Active Subspaces of Airfoil Shape Parameterizations

NASA Astrophysics Data System (ADS)

Grey, Zachary J.; Constantine, Paul G.

2018-05-01

Design and optimization benefit from understanding the dependence of a quantity of interest (e.g., a design objective or constraint function) on the design variables. A low-dimensional active subspace, when present, identifies important directions in the space of design variables; perturbing a design along the active subspace associated with a particular quantity of interest changes that quantity more, on average, than perturbing the design orthogonally to the active subspace. This low-dimensional structure provides insights that characterize the dependence of quantities of interest on design variables. Airfoil design in a transonic flow field with a parameterized geometry is a popular test problem for design methodologies. We examine two particular airfoil shape parameterizations, PARSEC and CST, and study the active subspaces present in two common design quantities of interest, transonic lift and drag coefficients, under each shape parameterization. We mathematically relate the two parameterizations with a common polynomial series. The active subspaces enable low-dimensional approximations of lift and drag that relate to physical airfoil properties. In particular, we obtain and interpret a two-dimensional approximation of both transonic lift and drag, and we show how these approximation inform a multi-objective design problem.

Unsupervised spike sorting based on discriminative subspace learning.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Characterizing L1-norm best-fit subspaces

NASA Astrophysics Data System (ADS)

Brooks, J. Paul; Dulá, José H.

2017-05-01

Fitting affine objects to data is the basis of many tools and methodologies in statistics, machine learning, and signal processing. The L1 norm is often employed to produce subspaces exhibiting a robustness to outliers and faulty observations. The L1-norm best-fit subspace problem is directly formulated as a nonlinear, nonconvex, and nondifferentiable optimization problem. The case when the subspace is a hyperplane can be solved to global optimality efficiently by solving a series of linear programs. The problem of finding the best-fit line has recently been shown to be NP-hard. We present necessary conditions for optimality for the best-fit subspace problem, and use them to characterize properties of optimal solutions.

Zeno subspace in quantum-walk dynamics

NASA Astrophysics Data System (ADS)

Chandrashekar, C. M.

2010-11-01

We investigate discrete-time quantum-walk evolution under the influence of periodic measurements in position subspace. The undisturbed survival probability of the particle at the position subspace P(0,t) is compared with the survival probability after frequent (n) measurements at interval τ=t/n, P(0,τ)n. We show that P(0,τ)n>P(0,t) leads to the quantum Zeno effect in position subspace when a parameter θ in the quantum coin operations and frequency of measurements is greater than the critical value, θ>θc and n>nc. This Zeno effect in the subspace preserves the dynamics in coin Hilbert space of the walk dynamics and has the potential to play a significant role in quantum tasks such as preserving the quantum state of the particle at any particular position, and to understand the Zeno dynamics in a multidimensional system that is highly transient in nature.

Targeting the Hedgehog pathway in cancer: can the spines be smoothened?

PubMed

Ailles, Laurie; Siu, Lillian L

2011-04-15

Aberrant Hedgehog (Hh) pathway signaling has been suggested to play a role in the development of multiple solid tumors and hematologic malignancies. GDC-0449 is a novel first-in-human, first-in-class smoothened (SMO) inhibitor, which has completed its phase I evaluation and achieved proof of concept in tumors with Hh pathway mutations. ©2011 AACR.

Krylov subspace methods - Theory, algorithms, and applications

NASA Technical Reports Server (NTRS)

Sad, Youcef

1990-01-01

Projection methods based on Krylov subspaces for solving various types of scientific problems are reviewed. The main idea of this class of methods when applied to a linear system Ax = b, is to generate in some manner an approximate solution to the original problem from the so-called Krylov subspace span. Thus, the original problem of size N is approximated by one of dimension m, typically much smaller than N. Krylov subspace methods have been very successful in solving linear systems and eigenvalue problems and are now becoming popular for solving nonlinear equations. The main ideas in Krylov subspace methods are shown and their use in solving linear systems, eigenvalue problems, parabolic partial differential equations, Liapunov matrix equations, and nonlinear system of equations are discussed.

Active Subspaces for Wind Plant Surrogate Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

King, Ryan N; Quick, Julian; Dykes, Katherine L

Understanding the uncertainty in wind plant performance is crucial to their cost-effective design and operation. However, conventional approaches to uncertainty quantification (UQ), such as Monte Carlo techniques or surrogate modeling, are often computationally intractable for utility-scale wind plants because of poor congergence rates or the curse of dimensionality. In this paper we demonstrate that wind plant power uncertainty can be well represented with a low-dimensional active subspace, thereby achieving a significant reduction in the dimension of the surrogate modeling problem. We apply the active sub-spaces technique to UQ of plant power output with respect to uncertainty in turbine axial inductionmore » factors, and find a single active subspace direction dominates the sensitivity in power output. When this single active subspace direction is used to construct a quadratic surrogate model, the number of model unknowns can be reduced by up to 3 orders of magnitude without compromising performance on unseen test data. We conclude that the dimension reduction achieved with active subspaces makes surrogate-based UQ approaches tractable for utility-scale wind plants.« less

Nonadiabatic holonomic quantum computation in decoherence-free subspaces.

PubMed

Xu, G F; Zhang, J; Tong, D M; Sjöqvist, Erik; Kwek, L C

2012-10-26

Quantum computation that combines the coherence stabilization virtues of decoherence-free subspaces and the fault tolerance of geometric holonomic control is of great practical importance. Some schemes of adiabatic holonomic quantum computation in decoherence-free subspaces have been proposed in the past few years. However, nonadiabatic holonomic quantum computation in decoherence-free subspaces, which avoids a long run-time requirement but with all the robust advantages, remains an open problem. Here, we demonstrate how to realize nonadiabatic holonomic quantum computation in decoherence-free subspaces. By using only three neighboring physical qubits undergoing collective dephasing to encode one logical qubit, we realize a universal set of quantum gates.

On iterative processes in the Krylov-Sonneveld subspaces

NASA Astrophysics Data System (ADS)

Ilin, Valery P.

2016-10-01

The iterative Induced Dimension Reduction (IDR) methods are considered for solving large systems of linear algebraic equations (SLAEs) with nonsingular nonsymmetric matrices. These approaches are investigated by many authors and are charachterized sometimes as the alternative to the classical processes of Krylov type. The key moments of the IDR algorithms consist in the construction of the embedded Sonneveld subspaces, which have the decreasing dimensions and use the orthogonalization to some fixed subspace. Other independent approaches for research and optimization of the iterations are based on the augmented and modified Krylov subspaces by using the aggregation and deflation procedures with present various low rank approximations of the original matrices. The goal of this paper is to show, that IDR method in Sonneveld subspaces present an original interpretation of the modified algorithms in the Krylov subspaces. In particular, such description is given for the multi-preconditioned semi-conjugate direction methods which are actual for the parallel algebraic domain decomposition approaches.

An alternative subspace approach to EEG dipole source localization

NASA Astrophysics Data System (ADS)

Xu, Xiao-Liang; Xu, Bobby; He, Bin

2004-01-01

In the present study, we investigate a new approach to electroencephalography (EEG) three-dimensional (3D) dipole source localization by using a non-recursive subspace algorithm called FINES. In estimating source dipole locations, the present approach employs projections onto a subspace spanned by a small set of particular vectors (FINES vector set) in the estimated noise-only subspace instead of the entire estimated noise-only subspace in the case of classic MUSIC. The subspace spanned by this vector set is, in the sense of principal angle, closest to the subspace spanned by the array manifold associated with a particular brain region. By incorporating knowledge of the array manifold in identifying FINES vector sets in the estimated noise-only subspace for different brain regions, the present approach is able to estimate sources with enhanced accuracy and spatial resolution, thus enhancing the capability of resolving closely spaced sources and reducing estimation errors. The present computer simulations show, in EEG 3D dipole source localization, that compared to classic MUSIC, FINES has (1) better resolvability of two closely spaced dipolar sources and (2) better estimation accuracy of source locations. In comparison with RAP-MUSIC, FINES' performance is also better for the cases studied when the noise level is high and/or correlations among dipole sources exist.

Geometry aware Stationary Subspace Analysis

DTIC Science & Technology

2016-11-22

approach to handling non-stationarity is to remove or minimize it before attempting to analyze the data. In the context of brain computer interface ( BCI ...context of brain computer interface ( BCI ) data analysis, two such note-worthy methods are stationary subspace analysis (SSA) (von Bünau et al., 2009a... BCI systems, is sCSP. Its goal is to project the data onto a subspace in which the various data classes are more separable. The sCSP method directs

Subspace-based interference removal methods for a multichannel biomagnetic sensor array.

PubMed

Sekihara, Kensuke; Nagarajan, Srikantan S

2017-10-01

In biomagnetic signal processing, the theory of the signal subspace has been applied to removing interfering magnetic fields, and a representative algorithm is the signal space projection algorithm, in which the signal/interference subspace is defined in the spatial domain as the span of signal/interference-source lead field vectors. This paper extends the notion of this conventional (spatial domain) signal subspace by introducing a new definition of signal subspace in the time domain. It defines the time-domain signal subspace as the span of row vectors that contain the source time course values. This definition leads to symmetric relationships between the time-domain and the conventional (spatial-domain) signal subspaces. As a review, this article shows that the notion of the time-domain signal subspace provides useful insights over existing interference removal methods from a unified perspective. Main results and significance. Using the time-domain signal subspace, it is possible to interpret a number of interference removal methods as the time domain signal space projection. Such methods include adaptive noise canceling, sensor noise suppression, the common temporal subspace projection, the spatio-temporal signal space separation, and the recently-proposed dual signal subspace projection. Our analysis using the notion of the time domain signal space projection reveals implicit assumptions these methods rely on, and shows that the difference between these methods results only from the manner of deriving the interference subspace. Numerical examples that illustrate the results of our arguments are provided.

Subspace-based interference removal methods for a multichannel biomagnetic sensor array

NASA Astrophysics Data System (ADS)

Sekihara, Kensuke; Nagarajan, Srikantan S.

2017-10-01

Objective. In biomagnetic signal processing, the theory of the signal subspace has been applied to removing interfering magnetic fields, and a representative algorithm is the signal space projection algorithm, in which the signal/interference subspace is defined in the spatial domain as the span of signal/interference-source lead field vectors. This paper extends the notion of this conventional (spatial domain) signal subspace by introducing a new definition of signal subspace in the time domain. Approach. It defines the time-domain signal subspace as the span of row vectors that contain the source time course values. This definition leads to symmetric relationships between the time-domain and the conventional (spatial-domain) signal subspaces. As a review, this article shows that the notion of the time-domain signal subspace provides useful insights over existing interference removal methods from a unified perspective. Main results and significance. Using the time-domain signal subspace, it is possible to interpret a number of interference removal methods as the time domain signal space projection. Such methods include adaptive noise canceling, sensor noise suppression, the common temporal subspace projection, the spatio-temporal signal space separation, and the recently-proposed dual signal subspace projection. Our analysis using the notion of the time domain signal space projection reveals implicit assumptions these methods rely on, and shows that the difference between these methods results only from the manner of deriving the interference subspace. Numerical examples that illustrate the results of our arguments are provided.

An accelerated subspace iteration for eigenvector derivatives

NASA Technical Reports Server (NTRS)

Ting, Tienko

1991-01-01

An accelerated subspace iteration method for calculating eigenvector derivatives has been developed. Factors affecting the effectiveness and the reliability of the subspace iteration are identified, and effective strategies concerning these factors are presented. The method has been implemented, and the results of a demonstration problem are presented.

Overview of Krylov subspace methods with applications to control problems

NASA Technical Reports Server (NTRS)

Saad, Youcef

1989-01-01

An overview of projection methods based on Krylov subspaces are given with emphasis on their application to solving matrix equations that arise in control problems. The main idea of Krylov subspace methods is to generate a basis of the Krylov subspace Span and seek an approximate solution the the original problem from this subspace. Thus, the original matrix problem of size N is approximated by one of dimension m typically much smaller than N. Krylov subspace methods have been very successful in solving linear systems and eigenvalue problems and are now just becoming popular for solving nonlinear equations. It is shown how they can be used to solve partial pole placement problems, Sylvester's equation, and Lyapunov's equation.

Seismic noise attenuation using an online subspace tracking algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

2018-02-01

We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

New subspace methods for ATR

NASA Astrophysics Data System (ADS)

Zhang, Peng; Peng, Jing; Sims, S. Richard F.

2005-05-01

In ATR applications, each feature is a convolution of an image with a filter. It is important to use most discriminant features to produce compact representations. We propose two novel subspace methods for dimension reduction to address limitations associated with Fukunaga-Koontz Transform (FKT). The first method, Scatter-FKT, assumes that target is more homogeneous, while clutter can be anything other than target and anywhere. Thus, instead of estimating a clutter covariance matrix, Scatter-FKT computes a clutter scatter matrix that measures the spread of clutter from the target mean. We choose dimensions along which the difference in variation between target and clutter is most pronounced. When the target follows a Gaussian distribution, Scatter-FKT can be viewed as a generalization of FKT. The second method, Optimal Bayesian Subspace, is derived from the optimal Bayesian classifier. It selects dimensions such that the minimum Bayes error rate can be achieved. When both target and clutter follow Gaussian distributions, OBS computes optimal subspace representations. We compare our methods against FKT using character image as well as IR data.

Surface smoothening effects on growth of diamond films

NASA Astrophysics Data System (ADS)

Reshi, Bilal Ahmad; Kumar, Shyam; Kartha, Moses J.; Varma, Raghava

2018-04-01

We have carried out a detailed study of the growth dynamics of the diamond film during initial time on diamond substrates. The diamond films are deposited using Microwave Plasma Chemical Vapor Deposition (MPCVD) method for different times. Surface morphology and its correlation with the number of hours of growth of thin films was invested using atomic force microscopy (AFM). Diamond films have smooth interface with average roughness of 48.6873nm. The initial growth dynamics of the thin film is investigated. Interestingly, it is found that there is a decrease in the surface roughness of the film. Thus a smoothening effect is observed in the grown films. The film enters into the growth regime in the later times. Our results also find application in building diamond detector.

General subspace learning with corrupted training data via graph embedding.

PubMed

Bao, Bing-Kun; Liu, Guangcan; Hong, Richang; Yan, Shuicheng; Xu, Changsheng

2013-11-01

We address the following subspace learning problem: supposing we are given a set of labeled, corrupted training data points, how to learn the underlying subspace, which contains three components: an intrinsic subspace that captures certain desired properties of a data set, a penalty subspace that fits the undesired properties of the data, and an error container that models the gross corruptions possibly existing in the data. Given a set of data points, these three components can be learned by solving a nuclear norm regularized optimization problem, which is convex and can be efficiently solved in polynomial time. Using the method as a tool, we propose a new discriminant analysis (i.e., supervised subspace learning) algorithm called Corruptions Tolerant Discriminant Analysis (CTDA), in which the intrinsic subspace is used to capture the features with high within-class similarity, the penalty subspace takes the role of modeling the undesired features with high between-class similarity, and the error container takes charge of fitting the possible corruptions in the data. We show that CTDA can well handle the gross corruptions possibly existing in the training data, whereas previous linear discriminant analysis algorithms arguably fail in such a setting. Extensive experiments conducted on two benchmark human face data sets and one object recognition data set show that CTDA outperforms the related algorithms.

Krylov-Subspace Recycling via the POD-Augmented Conjugate-Gradient Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlberg, Kevin; Forstall, Virginia; Tuminaro, Ray

This paper presents a new Krylov-subspace-recycling method for efficiently solving sequences of linear systems of equations characterized by varying right-hand sides and symmetric-positive-definite matrices. As opposed to typical truncation strategies used in recycling such as deflation, we propose a truncation method inspired by goal-oriented proper orthogonal decomposition (POD) from model reduction. This idea is based on the observation that model reduction aims to compute a low-dimensional subspace that contains an accurate solution; as such, we expect the proposed method to generate a low-dimensional subspace that is well suited for computing solutions that can satisfy inexact tolerances. In particular, we proposemore » specific goal-oriented POD `ingredients' that align the optimality properties of POD with the objective of Krylov-subspace recycling. To compute solutions in the resulting 'augmented' POD subspace, we propose a hybrid direct/iterative three-stage method that leverages 1) the optimal ordering of POD basis vectors, and 2) well-conditioned reduced matrices. Numerical experiments performed on solid-mechanics problems highlight the benefits of the proposed method over existing approaches for Krylov-subspace recycling.« less

Krylov-Subspace Recycling via the POD-Augmented Conjugate-Gradient Method

DOE PAGES

Carlberg, Kevin; Forstall, Virginia; Tuminaro, Ray

2016-01-01

This paper presents a new Krylov-subspace-recycling method for efficiently solving sequences of linear systems of equations characterized by varying right-hand sides and symmetric-positive-definite matrices. As opposed to typical truncation strategies used in recycling such as deflation, we propose a truncation method inspired by goal-oriented proper orthogonal decomposition (POD) from model reduction. This idea is based on the observation that model reduction aims to compute a low-dimensional subspace that contains an accurate solution; as such, we expect the proposed method to generate a low-dimensional subspace that is well suited for computing solutions that can satisfy inexact tolerances. In particular, we proposemore » specific goal-oriented POD `ingredients' that align the optimality properties of POD with the objective of Krylov-subspace recycling. To compute solutions in the resulting 'augmented' POD subspace, we propose a hybrid direct/iterative three-stage method that leverages 1) the optimal ordering of POD basis vectors, and 2) well-conditioned reduced matrices. Numerical experiments performed on solid-mechanics problems highlight the benefits of the proposed method over existing approaches for Krylov-subspace recycling.« less

Adiabatic evolution of decoherence-free subspaces and its shortcuts

NASA Astrophysics Data System (ADS)

Wu, S. L.; Huang, X. L.; Li, H.; Yi, X. X.

2017-10-01

The adiabatic theorem and shortcuts to adiabaticity for time-dependent open quantum systems are explored in this paper. Starting from the definition of dynamical stable decoherence-free subspace, we show that, under a compact adiabatic condition, the quantum state remains in the time-dependent decoherence-free subspace with an extremely high purity, even though the dynamics of the open quantum system may not be adiabatic. The adiabatic condition mentioned here in the adiabatic theorem for open systems is very similar to that for closed quantum systems, except that the operators required to change slowly are the Lindblad operators. We also show that the adiabatic evolution of decoherence-free subspaces depends on the existence of instantaneous decoherence-free subspaces, which requires that the Hamiltonian of open quantum systems be engineered according to the incoherent control protocol. In addition, shortcuts to adiabaticity for adiabatic decoherence-free subspaces are also presented based on the transitionless quantum driving method. Finally, we provide an example that consists of a two-level system coupled to a broadband squeezed vacuum field to show our theory. Our approach employs Markovian master equations and the theory can apply to finite-dimensional quantum open systems.

Local Subspace Classifier with Transform-Invariance for Image Classification

NASA Astrophysics Data System (ADS)

Hotta, Seiji

A family of linear subspace classifiers called local subspace classifier (LSC) outperforms the k-nearest neighbor rule (kNN) and conventional subspace classifiers in handwritten digit classification. However, LSC suffers very high sensitivity to image transformations because it uses projection and the Euclidean distances for classification. In this paper, I present a combination of a local subspace classifier (LSC) and a tangent distance (TD) for improving accuracy of handwritten digit recognition. In this classification rule, we can deal with transform-invariance easily because we are able to use tangent vectors for approximation of transformations. However, we cannot use tangent vectors in other type of images such as color images. Hence, kernel LSC (KLSC) is proposed for incorporating transform-invariance into LSC via kernel mapping. The performance of the proposed methods is verified with the experiments on handwritten digit and color image classification.

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

PubMed

Li, Kai; Qi, Guo-Jun; Ye, Jun; Hua, Kien A

2017-09-01

Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features' ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.

Subspace Methods for Massive and Messy Data

DTIC Science & Technology

2017-07-12

Subspace Methods for Massive and Messy Data The views, opinions and/or findings contained in this report are those of the author(s) and should not...AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 REPORT DOCUMENTATION PAGE 11. SPONSOR...Number: W911NF-14-1-0634 Organization: University of Michigan - Ann Arbor Title: Subspace Methods for Massive and Messy Data Report Term: 0-Other

Manifold learning-based subspace distance for machinery damage assessment

NASA Astrophysics Data System (ADS)

Sun, Chuang; Zhang, Zhousuo; He, Zhengjia; Shen, Zhongjie; Chen, Binqiang

2016-03-01

Damage assessment is very meaningful to keep safety and reliability of machinery components, and vibration analysis is an effective way to carry out the damage assessment. In this paper, a damage index is designed by performing manifold distance analysis on vibration signal. To calculate the index, vibration signal is collected firstly, and feature extraction is carried out to obtain statistical features that can capture signal characteristics comprehensively. Then, manifold learning algorithm is utilized to decompose feature matrix to be a subspace, that is, manifold subspace. The manifold learning algorithm seeks to keep local relationship of the feature matrix, which is more meaningful for damage assessment. Finally, Grassmann distance between manifold subspaces is defined as a damage index. The Grassmann distance reflecting manifold structure is a suitable metric to measure distance between subspaces in the manifold. The defined damage index is applied to damage assessment of a rotor and the bearing, and the result validates its effectiveness for damage assessment of machinery component.

Conjunctive patches subspace learning with side information for collaborative image retrieval.

PubMed

Zhang, Lining; Wang, Lipo; Lin, Weisi

2012-08-01

Content-Based Image Retrieval (CBIR) has attracted substantial attention during the past few years for its potential practical applications to image management. A variety of Relevance Feedback (RF) schemes have been designed to bridge the semantic gap between the low-level visual features and the high-level semantic concepts for an image retrieval task. Various Collaborative Image Retrieval (CIR) schemes aim to utilize the user historical feedback log data with similar and dissimilar pairwise constraints to improve the performance of a CBIR system. However, existing subspace learning approaches with explicit label information cannot be applied for a CIR task, although the subspace learning techniques play a key role in various computer vision tasks, e.g., face recognition and image classification. In this paper, we propose a novel subspace learning framework, i.e., Conjunctive Patches Subspace Learning (CPSL) with side information, for learning an effective semantic subspace by exploiting the user historical feedback log data for a CIR task. The CPSL can effectively integrate the discriminative information of labeled log images, the geometrical information of labeled log images and the weakly similar information of unlabeled images together to learn a reliable subspace. We formally formulate this problem into a constrained optimization problem and then present a new subspace learning technique to exploit the user historical feedback log data. Extensive experiments on both synthetic data sets and a real-world image database demonstrate the effectiveness of the proposed scheme in improving the performance of a CBIR system by exploiting the user historical feedback log data.

A Poisson nonnegative matrix factorization method with parameter subspace clustering constraint for endmember extraction in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Sun, Weiwei; Ma, Jun; Yang, Gang; Du, Bo; Zhang, Liangpei

2017-06-01

A new Bayesian method named Poisson Nonnegative Matrix Factorization with Parameter Subspace Clustering Constraint (PNMF-PSCC) has been presented to extract endmembers from Hyperspectral Imagery (HSI). First, the method integrates the liner spectral mixture model with the Bayesian framework and it formulates endmember extraction into a Bayesian inference problem. Second, the Parameter Subspace Clustering Constraint (PSCC) is incorporated into the statistical program to consider the clustering of all pixels in the parameter subspace. The PSCC could enlarge differences among ground objects and helps finding endmembers with smaller spectrum divergences. Meanwhile, the PNMF-PSCC method utilizes the Poisson distribution as the prior knowledge of spectral signals to better explain the quantum nature of light in imaging spectrometer. Third, the optimization problem of PNMF-PSCC is formulated into maximizing the joint density via the Maximum A Posterior (MAP) estimator. The program is finally solved by iteratively optimizing two sub-problems via the Alternating Direction Method of Multipliers (ADMM) framework and the FURTHESTSUM initialization scheme. Five state-of-the art methods are implemented to make comparisons with the performance of PNMF-PSCC on both the synthetic and real HSI datasets. Experimental results show that the PNMF-PSCC outperforms all the five methods in Spectral Angle Distance (SAD) and Root-Mean-Square-Error (RMSE), and especially it could identify good endmembers for ground objects with smaller spectrum divergences.

Modulated Hebb-Oja learning rule--a method for principal subspace analysis.

PubMed

Jankovic, Marko V; Ogawa, Hidemitsu

2006-03-01

This paper presents analysis of the recently proposed modulated Hebb-Oja (MHO) method that performs linear mapping to a lower-dimensional subspace. Principal component subspace is the method that will be analyzed. Comparing to some other well-known methods for yielding principal component subspace (e.g., Oja's Subspace Learning Algorithm), the proposed method has one feature that could be seen as desirable from the biological point of view--synaptic efficacy learning rule does not need the explicit information about the value of the other efficacies to make individual efficacy modification. Also, the simplicity of the "neural circuits" that perform global computations and a fact that their number does not depend on the number of input and output neurons, could be seen as good features of the proposed method.

Adaptive low-rank subspace learning with online optimization for robust visual tracking.

PubMed

Liu, Risheng; Wang, Di; Han, Yuzhuo; Fan, Xin; Luo, Zhongxuan

2017-04-01

In recent years, sparse and low-rank models have been widely used to formulate appearance subspace for visual tracking. However, most existing methods only consider the sparsity or low-rankness of the coefficients, which is not sufficient enough for appearance subspace learning on complex video sequences. Moreover, as both the low-rank and the column sparse measures are tightly related to all the samples in the sequences, it is challenging to incrementally solve optimization problems with both nuclear norm and column sparse norm on sequentially obtained video data. To address above limitations, this paper develops a novel low-rank subspace learning with adaptive penalization (LSAP) framework for subspace based robust visual tracking. Different from previous work, which often simply decomposes observations as low-rank features and sparse errors, LSAP simultaneously learns the subspace basis, low-rank coefficients and column sparse errors to formulate appearance subspace. Within LSAP framework, we introduce a Hadamard production based regularization to incorporate rich generative/discriminative structure constraints to adaptively penalize the coefficients for subspace learning. It is shown that such adaptive penalization can significantly improve the robustness of LSAP on severely corrupted dataset. To utilize LSAP for online visual tracking, we also develop an efficient incremental optimization scheme for nuclear norm and column sparse norm minimizations. Experiments on 50 challenging video sequences demonstrate that our tracker outperforms other state-of-the-art methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Randomized subspace-based robust principal component analysis for hyperspectral anomaly detection

NASA Astrophysics Data System (ADS)

Sun, Weiwei; Yang, Gang; Li, Jialin; Zhang, Dianfa

2018-01-01

A randomized subspace-based robust principal component analysis (RSRPCA) method for anomaly detection in hyperspectral imagery (HSI) is proposed. The RSRPCA combines advantages of randomized column subspace and robust principal component analysis (RPCA). It assumes that the background has low-rank properties, and the anomalies are sparse and do not lie in the column subspace of the background. First, RSRPCA implements random sampling to sketch the original HSI dataset from columns and to construct a randomized column subspace of the background. Structured random projections are also adopted to sketch the HSI dataset from rows. Sketching from columns and rows could greatly reduce the computational requirements of RSRPCA. Second, the RSRPCA adopts the columnwise RPCA (CWRPCA) to eliminate negative effects of sampled anomaly pixels and that purifies the previous randomized column subspace by removing sampled anomaly columns. The CWRPCA decomposes the submatrix of the HSI data into a low-rank matrix (i.e., background component), a noisy matrix (i.e., noise component), and a sparse anomaly matrix (i.e., anomaly component) with only a small proportion of nonzero columns. The algorithm of inexact augmented Lagrange multiplier is utilized to optimize the CWRPCA problem and estimate the sparse matrix. Nonzero columns of the sparse anomaly matrix point to sampled anomaly columns in the submatrix. Third, all the pixels are projected onto the complemental subspace of the purified randomized column subspace of the background and the anomaly pixels in the original HSI data are finally exactly located. Several experiments on three real hyperspectral images are carefully designed to investigate the detection performance of RSRPCA, and the results are compared with four state-of-the-art methods. Experimental results show that the proposed RSRPCA outperforms four comparison methods both in detection performance and in computational time.

Mining subspace clusters from DNA microarray data using large itemset techniques.

PubMed

Chang, Ye-In; Chen, Jiun-Rung; Tsai, Yueh-Chi

2009-05-01

Mining subspace clusters from the DNA microarrays could help researchers identify those genes which commonly contribute to a disease, where a subspace cluster indicates a subset of genes whose expression levels are similar under a subset of conditions. Since in a DNA microarray, the number of genes is far larger than the number of conditions, those previous proposed algorithms which compute the maximum dimension sets (MDSs) for any two genes will take a long time to mine subspace clusters. In this article, we propose the Large Itemset-Based Clustering (LISC) algorithm for mining subspace clusters. Instead of constructing MDSs for any two genes, we construct only MDSs for any two conditions. Then, we transform the task of finding the maximal possible gene sets into the problem of mining large itemsets from the condition-pair MDSs. Since we are only interested in those subspace clusters with gene sets as large as possible, it is desirable to pay attention to those gene sets which have reasonable large support values in the condition-pair MDSs. From our simulation results, we show that the proposed algorithm needs shorter processing time than those previous proposed algorithms which need to construct gene-pair MDSs.

Evaluating the utility of mid-infrared spectral subspaces for predicting soil properties.

PubMed

Sila, Andrew M; Shepherd, Keith D; Pokhariyal, Ganesh P

2016-04-15

We propose four methods for finding local subspaces in large spectral libraries. The proposed four methods include (a) cosine angle spectral matching; (b) hit quality index spectral matching; (c) self-organizing maps and (d) archetypal analysis methods. Then evaluate prediction accuracies for global and subspaces calibration models. These methods were tested on a mid-infrared spectral library containing 1907 soil samples collected from 19 different countries under the Africa Soil Information Service project. Calibration models for pH, Mehlich-3 Ca, Mehlich-3 Al, total carbon and clay soil properties were developed for the whole library and for the subspace. Root mean square error of prediction was used to evaluate predictive performance of subspace and global models. The root mean square error of prediction was computed using a one-third-holdout validation set. Effect of pretreating spectra with different methods was tested for 1st and 2nd derivative Savitzky-Golay algorithm, multiplicative scatter correction, standard normal variate and standard normal variate followed by detrending methods. In summary, the results show that global models outperformed the subspace models. We, therefore, conclude that global models are more accurate than the local models except in few cases. For instance, sand and clay root mean square error values from local models from archetypal analysis method were 50% poorer than the global models except for subspace models obtained using multiplicative scatter corrected spectra with which were 12% better. However, the subspace approach provides novel methods for discovering data pattern that may exist in large spectral libraries.

Smoothened-antagonists reverse homogentisic acid-induced alterations of Hedgehog signaling and primary cilium length in alkaptonuria.

PubMed

Gambassi, Silvia; Geminiani, Michela; Thorpe, Stephen D; Bernardini, Giulia; Millucci, Lia; Braconi, Daniela; Orlandini, Maurizio; Thompson, Clare L; Petricci, Elena; Manetti, Fabrizio; Taddei, Maurizio; Knight, Martin M; Santucci, Annalisa

2017-11-01

Alkaptonuria (AKU) is an ultra-rare genetic disease, in which the accumulation of a toxic metabolite, homogentisic acid (HGA) leads to the systemic development of ochronotic aggregates. These aggregates cause severe complications mainly at the level of joints with extensive degradation of the articular cartilage. Primary cilia have been demonstrated to play an essential role in development and the maintenance of articular cartilage homeostasis, through their involvement in mechanosignaling and Hedgehog signaling pathways. Hedgehog signaling has been demonstrated to be activated in osteoarthritis (OA) and to drive cartilage degeneration in vivo. The numerous similarities between OA and AKU suggest that primary cilia Hedgehog signaling may also be altered in AKU. Thus, we characterized an AKU cellular model in which healthy chondrocytes were treated with HGA (66 µM) to replicate AKU cartilage pathology. We investigated the degree of activation of the Hedgehog signaling pathway and how treatment with inhibitors of the receptor Smoothened (Smo) influenced Hedgehog activation and primary cilia structure. The results obtained in this work provide a further step in the comprehension of the pathophysiological features of AKU, suggesting a potential therapeutic approach to modulate AKU cartilage degradation processes through manipulation of the Hedgehog pathway. © 2016 Wiley Periodicals, Inc.

Identifying Optimal Measurement Subspace for the Ensemble Kalman Filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ning; Huang, Zhenyu; Welch, Greg

2012-05-24

To reduce the computational load of the ensemble Kalman filter while maintaining its efficacy, an optimization algorithm based on the generalized eigenvalue decomposition method is proposed for identifying the most informative measurement subspace. When the number of measurements is large, the proposed algorithm can be used to make an effective tradeoff between computational complexity and estimation accuracy. This algorithm also can be extended to other Kalman filters for measurement subspace selection.

Bi Sparsity Pursuit: A Paradigm for Robust Subspace Recovery

DTIC Science & Technology

2016-09-27

16. SECURITY CLASSIFICATION OF: The success of sparse models in computer vision and machine learning is due to the fact that, high dimensional data...Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 Signal recovery, Sparse learning , Subspace modeling REPORT DOCUMENTATION PAGE 11...vision and machine learning is due to the fact that, high dimensional data is distributed in a union of low dimensional subspaces in many real-world

Robust subspace clustering via joint weighted Schatten-p norm and Lq norm minimization

NASA Astrophysics Data System (ADS)

Zhang, Tao; Tang, Zhenmin; Liu, Qing

2017-05-01

Low-rank representation (LRR) has been successfully applied to subspace clustering. However, the nuclear norm in the standard LRR is not optimal for approximating the rank function in many real-world applications. Meanwhile, the L21 norm in LRR also fails to characterize various noises properly. To address the above issues, we propose an improved LRR method, which achieves low rank property via the new formulation with weighted Schatten-p norm and Lq norm (WSPQ). Specifically, the nuclear norm is generalized to be the Schatten-p norm and different weights are assigned to the singular values, and thus it can approximate the rank function more accurately. In addition, Lq norm is further incorporated into WSPQ to model different noises and improve the robustness. An efficient algorithm based on the inexact augmented Lagrange multiplier method is designed for the formulated problem. Extensive experiments on face clustering and motion segmentation clearly demonstrate the superiority of the proposed WSPQ over several state-of-the-art methods.

Locally indistinguishable subspaces spanned by three-qubit unextendible product bases

NASA Astrophysics Data System (ADS)

Duan, Runyao; Xin, Yu; Ying, Mingsheng

2010-03-01

We study the local distinguishability of general multiqubit states and show that local projective measurements and classical communication are as powerful as the most general local measurements and classical communication. Remarkably, this indicates that the local distinguishability of multiqubit states can be decided efficiently. Another useful consequence is that a set of orthogonal n-qubit states is locally distinguishable only if the summation of their orthogonal Schmidt numbers is less than the total dimension 2n. Employing these results, we show that any orthonormal basis of a subspace spanned by arbitrary three-qubit orthogonal unextendible product bases (UPB) cannot be exactly distinguishable by local operations and classical communication. This not only reveals another intrinsic property of three-qubit orthogonal UPB but also provides a class of locally indistinguishable subspaces with dimension 4. We also explicitly construct locally indistinguishable subspaces with dimensions 3 and 5, respectively. Similar to the bipartite case, these results on multipartite locally indistinguishable subspaces can be used to estimate the one-shot environment-assisted classical capacity of a class of quantum broadcast channels.

Independence and totalness of subspaces in phase space methods

NASA Astrophysics Data System (ADS)

Vourdas, A.

2018-04-01

The concepts of independence and totalness of subspaces are introduced in the context of quasi-probability distributions in phase space, for quantum systems with finite-dimensional Hilbert space. It is shown that due to the non-distributivity of the lattice of subspaces, there are various levels of independence, from pairwise independence up to (full) independence. Pairwise totalness, totalness and other intermediate concepts are also introduced, which roughly express that the subspaces overlap strongly among themselves, and they cover the full Hilbert space. A duality between independence and totalness, that involves orthocomplementation (logical NOT operation), is discussed. Another approach to independence is also studied, using Rota's formalism on independent partitions of the Hilbert space. This is used to define informational independence, which is proved to be equivalent to independence. As an application, the pentagram (used in discussions on contextuality) is analysed using these concepts.

Krylov subspace methods for computing hydrodynamic interactions in Brownian dynamics simulations

PubMed Central

Ando, Tadashi; Chow, Edmond; Saad, Yousef; Skolnick, Jeffrey

2012-01-01

Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a Brownian dynamics simulation. However, the calculation of correlated Brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studies methods based on Krylov subspaces for computing Brownian noise vectors. These methods are related to Chebyshev polynomial approximations, but do not require eigenvalue estimates. We show that only low accuracy is required in the Brownian noise vectors to accurately compute values of dynamic and static properties of polymer and monodisperse suspension models. With this level of accuracy, the computational time of Krylov subspace methods scales very nearly as O(N2) for the number of particles N up to 10 000, which was the limit tested. The performance of the Krylov subspace methods, especially the “block” version, is slightly better than that of the Chebyshev method, even without taking into account the additional cost of eigenvalue estimates required by the latter. Furthermore, at N = 10 000, the Krylov subspace method is 13 times faster than the exact Cholesky method. Thus, Krylov subspace methods are recommended for performing large-scale Brownian dynamics simulations with hydrodynamic interactions. PMID:22897254

BI-sparsity pursuit for robust subspace recovery

DOE PAGES

Bian, Xiao; Krim, Hamid

2015-09-01

Here, the success of sparse models in computer vision and machine learning in many real-world applications, may be attributed in large part, to the fact that many high dimensional data are distributed in a union of low dimensional subspaces. The underlying structure may, however, be adversely affected by sparse errors, thus inducing additional complexity in recovering it. In this paper, we propose a bi-sparse model as a framework to investigate and analyze this problem, and provide as a result , a novel algorithm to recover the union of subspaces in presence of sparse corruptions. We additionally demonstrate the effectiveness ofmore » our method by experiments on real-world vision data.« less

Loss of pericyte smoothened activity in mice with genetic deficiency of leptin.

PubMed

Xie, Guanhua; Swiderska-Syn, Marzena; Jewell, Mark L; Machado, Mariana Verdelho; Michelotti, Gregory A; Premont, Richard T; Diehl, Anna Mae

2017-04-20

Obesity is associated with multiple diseases, but it is unclear how obesity promotes progressive tissue damage. Recovery from injury requires repair, an energy-expensive process that is coupled to energy availability at the cellular level. The satiety factor, leptin, is a key component of the sensor that matches cellular energy utilization to available energy supplies. Leptin deficiency signals energy depletion, whereas activating the Hedgehog pathway drives energy-consuming activities. Tissue repair is impaired in mice that are obese due to genetic leptin deficiency. Tissue repair is also blocked and obesity enhanced by inhibiting Hedgehog activity. We evaluated the hypothesis that loss of leptin silences Hedgehog signaling in pericytes, multipotent leptin-target cells that regulate a variety of responses that are often defective in obesity, including tissue repair and adipocyte differentiation. We found that pericytes from liver and white adipose tissue require leptin to maintain expression of the Hedgehog co-receptor, Smoothened, which controls the activities of Hedgehog-regulated Gli transcription factors that orchestrate gene expression programs that dictate pericyte fate. Smoothened suppression prevents liver pericytes from being reprogrammed into myofibroblasts, but stimulates adipose-derived pericytes to become white adipocytes. Progressive Hedgehog pathway decay promotes senescence in leptin-deficient liver pericytes, which, in turn, generate paracrine signals that cause neighboring hepatocytes to become fatty and less proliferative, enhancing vulnerability to liver damage. Leptin-responsive pericytes evaluate energy availability to inform tissue construction by modulating Hedgehog pathway activity and thus, are at the root of progressive obesity-related tissue pathology. Leptin deficiency inhibits Hedgehog signaling in pericytes to trigger a pericytopathy that promotes both adiposity and obesity-related tissue damage.

Medulloblastomas derived from Cxcr6 mutant mice respond to treatment with a smoothened inhibitor.

PubMed

Sasai, Ken; Romer, Justyna T; Kimura, Hiromichi; Eberhart, Derek E; Rice, Dennis S; Curran, Tom

2007-04-15

The sonic hedgehog (Shh) pathway is activated in approximately 30% of human medulloblastoma resulting in increased expression of downstream target genes. In about half of these cases, this has been shown to be a consequence of mutations in regulatory genes within the pathway, including Ptc1, Smo, and Sufu. However, for some tumors, no mutations have been detected in known pathway genes. This suggests that either mutations in other genes promote tumorigenesis or that epigenetic alterations increase pathway activity in these tumors. Here, we report that 3% to 4% of mice lacking either one or both functional copies of Cxcr6 develop medulloblastoma. Although CXCR6 is not known to be involved in Shh signaling, tumors derived from Cxcr6 mutant mice expressed Shh pathway target genes including Gli1, Gli2, Ptc2, and Sfrp1, indicating elevated pathway activity. Interestingly, the level of Ptc1 expression was decreased in tumor cells although two normal copies of Ptc1 were retained. This implies that reduced CXCR6 function leads to suppression of Ptc1 thereby increasing Smoothened function and promoting tumorigenesis. We used a direct transplant model to test the sensitivity of medulloblastoma arising in Cxcr6 mutant mice to a small-molecule inhibitor of Smoothened (HhAntag). We found that transplanted tumors were dramatically inhibited in mice treated for only 4 days with HhAntag. These findings suggest that HhAntag may be effective against tumors lacking mutations in known Shh pathway genes.

Visual exploration of high-dimensional data through subspace analysis and dynamic projections

DOE PAGES

Liu, S.; Wang, B.; Thiagarajan, J. J.; ...

2015-06-01

Here, we introduce a novel interactive framework for visualizing and exploring high-dimensional datasets based on subspace analysis and dynamic projections. We assume the high-dimensional dataset can be represented by a mixture of low-dimensional linear subspaces with mixed dimensions, and provide a method to reliably estimate the intrinsic dimension and linear basis of each subspace extracted from the subspace clustering. Subsequently, we use these bases to define unique 2D linear projections as viewpoints from which to visualize the data. To understand the relationships among the different projections and to discover hidden patterns, we connect these projections through dynamic projections that createmore » smooth animated transitions between pairs of projections. We introduce the view transition graph, which provides flexible navigation among these projections to facilitate an intuitive exploration. Finally, we provide detailed comparisons with related systems, and use real-world examples to demonstrate the novelty and usability of our proposed framework.« less

Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, S.; Wang, B.; Thiagarajan, Jayaraman J.

