979 resultados para Piecewise linear techniques


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The purpose of this retrospective study was to intra-individually compare the image quality of computed radiography (CR) and low-dose linear-slit digital radiography (LSDR) for supine chest radiographs. A total of 90 patients (28 female, 62 male; mean age, 55.1 years) imaged with CR and LSDR within a mean time interval of 2.8 days +/- 3.0 were included in this study. Two independent readers evaluated the image quality of CR and LSDR based on modified European Guidelines for Quality Criteria for chest X-ray. The Wilcoxon test was used to analyse differences between the techniques. The overall image quality of LSDR was significantly better than the quality of CR (9.75 vs 8.16 of a maximum score of 10; p < 0.001). LSDR performed significantly better than CR for delineation of anatomical structures in the mediastinum and the retrocardiac lung (p < 0.001). CR was superior to LSDR for visually sharp delineation of the lung vessels and the thin linear structures in the lungs. We conclude that LSDR yields better image quality and may be more suitable for excluding significant pathological features of the chest in areas with high attenuation compared with CR.

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OBJECTIVES The aim of this study was to analyze trigger activity in the long-term follow-up after left atrial (LA) linear ablation. BACKGROUND Interventional strategies for curative treatment of atrial fibrillation (AF) are targeted at the triggers and/or the maintaining substrate. After substrate modification using nonisolating linear lesions, the activity of triggers is unknown. METHODS With the LA linear lesion concept, 129 patients were treated using intraoperative ablation with minimal invasive surgical techniques. Contiguous radiofrequency energy-induced lesion lines involving the mitral annulus and the orifices of the pulmonary veins without isolation were placed under direct vision. RESULTS After a mean follow-up of 3.6 +/- 0.4 years, atrial ectopy, atrial runs, and reoccurrence of AF episodes were analyzed by digital 7-day electrocardiograms in 30 patients. Atrial ectopy was present in all patients. Atrial runs were present in 25 of 30 patients (83%), with a median number of 9 runs per patient/week (range 1 to 321) and a median duration of 1.2 s/run (range 0.7 to 25), without a significant difference in atrial ectopy and atrial runs between patients with former paroxysmal (n = 17) or persistent AF (n = 13). Overall, 87% of all patients were completely free from AF without antiarrhythmic drugs. CONCLUSIONS A detailed rhythm analysis late after specific LA linear lesion ablation shows that trigger activity remains relatively frequent but short and does not induce AF episodes in most patients. The long-term success rate of this concept is high in patients with paroxysmal or persistent AF.

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The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

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BACKGROUND Since the pioneering work of Jacobson and Suarez, microsurgery has steadily progressed and is now used in all surgical specialities, particularly in plastic surgery. Before performing clinical procedures it is necessary to learn the basic techniques in the laboratory. OBJECTIVE To assess an animal model, thereby circumventing the following issues: ethical rules, cost, anesthesia and training time. METHODS Between July 2012 and September 2012, 182 earthworms were used for 150 microsurgical trainings to simulate discrepancy microanastomoses. Training was undertaken over 10 weekly periods. Each training session included 15 simulations of microanastomoses performed using the Harashina technique (earthworm diameters >1.5 mm [n=5], between 1.0 mm and 1.5 mm [n=5], and <1.0 mm [n=5]). The technique is presented and documented. A linear model with main variable as the number of the week (as a numeric covariate) and the size of the animal (as a factor) was used to determine the trend in time of anastomosis over subsequent weeks as well as differences between the different size groups. RESULTS The linear model showed a significant trend (P<0.001) in time of anastomosis in the course of the training, as well as significant differences (P<0.001) between the groups of animal of different sizes. For diameter >1.5 mm, mean anastomosis time decreased from 19.6±1.9 min to 12.6±0.7 min between the first and last week of training. For training involving smaller diameters, the results showed a reduction in execution time of 36.1% (P<0.01) (diameter between 1.0 mm and 1.5 mm) and 40.6% (P<0.01) (diameter <1.0 mm) between the first and last weeks. The study demonstrates an improvement in the dexterity and speed of nodes' execution. CONCLUSION The earthworm appears to be a reliable experimental model for microsurgical training of discrepancy microanastomoses. Its numerous advantages, as discussed in the present report, show that this model of training will significantly grow and develop in the near future.

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An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.

