995 resultados para PROXIMAL METHODS


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Structural Support Vector Machines (SSVMs) and Conditional Random Fields (CRFs) are popular discriminative methods used for classifying structured and complex objects like parse trees, image segments and part-of-speech tags. The datasets involved are very large dimensional, and the models designed using typical training algorithms for SSVMs and CRFs are non-sparse. This non-sparse nature of models results in slow inference. Thus, there is a need to devise new algorithms for sparse SSVM and CRF classifier design. Use of elastic net and L1-regularizer has already been explored for solving primal CRF and SSVM problems, respectively, to design sparse classifiers. In this work, we focus on dual elastic net regularized SSVM and CRF. By exploiting the weakly coupled structure of these convex programming problems, we propose a new sequential alternating proximal (SAP) algorithm to solve these dual problems. This algorithm works by sequentially visiting each training set example and solving a simple subproblem restricted to a small subset of variables associated with that example. Numerical experiments on various benchmark sequence labeling datasets demonstrate that the proposed algorithm scales well. Further, the classifiers designed are sparser than those designed by solving the respective primal problems and demonstrate comparable generalization performance. Thus, the proposed SAP algorithm is a useful alternative for sparse SSVM and CRF classifier design.

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This paper describes the first phase of a project attempting to construct an efficient general-purpose nonlinear optimizer using an augmented Lagrangian outer loop with a relative error criterion, and an inner loop employing a state-of-the art conjugate gradient solver. The outer loop can also employ double regularized proximal kernels, a fairly recent theoretical development that leads to fully smooth subproblems. We first enhance the existing theory to show that our approach is globally convergent in both the primal and dual spaces when applied to convex problems. We then present an extensive computational evaluation using the CUTE test set, showing that some aspects of our approach are promising, but some are not. These conclusions in turn lead to additional computational experiments suggesting where to next focus our theoretical and computational efforts.

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Solution of structural reliability problems by the First Order method require optimization algorithms to find the smallest distance between a limit state function and the origin of standard Gaussian space. The Hassofer-Lind-Rackwitz-Fiessler (HLRF) algorithm, developed specifically for this purpose, has been shown to be efficient but not robust, as it fails to converge for a significant number of problems. On the other hand, recent developments in general (augmented Lagrangian) optimization techniques have not been tested in aplication to structural reliability problems. In the present article, three new optimization algorithms for structural reliability analysis are presented. One algorithm is based on the HLRF, but uses a new differentiable merit function with Wolfe conditions to select step length in linear search. It is shown in the article that, under certain assumptions, the proposed algorithm generates a sequence that converges to the local minimizer of the problem. Two new augmented Lagrangian methods are also presented, which use quadratic penalties to solve nonlinear problems with equality constraints. Performance and robustness of the new algorithms is compared to the classic augmented Lagrangian method, to HLRF and to the improved HLRF (iHLRF) algorithms, in the solution of 25 benchmark problems from the literature. The new proposed HLRF algorithm is shown to be more robust than HLRF or iHLRF, and as efficient as the iHLRF algorithm. The two augmented Lagrangian methods proposed herein are shown to be more robust and more efficient than the classical augmented Lagrangian method.

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Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

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Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

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The aim of this clinical study was to evaluate and compare the performance of visual exam with use of the Nyvad criteria (visual examination - (VE)), interproximal radiography (BW), laser fluorescence device (DIAGNOdent Pen-DDPen), and their association in the diagnosis of proximal lesions in primary teeth. For this purpose, 45 children (n = 59 surfaces) of both sexes, aged between 5 and 9 years were selected, who presented healthy primary molars or primary molars with signs suggestive of the presence of caries lesions. The surfaces were clinically evaluated and coded according to the Nyvad criteria and immediately afterwards with the DDPen. Radiographic exam was performed only on the surfaces coded with Nyvad scores 2, 3, 5, or 6. Active caries lesions and/or those with discontinuous surfaces were restored, considering the depth of lesion as reference standard. Sensitivity, specificity, accuracy, and area under ROC curve were calculated for each technique and its associations. Visual exam with Nyvad criteria presented the highest specificity, accuracy, and area under ROC curve values. The DDPen presented the highest sensitivity values. Association with one or more methods resulted in an increase in specificity. The performance of visual, radiographic, and DDpen exams and their associations were good; however, the clinical examination with the Nyvad criteria was sufficient for the diagnosis of interproximal lesions in primary teeth.

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For nonsurgical treatment of fractures of the proximal phalanges of the triphalangeal fingers, different dynamic casts have been described. The main principle behind these casts is advancement and tightening of the extensor hood, caused by a combination of blocking the metacarpophalangeal joints in flexion and actively flexing the proximal interphalangeal joints. In contrast to established treatment protocols using functional forearm casts, the Lucerne cast allows for free mobilization of the wrist joint. The purpose of the current multicenter study was to compare the results of conservative, functional treatment using 2 different methods, either a forearm cast or a Lucerne cast.

