928 resultados para Applications in Economics and Epidemiology


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Transcatheter aortic valve replacement (TAVR) as well as thoracic and abdominal endovascular aortic repair (TEVAR and EVAR) rely on accurate pre- and postprocedural imaging. This review article discusses the application of imaging, including preprocedural assessment and measurements as well as postprocedural imaging of complications. Furthermore, the exciting perspective of computational fluid dynamics (CFD) based on cross-sectional imaging is presented. TAVR is a minimally invasive alternative for treatment of aortic valve stenosis in patients with high age and multiple comorbidities who cannot undergo traditional open surgical repair. Given the lack of direct visualization during the procedure, pre- and peri-procedural imaging forms an essential part of the intervention. Computed tomography angiography (CTA) is the imaging modality of choice for preprocedural planning. Routine postprocedural follow-up is performed by echocardiography to confirm treatment success and detect complications. EVAR and TEVAR are minimally invasive alternatives to open surgical repair of aortic pathologies. CTA constitutes the preferred imaging modality for both preoperative planning and postoperative follow-up including detection of endoleaks. Magnetic resonance imaging is an excellent alternative to CT for postoperative follow-up, and is especially beneficial for younger patients given the lack of radiation. Ultrasound is applied in screening and postoperative follow-up of abdominal aortic aneurysms, but cross-sectional imaging is required once abnormalities are detected. Contrast-enhanced ultrasound may be as sensitive as CTA in detecting endoleaks.

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Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) provide metabolic information on the musculoskeletal system, thus helping to understand the biochemical and pathophysiological nature of numerous diseases. In particular, MRS has been used to study the energy metabolism of muscular tissue since the very beginning of magnetic resonance examinations in humans when small-bore magnets for studies of the limbs became available. Even more than in other organs, the observation of non-proton-nuclei was important in muscle tissue. Spatial localization was less demanding in these studies, however, high temporal resolution was necessary to follow metabolism during exercise and recovery. The observation of high-energy phosphates during and after the application of workload gives insight into oxidative phosphorylation, a process that takes place in the mitochondria and characterizes impaired mitochondrial function. New applications in insulin-resistant patients followed the development of volume-selective 1H-MRS in whole-body magnets. Nowadays, multinuclear MRS and MRSI of the musculoskeletal system provide several windows to vital biochemical pathways noninvasively. It is shown how MRS and MRSI have been used in numerous diseases to characterize an involvement of the muscular metabolism.

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We study pathwise invariances and degeneracies of random fields with motivating applications in Gaussian process modelling. The key idea is that a number of structural properties one may wish to impose a priori on functions boil down to degeneracy properties under well-chosen linear operators. We first show in a second order set-up that almost sure degeneracy of random field paths under some class of linear operators defined in terms of signed measures can be controlled through the two first moments. A special focus is then put on the Gaussian case, where these results are revisited and extended to further linear operators thanks to state-of-the-art representations. Several degeneracy properties are tackled, including random fields with symmetric paths, centred paths, harmonic paths, or sparse paths. The proposed approach delivers a number of promising results and perspectives in Gaussian process modelling. In a first numerical experiment, it is shown that dedicated kernels can be used to infer an axis of symmetry. Our second numerical experiment deals with conditional simulations of a solution to the heat equation, and it is found that adapted kernels notably enable improved predictions of non-linear functionals of the field such as its maximum.

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BACKGROUND & AIMS Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. An increasing number of reports describe HCC in the setting of obesity and diabetes, two major risk factors for non-alcoholic fatty liver disease (NAFLD). The increasing incidence of these conditions and the emerging evidence of HCC in non-cirrhotic NAFLD prioritize a better understanding of NAFLD-related HCC epidemiology and pathogenesis in order to target screening policies and develop preventive-therapeutic strategies. In this review, we focus on the epidemiological impact of this condition, suggesting a possible link between HCC in cryptogenic cirrhosis and NAFLD. Furthermore, we analyse the suggested pathogenic mechanisms and the possible preventive-therapeutic strategies.