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BACKGROUND The aim of this study was to evaluate the accuracy of linear measurements on three imaging modalities: lateral cephalograms from a cephalometric machine with a 3 m source-to-mid-sagittal-plane distance (SMD), from a machine with 1.5 m SMD and 3D models from cone-beam computed tomography (CBCT) data. METHODS Twenty-one dry human skulls were used. Lateral cephalograms were taken, using two cephalometric devices: one with a 3 m SMD and one with a 1.5 m SMD. CBCT scans were taken by 3D Accuitomo® 170, and 3D surface models were created in Maxilim® software. Thirteen linear measurements were completed twice by two observers with a 4 week interval. Direct physical measurements by a digital calliper were defined as the gold standard. Statistical analysis was performed. RESULTS Nasion-Point A was significantly different from the gold standard in all methods. More statistically significant differences were found on the measurements of the 3 m SMD cephalograms in comparison to the other methods. Intra- and inter-observer agreement based on 3D measurements was slightly better than others. LIMITATIONS Dry human skulls without soft tissues were used. Therefore, the results have to be interpreted with caution, as they do not fully represent clinical conditions. CONCLUSIONS 3D measurements resulted in a better observer agreement. The accuracy of the measurements based on CBCT and 1.5 m SMD cephalogram was better than a 3 m SMD cephalogram. These findings demonstrated the linear measurements accuracy and reliability of 3D measurements based on CBCT data when compared to 2D techniques. Future studies should focus on the implementation of 3D cephalometry in clinical practice.

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In applied work economists often seek to relate a given response variable y to some causal parameter mu* associated with it. This parameter usually represents a summarization based on some explanatory variables of the distribution of y, such as a regression function, and treating it as a conditional expectation is central to its identification and estimation. However, the interpretation of mu* as a conditional expectation breaks down if some or all of the explanatory variables are endogenous. This is not a problem when mu* is modelled as a parametric function of explanatory variables because it is well known how instrumental variables techniques can be used to identify and estimate mu*. In contrast, handling endogenous regressors in nonparametric models, where mu* is regarded as fully unknown, presents di±cult theoretical and practical challenges. In this paper we consider an endogenous nonparametric model based on a conditional moment restriction. We investigate identification related properties of this model when the unknown function mu* belongs to a linear space. We also investigate underidentification of mu* along with the identification of its linear functionals. Several examples are provided in order to develop intuition about identification and estimation for endogenous nonparametric regression and related models.

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Lung damage is a common side effect of chemotherapeutic drugs such as bleomycin. This study used a bleomycin mouse model which simulates the lung damage observed in humans. Noninvasive, in vivo cone-beam computed tomography (CBCT) was used to visualize and quantify fibrotic and inflammatory damage over the entire lung volume of mice. Bleomycin was used to induce pulmonary damage in vivo and the results from two CBCT systems, a micro-CT and flat panel CT (fpCT), were compared to histologic measurements, the standard method of murine lung damage quantification. Twenty C57BL/6 mice were given either 3 U/kg of bleomycin or saline intratracheally. The mice were scanned at baseline, before the administration of bleomycin, and then 10, 14, and 21 days afterward. At each time point, a subset of mice was sacrificed for histologic analysis. The resulting CT images were used to assess lung volume. Percent lung damage (PLD) was calculated for each mouse on both the fpCT (PLDfpcT) and the micro-CT (PLDμCT). Histologic PLD (PLDH) was calculated for each histologic section at each time point (day 10, n = 4; day 14, n = 4; day 21, n = 5; control group, n = 5). A linear regression was applied to the PLDfpCT vs. PLDH, PLDμCT vs. PLDH and PLDfpCT vs. PLDμCT distributions. This study did not demonstrate strong correlations between PLDCT and PLDH. The coefficient of determination, R, was 0.68 for PLDμCT vs. PLDH and 0.75 for the PLD fpCT vs. PLDH. The experimental issues identified from this study were: (1) inconsistent inflation of the lungs from scan to scan, (2) variable distribution of damage (one histologic section not representative of overall lung damage), (3) control mice not scanned with each group of bleomycin mice, (4) two CT systems caused long anesthesia time for the mice, and (5) respiratory gating did not hold the volume of lung constant throughout the scan. Addressing these issues might allow for further improvement of the correlation between PLDCT and PLDH. ^

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With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

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Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^

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We present a novel approach for detecting severe obstructive sleep apnea (OSA) cases by introducing non-linear analysis into sustained speech characterization. The proposed scheme was designed for providing additional information into our baseline system, built on top of state-of-the-art cepstral domain modeling techniques, aiming to improve accuracy rates. This new information is lightly correlated with our previous MFCC modeling of sustained speech and uncorrelated with the information in our continuous speech modeling scheme. Tests have been performed to evaluate the improvement for our detection task, based on sustained speech as well as combined with a continuous speech classifier, resulting in a 10% relative reduction in classification for the first and a 33% relative reduction for the fused scheme. Results encourage us to consider the existence of non-linear effects on OSA patients' voices, and to think about tools which could be used to improve short-time analysis.

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Classical linear amplifiers such as A, AB and B offer very good linearity suitable for RF power amplifiers. However, its inherent low efficiency limits its use especially in base-stations that manage tens or hundreds of Watts. The use of linearization techniques such as Envelope Elimination and Restoration (EER) allow an increase of efficiency keeping good linearity. This technique requires a very fast dc-dc power converter to provide variable voltage supply to the power amplifier. In this paper, several alternatives are analyzed to implement the envelope amplifier based on a cascade association of a switched dc-dc converter and a linear regulator. A simplified version of this approach is also suitable to operate with Envelope Tracking technique.