2015-06-01

We introduce a novel interactive framework for visualizing and exploring high-dimensional datasets based on subspace analysis and dynamic projections. We assume the high-dimensional dataset can be represented by a mixture of low-dimensional linear subspaces with mixed dimensions, and provide a method to reliably estimate the intrinsic dimension and linear basis of each subspace extracted from the subspace clustering. Subsequently, we use these bases to define unique 2D linear projections as viewpoints from which to visualize the data. To understand the relationships among the different projections and to discover hidden patterns, we connect these projections through dynamic projections that create smoothmore » animated transitions between pairs of projections. We introduce the view transition graph, which provides flexible navigation among these projections to facilitate an intuitive exploration. Finally, we provide detailed comparisons with related systems, and use real-world examples to demonstrate the novelty and usability of our proposed framework.« less

Variational second order density matrix study of F3-: importance of subspace constraints for size-consistency.

PubMed

van Aggelen, Helen; Verstichel, Brecht; Bultinck, Patrick; Van Neck, Dimitri; Ayers, Paul W; Cooper, David L

2011-02-07

Variational second order density matrix theory under "two-positivity" constraints tends to dissociate molecules into unphysical fractionally charged products with too low energies. We aim to construct a qualitatively correct potential energy surface for F(3)(-) by applying subspace energy constraints on mono- and diatomic subspaces of the molecular basis space. Monoatomic subspace constraints do not guarantee correct dissociation: the constraints are thus geometry dependent. Furthermore, the number of subspace constraints needed for correct dissociation does not grow linearly with the number of atoms. The subspace constraints do impose correct chemical properties in the dissociation limit and size-consistency, but the structure of the resulting second order density matrix method does not exactly correspond to a system of noninteracting units.

Low-Rank Tensor Subspace Learning for RGB-D Action Recognition.

PubMed

Jia, Chengcheng; Fu, Yun

2016-07-09

Since RGB-D action data inherently equip with extra depth information compared with RGB data, recently many works employ RGB-D data in a third-order tensor representation containing spatio-temporal structure to find a subspace for action recognition. However, there are two main challenges of these methods. First, the dimension of subspace is usually fixed manually. Second, preserving local information by finding intraclass and inter-class neighbors from a manifold is highly timeconsuming. In this paper, we learn a tensor subspace, whose dimension is learned automatically by low-rank learning, for RGB-D action recognition. Particularly, the tensor samples are factorized to obtain three Projection Matrices (PMs) by Tucker Decomposition, where all the PMs are performed by nuclear norm in a close-form to obtain the tensor ranks which are used as tensor subspace dimension. Additionally, we extract the discriminant and local information from a manifold using a graph constraint. This graph preserves the local knowledge inherently, which is faster than the previous way by calculating both the intra-class and inter-class neighbors of each sample. We evaluate the proposed method on four widely used RGB-D action datasets including MSRDailyActivity3D, MSRActionPairs, MSRActionPairs skeleton and UTKinect-Action3D datasets, and the experimental results show higher accuracy and efficiency of the proposed method.

Krylov Subspace Methods for Complex Non-Hermitian Linear Systems. Thesis

NASA Technical Reports Server (NTRS)

Freund, Roland W.

1991-01-01

We consider Krylov subspace methods for the solution of large sparse linear systems Ax = b with complex non-Hermitian coefficient matrices. Such linear systems arise in important applications, such as inverse scattering, numerical solution of time-dependent Schrodinger equations, underwater acoustics, eddy current computations, numerical computations in quantum chromodynamics, and numerical conformal mapping. Typically, the resulting coefficient matrices A exhibit special structures, such as complex symmetry, or they are shifted Hermitian matrices. In this paper, we first describe a Krylov subspace approach with iterates defined by a quasi-minimal residual property, the QMR method, for solving general complex non-Hermitian linear systems. Then, we study special Krylov subspace methods designed for the two families of complex symmetric respectively shifted Hermitian linear systems. We also include some results concerning the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.

Dual signal subspace projection (DSSP): a novel algorithm for removing large interference in biomagnetic measurements

NASA Astrophysics Data System (ADS)

Sekihara, Kensuke; Kawabata, Yuya; Ushio, Shuta; Sumiya, Satoshi; Kawabata, Shigenori; Adachi, Yoshiaki; Nagarajan, Srikantan S.

2016-06-01

Objective. In functional electrophysiological imaging, signals are often contaminated by interference that can be of considerable magnitude compared to the signals of interest. This paper proposes a novel algorithm for removing such interferences that does not require separate noise measurements. Approach. The algorithm is based on a dual definition of the signal subspace in the spatial- and time-domains. Since the algorithm makes use of this duality, it is named the dual signal subspace projection (DSSP). The DSSP algorithm first projects the columns of the measured data matrix onto the inside and outside of the spatial-domain signal subspace, creating a set of two preprocessed data matrices. The intersection of the row spans of these two matrices is estimated as the time-domain interference subspace. The original data matrix is projected onto the subspace that is orthogonal to this interference subspace. Main results. The DSSP algorithm is validated by using the computer simulation, and using two sets of real biomagnetic data: spinal cord evoked field data measured from a healthy volunteer and magnetoencephalography data from a patient with a vagus nerve stimulator. Significance. The proposed DSSP algorithm is effective for removing overlapped interference in a wide variety of biomagnetic measurements.

Entanglement dynamics of coupled qubits and a semi-decoherence free subspace

NASA Astrophysics Data System (ADS)

Campagnano, Gabriele; Hamma, Alioscia; Weiss, Ulrich

2010-01-01

We study the entanglement dynamics and relaxation properties of a system of two interacting qubits in the cases of (I) two independent bosonic baths and (II) one common bath. We find that in the case (II) the existence of a decoherence-free subspace (DFS) makes entanglement dynamics very rich. We show that when the system is initially in a state with a component in the DFS the relaxation time is surprisingly long, showing the existence of semi-decoherence free subspaces.

Subspace in Linear Algebra: Investigating Students' Concept Images and Interactions with the Formal Definition

ERIC Educational Resources Information Center

Wawro, Megan; Sweeney, George F.; Rabin, Jeffrey M.

2011-01-01

This paper reports on a study investigating students' ways of conceptualizing key ideas in linear algebra, with the particular results presented here focusing on student interactions with the notion of subspace. In interviews conducted with eight undergraduates, we found students' initial descriptions of subspace often varied substantially from…

Extended Krylov subspaces approximations of matrix functions. Application to computational electromagnetics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Druskin, V.; Lee, Ping; Knizhnerman, L.

There is now a growing interest in the area of using Krylov subspace approximations to compute the actions of matrix functions. The main application of this approach is the solution of ODE systems, obtained after discretization of partial differential equations by method of lines. In the event that the cost of computing the matrix inverse is relatively inexpensive, it is sometimes attractive to solve the ODE using the extended Krylov subspaces, originated by actions of both positive and negative matrix powers. Examples of such problems can be found frequently in computational electromagnetics.

Sparse subspace clustering for data with missing entries and high-rank matrix completion.

PubMed

Fan, Jicong; Chow, Tommy W S

2017-09-01

Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Active subspace uncertainty quantification for a polydomain ferroelectric phase-field model

NASA Astrophysics Data System (ADS)

Leon, Lider S.; Smith, Ralph C.; Miles, Paul; Oates, William S.

2018-03-01

Quantum-informed ferroelectric phase field models capable of predicting material behavior, are necessary for facilitating the development and production of many adaptive structures and intelligent systems. Uncertainty is present in these models, given the quantum scale at which calculations take place. A necessary analysis is to determine how the uncertainty in the response can be attributed to the uncertainty in the model inputs or parameters. A second analysis is to identify active subspaces within the original parameter space, which quantify directions in which the model response varies most dominantly, thus reducing sampling effort and computational cost. In this investigation, we identify an active subspace for a poly-domain ferroelectric phase-field model. Using the active variables as our independent variables, we then construct a surrogate model and perform Bayesian inference. Once we quantify the uncertainties in the active variables, we obtain uncertainties for the original parameters via an inverse mapping. The analysis provides insight into how active subspace methodologies can be used to reduce computational power needed to perform Bayesian inference on model parameters informed by experimental or simulated data.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Minimal Krylov Subspaces for Dimension Reduction

DTIC Science & Technology

2013-01-01

these applications realized a maximal compute time improvement with minimal Krylov subspaces. More recently, Halko et . al . [36] have investigated... Halko et . al . proposed a variety of them in [36], but we focus on the “direct eigenvalue approximation for Hermitian matri- ces with random...result due to Halko et . al . Theorem 5 ( Halko , Martinsson and Tropp [36]). Let A ∈ Rn×m be the input matrix with partitioned singular value

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control.

PubMed

Brunton, Steven L; Brunton, Bingni W; Proctor, Joshua L; Kutz, J Nathan

2016-01-01

In this wIn this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control.ork, we explore finite

Subspace-based analysis of the ERT inverse problem

NASA Astrophysics Data System (ADS)

Ben Hadj Miled, Mohamed Khames; Miller, Eric L.

2004-05-01

In a previous work, we proposed a source-type formulation to the electrical resistance tomography (ERT) problem. Specifically, we showed that inhomogeneities in the medium can be viewed as secondary sources embedded in the homogeneous background medium and located at positions associated with variation in electrical conductivity. Assuming a piecewise constant conductivity distribution, the support of equivalent sources is equal to the boundary of the inhomogeneity. The estimation of the anomaly shape takes the form of an inverse source-type problem. In this paper, we explore the use of subspace methods to localize the secondary equivalent sources associated with discontinuities in the conductivity distribution. Our first alternative is the multiple signal classification (MUSIC) algorithm which is commonly used in the localization of multiple sources. The idea is to project a finite collection of plausible pole (or dipole) sources onto an estimated signal subspace and select those with largest correlations. In ERT, secondary sources are excited simultaneously but in different ways, i.e. with distinct amplitude patterns, depending on the locations and amplitudes of primary sources. If the number of receivers is "large enough", different source configurations can lead to a set of observation vectors that span the data subspace. However, since sources that are spatially close to each other have highly correlated signatures, seperation of such signals becomes very difficult in the presence of noise. To overcome this problem we consider iterative MUSIC algorithms like R-MUSIC and RAP-MUSIC. These recursive algorithms pose a computational burden as they require multiple large combinatorial searches. Results obtained with these algorithms using simulated data of different conductivity patterns are presented.

Global Scale Simultaneous Retrieval of Smoothened Vegetation Optical Depth and Surface Roughness Parameter using AMSR-E X-band Observations

NASA Astrophysics Data System (ADS)

Lanka, Karthikeyan; Pan, Ming; Konings, Alexandra; Piles, María; D, Nagesh Kumar; Wood, Eric

2017-04-01

Traditionally, passive microwave retrieval algorithms such as Land Parameter Retrieval Model (LPRM) estimate simultaneously soil moisture and Vegetation Optical Depth (VOD) using brightness temperature (Tb) data. The algorithm requires a surface roughness parameter which - despite implications - is generally assumed to be constant at global scale. Due to inherent noise in the satellite data and retrieval algorithm, the VOD retrievals are usually observed to be highly fluctuating at daily scale which may not occur in reality. Such noisy VOD retrievals along with spatially invariable roughness parameter may affect the quality of soil moisture retrievals. The current work aims to smoothen the VOD retrievals (with an assumption that VOD remains constant over a period of time) and simultaneously generate, for the first time, global surface roughness map using multiple descending X-band Tb observations of AMSR-E. The methodology utilizes Tb values under a moving-time-window-setup to estimate concurrently the soil moisture of each day and a constant VOD in the window. Prior to this step, surface roughness parameter is estimated using the complete time series of Tb record. Upon carrying out the necessary sensitivity analysis, the smoothened VOD along with soil moisture retrievals is generated for the 10-year duration of AMSR-E (2002-2011) with a 7-day moving window using the LPRM framework. The spatial patterns of resulted global VOD maps are in coherence with vegetation biomass and climate conditions. The VOD results also exhibit a smoothening effect in terms of lower values of standard deviation. This is also evident from time series comparison of VOD and LPRM VOD retrievals without optimization over moving windows at several grid locations across the globe. The global surface roughness map also exhibited spatial patterns that are strongly influenced by topography and land use conditions. Some of the noticeable features include high roughness over mountainous regions and

Active subspace: toward scalable low-rank learning.

PubMed

Liu, Guangcan; Yan, Shuicheng

2012-12-01

We address the scalability issues in low-rank matrix learning problems. Usually these problems resort to solving nuclear norm regularized optimization problems (NNROPs), which often suffer from high computational complexities if based on existing solvers, especially in large-scale settings. Based on the fact that the optimal solution matrix to an NNROP is often low rank, we revisit the classic mechanism of low-rank matrix factorization, based on which we present an active subspace algorithm for efficiently solving NNROPs by transforming large-scale NNROPs into small-scale problems. The transformation is achieved by factorizing the large solution matrix into the product of a small orthonormal matrix (active subspace) and another small matrix. Although such a transformation generally leads to nonconvex problems, we show that a suboptimal solution can be found by the augmented Lagrange alternating direction method. For the robust PCA (RPCA) (Candès, Li, Ma, & Wright, 2009 ) problem, a typical example of NNROPs, theoretical results verify the suboptimality of the solution produced by our algorithm. For the general NNROPs, we empirically show that our algorithm significantly reduces the computational complexity without loss of optimality.

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control

PubMed Central

Brunton, Steven L.; Brunton, Bingni W.; Proctor, Joshua L.; Kutz, J. Nathan

2016-01-01

In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control. PMID:26919740

Improved Detection of Local Earthquakes in the Vienna Basin (Austria), using Subspace Detectors

NASA Astrophysics Data System (ADS)

Apoloner, Maria-Theresia; Caffagni, Enrico; Bokelmann, Götz

2016-04-01

The Vienna Basin in Eastern Austria is densely populated and highly-developed; it is also a region of low to moderate seismicity, yet the seismological network coverage is relatively sparse. This demands improving our capability of earthquake detection by testing new methods, enlarging the existing local earthquake catalogue. This contributes to imaging tectonic fault zones for better understanding seismic hazard, also through improved earthquake statistics (b-value, magnitude of completeness). Detection of low-magnitude earthquakes or events for which the highest amplitudes slightly exceed the signal-to-noise-ratio (SNR), may be possible by using standard methods like the short-term over long-term average (STA/LTA). However, due to sparse network coverage and high background noise, such a technique may not detect all potentially recoverable events. Yet, earthquakes originating from the same source region and relatively close to each other, should be characterized by similarity in seismic waveforms, at a given station. Therefore, waveform similarity can be exploited by using specific techniques such as correlation-template based (also known as matched filtering) or subspace detection methods (based on the subspace theory). Matching techniques basically require a reference or template event, usually characterized by high waveform coherence in the array receivers, and high SNR, which is cross-correlated with the continuous data. Instead, subspace detection methods overcome in principle the necessity of defining template events as single events, but use a subspace extracted from multiple events. This approach theoretically should be more robust in detecting signals that exhibit a strong variability (e.g. because of source or magnitude). In this study we scan the continuous data recorded in the Vienna Basin with a subspace detector to identify additional events. This will allow us to estimate the increase of the seismicity rate in the local earthquake catalogue

Conditioned invariant subspaces, disturbance decoupling and solutions of rational matrix equations

NASA Technical Reports Server (NTRS)

Li, Z.; Sastry, S. S.

1986-01-01

Conditioned invariant subspaces are introduced both in terms of output injection and in terms of state estimation. Various properties of these subspaces are explored and the problem of disturbance decoupling by output injection (OIP) is defined. It is then shown that OIP is equivalent to the problem of disturbance decoupled estimation as introduced in Willems (1982) and Willems and Commault (1980). Both solvability conditions and a description of solutions for a class of rational matrix equations of the form X(s)M(s) = Q(s) on several ways are given in state-space form. Finally, the problem of output stabilization with respect to a disturbance is briefly addressed.

Active Subspace Methods for Data-Intensive Inverse Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Qiqi

2017-04-27

The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.

Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value Decomposition (SVD)

DTIC Science & Technology

2017-09-27

ARL-TR-8161•SEP 2017 US Army Research Laboratory Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value...originator. ARL-TR-8161•SEP 2017 US Army Research Laboratory Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value...unlimited. October 2015–January 2016 US Army Research Laboratory ATTN: RDRL-CIH-C Aberdeen Proving Ground, MD 21005-5066 primary author’s email

Structural basis for Smoothened receptor modulation and chemoresistance to anti-cancer drugs

PubMed Central

Wang, Chong; Wu, Huixian; Evron, Tama; Vardy, Eyal; Han, Gye Won; Huang, Xi-Ping; Hufeisen, Sandy J.; Mangano, Thomas J.; Urban, Dan J.; Katritch, Vsevolod; Cherezov, Vadim; Caron, Marc G.; Roth, Bryan L.; Stevens, Raymond C.

2014-01-01

The Smoothened receptor (SMO) mediates signal transduction in the hedgehog pathway, which is implicated in normal development and carcinogenesis. SMO antagonists can suppress the growth of some tumors; however, mutations at SMO have been found to abolish their anti-tumor effects, a phenomenon known as chemoresistance. Here we report three crystal structures of human SMO bound to the antagonists SANT1 and Anta XV, and the agonist, SAG1.5, at 2.6–2.8Å resolution. The long and narrow cavity in the transmembrane domain of SMO harbors multiple ligand binding sites, where SANT1 binds at a deeper site as compared with other ligands. Distinct interactions at D4736.55 elucidated the structural basis for the differential effects of chemoresistance mutations on SMO antagonists. The agonist SAG1.5 induces a conformational rearrangement of the binding pocket residues, which could contribute to SMO activation. Collectively, these studies reveal the structural basis for the modulation of SMO by small molecules. PMID:25008467

Cholesterol activates the G-protein coupled receptor Smoothened to promote Hedgehog signaling

PubMed Central

Luchetti, Giovanni; Sircar, Ria; Kong, Jennifer H; Nachtergaele, Sigrid; Sagner, Andreas; Byrne, Eamon FX; Covey, Douglas F; Siebold, Christian; Rohatgi, Rajat

2016-01-01

Cholesterol is necessary for the function of many G-protein coupled receptors (GPCRs). We find that cholesterol is not just necessary but also sufficient to activate signaling by the Hedgehog (Hh) pathway, a prominent cell-cell communication system in development. Cholesterol influences Hh signaling by directly activating Smoothened (SMO), an orphan GPCR that transmits the Hh signal across the membrane in all animals. Unlike many GPCRs, which are regulated by cholesterol through their heptahelical transmembrane domains, SMO is activated by cholesterol through its extracellular cysteine-rich domain (CRD). Residues shown to mediate cholesterol binding to the CRD in a recent structural analysis also dictate SMO activation, both in response to cholesterol and to native Hh ligands. Our results show that cholesterol can initiate signaling from the cell surface by engaging the extracellular domain of a GPCR and suggest that SMO activity may be regulated by local changes in cholesterol abundance or accessibility. DOI: http://dx.doi.org/10.7554/eLife.20304.001 PMID:27705744

Metastable decoherence-free subspaces and electromagnetically induced transparency in interacting many-body systems

NASA Astrophysics Data System (ADS)

Macieszczak, Katarzyna; Zhou, YanLi; Hofferberth, Sebastian; Garrahan, Juan P.; Li, Weibin; Lesanovsky, Igor

2017-10-01

We investigate the dynamics of a generic interacting many-body system under conditions of electromagnetically induced transparency (EIT). This problem is of current relevance due to its connection to nonlinear optical media realized by Rydberg atoms. In an interacting system the structure of the dynamics and the approach to the stationary state becomes far more complex than in the case of conventional EIT. In particular, we discuss the emergence of a metastable decoherence-free subspace, whose dimension for a single Rydberg excitation grows linearly in the number of atoms. On approach to stationarity this leads to a slow dynamics, which renders the typical assumption of fast relaxation invalid. We derive analytically the effective nonequilibrium dynamics in the decoherence-free subspace, which features coherent and dissipative two-body interactions. We discuss the use of this scenario for the preparation of collective entangled dark states and the realization of general unitary dynamics within the spin-wave subspace.

Anomaly Detection in Moving-Camera Video Sequences Using Principal Subspace Analysis

DOE PAGES

Thomaz, Lucas A.; Jardim, Eric; da Silva, Allan F.; ...

2017-10-16

This study presents a family of algorithms based on sparse decompositions that detect anomalies in video sequences obtained from slow moving cameras. These algorithms start by computing the union of subspaces that best represents all the frames from a reference (anomaly free) video as a low-rank projection plus a sparse residue. Then, they perform a low-rank representation of a target (possibly anomalous) video by taking advantage of both the union of subspaces and the sparse residue computed from the reference video. Such algorithms provide good detection results while at the same time obviating the need for previous video synchronization. However,more » this is obtained at the cost of a large computational complexity, which hinders their applicability. Another contribution of this paper approaches this problem by using intrinsic properties of the obtained data representation in order to restrict the search space to the most relevant subspaces, providing computational complexity gains of up to two orders of magnitude. The developed algorithms are shown to cope well with videos acquired in challenging scenarios, as verified by the analysis of 59 videos from the VDAO database that comprises videos with abandoned objects in a cluttered industrial scenario.« less

Anomaly Detection in Moving-Camera Video Sequences Using Principal Subspace Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomaz, Lucas A.; Jardim, Eric; da Silva, Allan F.

This study presents a family of algorithms based on sparse decompositions that detect anomalies in video sequences obtained from slow moving cameras. These algorithms start by computing the union of subspaces that best represents all the frames from a reference (anomaly free) video as a low-rank projection plus a sparse residue. Then, they perform a low-rank representation of a target (possibly anomalous) video by taking advantage of both the union of subspaces and the sparse residue computed from the reference video. Such algorithms provide good detection results while at the same time obviating the need for previous video synchronization. However,more » this is obtained at the cost of a large computational complexity, which hinders their applicability. Another contribution of this paper approaches this problem by using intrinsic properties of the obtained data representation in order to restrict the search space to the most relevant subspaces, providing computational complexity gains of up to two orders of magnitude. The developed algorithms are shown to cope well with videos acquired in challenging scenarios, as verified by the analysis of 59 videos from the VDAO database that comprises videos with abandoned objects in a cluttered industrial scenario.« less

N-Screen Aware Multicriteria Hybrid Recommender System Using Weight Based Subspace Clustering

PubMed Central

Ullah, Farman; Lee, Sungchang

2014-01-01

This paper presents a recommender system for N-screen services in which users have multiple devices with different capabilities. In N-screen services, a user can use various devices in different locations and time and can change a device while the service is running. N-screen aware recommendation seeks to improve the user experience with recommended content by considering the user N-screen device attributes such as screen resolution, media codec, remaining battery time, and access network and the user temporal usage pattern information that are not considered in existing recommender systems. For N-screen aware recommendation support, this work introduces a user device profile collaboration agent, manager, and N-screen control server to acquire and manage the user N-screen devices profile. Furthermore, a multicriteria hybrid framework is suggested that incorporates the N-screen devices information with user preferences and demographics. In addition, we propose an individual feature and subspace weight based clustering (IFSWC) to assign different weights to each subspace and each feature within a subspace in the hybrid framework. The proposed system improves the accuracy, precision, scalability, sparsity, and cold start issues. The simulation results demonstrate the effectiveness and prove the aforementioned statements. PMID:25152921

Improvement in the Accuracy of Matching by Different Feature Subspaces in Traffic Sign Recognition

NASA Astrophysics Data System (ADS)

Ihara, Arihito; Fujiyoshi, Hironobu; Takaki, Masanari; Kumon, Hiroaki; Tamatsu, Yukimasa

A technique for recognizing traffic signs from an image taken with an in-vehicle camera has already been proposed as driver's drive assist. SIFT feature is used for traffic sign recognition, because it is robust to changes in scaling and rotating of the traffic sign. However, it is difficult to process in real-time because the computation cost of the SIFT feature extraction and matching is expensive. This paper presents a method of traffic sign recognition based on keypoint classifier by AdaBoost using PCA-SIFT features in different feature subspaces. Each subspace is constructed from gradients of traffic sign images and general images respectively. A detected keypoint is projected to both subspaces, and then the AdaBoost employs to classy into whether the keypoint is on the traffic sign or not. Experimental results show that the computation cost for keypoint matching can be reduced to about 1/2 compared with the conventional method.

Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2004-10-01

Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such algorithms and their implementation in neural networks are potentially useful in cases of tracking slow changes of correlations in the input data or in updating eigenvectors with new samples. In this paper we propose PCA learning algorithm that is fully homogeneous with respect to neurons. The algorithm is obtained by modification of one of the most famous PSA learning algorithms--Subspace Learning Algorithm (SLA). Modification of the algorithm is based on Time-Oriented Hierarchical Method (TOHM). The method uses two distinct time scales. On a faster time scale PSA algorithm is responsible for the "behavior" of all output neurons. On a slower scale, output neurons will compete for fulfillment of their "own interests". On this scale, basis vectors in the principal subspace are rotated toward the principal eigenvectors. At the end of the paper it will be briefly analyzed how (or why) time-oriented hierarchical method can be used for transformation of any of the existing neural network PSA method, into PCA method.

Structure of the human smoothened receptor 7TM bound to an antitumor agent

PubMed Central

Wang, Chong; Wu, Huixian; Katritch, Vsevolod; Han, Gye Won; Huang, Xi-Ping; Liu, Wei; Siu, Fai Yiu; Roth, Bryan L.; Cherezov, Vadim; Stevens, Raymond C.

2013-01-01

The smoothened (SMO) receptor, a key signal transducer in the Hedgehog (Hh) signaling pathway is both responsible for the maintenance of normal embryonic development and implicated in carcinogenesis. The SMO receptor is classified as a class Frizzled (class F) G protein-coupled receptor (GPCR), although the canonical Hh signaling pathway involves the transcription factor Gli and the sequence similarity with class A GPCRs is less than 10%. Here we report the crystal structure at 2.5 Å resolution of the transmembrane domain of the human SMO receptor bound to the small molecule antagonist LY2940680. Although the SMO receptor shares the seven transmembrane helical (7TM) fold, most conserved motifs for class A GPCRs are absent, and the structure reveals an unusually complex arrangement of long extracellular loops stabilized by four disulfide bonds. The ligand binds at the extracellular end of the 7TM bundle and forms extensive contacts with the loops. PMID:23636324

Application of vector-valued rational approximations to the matrix eigenvalue problem and connections with Krylov subspace methods

NASA Technical Reports Server (NTRS)

Sidi, Avram

1992-01-01

Let F(z) be a vectored-valued function F: C approaches C sup N, which is analytic at z=0 and meromorphic in a neighborhood of z=0, and let its Maclaurin series be given. We use vector-valued rational approximation procedures for F(z) that are based on its Maclaurin series in conjunction with power iterations to develop bona fide generalizations of the power method for an arbitrary N X N matrix that may be diagonalizable or not. These generalizations can be used to obtain simultaneously several of the largest distinct eigenvalues and the corresponding invariant subspaces, and present a detailed convergence theory for them. In addition, it is shown that the generalized power methods of this work are equivalent to some Krylov subspace methods, among them the methods of Arnoldi and Lanczos. Thus, the theory provides a set of completely new results and constructions for these Krylov subspace methods. This theory suggests at the same time a new mode of usage for these Krylov subspace methods that were observed to possess computational advantages over their common mode of usage.

A sub-space greedy search method for efficient Bayesian Network inference.

PubMed

Zhang, Qing; Cao, Yong; Li, Yong; Zhu, Yanming; Sun, Samuel S M; Guo, Dianjing

2011-09-01

Bayesian network (BN) has been successfully used to infer the regulatory relationships of genes from microarray dataset. However, one major limitation of BN approach is the computational cost because the calculation time grows more than exponentially with the dimension of the dataset. In this paper, we propose a sub-space greedy search method for efficient Bayesian Network inference. Particularly, this method limits the greedy search space by only selecting gene pairs with higher partial correlation coefficients. Using both synthetic and real data, we demonstrate that the proposed method achieved comparable results with standard greedy search method yet saved ∼50% of the computational time. We believe that sub-space search method can be widely used for efficient BN inference in systems biology. Copyright © 2011 Elsevier Ltd. All rights reserved.

Polarimetric subspace target detector for SAR data based on the Huynen dihedral model

NASA Astrophysics Data System (ADS)

Larson, Victor J.; Novak, Leslie M.

1995-06-01

Two new polarimetric subspace target detectors are developed based on a dihedral signal model for bright peaks within a spatially extended target signature. The first is a coherent dihedral target detector based on the exact Huynen model for a dihedral. The second is a noncoherent dihedral target detector based on the Huynen model with an extra unknown phase term. Expressions for these polarimetric subspace target detectors are developed for both additive Gaussian clutter and more general additive spherically invariant random vector clutter including the K-distribution. For the case of Gaussian clutter with unknown clutter parameters, constant false alarm rate implementations of these polarimetric subspace target detectors are developed. The performance of these dihedral detectors is demonstrated with real millimeter-wave fully polarimetric SAR data. The coherent dihedral detector which is developed with a more accurate description of a dihedral offers no performance advantage over the noncoherent dihedral detector which is computationally more attractive. The dihedral detectors do a better job of separating a set of tactical military targets from natural clutter compared to a detector that assumes no knowledge about the polarimetric structure of the target signal.

Slope angle estimation method based on sparse subspace clustering for probe safe landing

NASA Astrophysics Data System (ADS)

Li, Haibo; Cao, Yunfeng; Ding, Meng; Zhuang, Likui

2018-06-01

To avoid planetary probes landing on steep slopes where they may slip or tip over, a new method of slope angle estimation based on sparse subspace clustering is proposed to improve accuracy. First, a coordinate system is defined and established to describe the measured data of light detection and ranging (LIDAR). Second, this data is processed and expressed with a sparse representation. Third, on this basis, the data is made to cluster to determine which subspace it belongs to. Fourth, eliminating outliers in subspace, the correct data points are used for the fitting planes. Finally, the vectors normal to the planes are obtained using the plane model, and the angle between the normal vectors is obtained through calculation. Based on the geometric relationship, this angle is equal in value to the slope angle. The proposed method was tested in a series of experiments. The experimental results show that this method can effectively estimate the slope angle, can overcome the influence of noise and obtain an exact slope angle. Compared with other methods, this method can minimize the measuring errors and further improve the estimation accuracy of the slope angle.

Molecular activity prediction by means of supervised subspace projection based ensembles of classifiers.

PubMed

Cerruela García, G; García-Pedrajas, N; Luque Ruiz, I; Gómez-Nieto, M Á

2018-03-01

This paper proposes a method for molecular activity prediction in QSAR studies using ensembles of classifiers constructed by means of two supervised subspace projection methods, namely nonparametric discriminant analysis (NDA) and hybrid discriminant analysis (HDA). We studied the performance of the proposed ensembles compared to classical ensemble methods using four molecular datasets and eight different models for the representation of the molecular structure. Using several measures and statistical tests for classifier comparison, we observe that our proposal improves the classification results with respect to classical ensemble methods. Therefore, we show that ensembles constructed using supervised subspace projections offer an effective way of creating classifiers in cheminformatics.

Physical subspace in a model of the quantized electromagnetic field coupled to an external field with an indefinite metric

NASA Astrophysics Data System (ADS)

Suzuki, Akito

2008-04-01

We study a model of the quantized electromagnetic field interacting with an external static source ρ in the Feynman (Lorentz) gauge and construct the quantized radiation field Aμ (μ=0,1,2,3) as an operator-valued distribution acting on the Fock space F with an indefinite metric. By using the Gupta subsidiary condition ∂μAμ(x)(+)Ψ=0, one can select the physical subspace Vphys. According to the Gupta-Bleuler formalism, Vphys is a non-negative subspace so that elements of Vphys, called physical states, can be probabilistically interpretable. Indeed, assuming that the external source ρ is infrared regular, i.e., ρ̂/∣k∣3/2ɛL2(R3), we can characterize the physical subspace Vphys and show that Vphys is non-negative. In addition, we find that the Hamiltonian of the model is reduced to the Hamiltonian of the transverse photons with the Coulomb interaction. We, however, prove that the physical subspace is trivial, i.e., Vphys={0}, if and only if the external source ρ is infrared singular, i.e., ρ̂/∣k∣3/2∉L2(R3). We also discuss a representation different from the above representation such that the physical subspace is not trivial under the infrared singular condition.

Application of Earthquake Subspace Detectors at Kilauea and Mauna Loa Volcanoes, Hawai`i

NASA Astrophysics Data System (ADS)

Okubo, P.; Benz, H.; Yeck, W.

2016-12-01

Recent studies have demonstrated the capabilities of earthquake subspace detectors for detailed cataloging and tracking of seismicity in a number of regions and settings. We are exploring the application of subspace detectors at the United States Geological Survey's Hawaiian Volcano Observatory (HVO) to analyze seismicity at Kilauea and Mauna Loa volcanoes. Elevated levels of microseismicity and occasional swarms of earthquakes associated with active volcanism here present cataloging challenges due the sheer numbers of earthquakes and an intrinsically low signal-to-noise environment featuring oceanic microseism and volcanic tremor in the ambient seismic background. With high-quality continuous recording of seismic data at HVO, we apply subspace detectors (Harris and Dodge, 2011, Bull. Seismol. Soc. Am., doi: 10.1785/0120100103) during intervals of noteworthy seismicity. Waveform templates are drawn from Magnitude 2 and larger earthquakes within clusters of earthquakes cataloged in the HVO seismic database. At Kilauea, we focus on seismic swarms in the summit caldera region where, despite continuing eruptions from vents in the summit region and in the east rift zone, geodetic measurements reflect a relatively inflated volcanic state. We also focus on seismicity beneath and adjacent to Mauna Loa's summit caldera that appears to be associated with geodetic expressions of gradual volcanic inflation, and where precursory seismicity clustered prior to both Mauna Loa's most recent eruptions in 1975 and 1984. We recover several times more earthquakes with the subspace detectors - down to roughly 2 magnitude units below the templates, based on relative amplitudes - compared to the numbers of cataloged earthquakes. The increased numbers of detected earthquakes in these clusters, and the ability to associate and locate them, allow us to infer details of the spatial and temporal distributions and possible variations in stresses within these key regions of the volcanoes.

Discrete-State Stochastic Models of Calcium-Regulated Calcium Influx and Subspace Dynamics Are Not Well-Approximated by ODEs That Neglect Concentration Fluctuations

PubMed Central

Weinberg, Seth H.; Smith, Gregory D.

2012-01-01

Cardiac myocyte calcium signaling is often modeled using deterministic ordinary differential equations (ODEs) and mass-action kinetics. However, spatially restricted “domains” associated with calcium influx are small enough (e.g., 10−17 liters) that local signaling may involve 1–100 calcium ions. Is it appropriate to model the dynamics of subspace calcium using deterministic ODEs or, alternatively, do we require stochastic descriptions that account for the fundamentally discrete nature of these local calcium signals? To address this question, we constructed a minimal Markov model of a calcium-regulated calcium channel and associated subspace. We compared the expected value of fluctuating subspace calcium concentration (a result that accounts for the small subspace volume) with the corresponding deterministic model (an approximation that assumes large system size). When subspace calcium did not regulate calcium influx, the deterministic and stochastic descriptions agreed. However, when calcium binding altered channel activity in the model, the continuous deterministic description often deviated significantly from the discrete stochastic model, unless the subspace volume is unrealistically large and/or the kinetics of the calcium binding are sufficiently fast. This principle was also demonstrated using a physiologically realistic model of calmodulin regulation of L-type calcium channels introduced by Yue and coworkers. PMID:23509597

Subspace Clustering via Learning an Adaptive Low-Rank Graph.

PubMed

Yin, Ming; Xie, Shengli; Wu, Zongze; Zhang, Yun; Gao, Junbin

2018-08-01

By using a sparse representation or low-rank representation of data, the graph-based subspace clustering has recently attracted considerable attention in computer vision, given its capability and efficiency in clustering data. However, the graph weights built using the representation coefficients are not the exact ones as the traditional definition is in a deterministic way. The two steps of representation and clustering are conducted in an independent manner, thus an overall optimal result cannot be guaranteed. Furthermore, it is unclear how the clustering performance will be affected by using this graph. For example, the graph parameters, i.e., the weights on edges, have to be artificially pre-specified while it is very difficult to choose the optimum. To this end, in this paper, a novel subspace clustering via learning an adaptive low-rank graph affinity matrix is proposed, where the affinity matrix and the representation coefficients are learned in a unified framework. As such, the pre-computed graph regularizer is effectively obviated and better performance can be achieved. Experimental results on several famous databases demonstrate that the proposed method performs better against the state-of-the-art approaches, in clustering.

Patient with Gorlin syndrome and metastatic basal cell carcinoma refractory to smoothened inhibitors.

PubMed

Zhu, Gefei A; Li, Angela S; Chang, Anne Lynn S

2014-08-01

Basal cell carcinomas (BCCs) in patients with Gorlin syndrome have been reported to be extremely sensitive to Smoothened (SMO) inhibitors, a novel targeted therapy against the Hedgehog pathway, because of characteristic mutations in these patients. A few cases of disease refractory to oral therapy with SMO inhibitors have been reported in patients with Gorlin syndrome and nonmetastatic BCCs, but refractory disease in distantly metastatic tumors has not been documented in this high-risk group. A man with Gorlin syndrome and innumerable cutaneous BCCs presented with biopsy-proven BCC in his lungs. After SMO inhibitor therapy, almost all of his cutaneous tumors shrank, but his lung metastases did not. These lung metastases remained refractory to treatment despite institution of a second SMO inhibitor. We report a case of Gorlin syndrome in a patient with metastatic BCC refractory to SMO inhibitors. Furthermore, clinical responses in this patient's cutaneous tumors did not parallel the responses in the distant site. However, serial imaging after diagnosis of metastatic disease can be critical to monitor for response to therapy.

Updating Hawaii Seismicity Catalogs with Systematic Relocations and Subspace Detectors

NASA Astrophysics Data System (ADS)

Okubo, P.; Benz, H.; Matoza, R. S.; Thelen, W. A.

2015-12-01

We continue the systematic relocation of seismicity recorded in Hawai`i by the United States Geological Survey's (USGS) Hawaiian Volcano Observatory (HVO), with interests in adding to the products derived from the relocated seismicity catalogs published by Matoza et al., (2013, 2014). Another goal of this effort is updating the systematically relocated HVO catalog since 2009, when earthquake cataloging at HVO was migrated to the USGS Advanced National Seismic System Quake Management Software (AQMS) systems. To complement the relocation analyses of the catalogs generated from traditional STA/LTA event-triggered and analyst-reviewed approaches, we are also experimenting with subspace detection of events at Kilauea as a means to augment AQMS procedures for cataloging seismicity to lower magnitudes and during episodes of elevated volcanic activity. Our earlier catalog relocations have demonstrated the ability to define correlated or repeating families of earthquakes and provide more detailed definition of seismogenic structures, as well as the capability for improved automatic identification of diverse volcanic seismic sources. Subspace detectors have been successfully applied to cataloging seismicity in situations of low seismic signal-to-noise and have significantly increased catalog sensitivity to lower magnitude thresholds. We anticipate similar improvements using event subspace detections and cataloging of volcanic seismicity that include improved discrimination among not only evolving earthquake sequences but also diverse volcanic seismic source processes. Matoza et al., 2013, Systematic relocation of seismicity on Hawai`i Island from 1992 to 2009 using waveform cross correlation and cluster analysis, J. Geophys. Res., 118, 2275-2288, doi:10.1002/jgrb.580189 Matoza et al., 2014, High-precision relocation of long-period events beneath the summit region of Kīlauea Volcano, Hawai`i, from 1986 to 2009, Geophys. Res. Lett., 41, 3413-3421, doi:10.1002/2014GL059819

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

Visual tracking based on the sparse representation of the PCA subspace

NASA Astrophysics Data System (ADS)

Chen, Dian-bing; Zhu, Ming; Wang, Hui-li

2017-09-01

We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.

Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

PubMed

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

2016-10-05

Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

Detecting and characterizing coal mine related seismicity in the Western U.S. using subspace methods

NASA Astrophysics Data System (ADS)

Chambers, Derrick J. A.; Koper, Keith D.; Pankow, Kristine L.; McCarter, Michael K.

2015-11-01

We present an approach for subspace detection of small seismic events that includes methods for estimating magnitudes and associating detections from multiple stations into unique events. The process is used to identify mining related seismicity from a surface coal mine and an underground coal mining district, both located in the Western U.S. Using a blasting log and a locally derived seismic catalogue as ground truth, we assess detector performance in terms of verified detections, false positives and failed detections. We are able to correctly identify over 95 per cent of the surface coal mine blasts and about 33 per cent of the events from the underground mining district, while keeping the number of potential false positives relatively low by requiring all detections to occur on two stations. We find that most of the potential false detections for the underground coal district are genuine events missed by the local seismic network, demonstrating the usefulness of regional subspace detectors in augmenting local catalogues. We note a trade-off in detection performance between stations at smaller source-receiver distances, which have increased signal-to-noise ratio, and stations at larger distances, which have greater waveform similarity. We also explore the increased detection capabilities of a single higher dimension subspace detector, compared to multiple lower dimension detectors, in identifying events that can be described as linear combinations of training events. We find, in our data set, that such an advantage can be significant, justifying the use of a subspace detection scheme over conventional correlation methods.

Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation.

PubMed

Xu, Yong; Fang, Xiaozhao; Wu, Jian; Li, Xuelong; Zhang, David

2016-02-01

In this paper, we address the problem of unsupervised domain transfer learning in which no labels are available in the target domain. We use a transformation matrix to transfer both the source and target data to a common subspace, where each target sample can be represented by a combination of source samples such that the samples from different domains can be well interlaced. In this way, the discrepancy of the source and target domains is reduced. By imposing joint low-rank and sparse constraints on the reconstruction coefficient matrix, the global and local structures of data can be preserved. To enlarge the margins between different classes as much as possible and provide more freedom to diminish the discrepancy, a flexible linear classifier (projection) is obtained by learning a non-negative label relaxation matrix that allows the strict binary label matrix to relax into a slack variable matrix. Our method can avoid a potentially negative transfer by using a sparse matrix to model the noise and, thus, is more robust to different types of noise. We formulate our problem as a constrained low-rankness and sparsity minimization problem and solve it by the inexact augmented Lagrange multiplier method. Extensive experiments on various visual domain adaptation tasks show the superiority of the proposed method over the state-of-the art methods. The MATLAB code of our method will be publicly available at http://www.yongxu.org/lunwen.html.

Similarity preserving low-rank representation for enhanced data representation and effective subspace learning.

