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Constraint based modeling

Cong Yang, Weiguo Wu, Yuanqi Su, Shaoxiang Zhang
This paper proposes a circular shape constraint and a novel two-layer level set method for the segmentation of the left ventricle (LV) from short-axis magnetic resonance images without training any shape models. Since the shape of LV throughout the apex-base axis is close to a ring shape, we propose a circle fitting term in the level set framework to detect the endocardium. The circle fitting term imposes a penalty on the evolving contour from its fitting circle, and thereby handles quite well with issues in LV segmentation, especially the presence of outflow track in basal slices and the intensity overlap between TPM and the myocardium...
January 17, 2017: Magnetic Resonance Imaging
Zhengkang Zhang
W boson pair production processes at e^{+}e^{-} and pp colliders have been conventionally interpreted as measurements of WWZ and WWγ triple gauge couplings (TGCs). Such an interpretation is based on the assumption that new physics effects other than anomalous TGCs are negligible. While this "TGC dominance assumption" was well motivated and useful at LEP2 thanks to precision electroweak constraints, it is already challenged by recent LHC data. In fact, contributions from anomalous Z boson couplings that are allowed by electroweak precision data but neglected in LHC analyses, which are enhanced at high energy, can even dominate over those from the anomalous TGCs considered...
January 6, 2017: Physical Review Letters
André Veríssimo, Arlindo Limede Oliveira, Marie-France Sagot, Susana Vinga
BACKGROUND: Modeling survival oncological data has become a major challenge as the increase in the amount of molecular information nowadays available means that the number of features greatly exceeds the number of observations. One possible solution to cope with this dimensionality problem is the use of additional constraints in the cost function optimization. LASSO and other sparsity methods have thus already been successfully applied with such idea. Although this leads to more interpretable models, these methods still do not fully profit from the relations between the features, specially when these can be represented through graphs...
December 13, 2016: BMC Bioinformatics
Nadia C Lara, Asad A Haider, Lon J Wilson, Steven A Curley, Stuart J Corr
Aqueous and nanoparticle-based solutions have been reported to heat when exposed to an alternating radiofrequency (RF) electric-field. Although the theoretical models have been developed to accurately model such a behavior given the solution composition as well as the geometrical constraints of the sample holder, these models have not been investigated across a wide-range of solutions where the dielectric properties differ, especially with regard to the real permittivity. In this work, we investigate the RF heating properties of non-aqueous solutions composed of ethanol, propylene glycol, and glycine betaine with and without varying amounts of NaCl and LiCl...
January 2, 2017: Applied Physics Letters
Joseph J Gardner, Nanette R Boyle
BACKGROUND: Computational, genome based predictions of organism phenotypes has enhanced the ability to investigate the biological phenomena that help organisms survive and respond to their environments. In this study, we have created the first genome-scale metabolic network reconstruction of the nitrogen fixing cyanobacterium T. erythraeum and used genome-scale modeling approaches to investigate carbon and nitrogen fluxes as well as growth and equilibrium population composition. RESULTS: We created a genome-scale reconstruction of T...
January 19, 2017: BMC Systems Biology
Tomas Jonsson
1.The Metabolic Theory of Ecology (MTE) predicts observed patterns in ecology based on metabolic rates of individuals. The theory is influential but also criticized for a lack of firm empirical evidence confirming MTE's quantitative predictions of processes, e.g. outcome of competition, at population or community level. 2.Self-thinning is a well-known population level phenomenon among plants, but a much less studied phenomenon in animal populations and no consensus exists on what a universal thinning slope for animal populations might be, or if it exists...
January 19, 2017: Journal of Animal Ecology
Jhih-An Yang, Stephen Parham, Daniel Dessau, Dmitry Reznik
Time dynamics of photoexcited electron-hole pairs is important for a number of technologies, in particular solar cells. We combined ultrafast pump-probe Raman scattering and photoemission to directly follow electron-hole excitations as well as the G-phonon in graphite after an excitation by an intense laser pulse. This phonon is known to couple relatively strongly to electrons. Cross-correlating effective electronic and phonon temperatures places new constraints on model-based fits. The accepted two-temperature model predicts that G-phonon population should start to increase as soon as excited electron-hole pairs are created and that the rate of increase should not depend strongly on the pump fluence...
January 19, 2017: Scientific Reports
Chengyi Yu, Xiaobo Chen, Juntong Xi
A laser stripe sensor has limited application when a point cloud of geometric samples on the surface of the object needs to be collected, so a galvanometric laser scanner is designed by using a one-mirror galvanometer element as its mechanical device to drive the laser stripe to sweep along the object. A novel mathematical model is derived for the proposed galvanometer laser scanner without any position assumptions and then a model-driven calibration procedure is proposed. Compared with available model-driven approaches, the influence of machining and assembly errors is considered in the proposed model...
January 15, 2017: Sensors
Ding Ma, Laurence Yang, Ronan M T Fleming, Ines Thiele, Bernhard O Palsson, Michael A Saunders
Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger)...
January 18, 2017: Scientific Reports
Jesse D Bloom
BACKGROUND: Sites of positive selection are identified by comparing observed evolutionary patterns to those expected under a null model for evolution in the absence of such selection. For protein-coding genes, the most common null model is that nonsynonymous and synonymous mutations fix at equal rates; this unrealistic model has limited power to detect many interesting forms of selection. RESULTS: I describe a new approach that uses a null model based on experimental measurements of a gene's site-specific amino-acid preferences generated by deep mutational scanning in the lab...