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Introduction: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (Nmm−1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived froma single 2D radiographic image. Methods: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. Results: The coefficient of determination (R2%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. Conclusions: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry. Crown Copyright © 2009 Published by Elsevier Ltd on behalf of IPEM. All rights reserved

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Summary Generalized Procrustes analysis and thin plate splines were employed to create an average 3D shape template of the proximal femur that was warped to the size and shape of a single 2D radiographic image of a subject. Mean absolute depth errors are comparable with previous approaches utilising multiple 2D input projections. Introduction Several approaches have been adopted to derive volumetric density (g cm-3) from a conventional 2D representation of areal bone mineral density (BMD, g cm-2). Such approaches have generally aimed at deriving an average depth across the areal projection rather than creating a formal 3D shape of the bone. Methods Generalized Procrustes analysis and thin plate splines were employed to create an average 3D shape template of the proximal femur that was subsequently warped to suit the size and shape of a single 2D radiographic image of a subject. CT scans of excised human femora, 18 and 24 scanned at pixel resolutions of 1.08 mm and 0.674 mm, respectively, were equally split into training (created 3D shape template) and test cohorts. Results The mean absolute depth errors of 3.4 mm and 1.73 mm, respectively, for the two CT pixel sizes are comparable with previous approaches based upon multiple 2D input projections. Conclusions This technique has the potential to derive volumetric density from BMD and to facilitate 3D finite element analysis for prediction of the mechanical integrity of the proximal femur. It may further be applied to other anatomical bone sites such as the distal radius and lumbar spine.

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BACKGROUND: Treatment of proximal humerus fractures in elderly patients is challenging because of reduced bone quality. We determined the in vitro characteristics of a new implant developed to target the remaining bone stock, and compared it with an implant in clinical use. METHODS: Following osteotomy, left and right humeral pairs from cadavers were treated with either the Button-Fix or the Humerusblock fixation system. Implant stiffness was determined for three clinically relevant cases of load: axial compression, torsion, and varus bending. In addition, a cyclic varus-bending test was performed. RESULTS: We found higher stiffness values for the humeri treated with the ButtonFix system--with almost a doubling of the compression, torsion, and bending stiffness values. Under dynamic loading, the ButtonFix system had superior stiffness and less K-wire migration compared to the Humerusblock system. INTERPRETATION: When compared to the Humerusblock design, the ButtonFix system showed superior biomechanical properties, both static and dynamic. It offers a minimally invasive alternative for the treatment of proximal humerus fractures.

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Background: Distal-to-proximal technique has been recommended for anti-cancer therapy administration. There is no evidence to suggest that a 24-hour delay of treatment is necessary for patients with a previous uncomplicated venous puncture proximal to the administration site. Objectives: This study aims to identify if the practice of 24-hour delay between a venous puncture and subsequent cannulation for anti-cancer therapies at a distal site is necessary for preventing extravasation. Methods: A prospective cohort study was conducted with 72 outpatients receiving anti-cancer therapy via an administration site distal to at least one previous uncomplicated venous puncture on the same arm in a tertiary cancer centre in Australia. Participants were interviewed and assessed at baseline data before treatment and on day 7 for incidence of extravasation/phlebitis. Results: Of 72 participants with 99 occasions of treatment, there was one incident of infiltration (possible extravasation) at the venous puncture site proximal to the administration site and two incidents of phlebitis at the administration site. Conclusions: A 24 hour delay is unnecessary if an alternative vein can be accessed for anti-cancer therapy after a proximal venous puncture. Implications for practice: Extravasation can occur at a venous puncture site proximal to an administration site in the same vein. However, the nurse can administer anti-cancer therapy at a distal site if the nurse can confidently determine the vein of choice is not in any way connected to the previous puncture site through visual inspection and palpation.

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Background We have previously demonstrated that human kidney proximal tubule epithelial cells (PTEC) are able to modulate autologous T and B lymphocyte responses. It is well established that dendritic cells (DC) are responsible for the initiation and direction of adaptive immune responses and that these cells occur in the renal interstitium in close apposition to PTEC under inflammatory disease settings. However, there is no information regarding the interaction of PTEC with DC in an autologous human context. Methods Human monocytes were differentiated into monocyte-derived DC (MoDC) in the absence or presence of primary autologous activated PTEC and matured with polyinosinic:polycytidylic acid [poly(I:C)], while purified, pre-formed myeloid blood DC (CD1c+ BDC) were cultured with autologous activated PTEC in the absence or presence of poly(I:C) stimulation. DC responses were monitored by surface antigen expression, cytokine secretion, antigen uptake capacity and allogeneic T-cell-stimulatory ability. Results The presence of autologous activated PTEC inhibited the differentiation of monocytes to MoDC. Furthermore, MoDC differentiated in the presence of PTEC displayed an immature surface phenotype, efficient phagocytic capacity and, upon poly(I:C) stimulation, secreted low levels of pro-inflammatory cytokine interleukin (IL)-12p70, high levels of anti-inflammatory cytokine IL-10 and induced weak Th1 responses. Similarly, pre-formed CD1c+ BDC matured in the presence of PTEC exhibited an immature tolerogenic surface phenotype, strong endocytic and phagocytic ability and stimulated significantly attenuated T-cell proliferative responses. Conclusions Our data suggest that activated PTEC regulate human autologous immunity via complex interactions with DC. The ability of PTEC to modulate autologous DC function has important implications for the dampening of pro-inflammatory immune responses within the tubulointerstitium in renal injuries. Further dissection of the mechanisms of PTEC modulation of autologous immune responses may offer targets for therapeutic intervention in renal medicine.