PubMed

Zhang, Zhao; Yan, Shuicheng; Zhao, Mingbo

2014-05-01

Latent Low-Rank Representation (LatLRR) delivers robust and promising results for subspace recovery and feature extraction through mining the so-called hidden effects, but the locality of both similar principal and salient features cannot be preserved in the optimizations. To solve this issue for achieving enhanced performance, a boosted version of LatLRR, referred to as Regularized Low-Rank Representation (rLRR), is proposed through explicitly including an appropriate Laplacian regularization that can maximally preserve the similarity among local features. Resembling LatLRR, rLRR decomposes given data matrix from two directions by seeking a pair of low-rank matrices. But the similarities of principal and salient features can be effectively preserved by rLRR. As a result, the correlated features are well grouped and the robustness of representations is also enhanced. Based on the outputted bi-directional low-rank codes by rLRR, an unsupervised subspace learning framework termed Low-rank Similarity Preserving Projections (LSPP) is also derived for feature learning. The supervised extension of LSPP is also discussed for discriminant subspace learning. The validity of rLRR is examined by robust representation and decomposition of real images. Results demonstrated the superiority of our rLRR and LSPP in comparison to other related state-of-the-art algorithms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fuzzy Subspace Clustering

NASA Astrophysics Data System (ADS)

Borgelt, Christian

In clustering we often face the situation that only a subset of the available attributes is relevant for forming clusters, even though this may not be known beforehand. In such cases it is desirable to have a clustering algorithm that automatically weights attributes or even selects a proper subset. In this paper I study such an approach for fuzzy clustering, which is based on the idea to transfer an alternative to the fuzzifier (Klawonn and Höppner, What is fuzzy about fuzzy clustering? Understanding and improving the concept of the fuzzifier, In: Proc. 5th Int. Symp. on Intelligent Data Analysis, 254-264, Springer, Berlin, 2003) to attribute weighting fuzzy clustering (Keller and Klawonn, Int J Uncertain Fuzziness Knowl Based Syst 8:735-746, 2000). In addition, by reformulating Gustafson-Kessel fuzzy clustering, a scheme for weighting and selecting principal axes can be obtained. While in Borgelt (Feature weighting and feature selection in fuzzy clustering, In: Proc. 17th IEEE Int. Conf. on Fuzzy Systems, IEEE Press, Piscataway, NJ, 2008) I already presented such an approach for a global selection of attributes and principal axes, this paper extends it to a cluster-specific selection, thus arriving at a fuzzy subspace clustering algorithm (Parsons, Haque, and Liu, 2004).

Beamforming using subspace estimation from a diagonally averaged sample covariance.

PubMed

Quijano, Jorge E; Zurk, Lisa M

2017-08-01

The potential benefit of a large-aperture sonar array for high resolution target localization is often challenged by the lack of sufficient data required for adaptive beamforming. This paper introduces a Toeplitz-constrained estimator of the clairvoyant signal covariance matrix corresponding to multiple far-field targets embedded in background isotropic noise. The estimator is obtained by averaging along subdiagonals of the sample covariance matrix, followed by covariance extrapolation using the method of maximum entropy. The sample covariance is computed from limited data snapshots, a situation commonly encountered with large-aperture arrays in environments characterized by short periods of local stationarity. Eigenvectors computed from the Toeplitz-constrained covariance are used to construct signal-subspace projector matrices, which are shown to reduce background noise and improve detection of closely spaced targets when applied to subspace beamforming. Monte Carlo simulations corresponding to increasing array aperture suggest convergence of the proposed projector to the clairvoyant signal projector, thereby outperforming the classic projector obtained from the sample eigenvectors. Beamforming performance of the proposed method is analyzed using simulated data, as well as experimental data from the Shallow Water Array Performance experiment.

View subspaces for indexing and retrieval of 3D models

NASA Astrophysics Data System (ADS)

Dutagaci, Helin; Godil, Afzal; Sankur, Bülent; Yemez, Yücel

2010-02-01

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithms.

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

PubMed

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Crystal structure of a multi-domain human smoothened receptor in complex with a super stabilizing ligand

NASA Astrophysics Data System (ADS)

Zhang, Xianjun; Zhao, Fei; Wu, Yiran; Yang, Jun; Han, Gye Won; Zhao, Suwen; Ishchenko, Andrii; Ye, Lintao; Lin, Xi; Ding, Kang; Dharmarajan, Venkatasubramanian; Griffin, Patrick R.; Gati, Cornelius; Nelson, Garrett; Hunter, Mark S.; Hanson, Michael A.; Cherezov, Vadim; Stevens, Raymond C.; Tan, Wenfu; Tao, Houchao; Xu, Fei

2017-05-01

The Smoothened receptor (SMO) belongs to the Class Frizzled of the G protein-coupled receptor (GPCR) superfamily, constituting a key component of the Hedgehog signalling pathway. Here we report the crystal structure of the multi-domain human SMO, bound and stabilized by a designed tool ligand TC114, using an X-ray free-electron laser source at 2.9 Å. The structure reveals a precise arrangement of three distinct domains: a seven-transmembrane helices domain (TMD), a hinge domain (HD) and an intact extracellular cysteine-rich domain (CRD). This architecture enables allosteric interactions between the domains that are important for ligand recognition and receptor activation. By combining the structural data, molecular dynamics simulation, and hydrogen-deuterium-exchange analysis, we demonstrate that transmembrane helix VI, extracellular loop 3 and the HD play a central role in transmitting the signal employing a unique GPCR activation mechanism, distinct from other multi-domain GPCRs.

Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection.

PubMed

Zhu, Xiaofeng; Li, Xuelong; Zhang, Shichao; Ju, Chunhua; Wu, Xindong

2017-06-01

In this paper, we propose a new unsupervised spectral feature selection model by embedding a graph regularizer into the framework of joint sparse regression for preserving the local structures of data. To do this, we first extract the bases of training data by previous dictionary learning methods and, then, map original data into the basis space to generate their new representations, by proposing a novel joint graph sparse coding (JGSC) model. In JGSC, we first formulate its objective function by simultaneously taking subspace learning and joint sparse regression into account, then, design a new optimization solution to solve the resulting objective function, and further prove the convergence of the proposed solution. Furthermore, we extend JGSC to a robust JGSC (RJGSC) via replacing the least square loss function with a robust loss function, for achieving the same goals and also avoiding the impact of outliers. Finally, experimental results on real data sets showed that both JGSC and RJGSC outperformed the state-of-the-art algorithms in terms of k -nearest neighbor classification performance.

SIMULTANEOUS MULTISLICE MAGNETIC RESONANCE FINGERPRINTING WITH LOW-RANK AND SUBSPACE MODELING

PubMed Central

Zhao, Bo; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A.; Wald, Lawrence L.; Setsompop, Kawin

2018-01-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T1, T2, and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3x speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice. PMID:29060594

3D deformable image matching: a hierarchical approach over nested subspaces

NASA Astrophysics Data System (ADS)

Musse, Olivier; Heitz, Fabrice; Armspach, Jean-Paul

2000-06-01

This paper presents a fast hierarchical method to perform dense deformable inter-subject matching of 3D MR Images of the brain. To recover the complex morphological variations in neuroanatomy, a hierarchy of 3D deformations fields is estimated, by minimizing a global energy function over a sequence of nested subspaces. The nested subspaces, generated from a single scaling function, consist of deformation fields constrained at different scales. The highly non linear energy function, describing the interactions between the target and the source images, is minimized using a coarse-to-fine continuation strategy over this hierarchy. The resulting deformable matching method shows low sensitivity to local minima and is able to track large non-linear deformations, with moderate computational load. The performances of the approach are assessed both on simulated 3D transformations and on a real data base of 3D brain MR Images from different individuals. The method has shown efficient in putting into correspondence the principle anatomical structures of the brain. An application to atlas-based MRI segmentation, by transporting a labeled segmentation map on patient data, is also presented.

Multi-subject subspace alignment for non-stationary EEG-based emotion recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Liu, Xin; Liu, Dan; Bai, Ou

2018-01-01

Emotion recognition based on EEG signals is a critical component in Human-Machine collaborative environments and psychiatric health diagnoses. However, EEG patterns have been found to vary across subjects due to user fatigue, different electrode placements, and varying impedances, etc. This problem renders the performance of EEG-based emotion recognition highly specific to subjects, requiring time-consuming individual calibration sessions to adapt an emotion recognition system to new subjects. Recently, domain adaptation (DA) strategies have achieved a great deal success in dealing with inter-subject adaptation. However, most of them can only adapt one subject to another subject, which limits their applicability in real-world scenarios. To alleviate this issue, a novel unsupervised DA strategy called Multi-Subject Subspace Alignment (MSSA) is proposed in this paper, which takes advantage of subspace alignment solution and multi-subject information in a unified framework to build personalized models without user-specific labeled data. Experiments on a public EEG dataset known as SEED verify the effectiveness and superiority of MSSA over other state of the art methods for dealing with multi-subject scenarios.

Stochastic subspace identification for operational modal analysis of an arch bridge

NASA Astrophysics Data System (ADS)

Loh, Chin-Hsiung; Chen, Ming-Che; Chao, Shu-Hsien

2012-04-01

In this paer the application of output-only system identification technique, known as Stochastic Subspace Identification (SSI) algorithms, for civil infrastructures is carried out. The ability of covariance driven stochastic subspace identification (SSI-COV) was proved through the analysis of the ambient data of an arch bridge under operational condition. A newly developed signal processing technique, Singular Spectrum analysis (SSA), capable to smooth noisy signals, is adopted for pre-processing the recorded data before the SSI. The conjunction of SSA and SSICOV provides a useful criterion for the system order determination. With the aim of estimating accurate modal parameters of the structure in off-line analysis, a stabilization diagram is constructed by plotting the identified poles of the system with increasing the size of data Hankel matrix. Identification task of a real structure, Guandu Bridge, is carried out to identify the system natural frequencies and mode shapes. The uncertainty of the identified model parameters from output-only measurement of the bridge under operation condition, such as temperature and traffic loading conditions, is discussed.

Simultaneous multislice magnetic resonance fingerprinting with low-rank and subspace modeling.

PubMed

Bo Zhao; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A; Wald, Lawrence L; Setsompop, Kawin

2017-07-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T 1 , T 2 , and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3× speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice.

Expedited Holonomic Quantum Computation via Net Zero-Energy-Cost Control in Decoherence-Free Subspace.

PubMed

Pyshkin, P V; Luo, Da-Wei; Jing, Jun; You, J Q; Wu, Lian-Ao

2016-11-25

Holonomic quantum computation (HQC) may not show its full potential in quantum speedup due to the prerequisite of a long coherent runtime imposed by the adiabatic condition. Here we show that the conventional HQC can be dramatically accelerated by using external control fields, of which the effectiveness is exclusively determined by the integral of the control fields in the time domain. This control scheme can be realized with net zero energy cost and it is fault-tolerant against fluctuation and noise, significantly relaxing the experimental constraints. We demonstrate how to realize the scheme via decoherence-free subspaces. In this way we unify quantum robustness merits of this fault-tolerant control scheme, the conventional HQC and decoherence-free subspace, and propose an expedited holonomic quantum computation protocol.

Geometrical eigen-subspace framework based molecular conformation representation for efficient structure recognition and comparison

NASA Astrophysics Data System (ADS)

Li, Xiao-Tian; Yang, Xiao-Bao; Zhao, Yu-Jun

2017-04-01

We have developed an extended distance matrix approach to study the molecular geometric configuration through spectral decomposition. It is shown that the positions of all atoms in the eigen-space can be specified precisely by their eigen-coordinates, while the refined atomic eigen-subspace projection array adopted in our approach is demonstrated to be a competent invariant in structure comparison. Furthermore, a visual eigen-subspace projection function (EPF) is derived to characterize the surrounding configuration of an atom naturally. A complete set of atomic EPFs constitute an intrinsic representation of molecular conformation, based on which the interatomic EPF distance and intermolecular EPF distance can be reasonably defined. Exemplified with a few cases, the intermolecular EPF distance shows exceptional rationality and efficiency in structure recognition and comparison.

Limited Memory Block Krylov Subspace Optimization for Computing Dominant Singular Value Decompositions

DTIC Science & Technology

2012-03-22

with performance profiles, Math. Program., 91 (2002), pp. 201–213. [6] P. DRINEAS, R. KANNAN, AND M. W. MAHONEY , Fast Monte Carlo algorithms for matrices...computing invariant subspaces of non-Hermitian matri- ces, Numer. Math., 25 ( 1975 /76), pp. 123–136. [25] , Matrix algorithms Vol. II: Eigensystems

Code subspaces for LLM geometries

NASA Astrophysics Data System (ADS)

Berenstein, David; Miller, Alexandra

2018-03-01

We consider effective field theory around classical background geometries with a gauge theory dual, specifically those in the class of LLM geometries. These are dual to half-BPS states of N= 4 SYM. We find that the language of code subspaces is natural for discussing the set of nearby states, which are built by acting with effective fields on these backgrounds. This work extends our previous work by going beyond the strict infinite N limit. We further discuss how one can extract the topology of the state beyond N→∞ and find that, as before, uncertainty and entanglement entropy calculations provide a useful tool to do so. Finally, we discuss obstructions to writing down a globally defined metric operator. We find that the answer depends on the choice of reference state that one starts with. Therefore, within this setup, there is ambiguity in trying to write an operator that describes the metric globally.

Krylov subspace methods on supercomputers

NASA Technical Reports Server (NTRS)

Saad, Youcef

1988-01-01

A short survey of recent research on Krylov subspace methods with emphasis on implementation on vector and parallel computers is presented. Conjugate gradient methods have proven very useful on traditional scalar computers, and their popularity is likely to increase as three-dimensional models gain importance. A conservative approach to derive effective iterative techniques for supercomputers has been to find efficient parallel/vector implementations of the standard algorithms. The main source of difficulty in the incomplete factorization preconditionings is in the solution of the triangular systems at each step. A few approaches consisting of implementing efficient forward and backward triangular solutions are described in detail. Polynomial preconditioning as an alternative to standard incomplete factorization techniques is also discussed. Another efficient approach is to reorder the equations so as to improve the structure of the matrix to achieve better parallelism or vectorization. An overview of these and other ideas and their effectiveness or potential for different types of architectures is given.

A hybrid approach to generating search subspaces in dynamically constrained 4-dimensional data assimilation

NASA Astrophysics Data System (ADS)

Yaremchuk, Max; Martin, Paul; Beattie, Christopher

2017-09-01

Development and maintenance of the linearized and adjoint code for advanced circulation models is a challenging issue, requiring a significant proportion of total effort in operational data assimilation (DA). The ensemble-based DA techniques provide a derivative-free alternative, which appears to be competitive with variational methods in many practical applications. This article proposes a hybrid scheme for generating the search subspaces in the adjoint-free 4-dimensional DA method (a4dVar) that does not use a predefined ensemble. The method resembles 4dVar in that the optimal solution is strongly constrained by model dynamics and search directions are supplied iteratively using information from the current and previous model trajectories generated in the process of optimization. In contrast to 4dVar, which produces a single search direction from exact gradient information, a4dVar employs an ensemble of directions to form a subspace in order to proceed. In the earlier versions of a4dVar, search subspaces were built using the leading EOFs of either the model trajectory or the projections of the model-data misfits onto the range of the background error covariance (BEC) matrix at the current iteration. In the present study, we blend both approaches and explore a hybrid scheme of ensemble generation in order to improve the performance and flexibility of the algorithm. In addition, we introduce balance constraints into the BEC structure and periodically augment the search ensemble with BEC eigenvectors to avoid repeating minimization over already explored subspaces. Performance of the proposed hybrid a4dVar (ha4dVar) method is compared with that of standard 4dVar in a realistic regional configuration assimilating real data into the Navy Coastal Ocean Model (NCOM). It is shown that the ha4dVar converges faster than a4dVar and can be potentially competitive with 4dvar both in terms of the required computational time and the forecast skill.

Improving the Nulling Beamformer Using Subspace Suppression.

PubMed

Rana, Kunjan D; Hämäläinen, Matti S; Vaina, Lucia M

2018-01-01

Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources with sensors outside the head. In MEG analysis these current sources are estimated from the measured data to identify the locations and time courses of neural activity. Since there is no unique solution to this so-called inverse problem, multiple source estimation techniques have been developed. The nulling beamformer (NB), a modified form of the linearly constrained minimum variance (LCMV) beamformer, is specifically used in the process of inferring interregional interactions and is designed to eliminate shared signal contributions, or cross-talk, between regions of interest (ROIs) that would otherwise interfere with the connectivity analyses. The nulling beamformer applies the truncated singular value decomposition (TSVD) to remove small signal contributions from a ROI to the sensor signals. However, ROIs with strong crosstalk will have high separating power in the weaker components, which may be removed by the TSVD operation. To address this issue we propose a new method, the nulling beamformer with subspace suppression (NBSS). This method, controlled by a tuning parameter, reweights the singular values of the gain matrix mapping from source to sensor space such that components with high overlap are reduced. By doing so, we are able to measure signals between nearby source locations with limited cross-talk interference, allowing for reliable cortical connectivity analysis between them. In two simulations, we demonstrated that NBSS reduces cross-talk while retaining ROIs' signal power, and has higher separating power than both the minimum norm estimate (MNE) and the nulling beamformer without subspace suppression. We also showed that NBSS successfully localized the auditory M100 event-related field in primary auditory cortex, measured from a subject undergoing an auditory localizer task, and suppressed cross-talk in a nearby region in the superior temporal sulcus.

Application of Subspace Detection to the 6 November 2011 M5.6 Prague, Oklahoma Aftershock Sequence

NASA Astrophysics Data System (ADS)

McMahon, N. D.; Benz, H.; Johnson, C. E.; Aster, R. C.; McNamara, D. E.

2015-12-01

Subspace detection is a powerful tool for the identification of small seismic events. Subspace detectors improve upon single-event matched filtering techniques by using multiple orthogonal waveform templates whose linear combinations characterize a range of observed signals from previously identified earthquakes. Subspace detectors running on multiple stations can significantly increasing the number of locatable events, lowering the catalog's magnitude of completeness and thus providing extraordinary detail on the kinematics of the aftershock process. The 6 November 2011 M5.6 earthquake near Prague, Oklahoma is the largest earthquake instrumentally recorded in Oklahoma history and the largest earthquake resultant from deep wastewater injection. A M4.8 foreshock on 5 November 2011 and the M5.6 mainshock triggered tens of thousands of detectable aftershocks along a 20 km splay of the Wilzetta Fault Zone known as the Meeker-Prague fault. In response to this unprecedented earthquake, 21 temporary seismic stations were deployed surrounding the seismic activity. We utilized a catalog of 767 previously located aftershocks to construct subspace detectors for the 21 temporary and 10 closest permanent seismic stations. Subspace detection identified more than 500,000 new arrival-time observations, which associated into more than 20,000 locatable earthquakes. The associated earthquakes were relocated using the Bayesloc multiple-event locator, resulting in ~7,000 earthquakes with hypocentral uncertainties of less than 500 m. The relocated seismicity provides unique insight into the spatio-temporal evolution of the aftershock sequence along the Wilzetta Fault Zone and its associated structures. We find that the crystalline basement and overlying sedimentary Arbuckle formation accommodate the majority of aftershocks. While we observe aftershocks along the entire 20 km length of the Meeker-Prague fault, the vast majority of earthquakes were confined to a 9 km wide by 9 km deep

Multi-frequency subspace migration for imaging of perfectly conducting, arc-like cracks in full- and limited-view inverse scattering problems

NASA Astrophysics Data System (ADS)

Park, Won-Kwang

2015-02-01

Multi-frequency subspace migration imaging techniques are usually adopted for the non-iterative imaging of unknown electromagnetic targets, such as cracks in concrete walls or bridges and anti-personnel mines in the ground, in the inverse scattering problems. It is confirmed that this technique is very fast, effective, robust, and can not only be applied to full- but also to limited-view inverse problems if a suitable number of incidents and corresponding scattered fields are applied and collected. However, in many works, the application of such techniques is heuristic. With the motivation of such heuristic application, this study analyzes the structure of the imaging functional employed in the subspace migration imaging technique in two-dimensional full- and limited-view inverse scattering problems when the unknown targets are arbitrary-shaped, arc-like perfectly conducting cracks located in the two-dimensional homogeneous space. In contrast to the statistical approach based on statistical hypothesis testing, our approach is based on the fact that the subspace migration imaging functional can be expressed by a linear combination of the Bessel functions of integer order of the first kind. This is based on the structure of the Multi-Static Response (MSR) matrix collected in the far-field at nonzero frequency in either Transverse Magnetic (TM) mode (Dirichlet boundary condition) or Transverse Electric (TE) mode (Neumann boundary condition). The investigation of the expression of imaging functionals gives us certain properties of subspace migration and explains why multi-frequency enhances imaging resolution. In particular, we carefully analyze the subspace migration and confirm some properties of imaging when a small number of incident fields are applied. Consequently, we introduce a weighted multi-frequency imaging functional and confirm that it is an improved version of subspace migration in TM mode. Various results of numerical simulations performed on the far

Expedited Holonomic Quantum Computation via Net Zero-Energy-Cost Control in Decoherence-Free Subspace

PubMed Central

Pyshkin, P. V.; Luo, Da-Wei; Jing, Jun; You, J. Q.; Wu, Lian-Ao

2016-01-01

Holonomic quantum computation (HQC) may not show its full potential in quantum speedup due to the prerequisite of a long coherent runtime imposed by the adiabatic condition. Here we show that the conventional HQC can be dramatically accelerated by using external control fields, of which the effectiveness is exclusively determined by the integral of the control fields in the time domain. This control scheme can be realized with net zero energy cost and it is fault-tolerant against fluctuation and noise, significantly relaxing the experimental constraints. We demonstrate how to realize the scheme via decoherence-free subspaces. In this way we unify quantum robustness merits of this fault-tolerant control scheme, the conventional HQC and decoherence-free subspace, and propose an expedited holonomic quantum computation protocol. PMID:27886234

Subcellular Localization of Patched and Smoothened, the Receptors for Sonic Hedgehog Signaling, in the Hippocampal Neuron

PubMed Central

Petralia, Ronald S.; Schwartz, Catherine M.; Wang, Ya-Xian; Mattson, Mark P.; Yao, Pamela J.

2011-01-01

Cumulative evidence suggests that, aside from patterning the embryonic neural tube, Sonic hedgehog (Shh) signaling plays important roles in the mature nervous system. In this study, we investigate the expression and localization of the Shh signaling receptors, Patched (Ptch) and Smoothened (Smo), in the hippocampal neurons of young and mature rats. Reverse transcriptase-polymerase chain reaction and immunoblotting analyses show that the expression of Ptch and Smo remains at a moderate level in young postnatal and adult brains. By using immunofluorescence light microscopy and immunoelectron microscopy, we examine the spatial distribution of Ptch and Smo within the hippocampal neurons. In young developing neurons, Ptch and Smo are present in the processes and are clustered at their growth cones. In mature neurons, Ptch and Smo are concentrated in dendrites, spines, and postsynaptic sites. Synaptic Ptch and Smo often co-exist with unusual structures—synaptic spinules and autophagosomes. Our results reveal the anatomical organization of the Shh receptors within both the young and the mature hippocampal neurons. PMID:21618238

Crystal structure of a multi-domain human smoothened receptor in complex with a super stabilizing ligand

DOE PAGES

Zhang, Xianjun; Zhao, Fei; Wu, Yiran; ...

2017-05-17

Here, the Smoothened receptor (SMO) belongs to the Class Frizzled of the G protein-coupled receptor (GPCR) superfamily, constituting a key component of the Hedgehog signalling pathway. Here we report the crystal structure of the multi-domain human SMO, bound and stabilized by a designed tool ligand TC114, using an X-ray free-electron laser source at 2.9 Å. The structure reveals a precise arrangement of three distinct domains: a seven-transmembrane helices domain (TMD), a hinge domain (HD) and an intact extracellular cysteine-rich domain (CRD). This architecture enables allosteric interactions between the domains that are important for ligand recognition and receptor activation. By combiningmore » the structural data, molecular dynamics simulation, and hydrogen-deuterium-exchange analysis, we demonstrate that transmembrane helix VI, extracellular loop 3 and the HD play a central role in transmitting the signal employing a unique GPCR activation mechanism, distinct from other multi-domain GPCRs.« less

Highly Entangled, Non-random Subspaces of Tensor Products from Quantum Groups

NASA Astrophysics Data System (ADS)

Brannan, Michael; Collins, Benoît

2018-03-01

In this paper we describe a class of highly entangled subspaces of a tensor product of finite-dimensional Hilbert spaces arising from the representation theory of free orthogonal quantum groups. We determine their largest singular values and obtain lower bounds for the minimum output entropy of the corresponding quantum channels. An application to the construction of d-positive maps on matrix algebras is also presented.

Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium

NASA Astrophysics Data System (ADS)

Chen, Xudong

2010-07-01

This paper proposes a version of the subspace-based optimization method to solve the inverse scattering problem with an inhomogeneous background medium where the known inhomogeneities are bounded in a finite domain. Although the background Green's function at each discrete point in the computational domain is not directly available in an inhomogeneous background scenario, the paper uses the finite element method to simultaneously obtain the Green's function at all discrete points. The essence of the subspace-based optimization method is that part of the contrast source is determined from the spectrum analysis without using any optimization, whereas the orthogonally complementary part is determined by solving a lower dimension optimization problem. This feature significantly speeds up the convergence of the algorithm and at the same time makes it robust against noise. Numerical simulations illustrate the efficacy of the proposed algorithm. The algorithm presented in this paper finds wide applications in nondestructive evaluation, such as through-wall imaging.

A combined joint diagonalization-MUSIC algorithm for subsurface targets localization

NASA Astrophysics Data System (ADS)

Wang, Yinlin; Sigman, John B.; Barrowes, Benjamin E.; O'Neill, Kevin; Shubitidze, Fridon

2014-06-01

This paper presents a combined joint diagonalization (JD) and multiple signal classification (MUSIC) algorithm for estimating subsurface objects locations from electromagnetic induction (EMI) sensor data, without solving ill-posed inverse-scattering problems. JD is a numerical technique that finds the common eigenvectors that diagonalize a set of multistatic response (MSR) matrices measured by a time-domain EMI sensor. Eigenvalues from targets of interest (TOI) can be then distinguished automatically from noise-related eigenvalues. Filtering is also carried out in JD to improve the signal-to-noise ratio (SNR) of the data. The MUSIC algorithm utilizes the orthogonality between the signal and noise subspaces in the MSR matrix, which can be separated with information provided by JD. An array of theoreticallycalculated Green's functions are then projected onto the noise subspace, and the location of the target is estimated by the minimum of the projection owing to the orthogonality. This combined method is applied to data from the Time-Domain Electromagnetic Multisensor Towed Array Detection System (TEMTADS). Examples of TEMTADS test stand data and field data collected at Spencer Range, Tennessee are analyzed and presented. Results indicate that due to its noniterative mechanism, the method can be executed fast enough to provide real-time estimation of objects' locations in the field.

Two-Level Chebyshev Filter Based Complementary Subspace Method: Pushing the Envelope of Large-Scale Electronic Structure Calculations.

PubMed

Banerjee, Amartya S; Lin, Lin; Suryanarayana, Phanish; Yang, Chao; Pask, John E

2018-06-12

We describe a novel iterative strategy for Kohn-Sham density functional theory calculations aimed at large systems (>1,000 electrons), applicable to metals and insulators alike. In lieu of explicit diagonalization of the Kohn-Sham Hamiltonian on every self-consistent field (SCF) iteration, we employ a two-level Chebyshev polynomial filter based complementary subspace strategy to (1) compute a set of vectors that span the occupied subspace of the Hamiltonian; (2) reduce subspace diagonalization to just partially occupied states; and (3) obtain those states in an efficient, scalable manner via an inner Chebyshev filter iteration. By reducing the necessary computation to just partially occupied states and obtaining these through an inner Chebyshev iteration, our approach reduces the cost of large metallic calculations significantly, while eliminating subspace diagonalization for insulating systems altogether. We describe the implementation of the method within the framework of the discontinuous Galerkin (DG) electronic structure method and show that this results in a computational scheme that can effectively tackle bulk and nano systems containing tens of thousands of electrons, with chemical accuracy, within a few minutes or less of wall clock time per SCF iteration on large-scale computing platforms. We anticipate that our method will be instrumental in pushing the envelope of large-scale ab initio molecular dynamics. As a demonstration of this, we simulate a bulk silicon system containing 8,000 atoms at finite temperature, and obtain an average SCF step wall time of 51 s on 34,560 processors; thus allowing us to carry out 1.0 ps of ab initio molecular dynamics in approximately 28 h (of wall time).

Sparsity-aware tight frame learning with adaptive subspace recognition for multiple fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yang, Boyuan

2017-09-01

It is a challenging problem to design excellent dictionaries to sparsely represent diverse fault information and simultaneously discriminate different fault sources. Therefore, this paper describes and analyzes a novel multiple feature recognition framework which incorporates the tight frame learning technique with an adaptive subspace recognition strategy. The proposed framework consists of four stages. Firstly, by introducing the tight frame constraint into the popular dictionary learning model, the proposed tight frame learning model could be formulated as a nonconvex optimization problem which can be solved by alternatively implementing hard thresholding operation and singular value decomposition. Secondly, the noises are effectively eliminated through transform sparse coding techniques. Thirdly, the denoised signal is decoupled into discriminative feature subspaces by each tight frame filter. Finally, in guidance of elaborately designed fault related sensitive indexes, latent fault feature subspaces can be adaptively recognized and multiple faults are diagnosed simultaneously. Extensive numerical experiments are sequently implemented to investigate the sparsifying capability of the learned tight frame as well as its comprehensive denoising performance. Most importantly, the feasibility and superiority of the proposed framework is verified through performing multiple fault diagnosis of motor bearings. Compared with the state-of-the-art fault detection techniques, some important advantages have been observed: firstly, the proposed framework incorporates the physical prior with the data-driven strategy and naturally multiple fault feature with similar oscillation morphology can be adaptively decoupled. Secondly, the tight frame dictionary directly learned from the noisy observation can significantly promote the sparsity of fault features compared to analytical tight frames. Thirdly, a satisfactory complete signal space description property is guaranteed and thus

Subspace projection method for unstructured searches with noisy quantum oracles using a signal-based quantum emulation device

NASA Astrophysics Data System (ADS)

La Cour, Brian R.; Ostrove, Corey I.

2017-01-01

This paper describes a novel approach to solving unstructured search problems using a classical, signal-based emulation of a quantum computer. The classical nature of the representation allows one to perform subspace projections in addition to the usual unitary gate operations. Although bandwidth requirements will limit the scale of problems that can be solved by this method, it can nevertheless provide a significant computational advantage for problems of limited size. In particular, we find that, for the same number of noisy oracle calls, the proposed subspace projection method provides a higher probability of success for finding a solution than does an single application of Grover's algorithm on the same device.

Visual characterization and diversity quantification of chemical libraries: 2. Analysis and selection of size-independent, subspace-specific diversity indices.

PubMed

Colliandre, Lionel; Le Guilloux, Vincent; Bourg, Stephane; Morin-Allory, Luc

2012-02-27

High Throughput Screening (HTS) is a standard technique widely used to find hit compounds in drug discovery projects. The high costs associated with such experiments have highlighted the need to carefully design screening libraries in order to avoid wasting resources. Molecular diversity is an established concept that has been used to this end for many years. In this article, a new approach to quantify the molecular diversity of screening libraries is presented. The approach is based on the Delimited Reference Chemical Subspace (DRCS) methodology, a new method that can be used to delimit the densest subspace spanned by a reference library in a reduced 2D continuous space. A total of 22 diversity indices were implemented or adapted to this methodology, which is used here to remove outliers and obtain a relevant cell-based partition of the subspace. The behavior of these indices was assessed and compared in various extreme situations and with respect to a set of theoretical rules that a diversity function should satisfy when libraries of different sizes have to be compared. Some gold standard indices are found inappropriate in such a context, while none of the tested indices behave perfectly in all cases. Five DRCS-based indices accounting for different aspects of diversity were finally selected, and a simple framework is proposed to use them effectively. Various libraries have been profiled with respect to more specific subspaces, which further illustrate the interest of the method.

A Subspace Semi-Definite programming-based Underestimation (SSDU) method for stochastic global optimization in protein docking*

PubMed Central

Nan, Feng; Moghadasi, Mohammad; Vakili, Pirooz; Vajda, Sandor; Kozakov, Dima; Ch. Paschalidis, Ioannis

2015-01-01

We propose a new stochastic global optimization method targeting protein docking problems. The method is based on finding a general convex polynomial underestimator to the binding energy function in a permissive subspace that possesses a funnel-like structure. We use Principal Component Analysis (PCA) to determine such permissive subspaces. The problem of finding the general convex polynomial underestimator is reduced into the problem of ensuring that a certain polynomial is a Sum-of-Squares (SOS), which can be done via semi-definite programming. The underestimator is then used to bias sampling of the energy function in order to recover a deep minimum. We show that the proposed method significantly improves the quality of docked conformations compared to existing methods. PMID:25914440

Subcellular localization of Patched and Smoothened, the receptors for Sonic hedgehog signaling, in the hippocampal neuron.

PubMed

Petralia, Ronald S; Schwartz, Catherine M; Wang, Ya-Xian; Mattson, Mark P; Yao, Pamela J

2011-12-15

Cumulative evidence suggests that, aside from patterning the embryonic neural tube, Sonic hedgehog (Shh) signaling plays important roles in the mature nervous system. In this study, we investigate the expression and localization of the Shh signaling receptors, Patched (Ptch) and Smoothened (Smo), in the hippocampal neurons of young and mature rats. Reverse transcriptase-polymerase chain reaction and immunoblotting analyses show that the expression of Ptch and Smo remains at a moderate level in young postnatal and adult brains. By using immunofluorescence light microscopy and immunoelectron microscopy, we examine the spatial distribution of Ptch and Smo within the hippocampal neurons. In young developing neurons, Ptch and Smo are present in the processes and are clustered at their growth cones. In mature neurons, Ptch and Smo are concentrated in dendrites, spines, and postsynaptic sites. Synaptic Ptch and Smo often co-exist with unusual structures-synaptic spinules and autophagosomes. Our results reveal the anatomical organization of the Shh receptors within both the young and the mature hippocampal neurons. Copyright © 2011 Wiley-Liss, Inc.

Blind equalization and automatic modulation classification based on subspace for subcarrier MPSK optical communications

NASA Astrophysics Data System (ADS)

Chen, Dan; Guo, Lin-yuan; Wang, Chen-hao; Ke, Xi-zheng

2017-07-01

Equalization can compensate channel distortion caused by channel multipath effects, and effectively improve convergent of modulation constellation diagram in optical wireless system. In this paper, the subspace blind equalization algorithm is used to preprocess M-ary phase shift keying (MPSK) subcarrier modulation signal in receiver. Mountain clustering is adopted to get the clustering centers of MPSK modulation constellation diagram, and the modulation order is automatically identified through the k-nearest neighbor (KNN) classifier. The experiment has been done under four different weather conditions. Experimental results show that the convergent of constellation diagram is improved effectively after using the subspace blind equalization algorithm, which means that the accuracy of modulation recognition is increased. The correct recognition rate of 16PSK can be up to 85% in any kind of weather condition which is mentioned in paper. Meanwhile, the correct recognition rate is the highest in cloudy and the lowest in heavy rain condition.

A Tensor-Based Subspace Approach for Bistatic MIMO Radar in Spatial Colored Noise

PubMed Central

Wang, Xianpeng; Wang, Wei; Li, Xin; Wang, Junxiang

2014-01-01

In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method. PMID:24573313

Moving Sound Source Localization Based on Sequential Subspace Estimation in Actual Room Environments

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Suyama, Kenji

This paper presents a novel method for moving sound source localization and its performance evaluation in actual room environments. The method is based on the MUSIC (MUltiple SIgnal Classification) which is one of the most high resolution localization methods. When using the MUSIC, a computation of eigenvectors of correlation matrix is required for the estimation. It needs often a high computational costs. Especially, in the situation of moving source, it becomes a crucial drawback because the estimation must be conducted at every the observation time. Moreover, since the correlation matrix varies its characteristics due to the spatial-temporal non-stationarity, the matrix have to be estimated using only a few observed samples. It makes the estimation accuracy degraded. In this paper, the PAST (Projection Approximation Subspace Tracking) is applied for sequentially estimating the eigenvectors spanning the subspace. In the PAST, the eigen-decomposition is not required, and therefore it is possible to reduce the computational costs. Several experimental results in the actual room environments are shown to present the superior performance of the proposed method.

A tensor-based subspace approach for bistatic MIMO radar in spatial colored noise.

PubMed

Wang, Xianpeng; Wang, Wei; Li, Xin; Wang, Junxiang

2014-02-25

In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method.

Development of Subspace-based Hybrid Monte Carlo-Deterministric Algorithms for Reactor Physics Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abdel-Khalik, Hany S.; Zhang, Qiong

2014-05-20

The development of hybrid Monte-Carlo-Deterministic (MC-DT) approaches, taking place over the past few decades, have primarily focused on shielding and detection applications where the analysis requires a small number of responses, i.e. at the detector locations(s). This work further develops a recently introduced global variance reduction approach, denoted by the SUBSPACE approach is designed to allow the use of MC simulation, currently limited to benchmarking calculations, for routine engineering calculations. By way of demonstration, the SUBSPACE approach is applied to assembly level calculations used to generate the few-group homogenized cross-sections. These models are typically expensive and need to be executedmore » in the order of 10 3 - 10 5 times to properly characterize the few-group cross-sections for downstream core-wide calculations. Applicability to k-eigenvalue core-wide models is also demonstrated in this work. Given the favorable results obtained in this work, we believe the applicability of the MC method for reactor analysis calculations could be realized in the near future.« less

Subspace Dimensionality: A Tool for Automated QC in Seismic Array Processing

NASA Astrophysics Data System (ADS)

Rowe, C. A.; Stead, R. J.; Begnaud, M. L.

2013-12-01

Because of the great resolving power of seismic arrays, the application of automated processing to array data is critically important in treaty verification work. A significant problem in array analysis is the inclusion of bad sensor channels in the beamforming process. We are testing an approach to automated, on-the-fly quality control (QC) to aid in the identification of poorly performing sensor channels prior to beam-forming in routine event detection or location processing. The idea stems from methods used for large computer servers, when monitoring traffic at enormous numbers of nodes is impractical on a node-by node basis, so the dimensionality of the node traffic is instead monitoried for anomalies that could represent malware, cyber-attacks or other problems. The technique relies upon the use of subspace dimensionality or principal components of the overall system traffic. The subspace technique is not new to seismology, but its most common application has been limited to comparing waveforms to an a priori collection of templates for detecting highly similar events in a swarm or seismic cluster. In the established template application, a detector functions in a manner analogous to waveform cross-correlation, applying a statistical test to assess the similarity of the incoming data stream to known templates for events of interest. In our approach, we seek not to detect matching signals, but instead, we examine the signal subspace dimensionality in much the same way that the method addresses node traffic anomalies in large computer systems. Signal anomalies recorded on seismic arrays affect the dimensional structure of the array-wide time-series. We have shown previously that this observation is useful in identifying real seismic events, either by looking at the raw signal or derivatives thereof (entropy, kurtosis), but here we explore the effects of malfunctioning channels on the dimension of the data and its derivatives, and how to leverage this effect for

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

PubMed

Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L

2018-02-01

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Joint Estimation of Time-Frequency Signature and DOA Based on STFD for Multicomponent Chirp Signals

PubMed Central

Zhao, Ziyue; Liu, Congfeng

2014-01-01

In the study of the joint estimation of time-frequency signature and direction of arrival (DOA) for multicomponent chirp signals, an estimation method based on spatial time-frequency distributions (STFDs) is proposed in this paper. Firstly, array signal model for multicomponent chirp signals is presented and then array processing is applied in time-frequency analysis to mitigate cross-terms. According to the results of the array processing, Hough transform is performed and the estimation of time-frequency signature is obtained. Subsequently, subspace method for DOA estimation based on STFD matrix is achieved. Simulation results demonstrate the validity of the proposed method. PMID:27382610

Joint Estimation of Time-Frequency Signature and DOA Based on STFD for Multicomponent Chirp Signals.

PubMed

Zhao, Ziyue; Liu, Congfeng

2014-01-01

In the study of the joint estimation of time-frequency signature and direction of arrival (DOA) for multicomponent chirp signals, an estimation method based on spatial time-frequency distributions (STFDs) is proposed in this paper. Firstly, array signal model for multicomponent chirp signals is presented and then array processing is applied in time-frequency analysis to mitigate cross-terms. According to the results of the array processing, Hough transform is performed and the estimation of time-frequency signature is obtained. Subsequently, subspace method for DOA estimation based on STFD matrix is achieved. Simulation results demonstrate the validity of the proposed method.

A new modulated Hebbian learning rule--biologically plausible method for local computation of a principal subspace.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2003-08-01

This paper presents one possible implementation of a transformation that performs linear mapping to a lower-dimensional subspace. Principal component subspace will be the one that will be analyzed. Idea implemented in this paper represents generalization of the recently proposed infinity OH neural method for principal component extraction. The calculations in the newly proposed method are performed locally--a feature which is usually considered as desirable from the biological point of view. Comparing to some other wellknown methods, proposed synaptic efficacy learning rule requires less information about the value of the other efficacies to make single efficacy modification. Synaptic efficacies are modified by implementation of Modulated Hebb-type (MH) learning rule. Slightly modified MH algorithm named Modulated Hebb Oja (MHO) algorithm, will be also introduced. Structural similarity of the proposed network with part of the retinal circuit will be presented, too.

Sharp inflaton potentials and bi-spectra: effects of smoothening the discontinuity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, Jérôme; Sriramkumar, L.; Hazra, Dhiraj Kumar, E-mail: jmartin@iap.fr, E-mail: sriram@physics.iitm.ac.in, E-mail: dhiraj@apctp.org

Sharp shapes in the inflaton potentials often lead to short departures from slow roll which, in turn, result in deviations from scale invariance in the scalar power spectrum. Typically, in such situations, the scalar power spectrum exhibits a burst of features associated with modes that leave the Hubble radius either immediately before or during the epoch of fast roll. Moreover, one also finds that the power spectrum turns scale invariant at smaller scales corresponding to modes that leave the Hubble radius at later stages, when slow roll has been restored. In other words, the imprints of brief departures from slowmore » roll, arising out of sharp shapes in the inflaton potential, are usually of a finite width in the scalar power spectrum. Intuitively, one may imagine that the scalar bi-spectrum too may exhibit a similar behavior, i.e. a restoration of scale invariance at small scales, when slow roll has been reestablished. However, in the case of the Starobinsky model (viz. the model described by a linear inflaton potential with a sudden change in its slope) involving the canonical scalar field, it has been found that, a rather sharp, though short, departure from slow roll can leave a lasting and significant imprint on the bi-spectrum. The bi-spectrum in this case is found to grow linearly with the wavenumber at small scales, a behavior which is clearly unphysical. In this work, we study the effects of smoothening the discontinuity in the Starobinsky model on the scalar bi-spectrum. Focusing on the equilateral limit, we analytically show that, for smoother potentials, the bi-spectrum indeed turns scale invariant at suitably large wavenumbers. We also confirm the analytical results numerically using our newly developed code BINGO. We conclude with a few comments on certain related points.« less

Wavelet subspace decomposition of thermal infrared images for defect detection in artworks

NASA Astrophysics Data System (ADS)

Ahmad, M. Z.; Khan, A. A.; Mezghani, S.; Perrin, E.; Mouhoubi, K.; Bodnar, J. L.; Vrabie, V.