January 17, 2017: Biology Direct
Jaekyun Jeon, Xin Qiao, Ivan Hung, Alok K Mitra, Ambroise Desfosses, Daniel Huang, Peter L Gor'kov, Rebecca C Craven, Richard L Kingston, Zhehong Gan, Fangqiang Zhu, Bo Chen
The orthoretroviral capsid protein (CA) assembles into polymorphic capsids, whose architecture, assembly and stability are still being investigated. The N-terminal and C-terminal domains of CA (NTD and CTD, respectively) engage in both homotypic and heterotypic interactions to create the capsid. Hexameric turrets formed by the NTD decorate the majority of the capsid surface. We report nearly-complete solid-state NMR (ssNMR) resonance assignments of Rous sarcoma virus (RSV) CA, assembled into hexamer tubes that mimic the authentic capsid...
January 17, 2017: Journal of the American Chemical Society
Ben Niu, Yanjun Liu, Guangdeng Zong, Zhaoyu Han, Jun Fu
In this paper, a new adaptive approximation-based tracking controller design approach is developed for a class of uncertain nonlinear switched lower-triangular systems with an output constraint using neural networks (NNs). By introducing a novel barrier Lyapunov function (BLF), the constrained switched system is first transformed into a new system without any constraint, which means the control objectives of the both systems are equivalent. Then command filter technique is applied to solve the so-called "explosion of complexity" problem in traditional backstepping procedure, and radial basis function NNs are directly employed to model the unknown nonlinear functions...
January 16, 2017: IEEE Transactions on Cybernetics
Nannan Wang, Xinbo Gao, Leiyu Sun, Jie Li
xemplar-based face sketch synthesis has been widely applied to both digital entertainment and law enforcement. In this paper, we propose a Bayesian framework for face sketch synthesis, which provides a systematic interpretation for understanding the common properties and intrinsic difference in different methods from the perspective of probabilistic graphical modelsxemplar-based face sketch synthesis has been widely applied to both digital entertainment and law enforcement. In this paper, we propose a Bayesian framework for face sketch synthesis, which provides a systematic interpretation for understanding the common properties and intrinsic difference in different methods from the perspective of probabilistic graphical modelsE...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Huazhu Fu, Dong Xu, Stephen Lin
We present an RGBD video segmentation method that takes advantage of depth data and can extract multiple foregrounds in the scene. This video segmentation is addressed as an object proposal selection problem formulated in a fullyconnected graph where a flexible number of foregrounds may be chosen. In the graph, each node represents a proposal, and the edges model intra-frame and inter-frame constraints on the solution. The proposals are generated based on an RGBD video saliency map in which depth-based features are utilized to enhance identification of foregrounds...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Renaud Hedouin, Olivier Commowick, Elise Bannier, Benoit Scherrer, Maxime Taquet, Simon Warfield, Christian Barillot
By shortening the acquisition time of MRI, Echo Planar Imaging (EPI) enables the acqui- sition of a large number of images in a short time, com- patible with clinical constraints as required for diffusion or functional MRI. However such images are subject to large, local distortions disrupting their correspondence with the underlying anatomy. The correction of those distortions is an open problem, especially in regions where large deformations occur. We propose a new block-matching registration method to perform EPI distortion correction based on the acquisition of two EPI with opposite phase encoding directions (PED)...
January 9, 2017: IEEE Transactions on Medical Imaging
Wen-Yan Lin, Fan Wang, Ming-Ming Cheng, Sai-Kit Yeung, Philip H S Torr, Minh N Do, Jiangbo Lu
A key challenge in feature correspondence is the difficulty in differentiating true and false matches at a local descriptor level. This forces adoption of strict similarity thresholds that discard many true matches. However, if analyzed at a global level, false matches are usually randomly scattered while true matches tend to be coherent (clustered around a few dominant motions), thus creating a coherence based separability constraint. This paper proposes a non-linear regression technique that can discover such a coherence based separability constraint from highly noisy matches and embed it into a correspondence likelihood model...
January 16, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Liang Lin, Keze Wang, Deyu Meng, Wangmeng Zuo, Lei Zhang
This paper aims to develop a novel cost-effective framework for face identification, which progressively maintains a batch of classifiers with the increasing face images of different individuals. By naturally combining two recently rising techniques: active learning (AL) and self-paced learning (SPL), our framework is capable of automatically annotating new instances and incorporating them into training under weak expert recertification. We first initialize the classifier using a few annotated samples for each individual, and extract image features using the convolutional neural nets...
January 16, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Oren Freifeld, Soren Hauberg, Kayhan Batmanghelich, John W Fisher
We propose novel finite-dimensional spaces of well-behaved Rn → Rn transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volume preservation and/or boundary conditions), and supports convenient modeling choices such as smoothing priors and coarse-to-fine analysis. Importantly, the proposed approach, partly due to its rapid likelihood evaluations and partly due to its other properties, facilitates tractable inference over rich transformation spaces, including using Markov-Chain Monte-Carlo methods...
January 11, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
James L Croft, Ryan T Schroeder, John E A Bertram
Human locomotion has been well described but is still not well understood. This is largely true because the observable aspects of locomotion-neuromuscular activity that generates forces and motions-relate to both the task solution and the problem being solved. Identifying the fundamental task achieved in locomotion makes it possible to critically evaluate the motor control strategy used to accomplish the task goal. We contend that the readily observed movements and activities of locomotion should be considered mechanism(s)...
January 13, 2017: Psychonomic Bulletin & Review
Wendy Harris, You Zhang, Fang-Fang Yin, Lei Ren
PURPOSE: To investigate the feasibility of using structural-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. METHODS: A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume...
January 12, 2017: Medical Physics
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