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BACKGROUND Tubulointerstitial lesions, characterized by tubular injury, interstitial fibrosis and the appearance of myofibroblasts, are the strongest predictors of the degree and progression of chronic renal failure. These lesions are typically preceded by macrophage infiltration of the tubulointerstitium, raising the possibility that these inflammatory cells promote progressive renal disease through fibrogenic actions on resident tubulointerstitial cells. The aim of the present study, therefore, was to investigate the potentially fibrogenic mechanisms of interleukin-1beta (IL-1beta), a macrophage-derived pro-inflammatory cytokine, on human proximal tubule cells (PTC). METHODS Confluent, quiescent, passage 2 PTC were established in primary culture from histologically normal segments of human renal cortex (N = 11) and then incubated in serum- and hormone-free media supplemented with either IL-1beta (0 to 4 ng/mL) or vehicle (control). RESULTS IL-1beta significantly enhanced fibronectin secretion by up to fourfold in a time- and concentration-dependent fashion. This was accompanied by significant (2.5- to 6-fold) increases in alpha-smooth muscle actin (alpha-SMA) expression, transforming growth factor beta (TGF-beta1) secretion, nitric oxide (NO) production, NO synthase 2 (NOS2) mRNA and lactate dehydrogenase (LDH) release. Cell proliferation was dose-dependently suppressed by IL-1beta. NG-methyl-l-arginine (L-NMMA; 1 mmol/L), a specific inhibitor of NOS, blocked NO production but did not alter basal or IL-1beta-stimulated fibronectin secretion. In contrast, a pan-specific TGF-beta neutralizing antibody significantly blocked the effects of IL-1beta on PTC fibronectin secretion (IL-1beta, 268.1 +/- 30.6 vs. IL-1beta+alphaTGF-beta 157.9 +/- 14.4%, of control values, P < 0.001) and DNA synthesis (IL-1beta 81.0 +/- 6.7% vs. IL-1beta+alphaTGF-beta 93.4 +/- 2.1%, of control values, P < 0.01). CONCLUSION IL-1beta acts on human PTC to suppress cell proliferation, enhance fibronectin production and promote alpha-smooth muscle actin expression. These actions appear to be mediated by a TGF-beta1 dependent mechanism and are independent of nitric oxide release.

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Purpose To test the effectiveness of static and dynamic orthoses using them as an exclusive treatment for proximal interphalangeal (PIP) joint flexion contracture compared with other hand therapy conservative treatments described in the literature. Methods 60 patients who used orthoses were compared with a control group that received other hand therapy treatments. Clinical assessments were measured before the experiment and 3 months after and included active PIP joint extension and function. Results A significant improvement in the extension active range of motion at the PIP joint in the second measurement was found in both groups, but it was significantly greater in the experimental group. Improvement in function (Disabilities of the Arm, Shoulder, and Hand score) between the first and second assessment was similar in the control and experimental groups. Conclusions Using night progressive static and daily dynamic orthoses as an exclusive treatment during the proliferative phase led to significant improvements in the PIP joint active extension, but the improvement did not correlate with increased function as perceived by the patient.

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PURPOSE: To compare pressures generated by 2 different cement pressurisers at various locations in the proximal femur. METHODS: Two groups of 5 synthetic femurs were used, and 6 pressure sensors were placed in the femur at 20-mm intervals proximally to distally. Cement was filled into the femoral canal retrogradely using a cement gun with either the half-moon pressuriser or the femoral canal pressuriser. Maximum pressures and pressure time integrals (cumulative pressure over time) of the 2 pressurisers were compared. RESULTS: At all sensors, the half-moon pressuriser produced higher maximum pressures and pressure time integrals than the femoral canal pressuriser, but the difference was significant only at sensor 1 (proximal femur). This may result in reduced cement interdigitation in the proximal femur. CONCLUSION: The half-moon pressuriser produced higher maximum cementation pressures and pressure time integrals than the femoral canal pressuriser in the proximal femur region, which is critical for rotational stability of the implant and prevention of implant fracture. KEYWORDS: arthroplasty, replacement, hip; bone cements; femur