2016-07-01

Health of ancient artworks must be routinely monitored for their adequate preservation. Faults in these artworks may develop over time and must be identified as precisely as possible. The classical acoustic testing techniques, being invasive, risk causing permanent damage during periodic inspections. Infrared thermometry offers a promising solution to map faults in artworks. It involves heating the artwork and recording its thermal response using infrared camera. A novel strategy based on pseudo-random binary excitation principle is used in this work to suppress the risks associated with prolonged heating. The objective of this work is to develop an automatic scheme for detecting faults in the captured images. An efficient scheme based on wavelet based subspace decomposition is developed which favors identification of, the otherwise invisible, weaker faults. Two major problems addressed in this work are the selection of the optimal wavelet basis and the subspace level selection. A novel criterion based on regional mutual information is proposed for the latter. The approach is successfully tested on a laboratory based sample as well as real artworks. A new contrast enhancement metric is developed to demonstrate the quantitative efficiency of the algorithm. The algorithm is successfully deployed for both laboratory based and real artworks.

Reweighted mass center based object-oriented sparse subspace clustering for hyperspectral images

NASA Astrophysics Data System (ADS)

Zhai, Han; Zhang, Hongyan; Zhang, Liangpei; Li, Pingxiang

2016-10-01

Considering the inevitable obstacles faced by the pixel-based clustering methods, such as salt-and-pepper noise, high computational complexity, and the lack of spatial information, a reweighted mass center based object-oriented sparse subspace clustering (RMC-OOSSC) algorithm for hyperspectral images (HSIs) is proposed. First, the mean-shift segmentation method is utilized to oversegment the HSI to obtain meaningful objects. Second, a distance reweighted mass center learning model is presented to extract the representative and discriminative features for each object. Third, assuming that all the objects are sampled from a union of subspaces, it is natural to apply the SSC algorithm to the HSI. Faced with the high correlation among the hyperspectral objects, a weighting scheme is adopted to ensure that the highly correlated objects are preferred in the procedure of sparse representation, to reduce the representation errors. Two widely used hyperspectral datasets were utilized to test the performance of the proposed RMC-OOSSC algorithm, obtaining high clustering accuracies (overall accuracy) of 71.98% and 89.57%, respectively. The experimental results show that the proposed method clearly improves the clustering performance with respect to the other state-of-the-art clustering methods, and it significantly reduces the computational time.

Gene selection for microarray data classification via subspace learning and manifold regularization.

PubMed

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

Krylov subspace iterative methods for boundary element method based near-field acoustic holography.

PubMed

Valdivia, Nicolas; Williams, Earl G

2005-02-01

The reconstruction of the acoustic field for general surfaces is obtained from the solution of a matrix system that results from a boundary integral equation discretized using boundary element methods. The solution to the resultant matrix system is obtained using iterative regularization methods that counteract the effect of noise on the measurements. These methods will not require the calculation of the singular value decomposition, which can be expensive when the matrix system is considerably large. Krylov subspace methods are iterative methods that have the phenomena known as "semi-convergence," i.e., the optimal regularization solution is obtained after a few iterations. If the iteration is not stopped, the method converges to a solution that generally is totally corrupted by errors on the measurements. For these methods the number of iterations play the role of the regularization parameter. We will focus our attention to the study of the regularizing properties from the Krylov subspace methods like conjugate gradients, least squares QR and the recently proposed Hybrid method. A discussion and comparison of the available stopping rules will be included. A vibrating plate is considered as an example to validate our results.

High resolution through-the-wall radar image based on beamspace eigenstructure subspace methods

NASA Astrophysics Data System (ADS)

Yoon, Yeo-Sun; Amin, Moeness G.

2008-04-01

Through-the-wall imaging (TWI) is a challenging problem, even if the wall parameters and characteristics are known to the system operator. Proper target classification and correct imaging interpretation require the application of high resolution techniques using limited array size. In inverse synthetic aperture radar (ISAR), signal subspace methods such as Multiple Signal Classification (MUSIC) are used to obtain high resolution imaging. In this paper, we adopt signal subspace methods and apply them to the 2-D spectrum obtained from the delay-andsum beamforming image. This is in contrast to ISAR, where raw data, in frequency and angle, is directly used to form the estimate of the covariance matrix and array response vector. Using beams rather than raw data has two main advantages, namely, it improves the signal-to-noise ratio (SNR) and can correctly image typical indoor extended targets, such as tables and cabinets, as well as point targets. The paper presents both simulated and experimental results using synthesized and real data. It compares the performance of beam-space MUSIC and Capon beamformer. The experimental data is collected at the test facility in the Radar Imaging Laboratory, Villanova University.

Deep Long-period Seismicity Beneath the Executive Committee Range, Marie Byrd Land, Antarctica, Studied Using Subspace Detection

NASA Astrophysics Data System (ADS)

Aster, R. C.; McMahon, N. D.; Myers, E. K.; Lough, A. C.

2015-12-01

Lough et al. (2014) first detected deep sub-icecap magmatic events beneath the Executive Committee Range volcanoes of Marie Byrd Land. Here, we extend the identification and analysis of these events in space and time utilizing subspace detection. Subspace detectors provide a highly effective methodology for studying events within seismic swarms that have similar moment tensor and Green's function characteristics and are particularly effective for identifying low signal-to-noise events. Marie Byrd Land (MBL) is an extremely remote continental region that is nearly completely covered by the West Antarctic Ice Sheet (WAIS). The southern extent of Marie Byrd Land lies within the West Antarctic Rift System (WARS), which includes the volcanic Executive Committee Range (ECR). The ECR shows north-to-south progression of volcanism across the WARS during the Holocene. In 2013, the POLENET/ANET seismic data identified two swarms of seismic activity in 2010 and 2011. These events have been interpreted as deep, long-period (DLP) earthquakes based on depth (25-40 km) and low frequency content. The DLP events in MBL lie beneath an inferred sub-WAIS volcanic edifice imaged with ice penetrating radar and have been interpreted as a present location of magmatic intrusion. The magmatic swarm activity in MBL provides a promising target for advanced subspace detection and temporal, spatial, and event size analysis of an extensive deep long period earthquake swarm using a remote seismographic network. We utilized a catalog of 1,370 traditionally identified DLP events to construct subspace detectors for the six nearest stations and analyzed two years of data spanning 2010-2011. Association of these detections into events resulted in an approximate ten-fold increase in number of locatable earthquakes. In addition to the two previously identified swarms during early 2010 and early 2011, we find sustained activity throughout the two years of study that includes several previously

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification.

PubMed

Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan

2018-02-01

In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.

Subspace techniques to remove artifacts from EEG: a quantitative analysis.

PubMed

Teixeira, A R; Tome, A M; Lang, E W; Martins da Silva, A

2008-01-01

In this work we discuss and apply projective subspace techniques to both multichannel as well as single channel recordings. The single-channel approach is based on singular spectrum analysis(SSA) and the multichannel approach uses the extended infomax algorithm which is implemented in the opensource toolbox EEGLAB. Both approaches will be evaluated using artificial mixtures of a set of selected EEG signals. The latter were selected visually to contain as the dominant activity one of the characteristic bands of an electroencephalogram (EEG). The evaluation is performed both in the time and frequency domain by using correlation coefficients and coherence function, respectively.

Advanced basal cell carcinoma, the hedgehog pathway, and treatment options – role of smoothened inhibitors

PubMed Central

Fecher, Leslie A; Sharfman, William H

2015-01-01

Cutaneous basal cell carcinoma (BCC) is the most common human cancer and its incidence is rising worldwide. Ultraviolet radiation exposure, including tanning bed use, as well as host factors play a role in its development. The majority of cases are treated and cured with local therapies including surgery. Yet, the health care costs of diagnosis and treatment of BCCs in the US is substantial. In the United States, the cost of nonmelanoma skin cancer care in the Medicare population is estimated to be US$426 million per year. While rare, locally advanced BCCs that can no longer be controlled with surgery and/or radiation, and metastatic BCCs do occur and can be associated with significant morbidity and mortality. Vismodegib (GDC-0449), a smoothened inhibitor targeted at the hedgehog pathway, is the first US Food and Drug Association (FDA)-approved agent in the treatment of locally advanced, unresectable, and metastatic BCCs. This class of agents appears to be changing the survival rates in advanced BCC patients, but appropriate patient selection and monitoring are important. Multidisciplinary assessments are essential for the optimal care and management of these patients. For some patients with locally advanced BCC, treatment with a hedgehog inhibitor may eliminate the need for an excessively disfiguring or morbid surgery. PMID:26604681

Single continuous lumen formation in the zebrafish gut is mediated by smoothened-dependent tissue remodeling

PubMed Central

Alvers, Ashley L.; Ryan, Sean; Scherz, Paul J.; Huisken, Jan; Bagnat, Michel

2014-01-01

The formation of a single lumen during tubulogenesis is crucial for the development and function of many organs. Although 3D cell culture models have identified molecular mechanisms controlling lumen formation in vitro, their function during vertebrate organogenesis is poorly understood. Using light sheet microscopy and genetic approaches we have investigated single lumen formation in the zebrafish gut. Here we show that during gut development multiple lumens open and enlarge to generate a distinct intermediate, which consists of two adjacent unfused lumens separated by basolateral contacts. We observed that these lumens arise independently from each other along the length of the gut and do not share a continuous apical surface. Resolution of this intermediate into a single, continuous lumen requires the remodeling of contacts between adjacent lumens and subsequent lumen fusion. We show that lumen resolution, but not lumen opening, is impaired in smoothened (smo) mutants, indicating that fluid-driven lumen enlargement and resolution are two distinct processes. Furthermore, we show that smo mutants exhibit perturbations in the Rab11 trafficking pathway and demonstrate that Rab11-mediated trafficking is necessary for single lumen formation. Thus, lumen resolution is a distinct genetically controlled process crucial for single, continuous lumen formation in the zebrafish gut. PMID:24504339

Targeting superficial or nodular Basal cell carcinoma with topically formulated small molecule inhibitor of smoothened.

PubMed

Tang, Tracy; Tang, Jean Y; Li, Dongwei; Reich, Mike; Callahan, Christopher A; Fu, Ling; Yauch, Robert L; Wang, Frank; Kotkow, Karen; Chang, Kris S; Shpall, Elana; Wu, Angela; Rubin, Lee L; Marsters, James C; Epstein, Ervin H; Caro, Ivor; de Sauvage, Frederic J

2011-05-15

Inappropriate activation of the Hedgehog (Hh) signaling pathway in skin is critical for the development of basal cell carcinomas (BCC). We have investigated the anti-BCC efficacy of topically-applied CUR61414, an inhibitor of the Hh signal transduction molecule Smoothened. In preclinical studies, we used a depilatory model to evaluate the ability of topical formulations of CUR61414 to repress Hh responsive cells found at the base of hair follicles in normal skin. We also tested the in vivo effects of topical CUR61414 on murine BCCs developed in Ptch1 (+/-) K14-CreER2 p53 fl/fl mice. In a phase I clinical study, we evaluated the safety, tolerability, and efficacy of a multidose regimen of CUR61414 (0.09%, 0.35%, 1.1%, and 3.1%) applied topically to human superficial or nodular BCCs for up to 28 days. In mice, topical CUR61414 significantly inhibited skin Hh signaling, blocked the induction of hair follicle anagen, and shrank existing BCCs. However, we observed no clinical activity of this formulation in human superficial or nodular BCCs in a phase I clinical study. Our data highlight some of the challenges of translating preclinical experience into successful human results for a topical anticancer agent. ©2011 AACR.

Separation of the low-frequency atmospheric variability into non-Gaussian multidimensional sources by Independent Subspace Analysis

NASA Astrophysics Data System (ADS)

Pires, Carlos; Ribeiro, Andreia

2016-04-01

An efficient nonlinear method of statistical source separation of space-distributed non-Gaussian distributed data is proposed. The method relies in the so called Independent Subspace Analysis (ISA), being tested on a long time-series of the stream-function field of an atmospheric quasi-geostrophic 3-level model (QG3) simulating the winter's monthly variability of the Northern Hemisphere. ISA generalizes the Independent Component Analysis (ICA) by looking for multidimensional and minimally dependent, uncorrelated and non-Gaussian distributed statistical sources among the rotated projections or subspaces of the multivariate probability distribution of the leading principal components of the working field whereas ICA restrict to scalar sources. The rationale of that technique relies upon the projection pursuit technique, looking for data projections of enhanced interest. In order to accomplish the decomposition, we maximize measures of the sources' non-Gaussianity by contrast functions which are given by squares of nonlinear, cross-cumulant-based correlations involving the variables spanning the sources. Therefore sources are sought matching certain nonlinear data structures. The maximized contrast function is built in such a way that it provides the minimization of the mean square of the residuals of certain nonlinear regressions. The issuing residuals, followed by spherization, provide a new set of nonlinear variable changes that are at once uncorrelated, quasi-independent and quasi-Gaussian, representing an advantage with respect to the Independent Components (scalar sources) obtained by ICA where the non-Gaussianity is concentrated into the non-Gaussian scalar sources. The new scalar sources obtained by the above process encompass the attractor's curvature thus providing improved nonlinear model indices of the low-frequency atmospheric variability which is useful since large circulation indices are nonlinearly correlated. The non-Gaussian tested sources (dyads and

Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations

DOE PAGES

Banerjee, Amartya S.; Lin, Lin; Hu, Wei; ...

2016-10-21

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) canmore » be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALB functions requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale twodimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. In conclusion, employing 55 296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8586 atoms is 90 s, and the time for a graphene sheet containing 11 520 atoms is 75 s.« less

A Framework for a Supervisory Expert System for Robotic Manipulators with Joint-Position Limits and Joint-Rate Limits

NASA Technical Reports Server (NTRS)

Mutambara, Arthur G. O.; Litt, Jonathan

1998-01-01

This report addresses the problem of path planning and control of robotic manipulators which have joint-position limits and joint-rate limits. The manipulators move autonomously and carry out variable tasks in a dynamic, unstructured and cluttered environment. The issue considered is whether the robotic manipulator can achieve all its tasks, and if it cannot, the objective is to identify the closest achievable goal. This problem is formalized and systematically solved for generic manipulators by using inverse kinematics and forward kinematics. Inverse kinematics are employed to define the subspace, workspace and constrained workspace, which are then used to identify when a task is not achievable. The closest achievable goal is obtained by determining weights for an optimal control redistribution scheme. These weights are quantified by using forward kinematics. Conditions leading to joint rate limits are identified, in particular it is established that all generic manipulators have singularities at the boundary of their workspace, while some have loci of singularities inside their workspace. Once the manipulator singularity is identified the command redistribution scheme is used to compute the closest achievable Cartesian velocities. Two examples are used to illustrate the use of the algorithm: A three link planar manipulator and the Unimation Puma 560. Implementation of the derived algorithm is effected by using a supervisory expert system to check whether the desired goal lies in the constrained workspace and if not, to evoke the redistribution scheme which determines the constraint relaxation between end effector position and orientation, and then computes optimal gains.

ERP denoising in multichannel EEG data using contrasts between signal and noise subspaces.

PubMed

Ivannikov, Andriy; Kalyakin, Igor; Hämäläinen, Jarmo; Leppänen, Paavo H T; Ristaniemi, Tapani; Lyytinen, Heikki; Kärkkäinen, Tommi

2009-06-15

In this paper, a new method intended for ERP denoising in multichannel EEG data is discussed. The denoising is done by separating ERP/noise subspaces in multidimensional EEG data by a linear transformation and the following dimension reduction by ignoring noise components during inverse transformation. The separation matrix is found based on the assumption that ERP sources are deterministic for all repetitions of the same type of stimulus within the experiment, while the other noise sources do not obey the determinancy property. A detailed derivation of the technique is given together with the analysis of the results of its application to a real high-density EEG data set. The interpretation of the results and the performance of the proposed method under conditions, when the basic assumptions are violated - e.g. the problem is underdetermined - are also discussed. Moreover, we study how the factors of the number of channels and trials used by the method influence the effectiveness of ERP/noise subspaces separation. In addition, we explore also the impact of different data resampling strategies on the performance of the considered algorithm. The results can help in determining the optimal parameters of the equipment/methods used to elicit and reliably estimate ERPs.

Static analysis of large-scale multibody system using joint coordinates and spatial algebra operator.

PubMed

Omar, Mohamed A

2014-01-01

Initial transient oscillations inhibited in the dynamic simulations responses of multibody systems can lead to inaccurate results, unrealistic load prediction, or simulation failure. These transients could result from incompatible initial conditions, initial constraints violation, and inadequate kinematic assembly. Performing static equilibrium analysis before the dynamic simulation can eliminate these transients and lead to stable simulation. Most exiting multibody formulations determine the static equilibrium position by minimizing the system potential energy. This paper presents a new general purpose approach for solving the static equilibrium in large-scale articulated multibody. The proposed approach introduces an energy drainage mechanism based on Baumgarte constraint stabilization approach to determine the static equilibrium position. The spatial algebra operator is used to express the kinematic and dynamic equations of the closed-loop multibody system. The proposed multibody system formulation utilizes the joint coordinates and modal elastic coordinates as the system generalized coordinates. The recursive nonlinear equations of motion are formulated using the Cartesian coordinates and the joint coordinates to form an augmented set of differential algebraic equations. Then system connectivity matrix is derived from the system topological relations and used to project the Cartesian quantities into the joint subspace leading to minimum set of differential equations.

Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method.

PubMed

Ye, Jinzuo; Chi, Chongwei; Xue, Zhenwen; Wu, Ping; An, Yu; Xu, Han; Zhang, Shuang; Tian, Jie

2014-02-01

Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.

Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

PubMed

Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

2012-12-01

Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

Uncontrolled Manifold Reference Feedback Control of Multi-Joint Robot Arms

PubMed Central

Togo, Shunta; Kagawa, Takahiro; Uno, Yoji

2016-01-01

The brain must coordinate with redundant bodies to perform motion tasks. The aim of the present study is to propose a novel control model that predicts the characteristics of human joint coordination at a behavioral level. To evaluate the joint coordination, an uncontrolled manifold (UCM) analysis that focuses on the trial-to-trial variance of joints has been proposed. The UCM is a nonlinear manifold associated with redundant kinematics. In this study, we directly applied the notion of the UCM to our proposed control model called the “UCM reference feedback control.” To simplify the problem, the present study considered how the redundant joints were controlled to regulate a given target hand position. We considered a conventional method that pre-determined a unique target joint trajectory by inverse kinematics or any other optimization method. In contrast, our proposed control method generates a UCM as a control target at each time step. The target UCM is a subspace of joint angles whose variability does not affect the hand position. The joint combination in the target UCM is then selected so as to minimize the cost function, which consisted of the joint torque and torque change. To examine whether the proposed method could reproduce human-like joint coordination, we conducted simulation and measurement experiments. In the simulation experiments, a three-link arm with a shoulder, elbow, and wrist regulates a one-dimensional target of a hand through proposed method. In the measurement experiments, subjects performed a one-dimensional target-tracking task. The kinematics, dynamics, and joint coordination were quantitatively compared with the simulation data of the proposed method. As a result, the UCM reference feedback control could quantitatively reproduce the difference of the mean value for the end hand position between the initial postures, the peaks of the bell-shape tangential hand velocity, the sum of the squared torque, the mean value for the torque

PI(4)P Promotes Phosphorylation and Conformational Change of Smoothened through Interaction with Its C-terminal Tail

PubMed Central

Zhang, Jie; Li, Xiang-An; Evers, B. Mark; Zhu, Haining; Jia, Jianhang

2016-01-01

In Hedgehog (Hh) signaling, binding of Hh to the Patched-Interference Hh (Ptc-Ihog) receptor complex relieves Ptc inhibition on Smoothened (Smo). A longstanding question is how Ptc inhibits Smo and how such inhibition is relieved by Hh stimulation. In this study, we found that Hh elevates production of phosphatidylinositol 4-phosphate (PI(4)P). Increased levels of PI(4)P promote, whereas decreased levels of PI(4)P inhibit, Hh signaling activity. We further found that PI(4)P directly binds Smo through an arginine motif, which then triggers Smo phosphorylation and activation. Moreover, we identified the pleckstrin homology (PH) domain of G protein-coupled receptor kinase 2 (Gprk2) as an essential component for enriching PI(4)P and facilitating Smo activation. PI(4)P also binds mouse Smo (mSmo) and promotes its phosphorylation and ciliary accumulation. Finally, Hh treatment increases the interaction between Smo and PI(4)P but decreases the interaction between Ptc and PI(4)P, indicating that, in addition to promoting PI(4)P production, Hh regulates the pool of PI(4)P associated with Ptc and Smo. PMID:26863604

Margin-Wide Earthquake Subspace Scanning Along the Cascadia Subduction Zone Using the Cascadia Initiative Amphibious Dataset

NASA Astrophysics Data System (ADS)

Morton, E.; Bilek, S. L.; Rowe, C. A.

2017-12-01

Understanding the spatial extent and behavior of the interplate contact in the Cascadia Subduction Zone (CSZ) may prove pivotal to preparation for future great earthquakes, such as the M9 event of 1700. Current and historic seismic catalogs are limited in their integrity by their short duration, given the recurrence rate of great earthquakes, and by their rather high magnitude of completeness for the interplate seismic zone, due to its offshore distance from these land-based networks. This issue is addressed via the 2011-2015 Cascadia Initiative (CI) amphibious seismic array deployment, which combined coastal land seismometers with more than 60 ocean-bottom seismometers (OBS) situated directly above the presumed plate interface. We search the CI dataset for small, previously undetected interplate earthquakes to identify seismic patches on the megathrust. Using the automated subspace detection method, we search for previously undetected events. Our subspace comprises eigenvectors derived from CI OBS and on-land waveforms extracted for existing catalog events that appear to have occurred on the plate interface. Previous work focused on analysis of two repeating event clusters off the coast of Oregon spanning all 4 years of deployment. Here we expand earlier results to include detection and location analysis to the entire CSZ margin during the first year of CI deployment, with more than 200 new events detected for the central portion of the margin. Template events used for subspace scanning primarily occurred beneath the land surface along the coast, at the downdip edge of modeled high slip patches for the 1700 event, with most concentrated at the northwestern edge of the Olympic Peninsula.

A Role for Smoothened during Murine Lens and Cornea Development

PubMed Central

Trogrlic, Lidia; Milevski, Stefan V.; Familari, Mary; Martinez, Gemma; de Iongh, Robb U

2014-01-01

Various studies suggest that Hedgehog (Hh) signalling plays roles in human and zebrafish ocular development. Recent studies (Kerr et al., Invest Ophthalmol Vis Sci. 2012; 53, 3316–30) showed that conditionally activating Hh signals promotes murine lens epithelial cell proliferation and disrupts fibre differentiation. In this study we examined the expression of the Hh pathway and the requirement for the Smoothened gene in murine lens development. Expression of Hh pathway components in developing lens was examined by RT-PCR, immunofluorescence and in situ hybridisation. The requirement of Smo in lens development was determined by conditional loss-of-function mutations, using LeCre and MLR10 Cre transgenic mice. The phenotype of mutant mice was examined by immunofluorescence for various markers of cell cycle, lens and cornea differentiation. Hh pathway components (Ptch1, Smo, Gli2, Gli3) were detected in lens epithelium from E12.5. Gli2 was particularly localised to mitotic nuclei and, at E13.5, Gli3 exhibited a shift from cytosol to nucleus, suggesting distinct roles for these transcription factors. Conditional deletion of Smo, from ∼E12.5 (MLR10 Cre) did not affect ocular development, whereas deletion from ∼E9.5 (LeCre) resulted in lens and corneal defects from E14.5. Mutant lenses were smaller and showed normal expression of p57Kip2, c-Maf, E-cadherin and Pax6, reduced expression of FoxE3 and Ptch1 and decreased nuclear Hes1. There was normal G1-S phase but decreased G2-M phase transition at E16.5 and epithelial cell death from E14.5-E16.5. Mutant corneas were thicker due to aberrant migration of Nrp2+ cells from the extraocular mesenchyme, resulting in delayed corneal endothelial but normal epithelial differentiation. These results indicate the Hh pathway is required during a discrete period (E9.5–E12.5) in lens development to regulate lens epithelial cell proliferation, survival and FoxE3 expression. Defective corneal development occurs secondary to

DYRK1B as therapeutic target in Hedgehog/GLI-dependent cancer cells with Smoothened inhibitor resistance

PubMed Central

Gruber, Wolfgang; Hutzinger, Martin; Elmer, Dominik Patrick; Parigger, Thomas; Sternberg, Christina; Cegielkowski, Lukasz; Zaja, Mirko; Leban, Johann; Michel, Susanne; Hamm, Svetlana; Vitt, Daniel; Aberger, Fritz

2016-01-01

A wide range of human malignancies displays aberrant activation of Hedgehog (HH)/GLI signaling, including cancers of the skin, brain, gastrointestinal tract and hematopoietic system. Targeting oncogenic HH/GLI signaling with small molecule inhibitors of the essential pathway effector Smoothened (SMO) has shown remarkable therapeutic effects in patients with advanced and metastatic basal cell carcinoma. However, acquired and de novo resistance to SMO inhibitors poses severe limitations to the use of SMO antagonists and urgently calls for the identification of novel targets and compounds. Here we report on the identification of the Dual-Specificity-Tyrosine-Phosphorylation-Regulated Kinase 1B (DYRK1B) as critical positive regulator of HH/GLI signaling downstream of SMO. Genetic and chemical inhibition of DYRK1B in human and mouse cancer cells resulted in marked repression of HH signaling and GLI1 expression, respectively. Importantly, DYRK1B inhibition profoundly impaired GLI1 expression in both SMO-inhibitor sensitive and resistant settings. We further introduce a novel small molecule DYRK1B inhibitor, DYRKi, with suitable pharmacologic properties to impair SMO-dependent and SMO-independent oncogenic GLI activity. The results support the use of DYRK1B antagonists for the treatment of HH/GLI-associated cancers where SMO inhibitors fail to demonstrate therapeutic efficacy. PMID:26784250

EEG Subspace Analysis and Classification Using Principal Angles for Brain-Computer Interfaces

NASA Astrophysics Data System (ADS)

Ashari, Rehab Bahaaddin

Brain-Computer Interfaces (BCIs) help paralyzed people who have lost some or all of their ability to communicate and control the outside environment from loss of voluntary muscle control. Most BCIs are based on the classification of multichannel electroencephalography (EEG) signals recorded from users as they respond to external stimuli or perform various mental activities. The classification process is fraught with difficulties caused by electrical noise, signal artifacts, and nonstationarity. One approach to reducing the effects of similar difficulties in other domains is the use of principal angles between subspaces, which has been applied mostly to video sequences. This dissertation studies and examines different ideas using principal angles and subspaces concepts. It introduces a novel mathematical approach for comparing sets of EEG signals for use in new BCI technology. The success of the presented results show that principal angles are also a useful approach to the classification of EEG signals that are recorded during a BCI typing application. In this application, the appearance of a subject's desired letter is detected by identifying a P300-wave within a one-second window of EEG following the flash of a letter. Smoothing the signals before using them is the only preprocessing step that was implemented in this study. The smoothing process based on minimizing the second derivative in time is implemented to increase the classification accuracy instead of using the bandpass filter that relies on assumptions on the frequency content of EEG. This study examines four different ways of removing outliers that are based on the principal angles and shows that the outlier removal methods did not help in the presented situations. One of the concepts that this dissertation focused on is the effect of the number of trials on the classification accuracies. The achievement of the good classification results by using a small number of trials starting from two trials only

Pigments identification of paintings using subspace distance unmixing algorithm

NASA Astrophysics Data System (ADS)

Li, Bin; Lyu, Shuqiang; Zhang, Dafeng; Dong, Qinghao

2018-04-01

In the digital protection of the cultural relics, the identification of the pigment mixtures on the surface of the painting has been the research spot for many years. In this paper, as a hyperspectral unmixing algorithm, sub-space distance unmixing is introduced to solve the problem of recognition of pigments mixture in paintings. Firstly, some mixtures of different pigments are designed to measure their reflectance spectra using spectrometer. Moreover, the factors affecting the unmixing accuracy of pigments' mixtures are discussed. The unmixing results of two cases with and without rice paper and its underlay as endmembers are compared. The experiment results show that the algorithm is able to unmixing the pigments effectively and the unmixing accuracy can be improved after considering the influence of spectra of the rich paper and the underlaying material.

Exploiting active subspaces to quantify uncertainty in the numerical simulation of the HyShot II scramjet

NASA Astrophysics Data System (ADS)

Constantine, P. G.; Emory, M.; Larsson, J.; Iaccarino, G.

2015-12-01

We present a computational analysis of the reactive flow in a hypersonic scramjet engine with focus on effects of uncertainties in the operating conditions. We employ a novel methodology based on active subspaces to characterize the effects of the input uncertainty on the scramjet performance. The active subspace identifies one-dimensional structure in the map from simulation inputs to quantity of interest that allows us to reparameterize the operating conditions; instead of seven physical parameters, we can use a single derived active variable. This dimension reduction enables otherwise infeasible uncertainty quantification, considering the simulation cost of roughly 9500 CPU-hours per run. For two values of the fuel injection rate, we use a total of 68 simulations to (i) identify the parameters that contribute the most to the variation in the output quantity of interest, (ii) estimate upper and lower bounds on the quantity of interest, (iii) classify sets of operating conditions as safe or unsafe corresponding to a threshold on the output quantity of interest, and (iv) estimate a cumulative distribution function for the quantity of interest.

Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction.

PubMed

Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang

2018-05-08

When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

A Least-Squares Commutator in the Iterative Subspace Method for Accelerating Self-Consistent Field Convergence.

PubMed

Li, Haichen; Yaron, David J

2016-11-08

A least-squares commutator in the iterative subspace (LCIIS) approach is explored for accelerating self-consistent field (SCF) calculations. LCIIS is similar to direct inversion of the iterative subspace (DIIS) methods in that the next iterate of the density matrix is obtained as a linear combination of past iterates. However, whereas DIIS methods find the linear combination by minimizing a sum of error vectors, LCIIS minimizes the Frobenius norm of the commutator between the density matrix and the Fock matrix. This minimization leads to a quartic problem that can be solved iteratively through a constrained Newton's method. The relationship between LCIIS and DIIS is discussed. Numerical experiments suggest that LCIIS leads to faster convergence than other SCF convergence accelerating methods in a statistically significant sense, and in a number of cases LCIIS leads to stable SCF solutions that are not found by other methods. The computational cost involved in solving the quartic minimization problem is small compared to the typical cost of SCF iterations and the approach is easily integrated into existing codes. LCIIS can therefore serve as a powerful addition to SCF convergence accelerating methods in computational quantum chemistry packages.

A Gaussian-based rank approximation for subspace clustering

NASA Astrophysics Data System (ADS)

Xu, Fei; Peng, Chong; Hu, Yunhong; He, Guoping

2018-04-01

Low-rank representation (LRR) has been shown successful in seeking low-rank structures of data relationships in a union of subspaces. Generally, LRR and LRR-based variants need to solve the nuclear norm-based minimization problems. Beyond the success of such methods, it has been widely noted that the nuclear norm may not be a good rank approximation because it simply adds all singular values of a matrix together and thus large singular values may dominant the weight. This results in far from satisfactory rank approximation and may degrade the performance of lowrank models based on the nuclear norm. In this paper, we propose a novel nonconvex rank approximation based on the Gaussian distribution function, which has demanding properties to be a better rank approximation than the nuclear norm. Then a low-rank model is proposed based on the new rank approximation with application to motion segmentation. Experimental results have shown significant improvements and verified the effectiveness of our method.

Towards automatic music transcription: note extraction based on independent subspace analysis

NASA Astrophysics Data System (ADS)

Wellhausen, Jens; Hoynck, Michael

2005-01-01

Due to the increasing amount of music available electronically the need of automatic search, retrieval and classification systems for music becomes more and more important. In this paper an algorithm for automatic transcription of polyphonic piano music into MIDI data is presented, which is a very interesting basis for database applications, music analysis and music classification. The first part of the algorithm performs a note accurate temporal audio segmentation. In the second part, the resulting segments are examined using Independent Subspace Analysis to extract sounding notes. Finally, the results are used to build a MIDI file as a new representation of the piece of music which is examined.

Towards automatic music transcription: note extraction based on independent subspace analysis

NASA Astrophysics Data System (ADS)

Wellhausen, Jens; Höynck, Michael

2004-12-01

Due to the increasing amount of music available electronically the need of automatic search, retrieval and classification systems for music becomes more and more important. In this paper an algorithm for automatic transcription of polyphonic piano music into MIDI data is presented, which is a very interesting basis for database applications, music analysis and music classification. The first part of the algorithm performs a note accurate temporal audio segmentation. In the second part, the resulting segments are examined using Independent Subspace Analysis to extract sounding notes. Finally, the results are used to build a MIDI file as a new representation of the piece of music which is examined.

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chowdhary, Kenny; Najm, Habib N.

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

DOE PAGES

Chowdhary, Kenny; Najm, Habib N.

2016-04-13

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Static Analysis of Large-Scale Multibody System Using Joint Coordinates and Spatial Algebra Operator

PubMed Central

Omar, Mohamed A.

2014-01-01

Initial transient oscillations inhibited in the dynamic simulations responses of multibody systems can lead to inaccurate results, unrealistic load prediction, or simulation failure. These transients could result from incompatible initial conditions, initial constraints violation, and inadequate kinematic assembly. Performing static equilibrium analysis before the dynamic simulation can eliminate these transients and lead to stable simulation. Most exiting multibody formulations determine the static equilibrium position by minimizing the system potential energy. This paper presents a new general purpose approach for solving the static equilibrium in large-scale articulated multibody. The proposed approach introduces an energy drainage mechanism based on Baumgarte constraint stabilization approach to determine the static equilibrium position. The spatial algebra operator is used to express the kinematic and dynamic equations of the closed-loop multibody system. The proposed multibody system formulation utilizes the joint coordinates and modal elastic coordinates as the system generalized coordinates. The recursive nonlinear equations of motion are formulated using the Cartesian coordinates and the joint coordinates to form an augmented set of differential algebraic equations. Then system connectivity matrix is derived from the system topological relations and used to project the Cartesian quantities into the joint subspace leading to minimum set of differential equations. PMID:25045732

A General Algorithm for Reusing Krylov Subspace Information. I. Unsteady Navier-Stokes

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Vuik, C.; Lucas, Peter; vanGijzen, Martin; Bijl, Hester

2010-01-01

A general algorithm is developed that reuses available information to accelerate the iterative convergence of linear systems with multiple right-hand sides A x = b (sup i), which are commonly encountered in steady or unsteady simulations of nonlinear equations. The algorithm is based on the classical GMRES algorithm with eigenvector enrichment but also includes a Galerkin projection preprocessing step and several novel Krylov subspace reuse strategies. The new approach is applied to a set of test problems, including an unsteady turbulent airfoil, and is shown in some cases to provide significant improvement in computational efficiency relative to baseline approaches.

On the selection of user-defined parameters in data-driven stochastic subspace identification

NASA Astrophysics Data System (ADS)

Priori, C.; De Angelis, M.; Betti, R.

2018-02-01

The paper focuses on the time domain output-only technique called Data-Driven Stochastic Subspace Identification (DD-SSI); in order to identify modal models (frequencies, damping ratios and mode shapes), the role of its user-defined parameters is studied, and rules to determine their minimum values are proposed. Such investigation is carried out using, first, the time histories of structural responses to stationary excitations, with a large number of samples, satisfying the hypothesis on the input imposed by DD-SSI. Then, the case of non-stationary seismic excitations with a reduced number of samples is considered. In this paper, partitions of the data matrix different from the one proposed in the SSI literature are investigated, together with the influence of different choices of the weighting matrices. The study is carried out considering two different applications: (1) data obtained from vibration tests on a scaled structure and (2) in-situ tests on a reinforced concrete building. Referring to the former, the identification of a steel frame structure tested on a shaking table is performed using its responses in terms of absolute accelerations to a stationary (white noise) base excitation and to non-stationary seismic excitations of low intensity. Black-box and modal models are identified in both cases and the results are compared with those from an input-output subspace technique. With regards to the latter, the identification of a complex hospital building is conducted using data obtained from ambient vibration tests.

Exact solution of mean-field plus an extended T = 1 nuclear pairing Hamiltonian in the seniority-zero symmetric subspace

NASA Astrophysics Data System (ADS)

Pan, Feng; Ding, Xiaoxue; Launey, Kristina D.; Dai, Lianrong; Draayer, Jerry P.

2018-05-01

An extended pairing Hamiltonian that describes multi-pair interactions among isospin T = 1 and angular momentum J = 0 neutron-neutron, proton-proton, and neutron-proton pairs in a spherical mean field, such as the spherical shell model, is proposed based on the standard T = 1 pairing formalism. The advantage of the model lies in the fact that numerical solutions within the seniority-zero symmetric subspace can be obtained more easily and with less computational time than those calculated from the mean-field plus standard T = 1 pairing model. Thus, large-scale calculations within the seniority-zero symmetric subspace of the model is feasible. As an example of the application, the average neutron-proton interaction in even-even N ∼ Z nuclei that can be suitably described in the f5 pg9 shell is estimated in the present model, with a focus on the role of np-pairing correlations.

Component-based subspace linear discriminant analysis method for face recognition with one training sample

NASA Astrophysics Data System (ADS)

Huang, Jian; Yuen, Pong C.; Chen, Wen-Sheng; Lai, J. H.

2005-05-01

Many face recognition algorithms/systems have been developed in the last decade and excellent performances have also been reported when there is a sufficient number of representative training samples. In many real-life applications such as passport identification, only one well-controlled frontal sample image is available for training. Under this situation, the performance of existing algorithms will degrade dramatically or may not even be implemented. We propose a component-based linear discriminant analysis (LDA) method to solve the one training sample problem. The basic idea of the proposed method is to construct local facial feature component bunches by moving each local feature region in four directions. In this way, we not only generate more samples with lower dimension than the original image, but also consider the face detection localization error while training. After that, we propose a subspace LDA method, which is tailor-made for a small number of training samples, for the local feature projection to maximize the discrimination power. Theoretical analysis and experiment results show that our proposed subspace LDA is efficient and overcomes the limitations in existing LDA methods. Finally, we combine the contributions of each local component bunch with a weighted combination scheme to draw the recognition decision. A FERET database is used for evaluating the proposed method and results are encouraging.

Investigation of Volcanic Seismo-Acoustic Signals: Applying Subspace Detection to Lava Fountain Activity at Etna Volcano

NASA Astrophysics Data System (ADS)

Sciotto, M.; Rowe, C. A.; Cannata, A.; Arrowsmith, S.; Privitera, E.; Gresta, S.

2011-12-01

The current eruption of Mount Etna, which began in January, 2011, has produced numerous energetic episodes of lava fountaining, which have bee recorded by the INGV seismic and acoustic sensors located on and around the volcano. The source of these events was the pit crater on the east flank of the Southeast crater of Etna. Simultaneously, small levels of activity were noted in the Bocca Nuova as well, prior to its lava fountaining activity. We will present an analysis of seismic and acoustic signals related to the 2011 activity wherein we apply the method of subspace detection to determine whether the source exhibits a temporal evolution within or between fountaining events, or otherwise produces repeating, classifiable events occurring through the continuous explosive degassing. We will examine not only the raw waveforms, but also spectral variations in time as well as time-varying statistical functions such as signal skewness and kurtosis. These results will be compared to straightforward cross-correlation analysis. In addition to classification performance, the subspace method has promise to outperform standard STA/LTA methods for real-time event detection in cases where similar events can be expected.

Skin subspace color modeling for daytime and nighttime group activity recognition in confined operational spaces

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Poshtyar, Azin; Chan, Alex; Hu, Shuowen

2016-05-01

In many military and homeland security persistent surveillance applications, accurate detection of different skin colors in varying observability and illumination conditions is a valuable capability for video analytics. One of those applications is In-Vehicle Group Activity (IVGA) recognition, in which significant changes in observability and illumination may occur during the course of a specific human group activity of interest. Most of the existing skin color detection algorithms, however, are unable to perform satisfactorily in confined operational spaces with partial observability and occultation, as well as under diverse and changing levels of illumination intensity, reflection, and diffraction. In this paper, we investigate the salient features of ten popular color spaces for skin subspace color modeling. More specifically, we examine the advantages and disadvantages of each of these color spaces, as well as the stability and suitability of their features in differentiating skin colors under various illumination conditions. The salient features of different color subspaces are methodically discussed and graphically presented. Furthermore, we present robust and adaptive algorithms for skin color detection based on this analysis. Through examples, we demonstrate the efficiency and effectiveness of these new color skin detection algorithms and discuss their applicability for skin detection in IVGA recognition applications.

LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction

PubMed Central

Huang, Li

2017-01-01

Predicting novel microRNA (miRNA)-disease associations is clinically significant due to miRNAs’ potential roles of diagnostic biomarkers and therapeutic targets for various human diseases. Previous studies have demonstrated the viability of utilizing different types of biological data to computationally infer new disease-related miRNAs. Yet researchers face the challenge of how to effectively integrate diverse datasets and make reliable predictions. In this study, we presented a computational model named Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction (LRSSLMDA), which projected miRNAs/diseases’ statistical feature profile and graph theoretical feature profile to a common subspace. It used Laplacian regularization to preserve the local structures of the training data and a L1-norm constraint to select important miRNA/disease features for prediction. The strength of dimensionality reduction enabled the model to be easily extended to much higher dimensional datasets than those exploited in this study. Experimental results showed that LRSSLMDA outperformed ten previous models: the AUC of 0.9178 in global leave-one-out cross validation (LOOCV) and the AUC of 0.8418 in local LOOCV indicated the model’s superior prediction accuracy; and the average AUC of 0.9181+/-0.0004 in 5-fold cross validation justified its accuracy and stability. In addition, three types of case studies further demonstrated its predictive power. Potential miRNAs related to Colon Neoplasms, Lymphoma, Kidney Neoplasms, Esophageal Neoplasms and Breast Neoplasms were predicted by LRSSLMDA. Respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predictions were validated by experimental evidences. Therefore, we conclude that LRSSLMDA would be a valuable computational tool for miRNA-disease association prediction. PMID:29253885

Constitutive Activation of Smoothened in the Renal Collecting Ducts Leads to Renal Hypoplasia, Hydronephrosis, and Hydroureter.