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Swarm colonies reproduce social habits. Working together in a group to reach a predefined goal is a social behaviour occurring in nature. Linear optimization problems have been approached by different techniques based on natural models. In particular, Particles Swarm optimization is a meta-heuristic search technique that has proven to be effective when dealing with complex optimization problems. This paper presents and develops a new method based on different penalties strategies to solve complex problems. It focuses on the training process of the neural networks, the constraints and the election of the parameters to ensure successful results and to avoid the most common obstacles when searching optimal solutions.

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The aim of this thesis is to study the mechanisms of instability that occur in swept wings when the angle of attack increases. For this, a simplified model for the a simplified model for the non-orthogonal swept leading edge boundary layer has been used as well as different numerical techniques in order to solve the linear stability problem that describes the behavior of perturbations superposed upon this base flow. Two different approaches, matrix-free and matrix forming methods, have been validated using direct numerical simulations with spectral resolution. In this way, flow instability in the non-orthogonal swept attachment-line boundary layer is addressed in a linear analysis framework via the solution of the pertinent global (Bi-Global) PDE-based eigenvalue problem. Subsequently, a simple extension of the extended G¨ortler-H¨ammerlin ODEbased polynomial model proposed by Theofilis, Fedorov, Obrist & Dallmann (2003) for orthogonal flow, which includes previous models as particular cases and recovers global instability analysis results, is presented for non-orthogonal flow. Direct numerical simulations have been used to verify the stability results and unravel the limits of validity of the basic flow model analyzed. The effect of the angle of attack, AoA, on the critical conditions of the non-orthogonal problem has been documented; an increase of the angle of attack, from AoA = 0 (orthogonal flow) up to values close to _/2 which make the assumptions under which the basic flow is derived questionable, is found to systematically destabilize the flow. The critical conditions of non-orthogonal flows at 0 _ AoA _ _/2 are shown to be recoverable from those of orthogonal flow, via a simple analytical transformation involving AoA. These results can help to understand the mechanisms of destabilization that occurs in the attachment line of wings at finite angles of attack. Studies taking into account variations of the pressure field in the basic flow or the extension to compressible flows are issues that remain open. El objetivo de esta tesis es estudiar los mecanismos de la inestabilidad que se producen en ciertos dispositivos aerodinámicos cuando se aumenta el ángulo de ataque. Para ello se ha utilizado un modelo simplificado del flujo de base, así como diferentes técnicas numéricas, con el fin de resolver el problema de estabilidad lineal asociado que describe el comportamiento de las perturbaciones. Estos métodos; sin y con formación de matriz, se han validado utilizando simulaciones numéricas directas con resolución espectral. De esta manera, la inestabilidad del flujo de capa límite laminar oblicuo entorno a la línea de estancamiento se aborda en un marco de análisis lineal por medio del método Bi-Global de resolución del problema de valores propios en derivadas parciales. Posteriormente se propone una extensión simple para el flujo no-ortogonal del modelo polinomial de ecuaciones diferenciales ordinarias, G¨ortler-H¨ammerlin extendido, propuesto por Theofilis et al. (2003) para el flujo ortogonal, que incluye los modelos previos como casos particulares y recupera los resultados del analisis global de estabilidad lineal. Se han realizado simulaciones directas con el fin de verificar los resultados del análisis de estabilidad así como para investigar los límites de validez del modelo de flujo base utilizado. En este trabajo se ha documentado el efecto del ángulo de ataque AoA en las condiciones críticas del problema no ortogonal obteniendo que el incremento del ángulo de ataque, de AoA = 0 (flujo ortogonal) hasta valores próximos a _/2, en el cual las hipótesis sobre las que se basa el flujo base dejan de ser válidas, tiende sistemáticamente a desestabilizar el flujo. Las condiciones críticas del caso no ortogonal 0 _ AoA _ _/2 pueden recuperarse a partir del caso ortogonal mediante el uso de una transformación analítica simple que implica el ángulo de ataque AoA. Estos resultados pueden ayudar a comprender los mecanismos de desestabilización que se producen en el borde de ataque de las alas de los aviones a ángulos de ataque finitos. Como tareas pendientes quedaría realizar estudios que tengan en cuenta variaciones del campo de presión en el flujo base así como la extensión de éste al caso de flujos compresibles.

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Dislocation mobility —the relation between applied stress and dislocation velocity—is an important property to model the mechanical behavior of structural materials. These mobilities reflect the interaction between the dislocation core and the host lattice and, thus, atomistic resolution is required to capture its details. Because the mobility function is multiparametric, its computation is often highly demanding in terms of computational requirements. Optimizing how tractions are applied can be greatly advantageous in accelerating convergence and reducing the overall computational cost of the simulations. In this paper we perform molecular dynamics simulations of ½ 〈1 1 1〉 screw dislocation motion in tungsten using step and linear time functions for applying external stress. We find that linear functions over time scales of the order of 10–20 ps reduce fluctuations and speed up convergence to the steady-state velocity value by up to a factor of two.