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This paper analyzes data from a recently completed study of discrimination against African-American and Hispanic homebuyers when they visit mortgage lending institutions in two major metropolitan markets to make pre-application inquiries. It represents the first application of paired testing to rigorously measure discrimination in the mortgage lending process. The paired tests isolated significant levels of differential treatment on the basis of race and ethnicity in Chicago with African Americans and Hispanics receiving less information and assistance than comparable whites. Adverse treatment of African-Americans and Hispanics is also observed in Los Angeles for specific treatments, but the overall pattern of treatment observed did not differ statistically from equal treatment. Multivariate analyses for Chicago indicate that large lenders treat minorities more favorably than small lenders and that lenders with substantial numbers of applications from African-Americans treat African Americans more favorably than lenders with predominantly white application pools.

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Development of homology modeling methods will remain an area of active research. These methods aim to develop and model increasingly accurate three-dimensional structures of yet uncrystallized therapeutically relevant proteins e.g. Class A G-Protein Coupled Receptors. Incorporating protein flexibility is one way to achieve this goal. Here, I will discuss the enhancement and validation of the ligand-steered modeling, originally developed by Dr. Claudio Cavasotto, via cross modeling of the newly crystallized GPCR structures. This method uses known ligands and known experimental information to optimize relevant protein binding sites by incorporating protein flexibility. The ligand-steered models were able to model, reasonably reproduce binding sites and the co-crystallized native ligand poses of the β2 adrenergic and Adenosine 2A receptors using a single template structure. They also performed better than the choice of template, and crude models in a small scale high-throughput docking experiments and compound selectivity studies. Next, the application of this method to develop high-quality homology models of Cannabinoid Receptor 2, an emerging non-psychotic pain management target, is discussed. These models were validated by their ability to rationalize structure activity relationship data of two, inverse agonist and agonist, series of compounds. The method was also applied to improve the virtual screening performance of the β2 adrenergic crystal structure by optimizing the binding site using β2 specific compounds. These results show the feasibility of optimizing only the pharmacologically relevant protein binding sites and applicability to structure-based drug design projects.