PubMed

Gupta, Deepak Prasad; Hwang, Jae-Won; Cho, Eui-Sic; Kim, Won; Song, Chang Ho; Chai, Ok Hee

2017-01-01

Sonic Hedgehog (Shh) signaling plays a major role in and is essential for regulation, patterning, and proliferation during renal development. Smoothened (Smo) plays a pivot role in transducing the Shh-glioma-associated oncogene Kruppel family member. However, the cellular and molecular mechanism underlying the role of sustained Smo activation in postnatal kidney development is still not clearly understood. Using a conditional knockin mouse model that expresses a constitutively activated form of Smo (SmoM2) upon Homeobox-B7-mediated recombination (Hoxb7-Cre), the effects of Shh signaling were determined in postnatal kidney development. SmoM2;Hoxb7-Cre mutant mice showed growth retardation with a reduction of body weight. Constitutive activation of Smo in the renal collecting ducts caused renal hypoplasia, hydronephrosis, and hydroureter. The parenchymal area and glomerular numbers were reduced, but the glomerular density was increased in SmoM2;Hoxb7-Cre mutant mice. The expression of Patched 1, the receptor of Shh and a downstream target gene of the Shh signaling pathway, was highly restricted and it was upregulated in the inner medullary collecting ducts of the kidney. The proliferative cells in the mesenchyme and collecting ducts were decreased in SmoM2;Hoxb7-Cre mutant mice. This study showed for the first time that sustained Smo inhibits postnatal kidney development by suppressing the proliferation of the mesenchyme and medullary collecting ducts in mice. © 2017 S. Karger AG, Basel.

Reduced Smoothened level rescues Aβ-induced memory deficits and neuronal inflammation in animal models of Alzheimer's disease.

PubMed

Ma, Weiwei; Wu, Mengnan; Zhou, Siyan; Tao, Ye; Xie, Zuolei; Zhong, Yi

2018-05-20

Emerging evidence suggests that neuro-inflammation begins early and drives the pathogenesis of Alzheimer's disease (AD), and anti-inflammatory therapies are under clinical development. However, several anti-inflammatory compounds failed to improve memory in clinical trials, indicating that reducing inflammation alone might not be enough. On the other hand, neuro-inflammation is implicated in a number of mental disorders which share the same therapeutic targets. Based on these observations, we screened a batch of genes related with mental disorder and neuro-inflammation in a classical olfactory conditioning in an amyloid beta (Aβ) overexpression fly model. A Smoothened (SMO) mutant was identified as a genetic modifier of Aβ toxicity in 3-min memory and downregulation of SMO rescued Aβ-induced 3-min and 1-h memory deficiency. Also, Aβ activated innate inflammatory response in fly by increasing the expression of antimicrobial peptides, which were alleviated by downregulating SMO. Furthermore, pharmaceutical administration of a SMO antagonist LDE rescued Aβ-induced upregulation of SMO in astrocytes of mouse hippocampus, improved memory in Morris water maze (MWM), and reduced expression of astrocyte secreting pro-inflammatory factors IL-1β, TNFα and the microglia marker IBA-1 in an APP/PS1 transgenic mouse model. Our study suggests that SMO is an important conserved modulator of Aβ toxicity in both fly and mouse models of AD. Copyright © 2018. Published by Elsevier Ltd.

Decomposition of Near-Infrared Spectroscopy Signals Using Oblique Subspace Projections: Applications in Brain Hemodynamic Monitoring.

PubMed

Caicedo, Alexander; Varon, Carolina; Hunyadi, Borbala; Papademetriou, Maria; Tachtsidis, Ilias; Van Huffel, Sabine

2016-01-01

Clinical data is comprised by a large number of synchronously collected biomedical signals that are measured at different locations. Deciphering the interrelationships of these signals can yield important information about their dependence providing some useful clinical diagnostic data. For instance, by computing the coupling between Near-Infrared Spectroscopy signals (NIRS) and systemic variables the status of the hemodynamic regulation mechanisms can be assessed. In this paper we introduce an algorithm for the decomposition of NIRS signals into additive components. The algorithm, SIgnal DEcomposition base on Obliques Subspace Projections (SIDE-ObSP), assumes that the measured NIRS signal is a linear combination of the systemic measurements, following the linear regression model y = Ax + ϵ . SIDE-ObSP decomposes the output such that, each component in the decomposition represents the sole linear influence of one corresponding regressor variable. This decomposition scheme aims at providing a better understanding of the relation between NIRS and systemic variables, and to provide a framework for the clinical interpretation of regression algorithms, thereby, facilitating their introduction into clinical practice. SIDE-ObSP combines oblique subspace projections (ObSP) with the structure of a mean average system in order to define adequate signal subspaces. To guarantee smoothness in the estimated regression parameters, as observed in normal physiological processes, we impose a Tikhonov regularization using a matrix differential operator. We evaluate the performance of SIDE-ObSP by using a synthetic dataset, and present two case studies in the field of cerebral hemodynamics monitoring using NIRS. In addition, we compare the performance of this method with other system identification techniques. In the first case study data from 20 neonates during the first 3 days of life was used, here SIDE-ObSP decoupled the influence of changes in arterial oxygen saturation from the

Spatially Correlated Sparse MIMO Channel Path Delay Estimation in Scattering Environments Based on Signal Subspace Tracking

PubMed Central

Chargé, Pascal; Bazzi, Oussama; Ding, Yuehua

2018-01-01

A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit–receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit–receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit–receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods. PMID:29734797

Spatially Correlated Sparse MIMO Channel Path Delay Estimation in Scattering Environments Based on Signal Subspace Tracking.

PubMed

Mohydeen, Ali; Chargé, Pascal; Wang, Yide; Bazzi, Oussama; Ding, Yuehua

2018-05-06

A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit⁻receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit⁻receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit⁻receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods.

Inverse transport calculations in optical imaging with subspace optimization algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Tian, E-mail: tding@math.utexas.edu; Ren, Kui, E-mail: ren@math.utexas.edu

2014-09-15

Inverse boundary value problems for the radiative transport equation play an important role in optics-based medical imaging techniques such as diffuse optical tomography (DOT) and fluorescence optical tomography (FOT). Despite the rapid progress in the mathematical theory and numerical computation of these inverse problems in recent years, developing robust and efficient reconstruction algorithms remains a challenging task and an active research topic. We propose here a robust reconstruction method that is based on subspace minimization techniques. The method splits the unknown transport solution (or a functional of it) into low-frequency and high-frequency components, and uses singular value decomposition to analyticallymore » recover part of low-frequency information. Minimization is then applied to recover part of the high-frequency components of the unknowns. We present some numerical simulations with synthetic data to demonstrate the performance of the proposed algorithm.« less

MicroRNA-1271 inhibits proliferation and promotes apoptosis of multiple myeloma cells through inhibiting smoothened-mediated Hedgehog signaling pathway.

PubMed

Xu, Zhengwei; Huang, Chen; Hao, Dingjun

2017-02-01

MicroRNAs (miRNAs) have emerged as important regulators in multiple myeloma (MM). miR-1271 is a tumor suppressor in many cancer types. However, the biological role of miR-1271 in MM remains unclear. In the present study, we elucidated the biological role of miR-1271 in MM. Results showed that miR-1271 was significantly decreased in primary MM cells from MM patients and MM cell lines. Overexpression of miR-1271 inhibited proliferation and promoted apoptosis of MM cells. Conversely, suppression of miR-1271 showed the opposite effect. Bioinformatics algorithm analysis predicted that smoothened (SMO), the activator of Hedgehog (HH) signaling pathway, was a direct target of miR-1271 that was experimentally verified by a dual-luciferase reporter assay. Furthermore, overexpression of miR-1271 inhibited SMO expression and HH signaling pathway. Conversely, the restoration of SMO expression markedly abolished the effect of miR-1271 overexpression on cell proliferation, apoptosis and HH signaling pathway in MM cells. Taken together, the present study suggests that miR-1271 functions as a tumor suppressor that inhibits proliferation and promotes apoptosis of MM cells through inhibiting SMO-mediated HH signaling pathway. This finding implies that miR-1271 is a potential therapeutic target for the treatment of MM.

Otic ablation of smoothened reveals direct and indirect requirements for Hedgehog signaling in inner ear development

PubMed Central

Brown, Alexander S.; Epstein, Douglas J.

2011-01-01

In mouse embryos lacking sonic hedgehog (Shh), dorsoventral polarity within the otic vesicle is disrupted. Consequently, ventral otic derivatives, including the cochlear duct and saccule, fail to form, and dorsal otic derivatives, including the semicircular canals, endolymphatic duct and utricle, are malformed or absent. Since inner ear patterning and morphogenesis are heavily dependent on extracellular signals derived from tissues that are also compromised by the loss of Shh, the extent to which Shh signaling acts directly on the inner ear for its development is unclear. To address this question, we generated embryos in which smoothened (Smo), an essential transducer of Hedgehog (Hh) signaling, was conditionally inactivated in the otic epithelium (Smoecko). Ventral otic derivatives failed to form in Smoecko embryos, whereas vestibular structures developed properly. Consistent with these findings, we demonstrate that ventral, but not dorsal, otic identity is directly dependent on Hh. The role of Hh in cochlear-vestibular ganglion (cvg) formation is more complex, as both direct and indirect signaling mechanisms are implicated. Our data suggest that the loss of cvg neurons in Shh–/– animals is due, in part, to an increase in Wnt responsiveness in the otic vesicle, resulting in the ectopic expression of Tbx1 in the neurogenic domain and subsequent repression of Ngn1 transcription. A mitogenic role for Shh in cvg progenitor proliferation was also revealed in our analysis of Smoecko embryos. Taken together, these data contribute to a better understanding of the intrinsic and extrinsic signaling properties of Shh during inner ear development. PMID:21831920

An adaptive optimal control for smart structures based on the subspace tracking identification technique

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele

2014-04-01

A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.

Reverse time migration by Krylov subspace reduced order modeling

NASA Astrophysics Data System (ADS)

Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali

2018-04-01

Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.

Estimation of hysteretic damping of structures by stochastic subspace identification

NASA Astrophysics Data System (ADS)

Bajrić, Anela; Høgsberg, Jan

2018-05-01

Output-only system identification techniques can estimate modal parameters of structures represented by linear time-invariant systems. However, the extension of the techniques to structures exhibiting non-linear behavior has not received much attention. This paper presents an output-only system identification method suitable for random response of dynamic systems with hysteretic damping. The method applies the concept of Stochastic Subspace Identification (SSI) to estimate the model parameters of a dynamic system with hysteretic damping. The restoring force is represented by the Bouc-Wen model, for which an equivalent linear relaxation model is derived. Hysteretic properties can be encountered in engineering structures exposed to severe cyclic environmental loads, as well as in vibration mitigation devices, such as Magneto-Rheological (MR) dampers. The identification technique incorporates the equivalent linear damper model in the estimation procedure. Synthetic data, representing the random vibrations of systems with hysteresis, validate the estimated system parameters by the presented identification method at low and high-levels of excitation amplitudes.

Extraction of process zones and low-dimensional attractive subspaces in stochastic fracture mechanics

PubMed Central

Kerfriden, P.; Schmidt, K.M.; Rabczuk, T.; Bordas, S.P.A.

2013-01-01

We propose to identify process zones in heterogeneous materials by tailored statistical tools. The process zone is redefined as the part of the structure where the random process cannot be correctly approximated in a low-dimensional deterministic space. Such a low-dimensional space is obtained by a spectral analysis performed on pre-computed solution samples. A greedy algorithm is proposed to identify both process zone and low-dimensional representative subspace for the solution in the complementary region. In addition to the novelty of the tools proposed in this paper for the analysis of localised phenomena, we show that the reduced space generated by the method is a valid basis for the construction of a reduced order model. PMID:27069423

Room-temperature storage of quantum entanglement using decoherence-free subspace in a solid-state spin system

NASA Astrophysics Data System (ADS)

Wang, F.; Huang, Y.-Y.; Zhang, Z.-Y.; Zu, C.; Hou, P.-Y.; Yuan, X.-X.; Wang, W.-B.; Zhang, W.-G.; He, L.; Chang, X.-Y.; Duan, L.-M.

2017-10-01

We experimentally demonstrate room-temperature storage of quantum entanglement using two nuclear spins weakly coupled to the electronic spin carried by a single nitrogen-vacancy center in diamond. We realize universal quantum gate control over the three-qubit spin system and produce entangled states in the decoherence-free subspace of the two nuclear spins. By injecting arbitrary collective noise, we demonstrate that the decoherence-free entangled state has coherence time longer than that of other entangled states by an order of magnitude in our experiment.

Deregulated hedgehog pathway signaling is inhibited by the smoothened antagonist LDE225 (Sonidegib) in chronic phase chronic myeloid leukaemia

PubMed Central

Irvine, David A.; Zhang, Bin; Kinstrie, Ross; Tarafdar, Anuradha; Morrison, Heather; Campbell, Victoria L.; Moka, Hothri A.; Ho, Yinwei; Nixon, Colin; Manley, Paul W.; Wheadon, Helen; Goodlad, John R.; Holyoake, Tessa L.; Bhatia, Ravi; Copland, Mhairi

2016-01-01

Targeting the Hedgehog (Hh) pathway represents a potential leukaemia stem cell (LSC)-directed therapy which may compliment tyrosine kinase inhibitors (TKIs) to eradicate LSC in chronic phase (CP) chronic myeloid leukaemia (CML). We set out to elucidate the role of Hh signaling in CP-CML and determine if inhibition of Hh signaling, through inhibition of smoothened (SMO), was an effective strategy to target CP-CML LSC. Assessment of Hh pathway gene and protein expression demonstrated that the Hh pathway is activated in CD34+ CP-CML stem/progenitor cells. LDE225 (Sonidegib), a small molecule, clinically investigated SMO inhibitor, used alone and in combination with nilotinib, inhibited the Hh pathway in CD34+ CP-CML cells, reducing the number and self-renewal capacity of CML LSC in vitro. The combination had no effect on normal haemopoietic stem cells. When combined, LDE225 + nilotinib reduced CD34+ CP-CML cell engraftment in NSG mice and, upon administration to EGFP+ /SCLtTA/TRE-BCR-ABL mice, the combination enhanced survival with reduced leukaemia development in secondary transplant recipients. In conclusion, the Hh pathway is deregulated in CML stem and progenitor cells. We identify Hh pathway inhibition, in combination with nilotinib, as a potentially effective therapeutic strategy to improve responses in CP-CML by targeting both stem and progenitor cells. PMID:27157927

Features in chemical kinetics. III. Attracting subspaces in a hyper-spherical representation of the reactive system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ceccato, Alessandro; Frezzato, Diego, E-mail: diego.frezzato@unipd.it; Nicolini, Paolo

In this work, we deal with general reactive systems involving N species and M elementary reactions under applicability of the mass-action law. Starting from the dynamic variables introduced in two previous works [P. Nicolini and D. Frezzato, J. Chem. Phys. 138(23), 234101 (2013); 138(23), 234102 (2013)], we turn to a new representation in which the system state is specified in a (N × M){sup 2}-dimensional space by a point whose coordinates have physical dimension of inverse-of-time. By adopting hyper-spherical coordinates (a set of dimensionless “angular” variables and a single “radial” one with physical dimension of inverse-of-time) and by examining themore » properties of their evolution law both formally and numerically on model kinetic schemes, we show that the system evolves towards the equilibrium as being attracted by a sequence of fixed subspaces (one at a time) each associated with a compact domain of the concentration space. Thus, we point out that also for general non-linear kinetics there exist fixed “objects” on the global scale, although they are conceived in such an abstract and extended space. Moreover, we propose a link between the persistence of the belonging of a trajectory to such subspaces and the closeness to the slow manifold which would be perceived by looking at the bundling of the trajectories in the concentration space.« less

Perturbed invariant subspaces and approximate generalized functional variable separation solution for nonlinear diffusion-convection equations with weak source

NASA Astrophysics Data System (ADS)

Xia, Ya-Rong; Zhang, Shun-Li; Xin, Xiang-Peng

2018-03-01

In this paper, we propose the concept of the perturbed invariant subspaces (PISs), and study the approximate generalized functional variable separation solution for the nonlinear diffusion-convection equation with weak source by the approximate generalized conditional symmetries (AGCSs) related to the PISs. Complete classification of the perturbed equations which admit the approximate generalized functional separable solutions (AGFSSs) is obtained. As a consequence, some AGFSSs to the resulting equations are explicitly constructed by way of examples.

Universal non-adiabatic holonomic quantum computation in decoherence-free subspaces with quantum dots inside a cavity

NASA Astrophysics Data System (ADS)

Liu, Jun; Dong, Ping; Zhou, Jian; Cao, Zhuo-Liang

2017-05-01

A scheme for implementing the non-adiabatic holonomic quantum computation in decoherence-free subspaces is proposed with the interactions between a microcavity and quantum dots. A universal set of quantum gates can be constructed on the encoded logical qubits with high fidelities. The current scheme can suppress both local and collective noises, which is very important for achieving universal quantum computation. Discussions about the gate fidelities with the experimental parameters show that our schemes can be implemented in current experimental technology. Therefore, our scenario offers a method for universal and robust solid-state quantum computation.

Application of a Subspace-Based Fault Detection Method to Industrial Structures

NASA Astrophysics Data System (ADS)

Mevel, L.; Hermans, L.; van der Auweraer, H.

1999-11-01

Early detection and localization of damage allow increased expectations of reliability, safety and reduction of the maintenance cost. This paper deals with the industrial validation of a technique to monitor the health of a structure in operating conditions (e.g. rotating machinery, civil constructions subject to ambient excitations, etc.) and to detect slight deviations in a modal model derived from in-operation measured data. In this paper, a statistical local approach based on covariance-driven stochastic subspace identification is proposed. The capabilities and limitations of the method with respect to health monitoring and damage detection are discussed and it is explained how the method can be practically used in industrial environments. After the successful validation of the proposed method on a few laboratory structures, its application to a sports car is discussed. The example illustrates that the method allows the early detection of a vibration-induced fatigue problem of a sports car.

Decentralized System Identification Using Stochastic Subspace Identification for Wireless Sensor Networks

PubMed Central

Cho, Soojin; Park, Jong-Woong; Sim, Sung-Han

2015-01-01

Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model. PMID:25856325

Cyclo-stationary linear parameter time-varying subspace realization method applied for identification of horizontal-axis wind turbines

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2013-04-01

Wind energy is becoming increasingly important worldwide as an alternative renewable energy source. Economical, maintenance and operation are critical issues for large slender dynamic structures, especially for remote offshore wind farms. Health monitoring systems are very promising instruments to assure reliability and good performance of the structure. These sensing and control technologies are typically informed by models based on mechanics or data-driven identification techniques in the time and/or frequency domain. Frequency response functions are popular but are difficult to realize autonomously for structures of higher order and having overlapping frequency content. Instead, time-domain techniques have shown powerful advantages from a practical point of view (e.g. embedded algorithms in wireless-sensor networks), being more suitable to differentiate closely-related modes. Customarily, time-varying effects are often neglected or dismissed to simplify the analysis, but such is not the case for wind loaded structures with spinning multibodies. A more complex scenario is constituted when dealing with both periodic mechanisms responsible for the vibration shaft of the rotor-blade system, and the wind tower substructure interaction. Transformations of the cyclic effects on the vibration data can be applied to isolate inertia quantities different from rotating-generated forces that are typically non-stationary in nature. After applying these transformations, structural identification can be carried out by stationary techniques via data-correlated Eigensystem realizations. In this paper an exploration of a periodic stationary or cyclo-stationary subspace identification technique is presented here by means of a modified Eigensystem Realization Algorithm (ERA) via Stochastic Subspace Identification (SSI) and Linear Parameter Time-Varying (LPTV) techniques. Structural response is assumed under stationary ambient excitation produced by a Gaussian (white) noise assembled

Removal of nuisance signals from limited and sparse 1H MRSI data using a union-of-subspaces model.

PubMed

Ma, Chao; Lam, Fan; Johnson, Curtis L; Liang, Zhi-Pei

2016-02-01

To remove nuisance signals (e.g., water and lipid signals) for (1) H MRSI data collected from the brain with limited and/or sparse (k, t)-space coverage. A union-of-subspace model is proposed for removing nuisance signals. The model exploits the partial separability of both the nuisance signals and the metabolite signal, and decomposes an MRSI dataset into several sets of generalized voxels that share the same spectral distributions. This model enables the estimation of the nuisance signals from an MRSI dataset that has limited and/or sparse (k, t)-space coverage. The proposed method has been evaluated using in vivo MRSI data. For conventional chemical shift imaging data with limited k-space coverage, the proposed method produced "lipid-free" spectra without lipid suppression during data acquisition at 130 ms echo time. For sparse (k, t)-space data acquired with conventional pulses for water and lipid suppression, the proposed method was also able to remove the remaining water and lipid signals with negligible residuals. Nuisance signals in (1) H MRSI data reside in low-dimensional subspaces. This property can be utilized for estimation and removal of nuisance signals from (1) H MRSI data even when they have limited and/or sparse coverage of (k, t)-space. The proposed method should prove useful especially for accelerated high-resolution (1) H MRSI of the brain. © 2015 Wiley Periodicals, Inc.

Biomedical image classification based on a cascade of an SVM with a reject option and subspace analysis.

PubMed

Lin, Dongyun; Sun, Lei; Toh, Kar-Ann; Zhang, Jing Bo; Lin, Zhiping

2018-05-01

Automated biomedical image classification could confront the challenges of high level noise, image blur, illumination variation and complicated geometric correspondence among various categorical biomedical patterns in practice. To handle these challenges, we propose a cascade method consisting of two stages for biomedical image classification. At stage 1, we propose a confidence score based classification rule with a reject option for a preliminary decision using the support vector machine (SVM). The testing images going through stage 1 are separated into two groups based on their confidence scores. Those testing images with sufficiently high confidence scores are classified at stage 1 while the others with low confidence scores are rejected and fed to stage 2. At stage 2, the rejected images from stage 1 are first processed by a subspace analysis technique called eigenfeature regularization and extraction (ERE), and then classified by another SVM trained in the transformed subspace learned by ERE. At both stages, images are represented based on two types of local features, i.e., SIFT and SURF, respectively. They are encoded using various bag-of-words (BoW) models to handle biomedical patterns with and without geometric correspondence, respectively. Extensive experiments are implemented to evaluate the proposed method on three benchmark real-world biomedical image datasets. The proposed method significantly outperforms several competing state-of-the-art methods in terms of classification accuracy. Copyright © 2018 Elsevier Ltd. All rights reserved.

Accelerating the weighted histogram analysis method by direct inversion in the iterative subspace.

PubMed

Zhang, Cheng; Lai, Chun-Liang; Pettitt, B Montgomery

The weighted histogram analysis method (WHAM) for free energy calculations is a valuable tool to produce free energy differences with the minimal errors. Given multiple simulations, WHAM obtains from the distribution overlaps the optimal statistical estimator of the density of states, from which the free energy differences can be computed. The WHAM equations are often solved by an iterative procedure. In this work, we use a well-known linear algebra algorithm which allows for more rapid convergence to the solution. We find that the computational complexity of the iterative solution to WHAM and the closely-related multiple Bennett acceptance ratio (MBAR) method can be improved by using the method of direct inversion in the iterative subspace. We give examples from a lattice model, a simple liquid and an aqueous protein solution.

Discovery of potent and novel smoothened antagonists via structure-based virtual screening and biological assays.

PubMed

Lu, Wenfeng; Zhang, Dihua; Ma, Haikuo; Tian, Sheng; Zheng, Jiyue; Wang, Qin; Luo, Lusong; Zhang, Xiaohu

2018-05-23

The Hedgehog (Hh) signaling pathway plays a critical role in controlling patterning, growth and cell migration during embryonic development. Aberrant activation of Hh signaling has been linked to tumorigenesis in various cancers, such as basal cell carcinoma (BCC) and medulloblastoma. As a key member of the Hh pathway, the Smoothened (Smo) receptor, a member of the G protein-coupled receptor (GPCR) family, has emerged as an attractive therapeutic target for the treatment and prevention of human cancers. The recent determination of several crystal structures of Smo in complex with different antagonists offers the possibility to perform structure-based virtual screening for discovering potent Smo antagonists with distinct chemical scaffolds. In this study, based on the two Smo crystal complexes with the best capacity to distinguish the known Smo antagonists from decoys, the molecular docking-based virtual screening was conducted to identify promising Smo antagonists from ChemDiv library. A total of 21 structurally novel and diverse compounds were selected for experimental testing, and six of them exhibited significant inhibitory activity against the Hh pathway activation (IC 50  < 10 μM) in a GRE (Gli-responsive element) reporter gene assay. Specifically, the most potent compound (compound 20: 47 nM) showed comparable Hh signaling inhibition to vismodegib (46 nM). Compound 20 was further confirmed to be a potent Smo antagonist in a fluorescence based competitive binding assay. Optimization using substructure searching method led to the discovery of 12 analogues of compound 20 with decent Hh pathway inhibition activity, including four compounds with IC 50 lower than 1 μM. The important residues uncovered by binding free energy calculation (MM/GBSA) and binding free energy decomposition were highlighted and discussed. These findings suggest that the novel scaffold afforded by compound 20 can be used as a good starting point for further modification

Randomized Subspace Learning for Proline Cis-Trans Isomerization Prediction.

PubMed

Al-Jarrah, Omar Y; Yoo, Paul D; Taha, Kamal; Muhaidat, Sami; Shami, Abdallah; Zaki, Nazar

2015-01-01

Proline residues are common source of kinetic complications during folding. The X-Pro peptide bond is the only peptide bond for which the stability of the cis and trans conformations is comparable. The cis-trans isomerization (CTI) of X-Pro peptide bonds is a widely recognized rate-limiting factor, which can not only induces additional slow phases in protein folding but also modifies the millisecond and sub-millisecond dynamics of the protein. An accurate computational prediction of proline CTI is of great importance for the understanding of protein folding, splicing, cell signaling, and transmembrane active transport in both the human body and animals. In our earlier work, we successfully developed a biophysically motivated proline CTI predictor utilizing a novel tree-based consensus model with a powerful metalearning technique and achieved 86.58 percent Q2 accuracy and 0.74 Mcc, which is a better result than the results (70-73 percent Q2 accuracies) reported in the literature on the well-referenced benchmark dataset. In this paper, we describe experiments with novel randomized subspace learning and bootstrap seeding techniques as an extension to our earlier work, the consensus models as well as entropy-based learning methods, to obtain better accuracy through a precise and robust learning scheme for proline CTI prediction.

Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions

PubMed Central

Golkar, Mahsa A.; Sobhani Tehrani, Ehsan; Kearney, Robert E.

2017-01-01

Dynamic joint stiffness is a dynamic, nonlinear relationship between the position of a joint and the torque acting about it, which can be used to describe the biomechanics of the joint and associated limb(s). This paper models and quantifies changes in ankle dynamic stiffness and its individual elements, intrinsic and reflex stiffness, in healthy human subjects during isometric, time-varying (TV) contractions of the ankle plantarflexor muscles. A subspace, linear parameter varying, parallel-cascade (LPV-PC) algorithm was used to identify the model from measured input position perturbations and output torque data using voluntary torque as the LPV scheduling variable (SV). Monte-Carlo simulations demonstrated that the algorithm is accurate, precise, and robust to colored measurement noise. The algorithm was then used to examine stiffness changes associated with TV isometric contractions. The SV was estimated from the Soleus EMG using a Hammerstein model of EMG-torque dynamics identified from unperturbed trials. The LPV-PC algorithm identified (i) a non-parametric LPV impulse response function (LPV IRF) for intrinsic stiffness and (ii) a LPV-Hammerstein model for reflex stiffness consisting of a LPV static nonlinearity followed by a time-invariant state-space model of reflex dynamics. The results demonstrated that: (a) intrinsic stiffness, in particular ankle elasticity, increased significantly and monotonically with activation level; (b) the gain of the reflex pathway increased from rest to around 10–20% of subject's MVC and then declined; and (c) the reflex dynamics were second order. These findings suggest that in healthy human ankle, reflex stiffness contributes most at low muscle contraction levels, whereas, intrinsic contributions monotonically increase with activation level. PMID:28579954

A multifaceted independent performance analysis of facial subspace recognition algorithms.

PubMed

Bajwa, Usama Ijaz; Taj, Imtiaz Ahmad; Anwar, Muhammad Waqas; Wang, Xuan

2013-01-01

Face recognition has emerged as the fastest growing biometric technology and has expanded a lot in the last few years. Many new algorithms and commercial systems have been proposed and developed. Most of them use Principal Component Analysis (PCA) as a base for their techniques. Different and even conflicting results have been reported by researchers comparing these algorithms. The purpose of this study is to have an independent comparative analysis considering both performance and computational complexity of six appearance based face recognition algorithms namely PCA, 2DPCA, A2DPCA, (2D)(2)PCA, LPP and 2DLPP under equal working conditions. This study was motivated due to the lack of unbiased comprehensive comparative analysis of some recent subspace methods with diverse distance metric combinations. For comparison with other studies, FERET, ORL and YALE databases have been used with evaluation criteria as of FERET evaluations which closely simulate real life scenarios. A comparison of results with previous studies is performed and anomalies are reported. An important contribution of this study is that it presents the suitable performance conditions for each of the algorithms under consideration.

Minimal subspace rotation on the Stiefel manifold for stabilization and enhancement of projection-based reduced order models for the compressible Navier–Stokes equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balajewicz, Maciej; Tezaur, Irina; Dowell, Earl

For a projection-based reduced order model (ROM) of a fluid flow to be stable and accurate, the dynamics of the truncated subspace must be taken into account. This paper proposes an approach for stabilizing and enhancing projection-based fluid ROMs in which truncated modes are accounted for a priori via a minimal rotation of the projection subspace. Attention is focused on the full non-linear compressible Navier–Stokes equations in specific volume form as a step toward a more general formulation for problems with generic non-linearities. Unlike traditional approaches, no empirical turbulence modeling terms are required, and consistency between the ROM and themore » Navier–Stokes equation from which the ROM is derived is maintained. Mathematically, the approach is formulated as a trace minimization problem on the Stiefel manifold. As a result, the reproductive as well as predictive capabilities of the method are evaluated on several compressible flow problems, including a problem involving laminar flow over an airfoil with a high angle of attack, and a channel-driven cavity flow problem.« less

Minimal subspace rotation on the Stiefel manifold for stabilization and enhancement of projection-based reduced order models for the compressible Navier–Stokes equations

DOE PAGES

Balajewicz, Maciej; Tezaur, Irina; Dowell, Earl

2016-05-25

For a projection-based reduced order model (ROM) of a fluid flow to be stable and accurate, the dynamics of the truncated subspace must be taken into account. This paper proposes an approach for stabilizing and enhancing projection-based fluid ROMs in which truncated modes are accounted for a priori via a minimal rotation of the projection subspace. Attention is focused on the full non-linear compressible Navier–Stokes equations in specific volume form as a step toward a more general formulation for problems with generic non-linearities. Unlike traditional approaches, no empirical turbulence modeling terms are required, and consistency between the ROM and themore » Navier–Stokes equation from which the ROM is derived is maintained. Mathematically, the approach is formulated as a trace minimization problem on the Stiefel manifold. As a result, the reproductive as well as predictive capabilities of the method are evaluated on several compressible flow problems, including a problem involving laminar flow over an airfoil with a high angle of attack, and a channel-driven cavity flow problem.« less

Quantum repeaters based on trapped ions with decoherence-free subspace encoding

NASA Astrophysics Data System (ADS)

Zwerger, M.; Lanyon, B. P.; Northup, T. E.; Muschik, C. A.; Dür, W.; Sangouard, N.

2017-12-01

Quantum repeaters provide an efficient solution to distribute Bell pairs over arbitrarily long distances. While scalable architectures are demanding regarding the number of qubits that need to be controlled, here we present a quantum repeater scheme aiming to extend the range of present day quantum communications that could be implemented in the near future with trapped ions in cavities. We focus on an architecture where ion-photon entangled states are created locally and subsequently processed with linear optics to create elementary links of ion-ion entangled states. These links are then used to distribute entangled pairs over long distances using successive entanglement swapping operations performed using deterministic ion-ion gates. We show how this architecture can be implemented while encoding the qubits in a decoherence-free subspace to protect them against collective dephasing. This results in a protocol that can be used to violate a Bell inequality over distances of about 800 km assuming state-of-the-art parameters. We discuss how this could be improved to several thousand kilometres in future setups.

Transferring multiqubit entanglement onto memory qubits in a decoherence-free subspace

NASA Astrophysics Data System (ADS)

He, Xiao-Ling; Yang, Chui-Ping

2017-03-01

Different from the previous works on generating entangled states, this work is focused on how to transfer the prepared entangled states onto memory qubits for protecting them against decoherence. We here consider a physical system consisting of n operation qubits and 2 n memory qubits placed in a cavity or coupled to a resonator. A method is presented for transferring n-qubit Greenberger-Horne-Zeilinger (GHZ) entangled states from the operation qubits (i.e., information processing cells) onto the memory qubits (i.e., information memory elements with long decoherence time). The transferred GHZ states are encoded in a decoherence-free subspace against collective dephasing and thus can be immune from decoherence induced by a dephasing environment. In addition, the state transfer procedure has nothing to do with the number of qubits, the operation time does not increase with the number of qubits, and no measurement is needed for the state transfer. This proposal can be applied to a wide range of hybrid qubits such as natural atoms and artificial atoms (e.g., various solid-state qubits).

Local sharpening and subspace wavefront correction with predictive dynamic digital holography

NASA Astrophysics Data System (ADS)

Sulaiman, Sennan; Gibson, Steve

2017-09-01

Digital holography holds several advantages over conventional imaging and wavefront sensing, chief among these being significantly fewer and simpler optical components and the retrieval of complex field. Consequently, many imaging and sensing applications including microscopy and optical tweezing have turned to using digital holography. A significant obstacle for digital holography in real-time applications, such as wavefront sensing for high energy laser systems and high speed imaging for target racking, is the fact that digital holography is computationally intensive; it requires iterative virtual wavefront propagation and hill-climbing to optimize some sharpness criteria. It has been shown recently that minimum-variance wavefront prediction can be integrated with digital holography and image sharpening to reduce significantly large number of costly sharpening iterations required to achieve near-optimal wavefront correction. This paper demonstrates further gains in computational efficiency with localized sharpening in conjunction with predictive dynamic digital holography for real-time applications. The method optimizes sharpness of local regions in a detector plane by parallel independent wavefront correction on reduced-dimension subspaces of the complex field in a spectral plane.

Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints.

PubMed

Chiew, Mark; Graedel, Nadine N; Miller, Karla L

2018-07-01

Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however, functional data recovery can be poor or incomplete. We introduce a method for improving reconstruction fidelity using external constraints, like an experimental design matrix, to partially orient the estimated fMRI temporal subspace. Combining these external constraints with low-rank constraints introduces a new image reconstruction model that is analogous to using a mixture of subspace-decomposition (PCA/ICA) and regression (GLM) models in fMRI analysis. We show that this approach improves fMRI reconstruction quality in simulations and experimental data, focusing on the model problem of detecting subtle 1-s latency shifts between brain regions in a block-design task-fMRI experiment. Successful latency discrimination is shown at acceleration factors up to R = 16 in a radial-Cartesian acquisition. We show that this approach works with approximate, or not perfectly informative constraints, where the derived benefit is commensurate with the information content contained in the constraints. The proposed method extends low-rank approximation methods for under-sampled fMRI data acquisition by leveraging knowledge of expected task-based variance in the data, enabling improvements in the speed and efficiency of fMRI data acquisition without the loss of subtle features. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Pengxiang; Nedelcu, Daniel; Watanabe, Miyako

In vertebrates, sterols are necessary for Hedgehog signaling, a pathway critical in embryogenesis and cancer. Sterols activate the membrane protein Smoothened by binding its extracellular, cysteine-rich domain (CRD). Major unanswered questions concern the nature of the endogenous, activating sterol and the mechanism by which it regulates Smoothened. We report crystal structures of CRD complexed with sterols and alone, revealing that sterols induce a dramatic conformational change of the binding site, which is sufficient for Smoothened activation and is unique among CRD-containing receptors. We demonstrate that Hedgehog signaling requires sterol binding to Smoothened and define key residues for sterol recognition andmore » activity. We also show that cholesterol itself binds and activates Smoothened. Furthermore, the effect of oxysterols is abolished in Smoothened mutants that retain activation by cholesterol and Hedgehog. We propose that the endogenous Smoothened activator is cholesterol, not oxysterols, and that vertebrate Hedgehog signaling controls Smoothened by regulating its access to cholesterol.« less

Neuromodulation and Synaptic Plasticity for the Control of Fast Periodic Movement: Energy Efficiency in Coupled Compliant Joints via PCA.

PubMed

Stratmann, Philipp; Lakatos, Dominic; Albu-Schäffer, Alin

2016-01-01

There are multiple indications that the nervous system of animals tunes muscle output to exploit natural dynamics of the elastic locomotor system and the environment. This is an advantageous strategy especially in fast periodic movements, since the elastic elements store energy and increase energy efficiency and movement speed. Experimental evidence suggests that coordination among joints involves proprioceptive input and neuromodulatory influence originating in the brain stem. However, the neural strategies underlying the coordination of fast periodic movements remain poorly understood. Based on robotics control theory, we suggest that the nervous system implements a mechanism to accomplish coordination between joints by a linear coordinate transformation from the multi-dimensional space representing proprioceptive input at the joint level into a one-dimensional controller space. In this one-dimensional subspace, the movements of a whole limb can be driven by a single oscillating unit as simple as a reflex interneuron. The output of the oscillating unit is transformed back to joint space via the same transformation. The transformation weights correspond to the dominant principal component of the movement. In this study, we propose a biologically plausible neural network to exemplify that the central nervous system (CNS) may encode our controller design. Using theoretical considerations and computer simulations, we demonstrate that spike-timing-dependent plasticity (STDP) for the input mapping and serotonergic neuromodulation for the output mapping can extract the dominant principal component of sensory signals. Our simulations show that our network can reliably control mechanical systems of different complexity and increase the energy efficiency of ongoing cyclic movements. The proposed network is simple and consistent with previous biologic experiments. Thus, our controller could serve as a candidate to describe the neural control of fast, energy

Neuromodulation and Synaptic Plasticity for the Control of Fast Periodic Movement: Energy Efficiency in Coupled Compliant Joints via PCA

PubMed Central

Stratmann, Philipp; Lakatos, Dominic; Albu-Schäffer, Alin

2016-01-01

There are multiple indications that the nervous system of animals tunes muscle output to exploit natural dynamics of the elastic locomotor system and the environment. This is an advantageous strategy especially in fast periodic movements, since the elastic elements store energy and increase energy efficiency and movement speed. Experimental evidence suggests that coordination among joints involves proprioceptive input and neuromodulatory influence originating in the brain stem. However, the neural strategies underlying the coordination of fast periodic movements remain poorly understood. Based on robotics control theory, we suggest that the nervous system implements a mechanism to accomplish coordination between joints by a linear coordinate transformation from the multi-dimensional space representing proprioceptive input at the joint level into a one-dimensional controller space. In this one-dimensional subspace, the movements of a whole limb can be driven by a single oscillating unit as simple as a reflex interneuron. The output of the oscillating unit is transformed back to joint space via the same transformation. The transformation weights correspond to the dominant principal component of the movement. In this study, we propose a biologically plausible neural network to exemplify that the central nervous system (CNS) may encode our controller design. Using theoretical considerations and computer simulations, we demonstrate that spike-timing-dependent plasticity (STDP) for the input mapping and serotonergic neuromodulation for the output mapping can extract the dominant principal component of sensory signals. Our simulations show that our network can reliably control mechanical systems of different complexity and increase the energy efficiency of ongoing cyclic movements. The proposed network is simple and consistent with previous biologic experiments. Thus, our controller could serve as a candidate to describe the neural control of fast, energy

SubspaceEM: A Fast Maximum-a-posteriori Algorithm for Cryo-EM Single Particle Reconstruction

PubMed Central

Dvornek, Nicha C.; Sigworth, Fred J.; Tagare, Hemant D.

2015-01-01

Single particle reconstruction methods based on the maximum-likelihood principle and the expectation-maximization (E–M) algorithm are popular because of their ability to produce high resolution structures. However, these algorithms are computationally very expensive, requiring a network of computational servers. To overcome this computational bottleneck, we propose a new mathematical framework for accelerating maximum-likelihood reconstructions. The speedup is by orders of magnitude and the proposed algorithm produces similar quality reconstructions compared to the standard maximum-likelihood formulation. Our approach uses subspace approximations of the cryo-electron microscopy (cryo-EM) data and projection images, greatly reducing the number of image transformations and comparisons that are computed. Experiments using simulated and actual cryo-EM data show that speedup in overall execution time compared to traditional maximum-likelihood reconstruction reaches factors of over 300. PMID:25839831

Supervised orthogonal discriminant subspace projects learning for face recognition.

PubMed

Chen, Yu; Xu, Xiao-Hong

2014-02-01

In this paper, a new linear dimension reduction method called supervised orthogonal discriminant subspace projection (SODSP) is proposed, which addresses high-dimensionality of data and the small sample size problem. More specifically, given a set of data points in the ambient space, a novel weight matrix that describes the relationship between the data points is first built. And in order to model the manifold structure, the class information is incorporated into the weight matrix. Based on the novel weight matrix, the local scatter matrix as well as non-local scatter matrix is defined such that the neighborhood structure can be preserved. In order to enhance the recognition ability, we impose an orthogonal constraint into a graph-based maximum margin analysis, seeking to find a projection that maximizes the difference, rather than the ratio between the non-local scatter and the local scatter. In this way, SODSP naturally avoids the singularity problem. Further, we develop an efficient and stable algorithm for implementing SODSP, especially, on high-dimensional data set. Moreover, the theoretical analysis shows that LPP is a special instance of SODSP by imposing some constraints. Experiments on the ORL, Yale, Extended Yale face database B and FERET face database are performed to test and evaluate the proposed algorithm. The results demonstrate the effectiveness of SODSP. Copyright © 2013 Elsevier Ltd. All rights reserved.

Quantum probabilities as Dempster-Shafer probabilities in the lattice of subspaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vourdas, A.

2014-08-15

The orthocomplemented modular lattice of subspaces L[H(d)], of a quantum system with d-dimensional Hilbert space H(d), is considered. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L[H(d)] (it is only valid within the Boolean subalgebras of L[H(d)]). This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. An operator D(H{sub 1},H{sub 2}), which quantifies deviations from Kolmogorov probability theory is introduced, and it is shown to be intimately related to the commutator of the projectors P(H{sub 1}),P(H{sub 2}), to the subspacesmore » H{sub 1}, H{sub 2}. As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities.« less

Novel Hyperspectral Anomaly Detection Methods Based on Unsupervised Nearest Regularized Subspace

NASA Astrophysics Data System (ADS)

Hou, Z.; Chen, Y.; Tan, K.; Du, P.

