Precisiones para el empleo del método del módulo de balasto en edificación

It has only been recently that computers were available to analyze the combined of structure and foundation, introducing more accuracy in structural analysis. Obviously, this technique involves the soil modeling as necessary. The model of the coefficient of subgrade reaction has been often used for this task. At last, the accuracy of the model depends on the agreement between predictions and soil behavior. The appropriate use of Winkler theory and the suitable determination of k are essential conditions for a good analysis. Unfortunately, manuals are not sufficiently concerned with this problem. The limits of this theory, some formulations for the determination of the k values and a few improvements of the model are described in this paper.Actualmente las herramientas informáticas permiten el cálculo conjunto de la estructura y cimentación, lo que introduce un mayor grado de precisión en el dimensionado de ambas. Obviamente, esta técnica implica la modelización del terreno como requisito sine qua non, modelización que frecuentemente ha sido resuelta recurriendo al método del módulo de balasto. En última instancia, la precisión del modelo de cálculo así generado va a depender del ajuste entre el comportamiento del terreno real y el representado por el modelo. El empleo del modelo dentro de sus límites de aplicación, así como la caracterización del suelo mediante un valor del módulo de balasto apropiado, son condiciones prioritarias para un cálculo correcto. Desgraciadamente, pese a su trascendencia, el problema no recibe un tratamiento adecuado en los manuales. Este texto pasa revista a los condicionantes del método, recoge diversas formulaciones para la determinación del módulo a emplear en función del tipo de terreno y de cimiento y reseña varias correcciones que diversos autores han propuesto para mejorar el modelo

Las bóvedas pétreas nervadas de Galicia: identificación de soluciones

This article presents the different groups of solutions of ribbed stone vaults on four supports that exist in Galicia and it plots them at the same scale. A small group of vaults on eight supports is also included. In order to classify the samples, a system based on the constructive features of the vaults has been used, taking into account their number of supports and the different types of nerves. The systematic approach used allows determining both the dimensions with which the different types of vaults were built as well as the solutions traditionally overlooked.El artículo presenta los distintos grupos de soluciones de bóvedas pétreas nervadas sobre cuatro apoyos que existen en Galicia, representándolas gráficamente a la misma escala. Complementariamente se incluye también un pequeño grupo de bóvedas sobre ocho apoyos. Para clasificar los ejemplos se ha empleado un sistema basado en los rasgos constructivos de las bóvedas, que tiene en cuenta el número de apoyos de éstas y los distintos tipos de nervios presentes. Este criterio sistemático permite apreciar tanto soluciones que tradicionalmente han pasado desapercibidas como las dimensiones con las éstas que han sido construidas

EVM and Achievable Data Rate Analysis of Clipped OFDM Signals in Visible Light Communication

Orthogonal frequency division multiplexing (OFDM) has been considered for visible light communication (VLC) thanks to its ability to boost data rates as well as its robustness against frequency-selective fading channels. A major disadvantage of OFDM is the large dynamic range of its time-domain waveforms, making OFDM vulnerable to nonlinearity of light emitting diodes (LEDs). DC biased optical OFDM (DCO-OFDM) and asymmetrically clipped optical OFDM (ACO-OFDM) are two popular OFDM techniques developed for the VLC. In this paper, we will analyze the performance of the DCO-OFDM and ACO-OFDM signals in terms of error vector magnitude (EVM), signal-to-distortion ratio (SDR), and achievable data rates under both average optical power and dynamic optical power constraints. EVM is a commonly used metric to characterize distortions. We will describe an approach to numerically calculate the EVM for DCO-OFDM and ACO-OFDM. We will derive the optimum biasing ratio in the sense of minimizing EVM for DCO-OFDM. Additionally, we will formulate the EVM minimization problem as a convex linear optimization problem and obtain an EVM lower bound against which to compare the DCO-OFDM and ACO-OFDM techniques. We will prove that the ACO-OFDM can achieve the lower bound. Average optical power and dynamic optical power are two main constraints in VLC. We will derive the achievable data rates under these two constraints for both additive white Gaussian noise (AWGN) channel and frequency-selective channel. We will compare the performance of DCO-OFDM and ACO-OFDM under different power constraint scenarios

Algoritmo Level-set para segmentación hepática en TAC con Restricciones de curvatura local

Actas de: XXIX Congreso Anual de la Sociedad Espñaola de Ingeniería Biomédica (CASEIB 2011). Cáceres, 16-18 Noviembre 2011.La cirugía hepática avanzada requiere de una precisa planificación pre-operatoria en la que tanto la segmentación anatómica como la estimación del volumen hepático remanente tienen una importancia clave a la hora de evitar un fallo hepático postoperatorio. En este contexto, algoritmos basados en level-sets han logrado mejores resultados que otros, especialmente cuando se tratan casos con un parénquima hepático alterado o en hígados previamente resecados. Con el objetivo de mejorar las medidas de volumen hepático funcional, se proponen dos estrategias para completar y realzar algoritmos previos basados en level-sets: una estrategia optimizada multi-resolución con curvatura adaptativa y corrección/refinamiento de detalles, junto con un paso semiautomático adicional en el que se imponen restricciones de curvatura local. Los resultados muestran segmentaciones robustas y precisas, especialmente en estructuras alargadas, detectando lesiones internas y evitando fugas o escapes a estructuras proximales.Este trabajo está parcialmente apoyado por los proyectos de investigación PI09/91058, PI09/91065, ENTEPRASE PS-300000-2009-5, AMIT-CDTI, TEC2010-21619-C04 and PRECISION IPT-300000-2010-3, del Ministerio de Ciencia e Innovación de España, el proyecto ARTEMIS de la Comunidad de Madrid y la ayuda de los fondos FEDER de la Unión Europea.Publicad

Neutrophil C5a receptor and the outcome in a rat model of sepsis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154259/1/fsb2fj030009fje.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154259/2/fsb2fj030009fje-sup-0001.pd

Organ-focused mutual information for nonrigid multimodal registration of liver CT and Gd–EOB–DTPA-enhanced MRI

Accurate detection of liver lesions is of great importance in hepatic surgery planning. Recent studies have shown that the detection rate of liver lesions is significantly higher in gadoxetic acid-enhanced magnetic resonance imaging (Gd–EOB–DTPA-enhanced MRI) than in contrast-enhanced portal-phase computed tomography (CT); however, the latter remains essential because of its high specificity, good performance in estimating liver volumes and better vessel visibility. To characterize liver lesions using both the above image modalities, we propose a multimodal nonrigid registration framework using organ-focused mutual information (OF-MI). This proposal tries to improve mutual information (MI) based registration by adding spatial information, benefiting from the availability of expert liver segmentation in clinical protocols. The incorporation of an additional information channel containing liver segmentation information was studied. A dataset of real clinical images and simulated images was used in the validation process. A Gd–EOB–DTPA-enhanced MRI simulation framework is presented. To evaluate results, warping index errors were calculated for the simulated data, and landmark-based and surface-based errors were calculated for the real data. An improvement of the registration accuracy for OF-MI as compared with MI was found for both simulated and real datasets. Statistical significance of the difference was tested and confirmed in the simulated dataset (p < 0.01)