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Nowadays, Computational Fluid Dynamics (CFD) solvers are widely used within the industry to model fluid flow phenomenons. Several fluid flow model equations have been employed in the last decades to simulate and predict forces acting, for example, on different aircraft configurations. Computational time and accuracy are strongly dependent on the fluid flow model equation and the spatial dimension of the problem considered. While simple models based on perfect flows, like panel methods or potential flow models can be very fast to solve, they usually suffer from a poor accuracy in order to simulate real flows (transonic, viscous). On the other hand, more complex models such as the full Navier- Stokes equations provide high fidelity predictions but at a much higher computational cost. Thus, a good compromise between accuracy and computational time has to be fixed for engineering applications. A discretisation technique widely used within the industry is the so-called Finite Volume approach on unstructured meshes. This technique spatially discretises the flow motion equations onto a set of elements which form a mesh, a discrete representation of the continuous domain. Using this approach, for a given flow model equation, the accuracy and computational time mainly depend on the distribution of nodes forming the mesh. Therefore, a good compromise between accuracy and computational time might be obtained by carefully defining the mesh. However, defining an optimal mesh for complex flows and geometries requires a very high level expertize in fluid mechanics and numerical analysis, and in most cases a simple guess of regions of the computational domain which might affect the most the accuracy is impossible. Thus, it is desirable to have an automatized remeshing tool, which is more flexible with unstructured meshes than its structured counterpart. However, adaptive methods currently in use still have an opened question: how to efficiently drive the adaptation ? Pioneering sensors based on flow features generally suffer from a lack of reliability, so in the last decade more effort has been made in developing numerical error-based sensors, like for instance the adjoint-based adaptation sensors. While very efficient at adapting meshes for a given functional output, the latter method is very expensive as it requires to solve a dual set of equations and computes the sensor on an embedded mesh. Therefore, it would be desirable to develop a more affordable numerical error estimation method. The current work aims at estimating the truncation error, which arises when discretising a partial differential equation. These are the higher order terms neglected in the construction of the numerical scheme. The truncation error provides very useful information as it is strongly related to the flow model equation and its discretisation. On one hand, it is a very reliable measure of the quality of the mesh, therefore very useful in order to drive a mesh adaptation procedure. On the other hand, it is strongly linked to the flow model equation, so that a careful estimation actually gives information on how well a given equation is solved, which may be useful in the context of _ -extrapolation or zonal modelling. The following work is organized as follows: Chap. 1 contains a short review of mesh adaptation techniques as well as numerical error prediction. In the first section, Sec. 1.1, the basic refinement strategies are reviewed and the main contribution to structured and unstructured mesh adaptation are presented. Sec. 1.2 introduces the definitions of errors encountered when solving Computational Fluid Dynamics problems and reviews the most common approaches to predict them. Chap. 2 is devoted to the mathematical formulation of truncation error estimation in the context of finite volume methodology, as well as a complete verification procedure. Several features are studied, such as the influence of grid non-uniformities, non-linearity, boundary conditions and non-converged numerical solutions. This verification part has been submitted and accepted for publication in the Journal of Computational Physics. Chap. 3 presents a mesh adaptation algorithm based on truncation error estimates and compares the results to a feature-based and an adjoint-based sensor (in collaboration with Jorge Ponsín, INTA). Two- and three-dimensional cases relevant for validation in the aeronautical industry are considered. This part has been submitted and accepted in the AIAA Journal. An extension to Reynolds Averaged Navier- Stokes equations is also included, where _ -estimation-based mesh adaptation and _ -extrapolation are applied to viscous wing profiles. The latter has been submitted in the Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. Keywords: mesh adaptation, numerical error prediction, finite volume Hoy en día, la Dinámica de Fluidos Computacional (CFD) es ampliamente utilizada dentro de la industria para obtener información sobre fenómenos fluidos. La Dinámica de Fluidos Computacional considera distintas modelizaciones de las ecuaciones fluidas (Potencial, Euler, Navier-Stokes, etc) para simular y predecir las fuerzas que actúan, por ejemplo, sobre una configuración de aeronave. El tiempo de cálculo y la precisión en la solución depende en gran medida de los modelos utilizados, así como de la dimensión espacial del problema considerado. Mientras que modelos simples basados en flujos perfectos, como modelos de flujos potenciales, se pueden resolver rápidamente, por lo general aducen de una baja precisión a la hora de simular flujos reales (viscosos, transónicos, etc). Por otro lado, modelos más complejos tales como el conjunto de ecuaciones de Navier-Stokes proporcionan predicciones de alta fidelidad, a expensas de un coste computacional mucho más elevado. Por lo tanto, en términos de aplicaciones de ingeniería se debe fijar un buen compromiso entre precisión y tiempo de cálculo. Una técnica de discretización ampliamente utilizada en la industria es el método de los Volúmenes Finitos en mallas no estructuradas. Esta técnica discretiza espacialmente las ecuaciones del movimiento del flujo sobre un conjunto de elementos que forman una malla, una representación discreta del dominio continuo. Utilizando este enfoque, para una ecuación de flujo dado, la precisión y el tiempo computacional dependen principalmente de la distribución de los nodos que forman la malla. Por consiguiente, un buen compromiso entre precisión y tiempo de cálculo se podría obtener definiendo cuidadosamente la malla, concentrando sus elementos en aquellas zonas donde sea estrictamente necesario. Sin embargo, la definición de una malla óptima para corrientes y geometrías complejas requiere un nivel muy alto de experiencia en la mecánica de fluidos y el análisis numérico, así como un conocimiento previo de la solución. Aspecto que en la mayoría de los casos no está disponible. Por tanto, es deseable tener una herramienta que permita adaptar los elementos de malla de forma automática, acorde a la solución fluida (remallado). Esta herramienta es generalmente más flexible en mallas no estructuradas que con su homóloga estructurada. No obstante, los métodos de adaptación actualmente en uso todavía dejan una pregunta abierta: cómo conducir de manera eficiente la adaptación. Sensores pioneros basados en las características del flujo en general, adolecen de una falta de fiabilidad, por lo que en la última década se han realizado grandes esfuerzos en el desarrollo numérico de sensores basados en el error, como por ejemplo los sensores basados en el adjunto. A pesar de ser muy eficientes en la adaptación de mallas para un determinado funcional, este último método resulta muy costoso, pues requiere resolver un doble conjunto de ecuaciones: la solución y su adjunta. Por tanto, es deseable desarrollar un método numérico de estimación de error más asequible. El presente trabajo tiene como objetivo estimar el error local de truncación, que aparece cuando se discretiza una ecuación en derivadas parciales. Estos son los términos de orden superior olvidados en la construcción del esquema numérico. El error de truncación proporciona una información muy útil sobre la solución: es una medida muy fiable de la calidad de la malla, obteniendo información que permite llevar a cabo un procedimiento de adaptación de malla. Está fuertemente relacionado al modelo matemático fluido, de modo que una estimación precisa garantiza la idoneidad de dicho modelo en un campo fluido, lo que puede ser útil en el contexto de modelado zonal. Por último, permite mejorar la precisión de la solución resolviendo un nuevo sistema donde el error local actúa como término fuente (_ -extrapolación). El presenta trabajo se organiza de la siguiente manera: Cap. 1 contiene una breve reseña de las técnicas de adaptación de malla, así como de los métodos de predicción de los errores numéricos. En la primera sección, Sec. 1.1, se examinan las estrategias básicas de refinamiento y se presenta la principal contribución a la adaptación de malla estructurada y no estructurada. Sec 1.2 introduce las definiciones de los errores encontrados en la resolución de problemas de Dinámica Computacional de Fluidos y se examinan los enfoques más comunes para predecirlos. Cap. 2 está dedicado a la formulación matemática de la estimación del error de truncación en el contexto de la metodología de Volúmenes Finitos, así como a un procedimiento de verificación completo. Se estudian varias características que influyen en su estimación: la influencia de la falta de uniformidad de la malla, el efecto de las no linealidades del modelo matemático, diferentes condiciones de contorno y soluciones numéricas no convergidas. Esta parte de verificación ha sido presentada y aceptada para su publicación en el Journal of Computational Physics. Cap. 3 presenta un algoritmo de adaptación de malla basado en la estimación del error de truncación y compara los resultados con sensores de featured-based y adjointbased (en colaboración con Jorge Ponsín del INTA). Se consideran casos en dos y tres dimensiones, relevantes para la validación en la industria aeronáutica. Este trabajo ha sido presentado y aceptado en el AIAA Journal. También se incluye una extensión de estos métodos a las ecuaciones RANS (Reynolds Average Navier- Stokes), en donde adaptación de malla basada en _ y _ -extrapolación son aplicados a perfiles con viscosidad de alas. Este último trabajo se ha presentado en los Actas de la Institución de Ingenieros Mecánicos, Parte G: Journal of Aerospace Engineering. Palabras clave: adaptación de malla, predicción del error numérico, volúmenes finitos