2018-04-01

Anomaly detection has been of great interest in hyperspectral imagery analysis. Most conventional anomaly detectors merely take advantage of spectral and spatial information within neighboring pixels. In this paper, two methods of Unsupervised Nearest Regularized Subspace-based with Outlier Removal Anomaly Detector (UNRSORAD) and Local Summation UNRSORAD (LSUNRSORAD) are proposed, which are based on the concept that each pixel in background can be approximately represented by its spatial neighborhoods, while anomalies cannot. Using a dual window, an approximation of each testing pixel is a representation of surrounding data via a linear combination. The existence of outliers in the dual window will affect detection accuracy. Proposed detectors remove outlier pixels that are significantly different from majority of pixels. In order to make full use of various local spatial distributions information with the neighboring pixels of the pixels under test, we take the local summation dual-window sliding strategy. The residual image is constituted by subtracting the predicted background from the original hyperspectral imagery, and anomalies can be detected in the residual image. Experimental results show that the proposed methods have greatly improved the detection accuracy compared with other traditional detection method.

Removal of EOG Artifacts from EEG Recordings Using Stationary Subspace Analysis

PubMed Central

Zeng, Hong; Song, Aiguo

2014-01-01

An effective approach is proposed in this paper to remove ocular artifacts from the raw EEG recording. The proposed approach first conducts the blind source separation on the raw EEG recording by the stationary subspace analysis (SSA) algorithm. Unlike the classic blind source separation algorithms, SSA is explicitly tailored to the understanding of distribution changes, where both the mean and the covariance matrix are taken into account. In addition, neither independency nor uncorrelation is required among the sources by SSA. Thereby, it can concentrate artifacts in fewer components than the representative blind source separation methods. Next, the components that are determined to be related to the ocular artifacts are projected back to be subtracted from EEG signals, producing the clean EEG data eventually. The experimental results on both the artificially contaminated EEG data and real EEG data have demonstrated the effectiveness of the proposed method, in particular for the cases where limited number of electrodes are used for the recording, as well as when the artifact contaminated signal is highly nonstationary and the underlying sources cannot be assumed to be independent or uncorrelated. PMID:24550696

Output-only cyclo-stationary linear-parameter time-varying stochastic subspace identification method for rotating machinery and spinning structures

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2015-02-01

Economical maintenance and operation are critical issues for rotating machinery and spinning structures containing blade elements, especially large slender dynamic beams (e.g., wind turbines). Structural health monitoring systems represent promising instruments to assure reliability and good performance from the dynamics of the mechanical systems. However, such devices have not been completely perfected for spinning structures. These sensing technologies are typically informed by both mechanistic models coupled with data-driven identification techniques in the time and/or frequency domain. Frequency response functions are popular but are difficult to realize autonomously for structures of higher order, especially when overlapping frequency content is present. Instead, time-domain techniques have shown to possess powerful advantages from a practical point of view (i.e. low-order computational effort suitable for real-time or embedded algorithms) and also are more suitable to differentiate closely-related modes. Customarily, time-varying effects are often neglected or dismissed to simplify this analysis, but such cannot be the case for sinusoidally loaded structures containing spinning multi-bodies. A more complex scenario is constituted when dealing with both periodic mechanisms responsible for the vibration shaft of the rotor-blade system and the interaction of the supporting substructure. Transformations of the cyclic effects on the vibrational data can be applied to isolate inertial quantities that are different from rotation-generated forces that are typically non-stationary in nature. After applying these transformations, structural identification can be carried out by stationary techniques via data-correlated eigensystem realizations. In this paper, an exploration of a periodic stationary or cyclo-stationary subspace identification technique is presented here for spinning multi-blade systems by means of a modified Eigensystem Realization Algorithm (ERA) via

Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining.

PubMed

Cheng, Wenlong; Zhao, Mingbo; Xiong, Naixue; Chui, Kwok Tai

2017-07-15

Parsimony, including sparsity and low-rank, has shown great importance for data mining in social networks, particularly in tasks such as segmentation and recognition. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with convex l ₁-norm or nuclear norm constraints. However, the obtained results by convex optimization are usually suboptimal to solutions of original sparse or low-rank problems. In this paper, a novel robust subspace segmentation algorithm has been proposed by integrating l p -norm and Schatten p -norm constraints. Our so-obtained affinity graph can better capture local geometrical structure and the global information of the data. As a consequence, our algorithm is more generative, discriminative and robust. An efficient linearized alternating direction method is derived to realize our model. Extensive segmentation experiments are conducted on public datasets. The proposed algorithm is revealed to be more effective and robust compared to five existing algorithms.

Maximum likelihood orientation estimation of 1-D patterns in Laguerre-Gauss subspaces.

PubMed

Di Claudio, Elio D; Jacovitti, Giovanni; Laurenti, Alberto

2010-05-01

A method for measuring the orientation of linear (1-D) patterns, based on a local expansion with Laguerre-Gauss circular harmonic (LG-CH) functions, is presented. It lies on the property that the polar separable LG-CH functions span the same space as the 2-D Cartesian separable Hermite-Gauss (2-D HG) functions. Exploiting the simple steerability of the LG-CH functions and the peculiar block-linear relationship among the two expansion coefficients sets, maximum likelihood (ML) estimates of orientation and cross section parameters of 1-D patterns are obtained projecting them in a proper subspace of the 2-D HG family. It is shown in this paper that the conditional ML solution, derived by elimination of the cross section parameters, surprisingly yields the same asymptotic accuracy as the ML solution for known cross section parameters. The accuracy of the conditional ML estimator is compared to the one of state of art solutions on a theoretical basis and via simulation trials. A thorough proof of the key relationship between the LG-CH and the 2-D HG expansions is also provided.

A Variational Approach to Video Registration with Subspace Constraints.

PubMed

Garg, Ravi; Roussos, Anastasios; Agapito, Lourdes

2013-01-01

This paper addresses the problem of non-rigid video registration, or the computation of optical flow from a reference frame to each of the subsequent images in a sequence, when the camera views deformable objects. We exploit the high correlation between 2D trajectories of different points on the same non-rigid surface by assuming that the displacement of any point throughout the sequence can be expressed in a compact way as a linear combination of a low-rank motion basis. This subspace constraint effectively acts as a trajectory regularization term leading to temporally consistent optical flow. We formulate it as a robust soft constraint within a variational framework by penalizing flow fields that lie outside the low-rank manifold. The resulting energy functional can be decoupled into the optimization of the brightness constancy and spatial regularization terms, leading to an efficient optimization scheme. Additionally, we propose a novel optimization scheme for the case of vector valued images, based on the dualization of the data term. This allows us to extend our approach to deal with colour images which results in significant improvements on the registration results. Finally, we provide a new benchmark dataset, based on motion capture data of a flag waving in the wind, with dense ground truth optical flow for evaluation of multi-frame optical flow algorithms for non-rigid surfaces. Our experiments show that our proposed approach outperforms state of the art optical flow and dense non-rigid registration algorithms.

A description of the location and structure of the essential spectrum of a model operator in a subspace of a Fock space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yodgorov, G R; Ismail, F; Muminov, Z I

2014-12-31

We consider a certain model operator acting in a subspace of a fermionic Fock space. We obtain an analogue of Faddeev's equation. We describe the location of the essential spectrum of the operator under consideration and show that the essential spectrum consists of the union of at most four segments. Bibliography: 19 titles.

Subspace Iteration Method for Complex Eigenvalue Problems with Nonsymmetric Matrices in Aeroelastic System

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Lung, Shun-fat

2009-01-01

Modern airplane design is a multidisciplinary task which combines several disciplines such as structures, aerodynamics, flight controls, and sometimes heat transfer. Historically, analytical and experimental investigations concerning the interaction of the elastic airframe with aerodynamic and in retia loads have been conducted during the design phase to determine the existence of aeroelastic instabilities, so called flutter .With the advent and increased usage of flight control systems, there is also a likelihood of instabilities caused by the interaction of the flight control system and the aeroelastic response of the airplane, known as aeroservoelastic instabilities. An in -house code MPASES (Ref. 1), modified from PASES (Ref. 2), is a general purpose digital computer program for the analysis of the closed-loop stability problem. This program used subroutines given in the International Mathematical and Statistical Library (IMSL) (Ref. 3) to compute all of the real and/or complex conjugate pairs of eigenvalues of the Hessenberg matrix. For high fidelity configuration, these aeroelastic system matrices are large and compute all eigenvalues will be time consuming. A subspace iteration method (Ref. 4) for complex eigenvalues problems with nonsymmetric matrices has been formulated and incorporated into the modified program for aeroservoelastic stability (MPASES code). Subspace iteration method only solve for the lowest p eigenvalues and corresponding eigenvectors for aeroelastic and aeroservoelastic analysis. In general, the selection of p is ranging from 10 for wing flutter analysis to 50 for an entire aircraft flutter analysis. The application of this newly incorporated code is an experiment known as the Aerostructures Test Wing (ATW) which was designed by the National Aeronautic and Space Administration (NASA) Dryden Flight Research Center, Edwards, California to research aeroelastic instabilities. Specifically, this experiment was used to study an instability

Ca2+-induced delayed afterdepolarizations are triggered by dyadic subspace Ca2+ affirming that increasing SERCA reduces aftercontractions

PubMed Central

Noble, Penelope J.; Noble, Denis

2011-01-01

Ca2+-induced delayed afterdepolarizations (DADs) are depolarizations that occur after full repolarization. They have been observed across multiple species and cell types. Experimental results have indicated that the main cause of DADs is Ca2+ overload. The main hypothesis as to their initiation has been Ca2+ overflow from the overloaded sarcoplasmic reticulum (SR). Our results using 37 previously published mathematical models provide evidence that Ca2+-induced DADs are initiated by the same mechanism as Ca2+-induced Ca2+ release, i.e., the modulation of the opening of ryanodine receptors (RyR) by Ca2+ in the dyadic subspace; an SR overflow mechanism was not necessary for the induction of DADs in any of the models. The SR Ca2+ level is better viewed as a modulator of the appearance of DADs and the magnitude of Ca2+ release. The threshold for the total Ca2+ level within the cell (not only the SR) at which Ca2+ oscillations arise in the models is close to their baseline level (∼1- to 3-fold). It is most sensitive to changes in the maximum sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) pump rate (directly proportional), the opening probability of RyRs, and the Ca2+ diffusion rate from the dyadic subspace into the cytosol (both indirectly proportional), indicating that the appearance of DADs is multifactorial. This shift in emphasis away from SR overload as the trigger for DADs toward a multifactorial analysis could explain why SERCA overexpression has been shown to suppress DADs (while increasing contractility) and why DADs appear during heart failure (at low SR Ca2+ levels). PMID:21666112

Performance Analysis of Blind Subspace-Based Signature Estimation Algorithms for DS-CDMA Systems with Unknown Correlated Noise

NASA Astrophysics Data System (ADS)

Zarifi, Keyvan; Gershman, Alex B.

2006-12-01

We analyze the performance of two popular blind subspace-based signature waveform estimation techniques proposed by Wang and Poor and Buzzi and Poor for direct-sequence code division multiple-access (DS-CDMA) systems with unknown correlated noise. Using the first-order perturbation theory, analytical expressions for the mean-square error (MSE) of these algorithms are derived. We also obtain simple high SNR approximations of the MSE expressions which explicitly clarify how the performance of these techniques depends on the environmental parameters and how it is related to that of the conventional techniques that are based on the standard white noise assumption. Numerical examples further verify the consistency of the obtained analytical results with simulation results.

Constitutive relations in multidimensional isotropic elasticity and their restrictions to subspaces of lower dimensions

NASA Astrophysics Data System (ADS)

Georgievskii, D. V.

2017-07-01

The mechanical meaning and the relationships among material constants in an n-dimensional isotropic elastic medium are discussed. The restrictions of the constitutive relations (Hooke's law) to subspaces of lower dimension caused by the conditions that an m-dimensional strain state or an m-dimensional stress state (1 ≤ m < n) is realized in the medium. Both the terminology and the general idea of the mathematical construction are chosen by analogy with the case n = 3 and m = 2, which is well known in the classical plane problem of elasticity theory. The quintuples of elastic constants of the same medium that enter both the n-dimensional relations and the relations written out for any m-dimensional restriction are expressed in terms of one another. These expressions in terms of the known constants, for example, of a three-dimensional medium, i.e., the classical elastic constants, enable us to judge the material properties of this medium immersed in a space of larger dimension.

Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter.

PubMed

Bolisetti, Siva Karteek; Patwary, Mohammad; Ahmed, Khawza; Soliman, Abdel-Hamid; Abdel-Maguid, Mohamed

2015-01-01

The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper.

Decentralized system identification using stochastic subspace identification on wireless smart sensor networks

NASA Astrophysics Data System (ADS)

Sim, Sung-Han; Spencer, Billie F., Jr.; Park, Jongwoong; Jung, Hyungjo

2012-04-01

Wireless Smart Sensor Networks (WSSNs) facilitates a new paradigm to structural identification and monitoring for civil infrastructure. Conventional monitoring systems based on wired sensors and centralized data acquisition and processing have been considered to be challenging and costly due to cabling and expensive equipment and maintenance costs. WSSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. Thus, several system identification methods have been implemented to process sensor data and extract essential information, including Natural Excitation Technique with Eigensystem Realization Algorithm, Frequency Domain Decomposition (FDD), and Random Decrement Technique (RDT); however, Stochastic Subspace Identification (SSI) has not been fully utilized in WSSNs, while SSI has the strong potential to enhance the system identification. This study presents a decentralized system identification using SSI in WSSNs. The approach is implemented on MEMSIC's Imote2 sensor platform and experimentally verified using a 5-story shear building model.

Dissatisfaction of Compact Picard Condition (CPC) with GRACE satellite data and its treatment by Generalized Tikhonov in Sobolev subspace

NASA Astrophysics Data System (ADS)

AllahTavakoli, Y.; Bagheri, H.; Safari, A.; Sharifi, M.

2012-04-01

This paper is mainly aiming to prove that the stripy noises in the map of earth's surface mass-density changes derived from GRACE Satellites gravimetry, is due to a dissatisfaction of Compact Picard Condition (CPC) with the GRACE data in the inversion of the Newton Integral Equation over the thin layer of earth; and hence the paper proposes the regularization strategies as efficient tools to treat the Ill-posedness and consequently to de-strip the data. First of all, we preferred to slightly modify the mathematical model of earth's surface mass-density changes developed creatively first by J. Wahr and et.al (1998), according to the all their previous assumptions plus taking into consideration the effect of the earth topography. By the modification we expect that some uncertainties in the prior model have been reduced to some extent. Then we analyzed the CPC on the model and we demonstrated how to perform Generalized Tikhonov regularization in Sobolev subspace for overcoming the instability of the problem. Then we applied the strategy in some simulations and case studies to validate our ideas. The simulations confirm that the stripy noises in the GRACE-derived map of the mass-density changes are due to the CPC dissatisfaction and furthermore the case studies show that Generalized Tikhonov regularization in Sobolev subspace is an influential filtering tool to de-strip the noisy data. Also, the case studies interestingly show that the effect of the topography is comparable to the effect of the load Love numbers on the Wahr's model; hence it may be taken into consideration when the load Love numbers have been taken into account.

Improved neutron-gamma discrimination for a 3He neutron detector using subspace learning methods

DOE PAGES

Wang, C. L.; Funk, L. L.; Riedel, R. A.; ...

2017-02-10

3He gas based neutron linear-position-sensitive detectors (LPSDs) have been applied for many neutron scattering instruments. Traditional Pulse-Height Analysis (PHA) for Neutron-Gamma Discrimination (NGD) resulted in the neutron-gamma efficiency ratio on the orders of 10 5-10 6. The NGD ratios of 3He detectors need to be improved for even better scientific results from neutron scattering. Digital Signal Processing (DSP) analyses of waveforms were proposed for obtaining better NGD ratios, based on features extracted from rise-time, pulse amplitude, charge integration, a simplified Wiener filter, and the cross-correlation between individual and template waveforms of neutron and gamma events. Fisher linear discriminant analysis (FLDA)more » and three multivariate analyses (MVAs) of the features were performed. The NGD ratios are improved by about 10 2-10 3 times compared with the traditional PHA method. Finally, our results indicate the NGD capabilities of 3He tube detectors can be significantly improved with subspace-learning based methods, which may result in a reduced data-collection time and better data quality for further data reduction.« less

Damage location and quantification of a pretensioned concrete beam using stochastic subspace identification

NASA Astrophysics Data System (ADS)

Cancelli, Alessandro; Micheli, Laura; Laflamme, Simon; Alipour, Alice; Sritharan, Sri; Ubertini, Filippo

2017-04-01

Stochastic subspace identification (SSID) is a first-order linear system identification technique enabling modal analysis through the time domain. Research in the field of structural health monitoring has demonstrated that SSID can be used to successfully retrieve modal properties, including modal damping ratios, using output-only measurements. In this paper, the utilization of SSID for indirectly retrieving structures' stiffness matrix was investigated, through the study of a simply supported reinforced concrete beam subjected to dynamic loads. Hence, by introducing a physical model of the structure, a second-order identification method is achieved. The reconstruction is based on system condensation methods, which enables calculation of reduced order stiffness, damping, and mass matrices for the structural system. The methods compute the reduced order matrices directly from the modal properties, obtained through the use of SSID. Lastly, the reduced properties of the system are used to reconstruct the stiffness matrix of the beam. The proposed approach is first verified through numerical simulations and then validated using experimental data obtained from a full-scale reinforced concrete beam that experienced progressive damage. Results show that the SSID technique can be used to diagnose, locate, and quantify damage through the reconstruction of the stiffness matrix.

MODAL TRACKING of A Structural Device: A Subspace Identification Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Candy, J. V.; Franco, S. N.; Ruggiero, E. L.

Mechanical devices operating in an environment contaminated by noise, uncertainties, and extraneous disturbances lead to low signal-to-noise-ratios creating an extremely challenging processing problem. To detect/classify a device subsystem from noisy data, it is necessary to identify unique signatures or particular features. An obvious feature would be resonant (modal) frequencies emitted during its normal operation. In this report, we discuss a model-based approach to incorporate these physical features into a dynamic structure that can be used for such an identification. The approach we take after pre-processing the raw vibration data and removing any extraneous disturbances is to obtain a representation ofmore » the structurally unknown device along with its subsystems that capture these salient features. One approach is to recognize that unique modal frequencies (sinusoidal lines) appear in the estimated power spectrum that are solely characteristic of the device under investigation. Therefore, the objective of this effort is based on constructing a black box model of the device that captures these physical features that can be exploited to “diagnose” whether or not the particular device subsystem (track/detect/classify) is operating normally from noisy vibrational data. Here we discuss the application of a modern system identification approach based on stochastic subspace realization techniques capable of both (1) identifying the underlying black-box structure thereby enabling the extraction of structural modes that can be used for analysis and modal tracking as well as (2) indicators of condition and possible changes from normal operation.« less

Spatio-temporal evolution of the 2011 Prague, Oklahoma aftershock sequence revealed using subspace detection and relocation

USGS Publications Warehouse

McMahon, Nicole D; Aster, Richard C.; Yeck, William; McNamara, Daniel E.; Benz, Harley M.

2017-01-01

The 6 November 2011 Mw 5.7 earthquake near Prague, Oklahoma is the second largest earthquake ever recorded in the state. A Mw 4.8 foreshock and the Mw 5.7 mainshock triggered a prolific aftershock sequence. Utilizing a subspace detection method, we increase by fivefold the number of precisely located events between 4 November and 5 December 2011. We find that while most aftershock energy is released in the crystalline basement, a significant number of the events occur in the overlying Arbuckle Group, indicating that active Meeker-Prague faulting extends into the sedimentary zone of wastewater disposal. Although the number of aftershocks in the Arbuckle Group is large, comprising ~40% of the aftershock catalog, the moment contribution of Arbuckle Group earthquakes is much less than 1% of the total aftershock moment budget. Aftershock locations are sparse in patches that experienced large slip during the mainshock.

A note on the blind deconvolution of multiple sparse signals from unknown subspaces

NASA Astrophysics Data System (ADS)

Cosse, Augustin

2017-08-01

This note studies the recovery of multiple sparse signals, xn ∈ ℝL, n = 1, . . . , N, from the knowledge of their convolution with an unknown point spread function h ∈ ℝL. When the point spread function is known to be nonzero, |h[k]| > 0, this blind deconvolution problem can be relaxed into a linear, ill-posed inverse problem in the vector concatenating the unknown inputs xn together with the inverse of the filter, d ∈ ℝL where d[k] := 1/h[k]. When prior information is given on the input subspaces, the resulting overdetermined linear system can be solved efficiently via least squares (see Ling et al. 20161). When no information is given on those subspaces, and the inputs are only known to be sparse, it still remains possible to recover these inputs along with the filter by considering an additional l1 penalty. This note certifies exact recovery of both the unknown PSF and unknown sparse inputs, from the knowledge of their convolutions, as soon as the number of inputs N and the dimension of each input, L , satisfy L ≳ N and N ≳ T2max, up to log factors. Here Tmax = maxn{Tn} and Tn, n = 1, . . . , N denote the supports of the inputs xn. Our proof system combines the recent results on blind deconvolution via least squares to certify invertibility of the linear map encoding the convolutions, with the construction of a dual certificate following the structure first suggested in Candés et al. 2007.2 Unlike in these papers, however, it is not possible to rely on the norm ||(A*TAT)-1|| to certify recovery. We instead use a combination of the Schur Complement and Neumann series to compute an expression for the inverse (A*TAT)-1. Given this expression, it is possible to show that the poorly scaled blocks in (A*TAT)-1 are multiplied by the better scaled ones or vanish in the

The α Subunit of the G Protein G13 Regulates Activity of One or More Gli Transcription Factors Independently of Smoothened*

PubMed Central

Douglas, Andrew E.; Heim, Jennifer A.; Shen, Feng; Almada, Luciana L.; Riobo, Natalia A.; Fernández-Zapico, Martin E.; Manning, David R.

2011-01-01

Smoothened (Smo) is a seven-transmembrane (7-TM) receptor that is essential to most actions of the Hedgehog family of morphogens. We found previously that Smo couples to members of the Gi family of heterotrimeric G proteins, which in some cases are integral although alone insufficient in the activation of Gli transcription factors through Hedgehog signaling. In response to a report that the G12/13 family is relevant to Hedgehog signaling as well, we re-evaluated the coupling of Smo to one member of this family, G13, and investigated the capacity of this and other G proteins to activate one or more of forms of Gli. We found no evidence that Smo couples directly to G13. We found nonetheless that Gα13 and to some extent Gαq and Gα12 are able to effect activation of Gli(s). This capacity is realized in some cells, e.g. C3H10T1/2, MC3T3, and pancreatic cancer cells, but not all cells. The mechanism employed is distinct from that achieved through canonical Hedgehog signaling, as the activation does not involve autocrine signaling or in any other way require active Smo and does not necessarily involve enhanced transcription of Gli1. The activation by Gα13 can be replicated through a Gq/G12/13-coupled receptor, CCKA, and is attenuated by inhibitors of p38 mitogen-activated protein kinase and Tec tyrosine kinases. We posit that G proteins, and perhaps G13 in particular, provide access to Gli that is independent of Smo and that they thus establish a basis for control of at least some forms of Gli-mediated transcription apart from Hedgehogs. PMID:21757753

A fast signal subspace approach for the determination of absolute levels from phased microphone array measurements

NASA Astrophysics Data System (ADS)

Sarradj, Ennes

2010-04-01

Phased microphone arrays are used in a variety of applications for the estimation of acoustic source location and spectra. The popular conventional delay-and-sum beamforming methods used with such arrays suffer from inaccurate estimations of absolute source levels and in some cases also from low resolution. Deconvolution approaches such as DAMAS have better performance, but require high computational effort. A fast beamforming method is proposed that can be used in conjunction with a phased microphone array in applications with focus on the correct quantitative estimation of acoustic source spectra. This method bases on an eigenvalue decomposition of the cross spectral matrix of microphone signals and uses the eigenvalues from the signal subspace to estimate absolute source levels. The theoretical basis of the method is discussed together with an assessment of the quality of the estimation. Experimental tests using a loudspeaker setup and an airfoil trailing edge noise setup in an aeroacoustic wind tunnel show that the proposed method is robust and leads to reliable quantitative results.

Uncertainty quantification in operational modal analysis with stochastic subspace identification: Validation and applications

NASA Astrophysics Data System (ADS)

Reynders, Edwin; Maes, Kristof; Lombaert, Geert; De Roeck, Guido

2016-01-01

Identified modal characteristics are often used as a basis for the calibration and validation of dynamic structural models, for structural control, for structural health monitoring, etc. It is therefore important to know their accuracy. In this article, a method for estimating the (co)variance of modal characteristics that are identified with the stochastic subspace identification method is validated for two civil engineering structures. The first structure is a damaged prestressed concrete bridge for which acceleration and dynamic strain data were measured in 36 different setups. The second structure is a mid-rise building for which acceleration data were measured in 10 different setups. There is a good quantitative agreement between the predicted levels of uncertainty and the observed variability of the eigenfrequencies and damping ratios between the different setups. The method can therefore be used with confidence for quantifying the uncertainty of the identified modal characteristics, also when some or all of them are estimated from a single batch of vibration data. Furthermore, the method is seen to yield valuable insight in the variability of the estimation accuracy from mode to mode and from setup to setup: the more informative a setup is regarding an estimated modal characteristic, the smaller is the estimated variance.

3D-Subspace-Based Auto-Paired Azimuth Angle, Elevation Angle, and Range Estimation for 24G FMCW Radar with an L-Shaped Array

PubMed Central

Nam, HyungSoo; Choi, ByungGil; Oh, Daegun

2018-01-01

In this paper, a three-dimensional (3D)-subspace-based azimuth angle, elevation angle, and range estimation method with auto-pairing is proposed for frequency-modulated continuous waveform (FMCW) radar with an L-shaped array. The proposed method is designed to exploit the 3D shift-invariant structure of the stacked Hankel snapshot matrix for auto-paired azimuth angle, elevation angle, and range estimation. The effectiveness of the proposed method is verified through a variety of experiments conducted in a chamber. For the realization of the proposed method, K-band FMCW radar is implemented with an L-shaped antenna. PMID:29621193

Degenerative joint disease: multiple joint involvement in young and mature dogs.

PubMed

Olsewski, J M; Lust, G; Rendano, V T; Summers, B A

1983-07-01

Radiologic, pathologic, and ancillary methods were used to determine the occurrence of degenerative joint disease involving multiple joints of immature and adult dogs. Animals were selected for the development of hip joint dysplasia and chronic degenerative joint disease. Of disease-prone dogs, 82% (45 of 55 dogs) had radiologic changes, indicative of hip dysplasia, by 1 year of age. At necropsy, more abnormal joints were identified than by radiographic examination. Among 92 dogs between 3 to 11 months of age that had joint abnormalities, 71% had hip joint involvement; 38%, shoulder joint involvement; 22%, stifle joint involvement; and 40% had multiple joint involvement. Polyarthritis was asymptomatic and unexpected. Radiographic examination of older dogs also revealed evidence of degenerative joint disease in many joints. Multiple joint involvement was substantiated at necropsy of young and mature dogs. A similar pattern of polyarticular osteoarthritis was revealed in a survey (computer search) of necropsy reports from medical case records of 100 adult and elderly dogs. Usually, the joint disease was an incidental observation, unrelated to the clinical disease or to the cause of death. The frequent occurrence of degenerative changes in several joints of dogs aged 6 months to 17 years indicated that osteoarthritis may be progressive in these joints and raises the possibility that systemic factors are involved in the disease process.

Hardware-efficient Bell state preparation using Quantum Zeno Dynamics in superconducting circuits

NASA Astrophysics Data System (ADS)

Flurin, Emmanuel; Blok, Machiel; Hacohen-Gourgy, Shay; Martin, Leigh S.; Livingston, William P.; Dove, Allison; Siddiqi, Irfan

By preforming a continuous joint measurement on a two qubit system, we restrict the qubit evolution to a chosen subspace of the total Hilbert space. This extension of the quantum Zeno effect, called Quantum Zeno Dynamics, has already been explored in various physical systems such as superconducting cavities, single rydberg atoms, atomic ensembles and Bose Einstein condensates. In this experiment, two superconducting qubits are strongly dispersively coupled to a high-Q cavity (χ >> κ) allowing for the doubly excited state | 11 〉 to be selectively monitored. The Quantum Zeno Dynamics in the complementary subspace enables us to coherently prepare a Bell state. As opposed to dissipation engineering schemes, we emphasize that our protocol is deterministic, does not rely direct coupling between qubits and functions only using single qubit controls and cavity readout. Such Quantum Zeno Dynamics can be generalized to larger Hilbert space enabling deterministic generation of many-body entangled states, and thus realizes a decoherence-free subspace allowing alternative noise-protection schemes.

Cavity QED implementation of non-adiabatic holonomies for universal quantum gates in decoherence-free subspaces with nitrogen-vacancy centers.

PubMed

Zhou, Jian; Yu, Wei-Can; Gao, Yu-Mei; Xue, Zheng-Yuan

2015-06-01

A cavity QED implementation of the non-adiabatic holonomic quantum computation in decoherence-free subspaces is proposed with nitrogen-vacancy centers coupled commonly to the whispering-gallery mode of a microsphere cavity, where a universal set of quantum gates can be realized on the qubits. In our implementation, with the assistant of the appropriate driving fields, the quantum evolution is insensitive to the cavity field state, which is only virtually excited. The implemented non-adiabatic holonomies, utilizing optical transitions in the Λ type of three-level configuration of the nitrogen-vacancy centers, can be used to construct a universal set of quantum gates on the encoded logical qubits. Therefore, our scheme opens up the possibility of realizing universal holonomic quantum computation with cavity assisted interaction on solid-state spins characterized by long coherence times.

Determination of Parachute Joint Factors using Seam and Joint Testing

NASA Technical Reports Server (NTRS)

Mollmann, Catherine

2015-01-01

This paper details the methodology for determining the joint factor for all parachute components. This method has been successfully implemented on the Capsule Parachute Assembly System (CPAS) for the NASA Orion crew module for use in determining the margin of safety for each component under peak loads. Also discussed are concepts behind the joint factor and what drives the loss of material strength at joints. The joint factor is defined as a "loss in joint strength...relative to the basic material strength" that occurs when "textiles are connected to each other or to metals." During the CPAS engineering development phase, a conservative joint factor of 0.80 was assumed for each parachute component. In order to refine this factor and eliminate excess conservatism, a seam and joint testing program was implemented as part of the structural validation. This method split each of the parachute structural joints into discrete tensile tests designed to duplicate the loading of each joint. Breaking strength data collected from destructive pull testing was then used to calculate the joint factor in the form of an efficiency. Joint efficiency is the percentage of the base material strength that remains after degradation due to sewing or interaction with other components; it is used interchangeably with joint factor in this paper. Parachute materials vary in type-mainly cord, tape, webbing, and cloth -which require different test fixtures and joint sample construction methods. This paper defines guidelines for designing and testing samples based on materials and test goals. Using the test methodology and analysis approach detailed in this paper, the minimum joint factor for each parachute component can be formulated. The joint factors can then be used to calculate the design factor and margin of safety for that component, a critical part of the design verification process.

Spacesuit mobility joints

NASA Technical Reports Server (NTRS)

Vykukal, H. C. (Inventor)

1978-01-01

Joints for use in interconnecting adjacent segments of an hermetically sealed spacesuit which have low torques, low leakage and a high degree of reliability are described. Each of the joints is a special purpose joint characterized by substantially constant volume and low torque characteristics. Linkages which restrain the joint from longitudinal distension and a flexible, substantially impermeable diaphragm of tubular configuration spanning the distance between pivotally supported annuli are featured. The diaphragms of selected joints include rolling convolutions for balancing the joints, while various joints include wedge-shaped sections which enhance the range of motion for the joints.

A unified classifier for robust face recognition based on combining multiple subspace algorithms

NASA Astrophysics Data System (ADS)

Ijaz Bajwa, Usama; Ahmad Taj, Imtiaz; Waqas Anwar, Muhammad

2012-10-01

Face recognition being the fastest growing biometric technology has expanded manifold in the last few years. Various new algorithms and commercial systems have been proposed and developed. However, none of the proposed or developed algorithm is a complete solution because it may work very well on one set of images with say illumination changes but may not work properly on another set of image variations like expression variations. This study is motivated by the fact that any single classifier cannot claim to show generally better performance against all facial image variations. To overcome this shortcoming and achieve generality, combining several classifiers using various strategies has been studied extensively also incorporating the question of suitability of any classifier for this task. The study is based on the outcome of a comprehensive comparative analysis conducted on a combination of six subspace extraction algorithms and four distance metrics on three facial databases. The analysis leads to the selection of the most suitable classifiers which performs better on one task or the other. These classifiers are then combined together onto an ensemble classifier by two different strategies of weighted sum and re-ranking. The results of the ensemble classifier show that these strategies can be effectively used to construct a single classifier that can successfully handle varying facial image conditions of illumination, aging and facial expressions.

Periprosthetic joint infection: are patients with multiple prosthetic joints at risk?

PubMed

Jafari, S Mehdi; Casper, David S; Restrepo, Camilo; Zmistowski, Benjamin; Parvizi, Javad; Sharkey, Peter F

2012-06-01

Patients who present with a periprosthetic joint infection in a single joint may have multiple prosthetic joints. The risk of these patients developing a subsequent infection in another prosthetic joint is unknown. Our purposes were (1) to identify the risk of developing a subsequent infection in another prosthetic joint and (2) to describe the time span and organism profile to the second prosthetic infection. We retrospectively identified 55 patients with periprosthetic joint infection who had another prosthetic joint in place at the time of presentation. Of the 55 patients, 11 (20%) developed a periprosthetic joint infection in a second joint. The type of organism was the same as the first infection in 4 (36%) of 11 patients. The time to developing a second infection averaged 2.0 years (range, 0-6.9 years). Copyright © 2012 Elsevier Inc. All rights reserved.

A novel osteogenic oxysterol compound for therapeutic development to promote bone growth: activation of hedgehog signaling and osteogenesis through smoothened binding.

PubMed

Montgomery, Scott R; Nargizyan, Taya; Meliton, Vicente; Nachtergaele, Sigrid; Rohatgi, Rajat; Stappenbeck, Frank; Jung, Michael E; Johnson, Jared S; Aghdasi, Bayan; Tian, Haijun; Weintraub, Gil; Inoue, Hirokazu; Atti, Elisa; Tetradis, Sotirios; Pereira, Renata C; Hokugo, Akishige; Alobaidaan, Raed; Tan, Yanlin; Hahn, Theodor J; Wang, Jeffrey C; Parhami, Farhad

2014-08-01

Osteogenic factors are often used in orthopedics to promote bone growth, improve fracture healing, and induce spine fusion. Osteogenic oxysterols are naturally occurring molecules that were shown to induce osteogenic differentiation in vitro and promote spine fusion in vivo. The purpose of this study was to identify an osteogenic oxysterol more suitable for clinical development than those previously reported, and evaluate its ability to promote osteogenesis in vitro and spine fusion in rats in vivo. Among more than 100 oxysterol analogues synthesized, Oxy133 induced significant expression of osteogenic markers Runx2, osterix (OSX), alkaline phosphatase (ALP), bone sialoprotein (BSP), and osteocalcin (OCN) in C3H10T1/2 mouse embryonic fibroblasts and in M2-10B4 mouse marrow stromal cells. Oxy133-induced activation of an 8X-Gli luciferase reporter, its direct binding to Smoothened, and the inhibition of Oxy133-induced osteogenic effects by the Hedgehog (Hh) pathway inhibitor, cyclopamine, demonstrated the role of Hh pathway in mediating osteogenic responses to Oxy133. Oxy133 did not stimulate osteogenesis via BMP or Wnt signaling. Oxy133 induced the expression of OSX, BSP, and OCN, and stimulated robust mineralization in primary human mesenchymal stem cells. In vivo, bilateral spine fusion occurred through endochondral ossification and was observed in animals treated with Oxy133 at the fusion site on X-ray after 4 weeks and confirmed with manual assessment, micro-CT (µCT), and histology after 8 weeks, with equal efficiency to recombinant human bone morphogenetic protein-2 (rhBMP-2). Unlike rhBMP-2, Oxy133 did not induce adipogenesis in the fusion mass and resulted in denser bone evidenced by greater bone volume/tissue volume (BV/TV) ratio and smaller trabecular separation. Findings here suggest that Oxy133 has significant potential as an osteogenic molecule with greater ease of synthesis and improved time to fusion compared to previously studied oxysterols. Small

A Novel Osteogenic Oxysterol Compound for Therapeutic Development to Promote Bone Growth: Activation of Hedgehog Signaling and Osteogenesis through Smoothened Binding

PubMed Central

Montgomery, Scott R.; Nargizyan, Taya; Meliton, Vicente; Nachtergaele, Sigrid; Rohatgi, Rajat; Stappenbeck, Frank; Jung, Michael E.; Johnson, Jared S.; Aghdasi, Bayan; Tian, Haijun; Weintraub, Gil; Inoue, Hirokazu; Atti, Elisa; Tetradis, Sotirios; Pereira, Renata C; Hokugo, Akishige; Alobaidaan, Raed; Tan, Yanlin; Hahn, Theodor J.; Wang, Jeffrey C; Parhami, Farhad

2015-01-01

Osteogenic factors are often used in orthopedics to promote bone growth, improve fracture healing, and induce spine fusion. Osteogenic oxysterols are naturally occurring molecules that were shown to induce osteogenic differentiation in vitro and promote spine fusion in vivo. The purpose of this study was to identify an osteogenic oxysterol more suitable for clinical development than those previously reported, and evaluate its ability to promote osteogenesis in vitro and spine fusion in rats in vivo. Among more than 100 oxysterol analogues synthesized, Oxy133 induced significant expression of osteogenic markers Runx2, osterix (OSX), alkaline phosphatase (ALP), bone sialoprotein (BSP), and osteocalcin (OCN) in C3H10T1/2 mouse embryonic fibroblasts and in M2-10B4 mouse marrow stromal cells. Oxy133-induced activation of an 8×-Gli luciferase reporter, its direct binding to Smoothened, and the inhibition of Oxy133-induced osteogenic effects by the Hedgehog (Hh) pathway inhibitor, cyclopamine, demonstrated the role of Hh pathway in mediating osteogenic responses to Oxy133. Oxy133 did not stimulate osteogenesis via BMP or Wnt signaling. Oxy133 induced the expression of OSX, BSP, and OCN and stimulated robust mineralization in primary human mesenchymal stem cells. In vivo, bilateral spine fusion occurred through endochondral ossification and was observed in animals treated with Oxy133 at the fusion site on xray after 4 weeks and confirmed with manual assessment, micro CT (μCT), and histology after 8 weeks, with equal efficiency to recombinant human bone morphogenetic protein-2 (rhBMP-2). Unlike rhBMP-2, Oxy133 did not induce adipogenesis in the fusion mass and resulted in denser bone evidenced by greater BV/TV ratio and smaller trabecular separation. Findings here suggest that Oxy133 has significant potential as an osteogenic molecule with greater ease of synthesis and improved time to fusion compared to previously studied oxysterols. Small molecule osteogenic oxysterols

Separation and imaging diffractions by a sparsity-promoting model and subspace trust-region algorithm

NASA Astrophysics Data System (ADS)

Yu, Caixia; Zhao, Jingtao; Wang, Yanfei; Wang, Chengxiang; Geng, Weifeng

2017-03-01

The small-scale geologic inhomogeneities or discontinuities, such as tiny faults, cavities or fractures, generally have spatial scales comparable to or even smaller than the seismic wavelength. Therefore, the seismic responses of these objects are coded in diffractions and an attempt to high-resolution imaging can be made if we can appropriately image them. As the amplitudes of reflections can be several orders of magnitude larger than those of diffractions, one of the key problems of diffraction imaging is to suppress reflections and at the same time to preserve diffractions. A sparsity-promoting method for separating diffractions in the common-offset domain is proposed that uses the Kirchhoff integral formula to enforce the sparsity of diffractions and the linear Radon transform to formulate reflections. A subspace trust-region algorithm that can provide globally convergent solutions is employed for solving this large-scale computation problem. The method not only allows for separation of diffractions in the case of interfering events but also ensures a high fidelity of the separated diffractions. Numerical experiment and field application demonstrate the good performance of the proposed method in imaging the small-scale geological features related to the migration channel and storage spaces of carbonate reservoirs.

Model reduction and frequency residuals for a robust estimation of nonlinearities in subspace identification

NASA Astrophysics Data System (ADS)

De Filippis, G.; Noël, J. P.; Kerschen, G.; Soria, L.; Stephan, C.

2017-09-01

The introduction of the frequency-domain nonlinear subspace identification (FNSI) method in 2013 constitutes one in a series of recent attempts toward developing a realistic, first-generation framework applicable to complex structures. If this method showed promising capabilities when applied to academic structures, it is still confronted with a number of limitations which needs to be addressed. In particular, the removal of nonphysical poles in the identified nonlinear models is a distinct challenge. In the present paper, it is proposed as a first contribution to operate directly on the identified state-space matrices to carry out spurious pole removal. A modal-space decomposition of the state and output matrices is examined to discriminate genuine from numerical poles, prior to estimating the extended input and feedthrough matrices. The final state-space model thus contains physical information only and naturally leads to nonlinear coefficients free of spurious variations. Besides spurious variations due to nonphysical poles, vibration modes lying outside the frequency band of interest may also produce drifts of the nonlinear coefficients. The second contribution of the paper is to include residual terms, accounting for the existence of these modes. The proposed improved FNSI methodology is validated numerically and experimentally using a full-scale structure, the Morane-Saulnier Paris aircraft.

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing

PubMed Central

2018-01-01

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets. PMID:29562642

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.

PubMed

Li, Jun; Lin, Qiu-Hua; Kang, Chun-Yu; Wang, Kai; Yang, Xiu-Ting

2018-03-18

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets.

Impact extractive fracture of jointed steel plates of a bolted joint

NASA Astrophysics Data System (ADS)

Daimaruya, M.; Fujiki, H.; Ambarita, H.

