation via the Phillips curve, while in the tradeable sector much of the excess demand is absorbed by the trade balance. We set up an unobserved-components model including both a Phillips curve and a current account equation to estimate ‘sustainable output’ for 45 countries. Our estimates for many countries differ substantially from the potential output estimates of the European Commission, IMF and OECD. We assemble a comprehensive real-time dataset to estimate our model on data which was available in each year from 2004-15. Our model was able to identify correctly the sign of pre-crisis output gaps using real time data for countries such as the United States, Spain and Ireland, in contrast to the estimates of the three institutions, which estimated negative output gaps real-time, while their current estimates for the pre-crisis period suggest positive gaps. In the past five years the annual output gap estimate revisions of our model, the European Commission, IMF, OECD and the Hodrick-Prescott filter were broadly similar in the range of 0.5-1.0 percent of GDP for advanced countries. Such large revisions are worrisome, because the European fiscal framework can translate the imprecision in output gap estimates into poorly grounded fiscal policymaking in the EU.

Analysis of analogue models by helical X-ray computed tomography

The aim of analogue model experiments in geology is to simulate structures in nature under specific imposed boundary conditions using materials whose rheological properties are similar to those of rocks in nature. In the late 1980s, X-ray computed tomography (CT) was first applied to the analysis of such models. In early studies only a limited number of cross-sectional slices could be recorded because of the time involved in CT data acquisition, the long cooling periods for the X-ray source and computational capacity. Technological improvements presently allow an almost unlimited number of closely spaced serial cross-sections to be acquired and calculated. Computer visualization software allows a full 3D analysis of every recorded stage. Such analyses are especially valuable when trying to understand complex geological structures, commonly with lateral changes in 3D geometry. Periodic acquisition of volumetric data sets in the course of the experiment makes it possible to carry out a 4D analysis of the model, i.e. 3D analysis through time. Examples are shown of 4D analysis of analogue models that tested the influence of lateral rheological changes on the structures obtained in contractional and extensional settings.

Downscaled land surface temperatures obtained by a particle smoothing approach, with links to NetCDF files

This dataset contains continuous time series of land surface temperature (LST) at spatial resolution of 300m around the 12 experimental sites of the PAGE21 project (grant agreement number 282700, funded by the EC seventh Framework Program theme FP7-ENV-2011). This dataset was produced from hourly LST time series at 25km scale, retrieved from SSM/I data (André et al., 2015, doi:10.1016/j.rse.2015.01.028) and downscaled to 300m using a dynamic model and a particle smoothing approach. This methodology is based on two main assumptions. First, LST spatial variability is mostly explained by land cover and soil hydric state. Second, LST is unique for a land cover class within the low resolution pixel. Given these hypotheses, this variable can be estimated using a land cover map and a physically based land surface model constrained with observations using a data assimilation process. This methodology described in Mechri et al. (2014, doi:10.1002/2013JD020354) was applied to the ORCHIDEE land surface model (Krinner et al., 2005, doi:10.1029/2003GB002199) to estimate prior values of each land cover class provided by the ESA CCI-Land Cover product (Bontemps et al., 2013) at 300m resolution . The assimilation process (particle smoother) consists in simulating ensemble of LST time series for each land cover class and for a large number of parameter sets. For each parameter set, the resulting temperatures are aggregated considering the grid fraction of each land cover and compared to the coarse observations. Miniminizing the distance between the aggregated model solutions and the observations allow us to select the simulated LST and the corresponding parameter sets which fit the observations most closely. The retained parameter sets are then duplicated and randomly perturbed before simulating the next time window. At the end, the most likely LST of each land cover class are estimated and used to reconstruct LST maps at 300m resolution using ESA CCI-Land Cover. The resulting temperature maps on which ice pixels were masked, are provided at daily time step during the nine-year analysis period (2000-2009).