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Patent and trademark offices which run according to principles of new management have an inherent need for dependable forecasting data in planning capacity and service levels. The ability of the Spanish Office of Patents and Trademarks to carry out efficient planning of its resource needs requires the use of methods which allow it to predict the changes in the number of patent and trademark applications at different time horizons. The approach for the prediction of time series of Spanish patents and trademarks applications (1979e2009) was based on the use of different techniques of time series prediction in a short-term horizon. The methods used can be grouped into two specifics areas: regression models of trends and time series models. The results of this study show that it is possible to model the series of patents and trademarks applications with different models, especially ARIMA, with satisfactory model adjustment and relatively low error.

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Laser material processing is being extensively used in photovoltaic applications for both the fabrication of thin film modules and the enhancement of the crystalline silicon solar cells. The two temperature model for thermal diffusion was numerically solved in this paper. Laser pulses of 1064, 532 or 248 nm with duration of 35, 26 or 10 ns were considered as the thermal source leading to the material ablation. Considering high irradiance levels (108–109 W cm−2), a total absorption of the energy during the ablation process was assumed in the model. The materials analysed in the simulation were aluminium (Al) and silver (Ag), which are commonly used as metallic electrodes in photovoltaic devices. Moreover, thermal diffusion was also simulated for crystalline silicon (c-Si). A similar trend of temperature as a function of depth and time was found for both metals and c-Si regardless of the employed wavelength. For each material, the ablation depth dependence on laser pulse parameters was determined by means of an ablation criterion. Thus, after the laser pulse, the maximum depth for which the total energy stored in the material is equal to the vaporisation enthalpy was considered as the ablation depth. For all cases, the ablation depth increased with the laser pulse fluence and did not exhibit a clear correlation with the radiation wavelength. Finally, the experimental validation of the simulation results was carried out and the ability of the model with the initial hypothesis of total energy absorption to closely fit experimental results was confirmed.

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P2P applications are increasingly present on the web. We have identified a gap in current proposals when it comes to the use of traditional P2P overlays for real-time multimedia streaming. We analyze the possibilities and challenges to extend WebRTC in order to implement JavaScript APIs for P2P streaming algorithms.

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Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”.