2012-08-01

This study is concerned with the development of a fracture criterion for the impact fracture of jointed steel plates of a bolted joint used in a car body. For the accurate prediction of crash characteristics of car bodies by computer-aided engineering (CAE), it is also necessary to examine the behavior and fracture of jointed steel plates subjected to impact loads. Although the actual impact fracture of jointed steel plates of a bolted joint used in cars is complicated, for simplifying the problem it might be classified into the shear fracture and the extractive fracture of jointed steel plates. Attention is given to the extractive fracture of jointed steel plates in this study. The extractive behavior and fracture of three kinds of steel plates used for cars are examined in experiments and numerical simulations. The impact extraction test of steel plates jointed by a bolt is performed using the one-bar method, together with the static test. In order to understand the mechanism of extractive fracture process of jointed steel plates, numerical simulations by a FEM code LS-DYNA are also carried out. The obtained results suggest that a stress-based fracture criterion may be developed for the impact extractive fracture of jointed steel plates of a bolted joint used in a car body.

Joint Instability and Osteoarthritis

PubMed Central

Blalock, Darryl; Miller, Andrew; Tilley, Michael; Wang, Jinxi

2015-01-01

Joint instability creates a clinical and economic burden in the health care system. Injuries and disorders that directly damage the joint structure or lead to joint instability are highly associated with osteoarthritis (OA). Thus, understanding the physiology of joint stability and the mechanisms of joint instability-induced OA is of clinical significance. The first section of this review discusses the structure and function of major joint tissues, including periarticular muscles, which play a significant role in joint stability. Because the knee, ankle, and shoulder joints demonstrate a high incidence of ligament injury and joint instability, the second section summarizes the mechanisms of ligament injury-associated joint instability of these joints. The final section highlights the recent advances in the understanding of the mechanical and biological mechanisms of joint instability-induced OA. These advances may lead to new opportunities for clinical intervention in the prevention and early treatment of OA. PMID:25741184

Joint instability and osteoarthritis.

PubMed

Blalock, Darryl; Miller, Andrew; Tilley, Michael; Wang, Jinxi

2015-01-01

Joint instability creates a clinical and economic burden in the health care system. Injuries and disorders that directly damage the joint structure or lead to joint instability are highly associated with osteoarthritis (OA). Thus, understanding the physiology of joint stability and the mechanisms of joint instability-induced OA is of clinical significance. The first section of this review discusses the structure and function of major joint tissues, including periarticular muscles, which play a significant role in joint stability. Because the knee, ankle, and shoulder joints demonstrate a high incidence of ligament injury and joint instability, the second section summarizes the mechanisms of ligament injury-associated joint instability of these joints. The final section highlights the recent advances in the understanding of the mechanical and biological mechanisms of joint instability-induced OA. These advances may lead to new opportunities for clinical intervention in the prevention and early treatment of OA.

Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise.

PubMed

Wang, Junxiang; Wang, Xianpeng; Xu, Dingjie; Bi, Guoan

2018-03-09

This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD) technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method.

Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise

PubMed Central

Wang, Junxiang; Wang, Xianpeng; Xu, Dingjie; Bi, Guoan

2018-01-01

This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD) technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method. PMID:29522499

The hindlimb in walking horses: 2. Net joint moments and joint powers.

PubMed

Clayton, H M; Hodson, E; Lanovaz, J L; Colborne, G R

2001-01-01

The objective of the study was to describe net joint moments and joint powers in the equine hindlimb during walking. The subjects were 5 sound horses. Kinematic and force data were collected synchronously and combined with morphometric information to determine net joint moments at each hindlimb joint throughout stance and swing. The results showed that the net joint moment was on the caudal/plantar side of all hindlimb joints at the start of stance when the limb was being actively retracted. It moved to the cranial/dorsal side around 24% stride at the hip and stifle and in terminal stance at the more distal joints. It remained on the cranial/dorsal side of all joints during the first half of swing to provide active limb protraction, then moved to the caudal/plantar aspect to reverse the direction of limb motion prior to ground contact. The hip joint was the main source of energy generation throughout the stride. It was assisted by the tarsal joint in both stance and swing phases and by the fetlock joint during the stance phase. The coffin joint acted as an energy damper during stance, whereas the stifle joint absorbed almost equal amounts of energy in the stance and swing phases. The coffin and fetlock joints absorbed energy as the limb was protracted and retracted during the swing phase, suggesting that their movements were driven by inertial forces. Future studies will apply these findings to detect changes in the energy profiles due to specific soft tissue injuries.

The Analysis of Adhesively Bonded Advanced Composite Joints Using Joint Finite Elements

NASA Technical Reports Server (NTRS)

Stapleton, Scott E.; Waas, Anthony M.

2012-01-01

The design and sizing of adhesively bonded joints has always been a major bottleneck in the design of composite vehicles. Dense finite element (FE) meshes are required to capture the full behavior of a joint numerically, but these dense meshes are impractical in vehicle-scale models where a course mesh is more desirable to make quick assessments and comparisons of different joint geometries. Analytical models are often helpful in sizing, but difficulties arise in coupling these models with full-vehicle FE models. Therefore, a joint FE was created which can be used within structural FE models to make quick assessments of bonded composite joints. The shape functions of the joint FE were found by solving the governing equations for a structural model for a joint. By analytically determining the shape functions of the joint FE, the complex joint behavior can be captured with very few elements. This joint FE was modified and used to consider adhesives with functionally graded material properties to reduce the peel stress concentrations located near adherend discontinuities. Several practical concerns impede the actual use of such adhesives. These include increased manufacturing complications, alterations to the grading due to adhesive flow during manufacturing, and whether changing the loading conditions significantly impact the effectiveness of the grading. An analytical study is conducted to address these three concerns. Furthermore, proof-of-concept testing is conducted to show the potential advantages of functionally graded adhesives. In this study, grading is achieved by strategically placing glass beads within the adhesive layer at different densities along the joint. Furthermore, the capability to model non-linear adhesive constitutive behavior with large rotations was developed, and progressive failure of the adhesive was modeled by re-meshing the joint as the adhesive fails. Results predicted using the joint FE was compared with experimental results for various

Spacesuit mobility knee joints

NASA Technical Reports Server (NTRS)

Vykukal, H. C. (Inventor)

1979-01-01

Pressure suit mobility joints are for use in interconnecting adjacent segments of an hermetically sealed spacesuit in which low torques, low leakage and a high degree of reliability are required. Each of the joints is a special purpose joint characterized by substantially constant volume and low torque characteristics and includes linkages which restrain the joint from longitudinal distension and includes a flexible, substantially impermeable diaphragm of tubular configuration spanning the distance between pivotally supported annuli. The diaphragms of selected joints include rolling convolutions for balancing the joints, while various joints include wedge-shaped sections which enhance the range of motion for the joints.

High-throughput ocular artifact reduction in multichannel electroencephalography (EEG) using component subspace projection.

PubMed

Ma, Junshui; Bayram, Sevinç; Tao, Peining; Svetnik, Vladimir

2011-03-15

After a review of the ocular artifact reduction literature, a high-throughput method designed to reduce the ocular artifacts in multichannel continuous EEG recordings acquired at clinical EEG laboratories worldwide is proposed. The proposed method belongs to the category of component-based methods, and does not rely on any electrooculography (EOG) signals. Based on a concept that all ocular artifact components exist in a signal component subspace, the method can uniformly handle all types of ocular artifacts, including eye-blinks, saccades, and other eye movements, by automatically identifying ocular components from decomposed signal components. This study also proposes an improved strategy to objectively and quantitatively evaluate artifact reduction methods. The evaluation strategy uses real EEG signals to synthesize realistic simulated datasets with different amounts of ocular artifacts. The simulated datasets enable us to objectively demonstrate that the proposed method outperforms some existing methods when no high-quality EOG signals are available. Moreover, the results of the simulated datasets improve our understanding of the involved signal decomposition algorithms, and provide us with insights into the inconsistency regarding the performance of different methods in the literature. The proposed method was also applied to two independent clinical EEG datasets involving 28 volunteers and over 1000 EEG recordings. This effort further confirms that the proposed method can effectively reduce ocular artifacts in large clinical EEG datasets in a high-throughput fashion. Copyright © 2011 Elsevier B.V. All rights reserved.

Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

NASA Astrophysics Data System (ADS)

Cui, Tiangang; Marzouk, Youssef; Willcox, Karen

2016-06-01

Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting-both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We present and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.

Joint Enabling Capabilities Command

Science.gov Websites

Executive Director Chief of Staff Joint Planning Support Element Joint Communications Support Element mission Joint Enabling Capabilities Command provides decisive joint communications, planning and public and responsive support for joint communications, planning and public affairs. Priorities * Deliver

Semi-Supervised Projective Non-Negative Matrix Factorization for Cancer Classification.

PubMed

Zhang, Xiang; Guan, Naiyang; Jia, Zhilong; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Advances in DNA microarray technologies have made gene expression profiles a significant candidate in identifying different types of cancers. Traditional learning-based cancer identification methods utilize labeled samples to train a classifier, but they are inconvenient for practical application because labels are quite expensive in the clinical cancer research community. This paper proposes a semi-supervised projective non-negative matrix factorization method (Semi-PNMF) to learn an effective classifier from both labeled and unlabeled samples, thus boosting subsequent cancer classification performance. In particular, Semi-PNMF jointly learns a non-negative subspace from concatenated labeled and unlabeled samples and indicates classes by the positions of the maximum entries of their coefficients. Because Semi-PNMF incorporates statistical information from the large volume of unlabeled samples in the learned subspace, it can learn more representative subspaces and boost classification performance. We developed a multiplicative update rule (MUR) to optimize Semi-PNMF and proved its convergence. The experimental results of cancer classification for two multiclass cancer gene expression profile datasets show that Semi-PNMF outperforms the representative methods.

MP Joint Arthritis

MedlinePlus

... is extensive and severe, joint replacement or joint fusion are effective surgical options. Learn more about joint ... the tabs at the top (Video, Articles/WEB, Images, JHS, Products/Vendors), or the filters on the ...

Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

PubMed

Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

2017-08-25

We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

Joint sealant study

DOT National Transportation Integrated Search

1987-09-01

ADOT has approximately 550 lane miles of jointed portland cement pavement under its jurisdiction. The current practice is to saw and seal the joints at the time of construction and reseal the joints under a rehabilitation project. ADOT does not speci...

Joint swelling

MedlinePlus

... of arthritis caused by buildup of uric acid crystals in a joint ( gout ) Arthritis caused by wear ... osteoarthritis ) Arthritis caused by buildup of calcium-type crystals in joints ( pseudogout ) Disorder that involves arthritis and ...

The joint flanker effect and the joint Simon effect: On the comparability of processes underlying joint compatibility effects.

PubMed

Dittrich, Kerstin; Bossert, Marie-Luise; Rothe-Wulf, Annelie; Klauer, Karl Christoph

2017-09-01

Previous studies observed compatibility effects in different interference paradigms such as the Simon and flanker task even when the task was distributed across two co-actors. In both Simon and flanker tasks, performance is improved in compatible trials relative to incompatible trials if one actor works on the task alone as well as if two co-actors share the task. These findings have been taken to indicate that actors automatically co-represent their co-actor's task. However, recent research on the joint Simon and joint flanker effect suggests alternative non-social interpretations. To which degree both joint effects are driven by the same underlying processes is the question of the present study, and it was scrutinized by manipulating the visibility of the co-actor. While the joint Simon effect was not affected by the visibility of the co-actor, the joint flanker effect was reduced when participants did not see their co-actors but knew where the co-actors were seated. These findings provide further evidence for a spatial interpretation of the joint Simon effect. In contrast to recent claims, however, we propose a new explanation of the joint flanker effect that attributes the effect to an impairment in the focusing of spatial attention contingent on the visibility of the co-actor.

Structural damage detection based on stochastic subspace identification and statistical pattern recognition: II. Experimental validation under varying temperature

NASA Astrophysics Data System (ADS)

Lin, Y. Q.; Ren, W. X.; Fang, S. E.

2011-11-01

Although most vibration-based damage detection methods can acquire satisfactory verification on analytical or numerical structures, most of them may encounter problems when applied to real-world structures under varying environments. The damage detection methods that directly extract damage features from the periodically sampled dynamic time history response measurements are desirable but relevant research and field application verification are still lacking. In this second part of a two-part paper, the robustness and performance of the statistics-based damage index using the forward innovation model by stochastic subspace identification of a vibrating structure proposed in the first part have been investigated against two prestressed reinforced concrete (RC) beams tested in the laboratory and a full-scale RC arch bridge tested in the field under varying environments. Experimental verification is focused on temperature effects. It is demonstrated that the proposed statistics-based damage index is insensitive to temperature variations but sensitive to the structural deterioration or state alteration. This makes it possible to detect the structural damage for the real-scale structures experiencing ambient excitations and varying environmental conditions.

A Modelling Method of Bolt Joints Based on Basic Characteristic Parameters of Joint Surfaces

NASA Astrophysics Data System (ADS)

Yuansheng, Li; Guangpeng, Zhang; Zhen, Zhang; Ping, Wang

2018-02-01

Bolt joints are common in machine tools and have a direct impact on the overall performance of the tools. Therefore, the understanding of bolt joint characteristics is essential for improving machine design and assembly. Firstly, According to the experimental data obtained from the experiment, the stiffness curve formula was fitted. Secondly, a finite element model of unit bolt joints such as bolt flange joints, bolt head joints, and thread joints was constructed, and lastly the stiffness parameters of joint surfaces were implemented in the model by the secondary development of ABAQUS. The finite element model of the bolt joint established by this method can simulate the contact state very well.

Mutual coordination strengthens the sense of joint agency in cooperative joint action.

PubMed

Bolt, Nicole K; Poncelet, Evan M; Schultz, Benjamin G; Loehr, Janeen D

2016-11-01

Philosophers have proposed that when people coordinate their actions with others they may experience a sense of joint agency, or shared control over actions and their effects. However, little empirical work has investigated the sense of joint agency. In the current study, pairs coordinated their actions to produce tone sequences and then rated their sense of joint agency on a scale ranging from shared to independent control. People felt more shared than independent control overall, confirming that people experience joint agency during joint action. Furthermore, people felt stronger joint agency when they (a) produced sequences that required mutual coordination compared to sequences in which only one partner had to coordinate with the other, (b) held the role of follower compared to leader, and (c) were better coordinated with their partner. Thus, the strength of joint agency is influenced by the degree to which people mutually coordinate with each other's actions. Copyright © 2016 Elsevier Inc. All rights reserved.

Joint Chiefs of Staff > Leadership

Science.gov Websites

Senior Enlisted Advisor Joint Staff History Joint Staff Inspector General Joint Staff Structure Origin of J8 | Force Structure, Resources & Assessment Contact Joint Staff Structure Joint Staff Organizational Chart Joint Chiefs of Staff Links Home Today in DOD About DOD Top Issues News Photos/Videos

Structural damage detection based on stochastic subspace identification and statistical pattern recognition: I. Theory

NASA Astrophysics Data System (ADS)

Ren, W. X.; Lin, Y. Q.; Fang, S. E.

2011-11-01

One of the key issues in vibration-based structural health monitoring is to extract the damage-sensitive but environment-insensitive features from sampled dynamic response measurements and to carry out the statistical analysis of these features for structural damage detection. A new damage feature is proposed in this paper by using the system matrices of the forward innovation model based on the covariance-driven stochastic subspace identification of a vibrating system. To overcome the variations of the system matrices, a non-singularity transposition matrix is introduced so that the system matrices are normalized to their standard forms. For reducing the effects of modeling errors, noise and environmental variations on measured structural responses, a statistical pattern recognition paradigm is incorporated into the proposed method. The Mahalanobis and Euclidean distance decision functions of the damage feature vector are adopted by defining a statistics-based damage index. The proposed structural damage detection method is verified against one numerical signal and two numerical beams. It is demonstrated that the proposed statistics-based damage index is sensitive to damage and shows some robustness to the noise and false estimation of the system ranks. The method is capable of locating damage of the beam structures under different types of excitations. The robustness of the proposed damage detection method to the variations in environmental temperature is further validated in a companion paper by a reinforced concrete beam tested in the laboratory and a full-scale arch bridge tested in the field.

Signaling networks in joint development

PubMed Central

Salva, Joanna E.; Merrill, Amy E.

2016-01-01

Here we review studies identifying regulatory networks responsible for synovial, cartilaginous, and fibrous joint development. Synovial joints, characterized by the fluid-filled synovial space between the bones, are found in high-mobility regions and are the most common type of joint. Cartilaginous joints unite adjacent bones through either a hyaline cartilage or fibrocartilage intermediate. Fibrous joints, which include the cranial sutures, form a direct union between bones through fibrous connective tissue. We describe how the distinct morphologic and histogenic characteristics of these joint classes are established during embryonic development. Collectively, these studies reveal that despite the heterogeneity of joint strength and mobility, joint development throughout the skeleton utilizes common signaling networks via long-range morphogen gradients and direct cell-cell contact. This suggests that different joint types represent specialized variants of homologous developmental modules. Identifying the unifying aspects of the signaling networks between joint classes allows a more complete understanding of the signaling code for joint formation, which is critical to improving strategies for joint regeneration and repair. PMID:27859991

Epigenetic targeting of Hedgehog pathway transcriptional output through BET bromodomain inhibition

PubMed Central

Tang, Yujie; Gholamin, Sharareh; Schubert, Simone; Willardson, Minde I.; Lee, Alex; Bandopadhayay, Pratiti; Bergthold, Guillame; Masoud, Sabran; Nguyen, Brian; Vue, Nujsaubnusi; Balansay, Brianna; Yu, Furong; Oh, Sekyung; Woo, Pamelyn; Chen, Spenser; Ponnuswami, Anitha; Monje, Michelle; Atwood, Scott X.; Whitson, Ramon J.; Mitra, Siddhartha; Cheshier, Samuel H.; Qi, Jun; Beroukhim, Rameen; Tang, Jean Y.; Wechsler-Reya, Rob; Oro, Anthony E.; Link, Brian A.; Bradner, James E.; Cho, Yoon-Jae

2014-01-01

Hedgehog signaling drives oncogenesis in several cancers and strategies targeting this pathway have been developed, most notably through inhibition of Smoothened. However, resistance to Smoothened inhibitors occurs via genetic changes of Smoothened or other downstream Hedgehog components. Here, we overcome these resistance mechanisms by modulating GLI transcription via inhibition of BET bromodomain proteins. We show the BET bromodomain protein, BRD4, regulates GLI transcription downstream of SMO and SUFU and chromatin immunoprecipitation studies reveal BRD4 directly occupies GLI1 and GLI2 promoters, with a substantial decrease in engagement of these sites upon treatment with JQ1, a small molecule inhibitor targeting BRD4. Globally, genes associated with medulloblastoma-specific GLI1 binding sites are downregulated in response to JQ1 treatment, supporting direct regulation of GLI activity by BRD4. Notably, patient- and GEMM-derived Hedgehog-driven tumors (basal cell carcinoma, medulloblastoma and atypical teratoid/rhabdoid tumor) respond to JQ1 even when harboring genetic lesions rendering them resistant to Smoothened antagonists. PMID:24973920

Novel joint cupping clinical maneuver for ultrasonographic detection of knee joint effusions.

PubMed

Uryasev, Oleg; Joseph, Oliver C; McNamara, John P; Dallas, Apostolos P

2013-11-01

Knee effusions occur due to traumatic and atraumatic causes. Clinical diagnosis currently relies on several provocative techniques to demonstrate knee joint effusions. Portable bedside ultrasonography (US) is becoming an adjunct to diagnosis of effusions. We hypothesized that a US approach with a clinical joint cupping maneuver increases sensitivity in identifying effusions as compared to US alone. Using unembalmed cadaver knees, we injected fluid to create effusions up to 10 mL. Each effusion volume was measured in a lateral transverse location with respect to the patella. For each effusion we applied a joint cupping maneuver from an inferior approach, and re-measured the effusion. With increased volume of saline infusion, the mean depth of effusion on ultrasound imaging increased as well. Using a 2-mm cutoff, we visualized an effusion without the joint cupping maneuver at 2.5 mL and with the joint cupping technique at 1 mL. Mean effusion diameter increased on average 0.26 cm for the joint cupping maneuver as compared to without the maneuver. The effusion depth was statistically different at 2.5 and 7.5 mL (P < .05). Utilizing a joint cupping technique in combination with US is a valuable tool in assessing knee effusions, especially those of subclinical levels. Effusion measurements are complicated by uneven distribution of effusion fluid. A clinical joint cupping maneuver concentrates the fluid in one recess of the joint, increasing the likelihood of fluid detection using US. © 2013 Elsevier Inc. All rights reserved.

Shear fracture of jointed steel plates of bolted joints under impact load

NASA Astrophysics Data System (ADS)

Daimaruya, M.; Fujiki, H.; Ambarita, H.; Kobayashi, H.; Shin, H.-S.

2013-07-01

The present study is concerned with the development of a fracture criterion for the impact fracture of jointed steel plates of bolted joints used in a car body, which contributes to crash simulations by CAE. We focus our attention on the shear fracture of the jointed steel plates of lap-bolted joints in the suspension of a car under impact load. Members of lap-bolted joints are modelled as a pair of steel plates connected by a bolt. One of the plates is a specimen subjected to plastic deformation and fracture and the other is a jig subjected to elastic deformation only. Three kinds of steel plate specimens are examined, i.e., a common steel plate with a tensile strength of 270 MPa and high tensile strength steel plates of 440 and 590 MPa used for cars. The impact shear test was performed using the split Hopkinson bar technique for tension impact, together with the static test using a universal testing machine INSTRON 5586. The behaviour of the shear stress and deformation up to rupture taking place in the joint was discussed. The obtained results suggest that a stress-based fracture criterion may be developed for the impact fracture of jointed steel plates of a lap-bolted joint.

Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters.

PubMed

Schneider, Matthias; Hirsch, Sven; Weber, Bruno; Székely, Gábor; Menze, Bjoern H

2015-01-01

We propose a novel framework for joint 3-D vessel segmentation and centerline extraction. The approach is based on multivariate Hough voting and oblique random forests (RFs) that we learn from noisy annotations. It relies on steerable filters for the efficient computation of local image features at different scales and orientations. We validate both the segmentation performance and the centerline accuracy of our approach both on synthetic vascular data and four 3-D imaging datasets of the rat visual cortex at 700 nm resolution. First, we evaluate the most important structural components of our approach: (1) Orthogonal subspace filtering in comparison to steerable filters that show, qualitatively, similarities to the eigenspace filters learned from local image patches. (2) Standard RF against oblique RF. Second, we compare the overall approach to different state-of-the-art methods for (1) vessel segmentation based on optimally oriented flux (OOF) and the eigenstructure of the Hessian, and (2) centerline extraction based on homotopic skeletonization and geodesic path tracing. Our experiments reveal the benefit of steerable over eigenspace filters as well as the advantage of oblique split directions over univariate orthogonal splits. We further show that the learning-based approach outperforms different state-of-the-art methods and proves highly accurate and robust with regard to both vessel segmentation and centerline extraction in spite of the high level of label noise in the training data. Copyright © 2014 Elsevier B.V. All rights reserved.

Early, asymptomatic stage of degenerative joint disease in canine hip joints.

PubMed

Lust, G; Summers, B A

1981-11-01

The early stages of degenerative joint disease were investigated in coxofemoral joints from dogs with a hereditary predisposition to hip dysplasia. Alterations observed included mild nonsuppurative synovitis, increased volume of both synovial fluid and the ligamentum teres, and focal degenerative articular cartilage lesions. On radiologic examination, subluxation of the femoral head was seen, but only in the most severely affected joints. Synovial inflammation with increased synovial fluid and ligament volumes were indicators of early degenerative joint disease in dogs. These changes seemed to coincide with, or perhaps to precede, microscopic evidence for articular cartilage degeneration and occurred before radiologic abnormalities were detected.

Joint Contact Stress

PubMed Central

Brand, Richard A

2005-01-01

A joint's normal mechanical history contributes to the maintenance of articular cartilage and underlying bone. Loading facilitates the flow of nutrients into cartilage and waste products away, and additionally provides the mechanical signals essential for normal cell and tissue maintenance. Deleteriously low or high contact stresses have been presumed to result in joint deterioration, and particular aspects of the mechanical environment may facilitate repair of damaged cartilage. For decades, investigators have explored static joint contact stresses (under some more or less arbitrary condition) as a surrogate of the relevant mechanical history. Contact stresses have been estimated in vitro in many joints and in a number of species, although only rarely in vivo. Despite a number of widely varying techniques (and spatial resolutions) to measure these contact stresses, reported ranges of static peak normal stresses are relatively similar from joint to joint across species, and in the range of 0.5 to 5.0 MPa. This suggests vertebrate diarthrodial joints have evolved to achieve similar mechanical design criteria. Available evidence also suggests some disorders of cartilage deterioration are associated with somewhat higher peak pressures ranging from 1-20 MPa, but overlapping the range of normal pressures. Some evidence and considerable logic suggests static contact stresses per se do not predict cartilage responses, but rather temporal aspects of the contact stress history. Static contact stresses may therefore not be a reasonable surrogate for biomechanical studies. Rather, temporal and spatial aspects of the loading history undoubtedly induce beneficial and deleterious biological responses. Finally, since all articular cartilage experiences similar stresses, the concept of a "weight-bearing" versus a "non-weight-bearing" joint seems flawed, and should be abandoned. PMID:16089079

Correlational Neural Networks.

PubMed

Chandar, Sarath; Khapra, Mitesh M; Larochelle, Hugo; Ravindran, Balaraman

2016-02-01

Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based approaches and autoencoder (AE)-based approaches. CCA-based approaches learn a joint representation by maximizing correlation of the views when projected to the common subspace. AE-based methods learn a common representation by minimizing the error of reconstructing the two views. Each of these approaches has its own advantages and disadvantages. For example, while CCA-based approaches outperform AE-based approaches for the task of transfer learning, they are not as scalable as the latter. In this work, we propose an AE-based approach, correlational neural network (CorrNet), that explicitly maximizes correlation among the views when projected to the common subspace. Through a series of experiments, we demonstrate that the proposed CorrNet is better than AE and CCA with respect to its ability to learn correlated common representations. We employ CorrNet for several cross-language tasks and show that the representations learned using it perform better than the ones learned using other state-of-the-art approaches.

Modeling Progressive Failure of Bonded Joints Using a Single Joint Finite Element

NASA Technical Reports Server (NTRS)

Stapleton, Scott E.; Waas, Anthony M.; Bednarcyk, Brett A.

2010-01-01

Enhanced finite elements are elements with an embedded analytical solution which can capture detailed local fields, enabling more efficient, mesh-independent finite element analysis. In the present study, an enhanced finite element is applied to generate a general framework capable of modeling an array of joint types. The joint field equations are derived using the principle of minimum potential energy, and the resulting solutions for the displacement fields are used to generate shape functions and a stiffness matrix for a single joint finite element. This single finite element thus captures the detailed stress and strain fields within the bonded joint, but it can function within a broader structural finite element model. The costs associated with a fine mesh of the joint can thus be avoided while still obtaining a detailed solution for the joint. Additionally, the capability to model non-linear adhesive constitutive behavior has been included within the method, and progressive failure of the adhesive can be modeled by using a strain-based failure criteria and re-sizing the joint as the adhesive fails. Results of the model compare favorably with experimental and finite element results.

Modeling of Human Joint Structures.

DTIC Science & Technology

1982-09-01

Acromioclavicular Joint .... ............. ... 20 Glenohumeral Joint .... ................ . 20 HIP JOINT .................. ...... 21 Iliofemoral Ligament...clavicle articulates with the manubrium of the sternum, and the acromioclavicular joint, where the clavicle articulates with the acromion process of the...the interclavicular ligament. Acromioclavicular Joint This articulation between the distal end of the clavicle and the acromion of the scapula is

Joint Chiefs of Staff > Media

Science.gov Websites

Senior Enlisted Advisor Joint Staff History Joint Staff Inspector General Joint Staff Structure Origin of J8 | Force Structure, Resources & Assessment Contact Joint Staff Media News Videos Chairman's

Experimental joint immobilization in guinea pigs. Effects on the knee joint

NASA Technical Reports Server (NTRS)

Marcondesdesouza, J. P.; Machado, F. F.; Sesso, A.; Valeri, V.

1980-01-01

In young and adult guinea pigs, the aftermath experimentally induced by the immobilization of the knee joint in hyperextended forced position was studied. Joint immobilization which varied from one to nine weeks was attained by plaster. Eighty knee joints were examined macro and microscopically. Findings included: (1) muscular hypotrophy and joint stiffness in all animals, directly proportional to the length of immobilization; (2) haemoarthrosis in the first week; (3) intra-articular fibrous tissue proliferation ending up with fibrous ankylosis; (4) hyaline articular cartilage erosions; (5) various degrees of destructive menisci changes. A tentative explanation of the fibrous tissue proliferation and of the cartilage changes is offered.

A Review of Natural Joint Systems and Numerical Investigation of Bio-Inspired GFRP-to-Steel Joints

PubMed Central

Avgoulas, Evangelos I.; Sutcliffe, Michael P. F.

2016-01-01

There are a great variety of joint types used in nature which can inspire engineering joints. In order to design such biomimetic joints, it is at first important to understand how biological joints work. A comprehensive literature review, considering natural joints from a mechanical point of view, was undertaken. This was used to develop a taxonomy based on the different methods/functions that nature successfully uses to attach dissimilar tissues. One of the key methods that nature uses to join dissimilar materials is a transitional zone of stiffness at the insertion site. This method was used to propose bio-inspired solutions with a transitional zone of stiffness at the joint site for several glass fibre reinforced plastic (GFRP) to steel adhesively bonded joint configurations. The transition zone was used to reduce the material stiffness mismatch of the joint parts. A numerical finite element model was used to identify the optimum variation in material stiffness that minimises potential failure of the joint. The best bio-inspired joints showed a 118% increase of joint strength compared to the standard joints. PMID:28773688

A Review of Natural Joint Systems and Numerical Investigation of Bio-Inspired GFRP-to-Steel Joints.

PubMed

Avgoulas, Evangelos I; Sutcliffe, Michael P F

2016-07-12

There are a great variety of joint types used in nature which can inspire engineering joints. In order to design such biomimetic joints, it is at first important to understand how biological joints work. A comprehensive literature review, considering natural joints from a mechanical point of view, was undertaken. This was used to develop a taxonomy based on the different methods/functions that nature successfully uses to attach dissimilar tissues. One of the key methods that nature uses to join dissimilar materials is a transitional zone of stiffness at the insertion site. This method was used to propose bio-inspired solutions with a transitional zone of stiffness at the joint site for several glass fibre reinforced plastic (GFRP) to steel adhesively bonded joint configurations. The transition zone was used to reduce the material stiffness mismatch of the joint parts. A numerical finite element model was used to identify the optimum variation in material stiffness that minimises potential failure of the joint. The best bio-inspired joints showed a 118% increase of joint strength compared to the standard joints.

Effect of Strain Rate on Joint Strength and Failure Mode of Lead-Free Solder Joints

NASA Astrophysics Data System (ADS)

Lin, Jian; Lei, Yongping; Fu, Hanguang; Guo, Fu

2018-03-01

In surface mount technology, the Sn-3.0Ag-0.5Cu solder joint has a shorter impact lifetime than a traditional lead-tin solder joint. In order to improve the impact property of SnAgCu lead-free solder joints and identify the effect of silver content on tensile strength and impact property, impact experiments were conducted at various strain rates on three selected SnAgCu based solder joints. It was found that joint failure mainly occurred in the solder material with large plastic deformation under low strain rate, while joint failure occurred at the brittle intermetallic compound layer without any plastic deformation at a high strain rate. Joint strength increased with the silver content in SnAgCu alloys in static tensile tests, while the impact property of the solder joint decreased with increasing silver content. When the strain rate was low, plastic deformation occurred with failure and the tensile strength of the Sn-3.0Ag-0.5Cu solder joint was higher than that of Sn-0.3Ag-0.7Cu; when the strain rate was high, joint failure mainly occurred at the brittle interface layer and the Sn-0.3Ag-0.7Cu solder joint had a better impact resistance with a thinner intermetallic compound layer.

The Joint Master Operational Planner

DTIC Science & Technology

2016-04-04

Daniel H. Hibner, United States Army Joint Forces Staff College Joint Advanced Warfighting School 7800 Hampton Blvd. Norfolk, VA 23511-1702 Approved...Operational Art. Unclass Unclass Unclass Unclassified Unlimited 66 757-443-6301 NATIONAL DEFENSE UNIVERSITY JOINT FORCES STAFF COLLEGE JOINT ADVANCED...of this paper reflect my own personal views and are not necessarily endorsed by the Joint Forces Staff College or the department of Defense. Thesis

Cellular Pressure-Actuated Joint

NASA Technical Reports Server (NTRS)

McGuire, John R.

2003-01-01

A modification of a pressure-actuated joint has been proposed to improve its pressure actuation in such a manner as to reduce the potential for leakage of the pressurizing fluid. The specific joint for which the modification is proposed is a field joint in a reusable solid-fuel rocket motor (RSRM), in which the pressurizing fluid is a mixture of hot combustion gases. The proposed modification could also be applicable to other pressure-actuated joints of similar configuration.

Mechanics of Suture Joints

NASA Astrophysics Data System (ADS)

Li, Yaning; Song, Juha; Ortiz, Christine; Boyce, Mary; Ortiz Group/DMSE/MIT Team; Boyce Group/ME/MIT Team

2011-03-01

Biological sutures are joints which connect two stiff skeletal or skeletal-like components. These joints possess a wavy geometry with a thin organic layer providing adhesion. Examples of biological sutures include mammalian skulls, the pelvic assembly of the armored fish Gasterosteus aculeatus (the three-spined stickleback), and the suture joints in the shell of the red-eared slider turtle. Biological sutures allow for movement and compliance, control stress concentrations, transmit loads, reduce fatigue stress and absorb energy. In this investigation, the mechanics of the role of suture geometry in providing a naturally optimized joint is explored. In particular, analytical and numerical micromechanical models of the suture joint are constructed. The anisotropic mechanical stiffness and strength are studied as a function of suture wavelength, amplitude and the material properties of the skeletal and organic components, revealing key insights into the optimized nature of these ubiquitous natural joints.

Generalised joint hypermobility and knee joint hypermobility: prevalence, knee joint symptoms and health-related quality of life in a Danish adult population.

PubMed

Junge, Tina; Henriksen, Peter; Hansen, Sebrina; Østengaard, Lasse; Golightly, Yvonne M; Juul-Kristensen, Birgit

2017-10-27

Several biomechanical factors, such as knee joint hypermobility (KJH), are suggested to play a role in the etiology of knee joint symptoms and knee osteoarthritis. Nevertheless, the prevalence or consequences of KJH solely or included in the classification of generalized joint hypermobility (GJHk) is unknown for a general population. Therefore, the objectives were to report the prevalence of self-reported GJHk and KJH, as well as the association of these conditions to knee joint symptoms, severity and duration of symptoms, and health-related quality of life (HRQoL) in a Danish adult population. This study is a cross-sectional population-based survey of 2056 Danish adults. Respondents received online questionnaires of GJHk and KJH, knee joint symptoms, the severity and duration of these, as well as HRQoL. Total response rate was 49% (n = 1006). The prevalence of self-reported GJHk and KJH was 13% and 23%, mostly representing women. More than half of the respondents with GJHk and KJH had knee joint symptoms. The odds for reporting knee joint symptoms, severity of knee joint symptoms and duration of knee joint symptoms were twice as high for respondents with GJHk and KJH. Respondents with GJHk and KJH reported lower HRQoL. GJHk and KJH were frequently reported in the Danish adult population, mostly in women. Respondents with GJHk and KJH were two times more likely to report knee joint-related symptoms such as pain, reduced performance of usual activity and lower HRQoL. The impact of these conditions on HRQoL is comparable with knee osteoarthritis. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

The Interface of Mechanics and Nociception in Joint Pathophysiology: Insights From the Facet and Temporomandibular Joints

PubMed Central

Sperry, Megan M.; Ita, Meagan E.; Kartha, Sonia; Zhang, Sijia; Yu, Ya-Hsin; Winkelstein, Beth

2017-01-01

Chronic joint pain is a widespread problem that frequently occurs with aging and trauma. Pain occurs most often in synovial joints, the body's load bearing joints. The mechanical and molecular mechanisms contributing to synovial joint pain are reviewed using two examples, the cervical spinal facet joints and the temporomandibular joint (TMJ). Although much work has focused on the macroscale mechanics of joints in health and disease, the combined influence of tissue mechanics, molecular processes, and nociception in joint pain has only recently become a focus. Trauma and repeated loading can induce structural and biochemical changes in joints, altering their microenvironment and modifying the biomechanics of their constitutive tissues, which themselves are innervated. Peripheral pain sensors can become activated in response to changes in the joint microenvironment and relay pain signals to the spinal cord and brain where pain is processed and perceived. In some cases, pain circuitry is permanently changed, which may be a potential mechanism for sustained joint pain. However, it is most likely that alterations in both the joint microenvironment and the central nervous system (CNS) contribute to chronic pain. As such, the challenge of treating joint pain and degeneration is temporally and spatially complicated. This review summarizes anatomy, physiology, and pathophysiology of these joints and the sensory pain relays. Pain pathways are postulated to be sensitized by many factors, including degeneration and biochemical priming, with effects on thresholds for mechanical injury and/or dysfunction. Initiators of joint pain are discussed in the context of clinical challenges including the diagnosis and treatment of pain. PMID:28056123

Joint Interference Alignment and Power Allocation for K-User Multicell MIMO Channel through Staggered Antenna Switching

PubMed Central

2018-01-01

In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K-user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the power allocation and feasibility condition for cooperative cell-edge (CE) mobile users (MUs) by assuming that the channel state information is unknown. The new insight behind the transmission strategy of the proposed scheme is premeditated (randomly generated transmission strategy) and partial cooperative CE MUs, where the transmitter is equipped with a conventional antenna, the receiver is equipped with a reconfigurable multimode antenna (staggered antenna switching pattern), and the receiver switches between preset T modes. Our proposed scheme assists and aligns the desired signals and interference signals to cancel the common interference signals because the received signal must have a corresponding independent signal subspace. The capacity for a K-user multicell MIMO Gaussian interference channel with reconfigurable multimode antennas is completely characterised. Furthermore, we show that the proposed K-user multicell MIMO scheduling and K-user L-cell CEUs partial cooperation algorithms elaborate the generalisation of K-user IA and power allocation strategies. The numerical results demonstrate that the proposed intercell interference scheme with partial-cooperative CE MUs achieves better capacity and signal-to-interference plus noise ratio (SINR) performance compared to noncooperative CE MUs and without intercell interference schemes. PMID:29382100

Joint Interference Alignment and Power Allocation for K-User Multicell MIMO Channel through Staggered Antenna Switching.

PubMed

Selvaprabhu, Poongundran; Chinnadurai, Sunil; Sarker, Md Abdul Latif; Lee, Moon Ho

2018-01-28

In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K -user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the power allocation and feasibility condition for cooperative cell-edge (CE) mobile users (MUs) by assuming that the channel state information is unknown. The new insight behind the transmission strategy of the proposed scheme is premeditated (randomly generated transmission strategy) and partial cooperative CE MUs, where the transmitter is equipped with a conventional antenna, the receiver is equipped with a reconfigurable multimode antenna (staggered antenna switching pattern), and the receiver switches between preset T modes. Our proposed scheme assists and aligns the desired signals and interference signals to cancel the common interference signals because the received signal must have a corresponding independent signal subspace. The capacity for a K -user multicell MIMO Gaussian interference channel with reconfigurable multimode antennas is completely characterised. Furthermore, we show that the proposed K -user multicell MIMO scheduling and K -user L -cell CEUs partial cooperation algorithms elaborate the generalisation of K -user IA and power allocation strategies. The numerical results demonstrate that the proposed intercell interference scheme with partial-cooperative CE MUs achieves better capacity and signal-to-interference plus noise ratio (SINR) performance compared to noncooperative CE MUs and without intercell interference schemes.

Strength Variation of Parachute Joints

NASA Technical Reports Server (NTRS)

Mollmann, Catherine

2017-01-01

A parachute joint is defined as a location where a component is sewn or connected to another component. During the design and developmental phase of a parachute system, the joints for each structural component are isolated and tested through a process called seam and joint testing. The objective of seam and joint testing is to determine the degradation on a single component due to interaction with other components; this data is then used when calculating the margin of safety for that component. During the engineering developmental phase of CPAS (Capsule Parachute Assembly System), the parachute system for the NASA Orion Crew Module, testing was completed for every joint of the six subsystems: the four parachutes (main, drogue, pilot, and FBCP [forward bay cover parachute]), the retention release bridle, and the retention panels. The number of joint tests for these subsystems totaled 92, which provides a plethora of data and results for further analysis. In this paper, the data and results of these seam and joint tests are examined to determine the effects, if any, of different operators and sewing machines on the strength of parachute joints. Other variables are also studied to determine their effect on joint strength, such as joint complexity, joint strength magnitude, material type, and material construction. Findings reveal that an optimally-run seam and joint test program could result in an increased understanding of the structure of the parachute; this should lead to a parachute built with optimal components, potentially saving system weight and volume.

Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling

PubMed Central

Silva, Rogers F.; Plis, Sergey M.; Sui, Jing; Pattichis, Marios S.; Adalı, Tülay; Calhoun, Vince D.

2016-01-01

In the past decade, numerous advances in the study of the human brain were fostered by successful applications of blind source separation (BSS) methods to a wide range of imaging modalities. The main focus has been on extracting “networks” represented as the underlying latent sources. While the broad success in learning latent representations from multiple datasets has promoted the wide presence of BSS in modern neuroscience, it also introduced a wide variety of objective functions, underlying graphical structures, and parameter constraints for each method. Such diversity, combined with a host of datatype-specific know-how, can cause a sense of disorder and confusion, hampering a practitioner’s judgment and impeding further development. We organize the diverse landscape of BSS models by exposing its key features and combining them to establish a novel unifying view of the area. In the process, we unveil important connections among models according to their properties and subspace structures. Consequently, a high-level descriptive structure is exposed, ultimately helping practitioners select the right model for their applications. Equipped with that knowledge, we review the current state of BSS applications to neuroimaging. The gained insight into model connections elicits a broader sense of generalization, highlighting several directions for model development. In light of that, we discuss emerging multi-dataset multidimensional (MDM) models and summarize their benefits for the study of the healthy brain and disease-related changes. PMID:28461840

Joint Enrollment Report, 2014

ERIC Educational Resources Information Center

Iowa Department of Education, 2014

2014-01-01

The Iowa Department of Education collects information on joint enrollment in Iowa's 15 community colleges. Jointly enrolled students are high school students enrolled in community college credit coursework. Most jointly enrolled students enroll through Senior Year Plus (SYP) programs such as Postsecondary Enrollment Options (PSEO) and concurrent…

Joint Enrollment Report, 2015

ERIC Educational Resources Information Center

Iowa Department of Education, 2015

2015-01-01

The Iowa Department of Education collects information on joint enrollment from Iowa's 15 community colleges. Jointly enrolled students are high school students enrolled in community college credit coursework. Most jointly enrolled students enroll through Senior Year Plus programs such as Postsecondary Enrollment Options (PSEO) and concurrent…

Migrating lumbar facet joint cysts.

PubMed

Palmieri, Francesco; Cassar-Pullicino, Victor N; Lalam, Radhesh K; Tins, Bernhard J; Tyrrell, Prudencia N M; McCall, Iain W

2006-04-01

The majority of lumbar facet joint cysts (LFJCs) are located in the spinal canal, on the medial aspect of the facet joint with characteristic diagnostic features. When they migrate away from the joint of origin, they cause diagnostic problems. In a 7-year period we examined by computed tomography (CT) and magnetic resonance (MR) imaging five unusual cases of facet joint cysts which migrated from the facet joint of origin. Three LFJCs were identified in the right S1 foramen, one in the right L5-S1 neural foramen and one in the left erector spinae and multifidus muscles between the levels of L2-L4 spinous process. Awareness that spinal lesions identified at MRI and CT could be due to migrating facet joint cyst requires a high level of suspicion. The identification of the appositional contact of the cyst and the facet joint needs to be actively sought in the presence of degenerative facet joints.

Joint Chiefs of Staff > Directorates > J7 | Joint Force Development

Science.gov Websites

development: Doctrine, Education, Concept Development & Experimentation, Training, Exercises and Lessons Coalition Partners. Joint Education Develop policies governing officer and enlisted Joint Professional Military Education (JPME), and the National Defense University. Direct JPME educational advisory group and

Effects of joints in truss structures

NASA Technical Reports Server (NTRS)

Ikegami, R.

1988-01-01

The response of truss-type structures for future space applications, such as Large Deployable Reflector (LDR), will be directly affected by joint performance. Some of the objectives of research at BAC were to characterize structural joints, establish analytical approaches that incorporate joint characteristics, and experimentally establish the validity of the analytical approaches. The test approach to characterize joints for both erectable and deployable-type structures was based upon a Force State Mapping Technique. The approach pictorially shows how the nonlinear joint results can be used for equivalent linear analysis. Testing of the Space Station joints developed at LaRC (a hinged joint at 2 Hz and a clevis joint at 2 Hz) successfully revealed the nonlinear characteristics of the joints. The Space Station joints were effectively linear when loaded to plus or minus 500 pounds with a corresponding displacement of about plus or minus 0.0015 inch. It was indicated that good linear joints exist which are compatible with errected structures, but that difficulty may be encountered if nonlinear-type joints are incorporated in the structure.

Culture - joint fluid

MedlinePlus

... this page: //medlineplus.gov/ency/article/003742.htm Culture - joint fluid To use the sharing features on this page, please enable JavaScript. Joint fluid culture is a laboratory test to detect infection-causing ...

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Ceramic joints

DOEpatents

Miller, Bradley J.; Patten, Jr., Donald O.

1991-01-01

Butt joints between materials having different coefficients of thermal expansion are prepared having a reduced probability of failure of stress facture. This is accomplished by narrowing/tapering the material having the lower coefficient of thermal expansion in a direction away from the joint interface and not joining the narrow-tapered surface to the material having the higher coefficient of thermal expansion.

Sacroiliac joint dysfunction.

PubMed

Ilaslan, Hakan; Arslan, Ahmet; Koç, Omer Nadir; Dalkiliç, Turker; Naderi, Sait

2010-07-01

Sacroiliac joint dysfunction is a disorder presenting with low back and groin pain. It should be taken into consideration during the preoperative differential diagnosis of lumbar disc herniation, lumbar spinal stenosis and facet syndrome. Four cases with sacroiliac dysfunction are presented. The clinical and radiological signs supported the evidence of sacroiliac dysfunction, and exact diagnosis was made after positive response to sacroiliac joint block. A percutaneous sacroiliac fixation provided pain relief in all cases. The mean VAS scores reduced from 8.2 to 2.2. It is concluded that sacroiliac joint dysfunction diagnosis requires a careful physical examination of the sacroiliac joints in all cases with low back and groin pain. The diagnosis is made based on positive response to the sacroiliac block. Sacroiliac fixation was found to be effective in carefully selected cases.

Cytokine mRNA expression in synovial fluid of affected and contralateral stifle joints and the left shoulder joint in dogs with unilateral disease of the stifle joint.

PubMed

de Bruin, Tanya; de Rooster, Hilde; van Bree, Henri; Duchateau, Luc; Cox, Eric

2007-09-01

To examine mRNA expression of cytokines in synovial fluid (SF) cells from dogs with cranial cruciate ligament (CrCL) rupture and medial patellar luxation (MPL) and determine mRNA expression for 3 joints (affected stifle, unaffected contralateral stifle, and left shoulder joints) in dogs with unilateral CrCL rupture. 29 stifle joints with CrCL rupture (29 dogs), 8 stifle joints with MPL (7 dogs), and 24 normal stifle joints (16 clinically normal dogs). Immediately before reconstructive surgery, SF was aspirated from the cruciate-deficient stifle joint or stifle joint with MPL. Fourteen of 29 dogs had unilateral CrCL rupture; SF was also aspirated from the unaffected contralateral stifle joint and left shoulder joint. Those 14 dogs were examined 6 and 12 months after reconstructive surgery. Total RNA was extracted from SF cells and reverse transcription-PCR assay was performed to obtain cDNA. Canine-specific cytokine mRNA expression was determined by use of a real-time PCR assay. Interleukin (IL)-8 and -10 and interferon-gamma expression differed significantly between dogs with arthropathies and dogs with normal stifle joints. For the 14 dogs with unilateral CrCL rupture, a significant difference was found for IL-8 expression. Before reconstructive surgery, IL-8 expression differed significantly between the affected stifle joint and left shoulder joint or contralateral stifle joint. Six months after surgery, IL-8 expression was significantly increased in the unaffected contralateral stifle joint, compared with the shoulder joint. No conclusions can be made regarding the role of the examined cytokines in initiation of CrCL disease.

Hip joint injection

MedlinePlus

... medicine into the joint. The provider uses a real-time x-ray (fluoroscopy) to see where to place ... Wakefield RJ. Arthrocentesis and injection of joints and soft tissue. In: Firestein GS, Budd RC, Gabriel SE, ...

A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem

PubMed Central

Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.

2013-01-01

Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy

Joint Aspiration (Arthrocentesis)

MedlinePlus

... arthritis, or JRA), systemic lupus erythematosus (SLE), and Lyme disease. Joint aspiration is diagnostic but it also can ... topic for: Parents Kids Teens Evaluate Your Child's Lyme Disease Risk Living With Lupus Bones, Muscles, and Joints ...

Longitudinal joint study.

DOT National Transportation Integrated Search

2001-09-01

In previous years there has been a problem with longitudinal joint : deterioration, due in part to poor construction techniques. : The degradation of the longitudinal joints has increased the cost of : maintaining these projects and caused unnecessar...

Joint Control for Dummies: An Elaboration of Lowenkron's Model of Joint (Stimulus) Control

ERIC Educational Resources Information Center

Sidener, David W.

2006-01-01

The following paper describes Lowenkron's model of joint (stimulus) control. Joint control is described as a means of accounting for performances, especially generalized performances, for which a history of contingency control does not provide an adequate account. Examples are provided to illustrate instances in which joint control may facilitate…

High pressure ceramic joint

DOEpatents

Ward, Michael E.; Harkins, Bruce D.

1993-01-01

Many recuperators have components which react to corrosive gases and are used in applications where the donor fluid includes highly corrosive gases. These recuperators have suffered reduced life, increased service or maintenance, and resulted in increased cost. The present joint when used with recuperators increases the use of ceramic components which do not react to highly corrosive gases. Thus, the present joint used with the present recuperator increases the life, reduces the service and maintenance, and reduces the increased cost associated with corrosive action of components used to manufacture recuperators. The present joint is comprised of a first ceramic member, a second ceramic member, a mechanical locking device having a groove defined in one of the first ceramic member and the second ceramic member. The joint and the mechanical locking device is further comprised of a refractory material disposed in the groove and contacting the first ceramic member and the second ceramic member. The present joint mechanically provides a high strength load bearing joint having good thermal cycling characteristics, good resistance to a corrosive environment and good steady state strength at elevated temperatures.

Joint Implications for Contracted Logistics

DTIC Science & Technology

2007-03-30

authority with the host nation country and policy on using UCMJ for contracted personnel. As tailored theater policies are developed and contracting...responsibility, this paper recommends better joint training, leader development and joint enablers for contracting operations. JOINT...U.S. Joint Forces Command (JFCOM) are analyzing Congressional and DOD policy to develop procedures and force structure to support contractor

Comparison of the use of notched wedge joints vs. traditional butt joints in Connecticut

DOT National Transportation Integrated Search

2008-11-07

Performance of Hot Mix Asphalt (HMA) longitudinal joints have been an item of increasing scrutiny in : Connecticut. The traditional butt joint has typically been the method used in Connecticut. These joints : have been reportedly opening up, creating...

Evaluation of narrow transverse contraction joints in jointed plain concrete pavements.

DOT National Transportation Integrated Search

2006-03-01

This report presents the results of a research project conducted at the Louisiana Transportation Research Center (LTRC) to evaluate the performance of narrow transverse contraction joints to control cracking in jointed plain concrete pavements. In ad...

Experimental Investigation of Composite Pressure Vessel Performance and Joint Stiffness for Pyramid and Inverted Pyramid Joints

NASA Technical Reports Server (NTRS)

Verhage, Joseph M.; Bower, Mark V.; Gilbert, Paul A. (Technical Monitor)

2001-01-01

The focus of this study is on the suitability in the application of classical laminate theory analysis tools for filament wound pressure vessels with adhesive laminated joints in particular: pressure vessel wall performance, joint stiffness and failure prediction. Two 18-inch diameter 12-ply filament wound pressure vessels were fabricated. One vessel was fabricated with a 24-ply pyramid laminated adhesive double strap butt joint. The second vessel was fabricated with the same number of plies in an inverted pyramid joint. Results from hydrostatic tests are presented. Experimental results were used as input to the computer programs GENLAM and Laminate, and the output compared to test. By using the axial stress resultant, the classical laminate theory results show a correlation within 1% to the experimental results in predicting the pressure vessel wall pressure performance. The prediction of joint stiffness for the two adhesive joints in the axial direction is within 1% of the experimental results. The calculated hoop direction joint stress resultant is 25% less than the measured resultant for both joint configurations. A correction factor is derived and used in the joint analysis. The correction factor is derived from the hoop stress resultant from the tank wall performance investigation. The vessel with the pyramid joint is determined to have failed in the joint area at a hydrostatic pressure 33% value below predicted failure. The vessel with the inverted pyramid joint failed in the wall acreage at a hydrostatic pressure within 10% of the actual failure pressure.

Longitudinal joint treatment.

DOT National Transportation Integrated Search

2006-03-01

Maine highways have been showing signs of longitudinal joint failure for a number of years. In an effort : to reduce the amount of joint failures the Maine Department of Transportation (MDOT) is currently : evaluating two projects. One project is mon...

Comparative analysis of cis-regulation following stroke and seizures in subspaces of conserved eigensystems

PubMed Central

2010-01-01

Background It is often desirable to separate effects of different regulators on gene expression, or to identify effects of the same regulator across several systems. Here, we focus on the rat brain following stroke or seizures, and demonstrate how the two tasks can be approached simultaneously. Results We applied SVD to time-series gene expression datasets from the rat experimental models of stroke and seizures. We demonstrate conservation of two eigensystems, reflecting inflammation and/or apoptosis (eigensystem 2) and neuronal synaptic activity (eigensystem 3), between the stroke and seizures. We analyzed cis-regulation of gene expression in the subspaces of the conserved eigensystems. Bayesian networks analysis was performed separately for either experimental model, with cross-system validation of the highest-ranking features. In this way, we correctly re-discovered the role of AP1 in the regulation of apoptosis, and the involvement of Creb and Egr in the regulation of synaptic activity-related genes. We identified a novel antagonistic effect of the motif recognized by the nuclear matrix attachment region-binding protein Satb1 on AP1-driven transcriptional activation, suggesting a link between chromatin loop structure and gene activation by AP1. The effects of motifs binding Satb1 and Creb on gene expression in brain conform to the assumption of the linear response model of gene regulation. Our data also suggest that numerous enhancers of neuronal-specific genes are important for their responsiveness to the synaptic activity. Conclusion Eigensystems conserved between stroke and seizures separate effects of inflammation/apoptosis and neuronal synaptic activity, exerted by different transcription factors, on gene expression in rat brain. PMID:20565733

Comparative analysis of different weight matrices in subspace system identification for structural health monitoring

NASA Astrophysics Data System (ADS)

Shokravi, H.; Bakhary, NH

2017-11-01

Subspace System Identification (SSI) is considered as one of the most reliable tools for identification of system parameters. Performance of a SSI scheme is considerably affected by the structure of the associated identification algorithm. Weight matrix is a variable in SSI that is used to reduce the dimensionality of the state-space equation. Generally one of the weight matrices of Principle Component (PC), Unweighted Principle Component (UPC) and Canonical Variate Analysis (CVA) are used in the structure of a SSI algorithm. An increasing number of studies in the field of structural health monitoring are using SSI for damage identification. However, studies that evaluate the performance of the weight matrices particularly in association with accuracy, noise resistance, and time complexity properties are very limited. In this study, the accuracy, noise-robustness, and time-efficiency of the weight matrices are compared using different qualitative and quantitative metrics. Three evaluation metrics of pole analysis, fit values and elapsed time are used in the assessment process. A numerical model of a mass-spring-dashpot and operational data is used in this research paper. It is observed that the principal components obtained using PC algorithms are more robust against noise uncertainty and give more stable results for the pole distribution. Furthermore, higher estimation accuracy is achieved using UPC algorithm. CVA had the worst performance for pole analysis and time efficiency analysis. The superior performance of the UPC algorithm in the elapsed time is attributed to using unit weight matrices. The obtained results demonstrated that the process of reducing dimensionality in CVA and PC has not enhanced the time efficiency but yield an improved modal identification in PC.

Determination of representative dimension parameter values of Korean knee joints for knee joint implant design.

PubMed

Kwak, Dai Soon; Tao, Quang Bang; Todo, Mitsugu; Jeon, Insu

2012-05-01

Knee joint implants developed by western companies have been imported to Korea and used for Korean patients. However, many clinical problems occur in knee joints of Korean patients after total knee joint replacement owing to the geometric mismatch between the western implants and Korean knee joint structures. To solve these problems, a method to determine the representative dimension parameter values of Korean knee joints is introduced to aid in the design of knee joint implants appropriate for Korean patients. Measurements of the dimension parameters of 88 male Korean knee joint subjects were carried out. The distribution of the subjects versus each measured parameter value was investigated. The measured dimension parameter values of each parameter were grouped by suitable intervals called the "size group," and average values of the size groups were calculated. The knee joint subjects were grouped as the "patient group" based on "size group numbers" of each parameter. From the iterative calculations to decrease the errors between the average dimension parameter values of each "patient group" and the dimension parameter values of the subjects, the average dimension parameter values that give less than the error criterion were determined to be the representative dimension parameter values for designing knee joint implants for Korean patients.

Novel Ultrasound Joint Selection Methods Using a Reduced Joint Number Demonstrate Inflammatory Improvement when Compared to Existing Methods and Disease Activity Score at 28 Joints.

PubMed

Tan, York Kiat; Allen, John C; Lye, Weng Kit; Conaghan, Philip G; D'Agostino, Maria Antonietta; Chew, Li-Ching; Thumboo, Julian

2016-01-01

A pilot study testing novel ultrasound (US) joint-selection methods in rheumatoid arthritis. Responsiveness of novel [individualized US (IUS) and individualized composite US (ICUS)] methods were compared with existing US methods and the Disease Activity Score at 28 joints (DAS28) for 12 patients followed for 3 months. IUS selected up to 7 and 12 most ultrasonographically inflamed joints, while ICUS additionally incorporated clinically symptomatic joints. The existing, IUS, and ICUS methods' standardized response means were -0.39, -1.08, and -1.11, respectively, for 7 joints; -0.49, -1.00, and -1.16, respectively, for 12 joints; and -0.94 for DAS28. Novel methods effectively demonstrate inflammatory improvement when compared with existing methods and DAS28.

Accuracy of acromioclavicular joint injections.

PubMed

Wasserman, Bradley R; Pettrone, Sarah; Jazrawi, Laith M; Zuckerman, Joseph D; Rokito, Andrew S

2013-01-01

Injection to the acromioclavicular (AC) joint can be both diagnostic and therapeutic. The purpose of this study was to evaluate the accuracy of in vivo AC joint injections. Case series; Level of evidence, 4. Thirty patients with pain localized to the AC joint were injected with 1 mL of 1% lidocaine and 0.5 mL of radiographic contrast material (Isovue). Radiographs of the AC joint were taken after the injection. Each radiograph was reviewed by a musculoskeletal radiologist and graded as intra-articular, extra-articular, or partially intra-articular. Of the 30 injections performed, 13 (43.3%) were intra-articular, 7 (23.3%) were partially articular, and 10 (33.3%) were extra-articular. When the intra-articular and the partially articular groups were combined, 20 patients (66.7%) had some contrast dye in the AC joint. This study demonstrates that despite the relatively superficial location of the AC joint, the clinical accuracy of AC joint injections remains relatively low.

Can symptomatic acromioclavicular joints be differentiated from asymptomatic acromioclavicular joints on 3-T MR imaging?

PubMed

Choo, Hye Jung; Lee, Sun Joo; Kim, Jung Han; Cha, Seong Sook; Park, Young Mi; Park, Ji Sung; Lee, Jun Woo; Oh, Minkyung

2013-04-01

To evaluate retrospectively whether symptomatic acromioclavicular joints can be differentiated from asymptomatic acromioclavicular joints on 3-T MR imaging. This study included 146 patients who underwent physical examination of acromioclavicular joints and 3-T MR imaging of the shoulder. Among them, 67 patients showing positive results on physical examination were assigned to the symptomatic group, whereas 79 showing negative results were assigned to the asymptomatic group. The following MR findings were compared between the symptomatic and asymptomatic groups: presence of osteophytes, articular surface irregularity, subchondral cysts, acromioclavicular joint fluid, subacromial fluid, subacromial bony spurs, joint capsular distension, bone edema, intraarticular enhancement, periarticular enhancement, superior and inferior joint capsular distension degree, and joint capsular thickness. The patients were subsequently divided into groups based on age (younger, older) and the method of MR arthrography (direct MR arthrography, indirect MR arthrography), and all the MR findings in each subgroup were reanalyzed. The meaningful cutoff value of each significant continuous variable was calculated using receiver operating characteristic analysis. The degree of superior capsular distension was the only significant MR finding of symptomatic acromioclavicular joints and its meaningful cutoff value was 2.1mm. After subgroup analyses, this variable was significant in the older age group and indirect MR arthrography group. On 3-T MR imaging, the degree of superior joint capsular distension might be a predictable MR finding in the diagnosis of symptomatic acromioclavicular joints. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

[Effects of exercise on joints.

PubMed

Moriyama, Hideki

Joints are composed of several different tissues(cartilage, capsule, meniscus, and ligament), and articular cartilage plays an important role in maintaining mechanical competence during exercise. Weight-bearing exercise has several benefit, including improved blood and synovial fluid circulation in a given joint. Consistent moderate activities facilitate cycles of anabolism and catabolism. Mechanical stresses are crucial for the maintenance of the morphologic and functional integrity of articular cartilage. Healthy cartilage is exposed by hydrostatic pressure and tensile strain, when cartilage degeneration develops, abnormal cartilage is exposed by shear stress. Moderate(physiological)exercise is characterized by a range of equilibrium between matrix anabolic and catabolic processes, or anabolism beyond catabolism. Joints are susceptible to insufficient or excessive activities, leading to joint degeneration. Lack of exercise is known to induce joint contracture seen clinically as a consequence of disuse changes, and excess mechanical stresses induce joint destruction such as osteoarthritis. Joint diseases resulting from insufficient or excessive activities are new and major challenging issues with our aging population. Thus, it is highly desirable to have an effective and efficient treatment to improve and protect against these joint diseases, and thereby to solve these clearly unanswered issues.

Functional disorders of the temporomandibular joints: Internal derangement of the temporomandibular joint.

PubMed

Chang, Chih-Ling; Wang, Ding-Han; Yang, Mu-Chen; Hsu, Wun-Eng; Hsu, Ming-Lun

2018-04-01

Temporomandibular joint (TMJ) is one of the most complex joints of the human body. Due to its unique movement, in terms of combination of rotation and translator movement, disc of the joint plays an important role to maintain its normal function. In order to sustain the normal function of the TMJ, disc must be kept in proper position as well as maintain normal shape in all circumstances. Once the disc is not any more in its normal position during function of the joint, disturbance of the joint can be occurred which will lead to subsequent distortion of the disc. Shape of the disc can be influenced by many factors i.e.: abnormal function or composition of the disc itself. Etiology of the internal derangement of the disc remains controversial. Multifactorial theory has been postulated in most of previous manuscripts. Disc is composed of mainly extracellular matrix. Abnormal proportion of collagen type I & III may also leads to joint hypermobility which may be also a predisposing factor of this disorder. Thus it can be recognized as local manifestation of a systemic disorder. Different treatment modalities with from conservative treatment to surgical intervention distinct success rate have been reported. Recently treatment with extracellular matrix injection becomes more and more popular to strengthen the joint itself. Since multifactorial in character, the best solution of the treatment modalities should be aimed to resolve possible etiology from different aspects. Team work may be indication to reach satisfied results. Copyright © 2018. Published by Elsevier Taiwan.

Predicting the Functional Roles of Knee Joint Muscles from Internal Joint Moments.

PubMed

Flaxman, Teresa E; Alkjær, Tine; Simonsen, Erik B; Krogsgaard, Michael R; Benoit, Daniel L

2017-03-01

Knee muscles are commonly labeled as flexors or extensors and aptly stabilize the knee against sagittal plane loads. However, how these muscles stabilize the knee against adduction-abduction and rotational loads remains unclear. Our study sought 1) to classify muscle roles as they relate to joint stability by quantifying the relationship between individual muscle activation patterns and internal net joint moments in all three loading planes and 2) to determine whether these roles change with increasing force levels. A standing isometric force matching protocol required subjects to modulate ground reaction forces to elicit various combinations and magnitudes of sagittal, frontal, and transverse internal joint moments. Surface EMG measured activities of 10 lower limb muscles. Partial least squares regressions determined which internal moment(s) were significantly related to the activation of individual muscles. Rectus femoris and tensor fasciae latae were classified as moment actuators for knee extension and hip flexion. Hamstrings were classified as moment actuators for hip extension and knee flexion. Gastrocnemius and hamstring muscles were classified as specific joint stabilizers for knee rotation. Vastii were classified as general joint stabilizers because activation was independent of moment generation. Muscle roles did not change with increasing effort levels. Our findings indicate muscle activation is not dependent on anatomical orientation but perhaps on its role in maintaining knee joint stability in the frontal and transverse loading planes. This is useful for delineating the roles of biarticular knee joint muscles and could have implications in robotics, musculoskeletal modeling, sports sciences, and rehabilitation.

New Joint Sealants. Criteria, Design and Materials.

ERIC Educational Resources Information Center

Building Research Inst., Inc., Washington, DC.

Contents include--(1) sealing concrete joints, (2) sealing glass and metal joints, (3) metal and glass joint sealants from a fabricator's viewpoint, (4) a theory of adhesion for joint sealants, (5) geometry of simple joint seals under strain, (6) joint sealant specifications from a manufacturer's viewpoint, (7) joint sealant requirements from an…

Steroid injections - tendon, bursa, joint

MedlinePlus

... a small amount of corticosteroid and a local anesthetic into the bursa. JOINT Any joint problem, such ... A small amount of corticosteroid and a local anesthetic will be injected into the joint. TENDON A ...

High pressure ceramic joint

DOEpatents

Ward, M.E.; Harkins, B.D.

1993-11-30

Many recuperators have components which react to corrosive gases and are used in applications where the donor fluid includes highly corrosive gases. These recuperators have suffered reduced life, increased service or maintenance, and resulted in increased cost. The present joint when used with recuperators increases the use of ceramic components which do not react to highly corrosive gases. Thus, the present joint used with the present recuperator increases the life, reduces the service and maintenance, and reduces the increased cost associated with corrosive action of components used to manufacture recuperators. The present joint is comprised of a first ceramic member, a second ceramic member, a mechanical locking device having a groove defined in one of the first ceramic member and the second ceramic member. The joint and the mechanical locking device is further comprised of a refractory material disposed in the groove and contacting the first ceramic member and the second ceramic member. The present joint mechanically provides a high strength load bearing joint having good thermal cycling characteristics, good resistance to a corrosive environment and good steady state strength at elevated temperatures. 4 figures.

[Classification and Treatment of Sacroiliac Joint Dislocation].

PubMed

Tan, Zhen; Huang, Zhong; Li, Liang; Meng, Wei-Kun; Liu, Lei; Zhang, Hui; Wang, Guang-Lin; Huang, Fu-Guo

2017-09-01

To develop a renewed classification and treatment regimen for sacroiliac joint dislocation. According to the direction of dislocation of sacroiliac joint,combined iliac,sacral fractures,and fracture morphology,sacroiliac joint dislocation was classified into 4 types. Type Ⅰ (sacroiliac anterior dislocation): main fracture fragments of posterior iliac wing dislocated in front of sacroiliac joint. Type Ⅱ (sacroiliac posterior dislocation): main fracture fragments of posterior iliac wing dislocated in posterior of sacroiliac joint. Type Ⅲ (Crescent fracturedislocation of the sacroiliac joint): upward dislocation of posterior iliac wing with oblique fracture through posterior iliac wing. Type ⅢA: a large crescent fragment and dislocation comprises no more than onethird of sacroiliac joint,which is typically inferior. Type ⅢB: intermediatesize crescent fragment and dislocation comprises between one and twothirds of joint. Type ⅢC: a small crescent fragment where dislocation comprises most,but not the entire joint. Different treatment regimens were selected for different types of fractures. Treatment for type Ⅰ sacroiliac joint dislocation: anterior iliac fossa approach pry stripping reset; sacroiliac joint fixed with sacroiliac screw through percutaneous. Treatment for type Ⅱ sacroiliac joint dislocation: posterior sacroiliac joint posterior approach; sacroiliac joint fixed with sacroiliac screw under computer guidance. Treatment for type ⅢA and ⅢB sacroiliac joint dislocation: posterior sacroiliac joint approach; sacroiliac joint fixed with reconstruction plate. Treatment for type ⅢC sacroiliac joint dislocation: sacroiliac joint closed reduction; sacroiliac joint fixed with sacroiliac screw through percutaneous. Treatment for type Ⅳ sacroiliac joint dislocation: posterior approach; sacroiliac joint fixed with spinal pelvic fixation. Results of 24 to 72 months patient follow-up (mean 34.5 months): 100% survival,100% wound healing,and 100

Metal to ceramic sealed joint

DOEpatents

Lasecki, J.V.; Novak, R.F.; McBride, J.R.

1991-08-27

A metal to ceramic sealed joint which can withstand wide variations in temperature and maintain a good seal is provided for use in a device adapted to withstand thermal cycling from about 20 to about 1000 degrees C. The sealed joint includes a metal member, a ceramic member having an end portion, and an active metal braze forming a joint to seal the metal member to the ceramic member. The joint is positioned remote from the end portion of the ceramic member to avoid stresses at the ends or edges of the ceramic member. The sealed joint is particularly suited for use to form sealed metal to ceramic joints in a thermoelectric generator such as a sodium heat engine where a solid ceramic electrolyte is joined to metal parts in the system. 11 figures.

Metal to ceramic sealed joint

DOEpatents

Lasecki, John V.; Novak, Robert F.; McBride, James R.

1991-01-01

A metal to ceramic sealed joint which can withstand wide variations in temperature and maintain a good seal is provided for use in a device adapted to withstand thermal cycling from about 20 to about 1000 degrees C. The sealed joint includes a metal member, a ceramic member having an end portion, and an active metal braze forming a joint to seal the metal member to the ceramic member. The joint is positioned remote from the end portion of the ceramic member to avoid stresses at the ends or edges of the ceramic member. The sealed joint is particularly suited for use to form sealed metal to ceramic joints in a thermoelectric generator such as a sodium heat engine where a solid ceramic electrolyte is joined to metal parts in the system.

Sacroiliac joint tuberculosis

PubMed Central

Govender, S.

2006-01-01

Infections of the sacroiliac joint are uncommon and the diagnosis is usually delayed. In a retrospective study, 17 patients who had been treated for tuberculosis sacroiliitis between 1994 and 2004 were reviewed. Two patients were excluded due to a short follow-up (less than 2 years). Low back pain and difficulty in walking were the most common presenting features. Two patients presented with a buttock abscess and spondylitis of the lumbar spine was noted in two patients. The Gaenslen’s and FABER (flexion, abduction and external rotation) tests were positive in all patients. Radiological changes included loss of cortical margins with erosion of the joints. An open biopsy and curettage was performed in all patients; histology revealed chronic infection and acid-fast bacilli were isolated in nine patients. Antituberculous (TB) medication was administered for 18 months and the follow-up ranged from 3 to 10 years (mean: 5 years). The sacroiliac joint fused spontaneously within 2 years. Although all patients had mild discomfort in the lower back following treatment they had no difficulty in walking. Sacroiliac joint infection must be included in the differential diagnosis of lower back pain and meticulous history and clinical evaluation of the joint are essential. PMID:16673102

Lower limb joint work and joint work contribution during downhill and uphill walking at different inclinations.

PubMed

Alexander, Nathalie; Strutzenberger, Gerda; Ameshofer, Lisa Maria; Schwameder, Hermann

2017-08-16

Work performance and individual joint contribution to total work are important information for creating training protocols, but were not assessed so far for sloped walking. Therefore, the purpose of this study was to analyze lower limb joint work and joint contribution of the hip, knee and ankle to total lower limb work during sloped walking in a healthy population. Eighteen male participants (27.0±4.7yrs, 1.80±0.05m, 74.5±8.2kg) walked on an instrumented ramp at inclination angles of 0°, ±6°, ±12° and ±18° at 1.1m/s. Kinematic and kinetic data were captured using a motion-capture system (Vicon) and two force plates (AMTI). Joint power curves, joint work (positive, negative, absolute) and each joint's contribution to total lower limb work were analyzed throughout the stance phase using an ANOVA with repeated measures. With increasing inclination positive joint work increased for the ankle and hip joint and in total during uphill walking. Negative joint work increased for each joint and in total work during downhill walking. Absolute work was increased during both uphill (all joints) and downhill (ankle & knee) walking. Knee joint contribution to total negative and absolute work increased during downhill walking while hip and ankle contributions decreased. This study identified, that, when switching from level to a 6° and from 6° to a 12° inclination the gain of individual joint work is more pronounced compared to switching from 12° to an 18° inclination. The results might be used for training recommendations and specific training intervention with respect to sloped walking. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Temporo-mandibular joint. Morpho-functional considerations].

PubMed

Scutariu, M D; Indrei, Anca

2004-01-01

The temporo-mandibular joint is distinguished from most other synovial joints of the body by two features: 1. the two jointed components carry teeth whose position and occlusion introduce a very strong influence on the movements of the temporo-mandibular joint and 2. its articular surfaces are not covered by hyaline cartilage, but by a dense, fibrous tissue. This paper describes the parts of the temporo-mandibular joint: the articular surfaces (the condylar process of the mandible and the glenoid part of the temporal bone), the fibrocartilaginous disc which is interposed between the mandibular and the temporal surface, the fibrous capsule of the temporo-mandibular joint and the ligaments of this joint. All these parts present a very strong adaptation at the important functions of the temporo-mandibular joint.

Utilization of Facet Joint and Sacroiliac Joint Interventions in Medicare Population from 2000 to 2014: Explosive Growth Continues!

PubMed

Manchikanti, Laxmaiah; Hirsch, Joshua A; Pampati, Vidyasagar; Boswell, Mark V

2016-10-01

Increasing utilization of interventional techniques in managing chronic spinal pain, specifically facet joint interventions and sacroiliac joint injections, is a major concern of healthcare policy makers. We analyzed the patterns of utilization of facet and sacroiliac joint interventions in managing chronic spinal pain. The results showed significant increase of facet joint interventions and sacroiliac joint injections from 2000 to 2014 in Medicare FFS service beneficiaries. Overall, the Medicare population increased 35 %, whereas facet joint and sacroiliac joint interventions increased 313.3 % per 100,000 Medicare population with an annual increase of 10.7 %. While the increases were uniform from 2000 to 2014, there were some decreases noted for facet joint interventions in 2007, 2010, and 2013, whereas for sacroiliac joint injections, the decreases were noted in 2007 and 2013. The increases were for cervical and thoracic facet neurolysis at 911.5 % compared to lumbosacral facet neurolysis of 567.8 %, 362.9 % of cervical and thoracic facet joint blocks, 316.9 % of sacroiliac joints injections, and finally 227.3 % of lumbosacral facet joint blocks.

Ball-joint grounding ring

NASA Technical Reports Server (NTRS)

Aperlo, P. J. A.; Buck, P. A.; Weldon, V. A.

1981-01-01

In ball and socket joint where electrical insulator such as polytetrafluoroethylene is used as line to minimize friction, good electrical contact across joint may be needed for lightning protection or to prevent static-charge build-up. Electrical contact is maintained by ring of spring-loaded fingers mounted in socket. It may be useful in industry for cranes, trailers, and other applications requiring ball and socket joint.

14 CFR 23.693 - Joints.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Systems § 23.693 Joints. Control system joints (in push-pull systems) that are subject to angular motion... factor may be reduced to 2.0 for joints in cable control systems. For ball or roller bearings, the...

Wrist joint assembly

NASA Technical Reports Server (NTRS)

Kersten, L.; Johnson, J. D. (Inventor)

1978-01-01

A wrist joint assembly is provided for use with a mechanical manipulator arm for finely positioning an end-effector carried by the wrist joint on the terminal end of the manipulator arm. The wrist joint assembly is pivotable about a first axis to produce a yaw motion, a second axis is to produce a pitch motion, and a third axis to produce a roll motion. The wrist joint assembly includes a disk segment affixed to the terminal end of the manipulator arm and a first housing member, a second housing member, and a third housing member. The third housing member and the mechanical end-effector are moved in the yaw, pitch, and roll motion. Drive means are provided for rotating each of the housings about their respective axis which includes a cluster of miniature motors having spur gears carried on the output drive shaft which mesh with a center drive gear affixed on the housing to be rotated.

Joint fMRI analysis and subject clustering using sparse dictionary learning

NASA Astrophysics Data System (ADS)

Kim, Seung-Jun; Dontaraju, Krishna K.

2017-08-01

Multi-subject fMRI data analysis methods based on sparse dictionary learning are proposed. In addition to identifying the component spatial maps by exploiting the sparsity of the maps, clusters of the subjects are learned by postulating that the fMRI volumes admit a subspace clustering structure. Furthermore, in order to tune the associated hyper-parameters systematically, a cross-validation strategy is developed based on entry-wise sampling of the fMRI dataset. Efficient algorithms for solving the proposed constrained dictionary learning formulations are developed. Numerical tests performed on synthetic fMRI data show promising results and provides insights into the proposed technique.

Product evaluation : Ruscoe 983 joint sealant

DOT National Transportation Integrated Search

1986-07-10

This report contains a product evaluation of Ruscoe's 983 joint sealant. Ruscoe 983 is an asphalt base single compound joint sealant. It contains an aluminum fortified adhesive and is designed for use on highway expansion joints, bridge joints, and r...

Gene-expression changes in knee-joint tissues with aging and menopause: implications for the joint as an organ

PubMed Central

Rollick, Natalie C; Lemmex, Devin B; Ono, Yohei; Reno, Carol R; Hart, David A; Lo, Ian KY; Thornton, Gail M

2018-01-01

Background When considering the “joint as an organ”, the tissues in a joint act as complementary components of an organ, and the “set point” is the cellular activity for homeostasis of the joint tissues. Even in the absence of injury, joint tissues have adaptive responses to processes, like aging and menopause, which result in changes to the set point. Purpose The purpose of this study in a preclinical model was to investigate age-related and menopause-related changes in knee-joint tissues with the hypothesis that tissues will change in unique ways that reflect their differing contributions to maintaining joint function (as measured by joint laxity) and the differing processes of aging and menopause. Methods Rabbit knee-joint tissues from three groups were evaluated: young adult (gene expression, n=8; joint laxity, n=7; water content, n=8), aging adult (gene expression, n=6; joint laxity, n=7; water content, n=5), and menopausal adult (gene expression, n=8; joint laxity, n=7; water content, n=8). Surgical menopause was induced with ovariohysterectomy surgery and gene expression was assessed using reverse-transcription quantitative polymerase chain reaction. Results Aging resulted in changes to 37 of the 150 gene–tissue combinations evaluated, and menopause resulted in changes to 39 of the 150. Despite the similar number of changes, only eleven changes were the same in both aging and menopause. No differences in joint laxity were detected comparing young adult rabbits with aging adult rabbits or with menopausal adult rabbits. Conclusion Aging and menopause affected the gene-expression patterns of the tissues of the knee joint differently, suggesting unique changes to the set point of the knee. Interestingly, aging and menopause did not affect knee-joint laxity, suggesting that joint function was maintained, despite changes in gene expression. Taken together, these findings support the theory of the joint as an organ where the tissues of the joint adapt to

Knee joint mobilization reduces secondary mechanical hyperalgesia induced by capsaicin injection into the ankle joint.

PubMed

Sluka, K A; Wright, A

2001-01-01

Joint mobilization is a treatment approach commonly used by physical therapists for the management of a variety of painful conditions. However, the clinical effectiveness when compared to placebo and the neurophysiological mechanism of action are not known. The purpose of this study was to establish that application of a manual therapy technique will produce antihyperalgesia in an animal model of joint inflammation and that the antihyperalgesia produced by joint mobilization depends on the time of treatment application. Capsaicin (0.2%, 50 microl) was injected into the lateral aspect of the left ankle joint and mechanical withdrawal threshold assessed before and after capsaicin injection in Sprague-Dawley rats. Joint mobilization of the ipsilateral knee joint was performed 2 h after capsaicin injection for a total of 3 min, 9 min or 15 min under halothane anaesthesia. Control groups included animals that received halothane for the same time as the group that received joint mobilization and those whose limbs were held for the same duration as the mobilization (no halothane). Capsaicin resulted in a decreased mechanical withdrawal threshold by 2 h after injection that was maintained through 4 h. Both 9 and 15 min of mobilization, but not 3 min of mobilization, increased the withdrawal threshold to mechanical stimuli to baseline values when compared with control groups. The antihyperalgesic effect of joint mobilization lasted 30 min. Thus, joint mobilization (9 or 15 min duration) produces a significant reversal of secondary mechanical hyperalgesia induced by intra-articular injection of capsaicin. Copyright 2001 European Federation of Chapters of the International Association for the Study of Pain.

Imaging of heart acoustic based on the sub-space methods using a microphone array.

PubMed

Moghaddasi, Hanie; Almasganj, Farshad; Zoroufian, Arezoo

2017-07-01

Heart disease is one of the leading causes of death around the world. Phonocardiogram (PCG) is an important bio-signal which represents the acoustic activity of heart, typically without any spatiotemporal information of the involved acoustic sources. The aim of this study is to analyze the PCG by employing a microphone array by which the heart internal sound sources could be localized, too. In this paper, it is intended to propose a modality by which the locations of the active sources in the heart could also be investigated, during a cardiac cycle. In this way, a microphone array with six microphones is employed as the recording set up to be put on the human chest. In the following, the Group Delay MUSIC algorithm which is a sub-space based localization method is used to estimate the location of the heart sources in different phases of the PCG. We achieved to 0.14cm mean error for the sources of first heart sound (S 1 ) simulator and 0.21cm mean error for the sources of second heart sound (S 2 ) simulator with Group Delay MUSIC algorithm. The acoustical diagrams created for human subjects show distinct patterns in various phases of the cardiac cycles such as the first and second heart sounds. Moreover, the evaluated source locations for the heart valves are matched with the ones that are obtained via the 4-dimensional (4D) echocardiography applied, to a real human case. Imaging of heart acoustic map presents a new outlook to indicate the acoustic properties of cardiovascular system and disorders of valves and thereby, in the future, could be used as a new diagnostic tool. Copyright © 2017. Published by Elsevier B.V.

Adjustable bias column end joint assembly

NASA Technical Reports Server (NTRS)

Wallsom, Richard E. (Inventor); Bush, Harold G. (Inventor)

1994-01-01

An adjustable mechanical end joint system for connecting structural column elements and eliminating the possibility of free movement between joint halves during loading or vibration has a node joint body having a cylindrical engaging end and a column end body having a cylindrical engaging end. The column end joint body has a compressible preload mechanism and plunger means housed therein. The compressible preload mechanism may be adjusted from the exterior of the column end joint body through a port.

Arch structure is associated with unique joint work, relative joint contributions and stiffness during landing.

PubMed

Powell, Douglas W; Queen, Robin M; Williams, D S Blaise

2016-10-01

To examine lower extremity joint contributions to a landing task in high-(HA) and low-arched (LA) female athletes by quantifying vertical stiffness, joint work and relative joint contributions to landing. Twenty healthy female recreational athletes (10 HA and 10 LA) performed five barefoot drop landings from a height of 30cm. Three-dimensional kinematics (240Hz) and ground reaction forces (960Hz) were recorded simultaneously. Vertical stiffness, joint work values and relative joint work values were calculated using Visual 3D and MatLab. HA athletes had significantly greater vertical stiffness compared to LA athletes (p=0.013). Though no differences in ankle joint work were observed (p=0.252), HA athletes had smaller magnitudes of knee (p=0.046), hip (p=0.019) and total lower extremity joint work values (p=0.016) compared to LA athletes. HA athletes had greater relative contributions of the ankle (p=0.032) and smaller relative contributions of the hip (p=0.049) compared to LA athletes. No differences in relative contributions of the knee were observed (p=0.255). These findings demonstrate that aberrant foot structure is associated with unique contributions of lower extremity joints to load attenuation during landing. These data may provide insight into the unique injury mechanisms associated with arch height in female athletes. Copyright © 2016 Elsevier B.V. All rights reserved.

Dissimilar metals joint evaluation

NASA Technical Reports Server (NTRS)

Wakefield, M. E.; Apodaca, L. E.

1974-01-01

Dissimilar metals tubular joints between 2219-T851 aluminum alloy and 304L stainless steel were fabricated and tested to evaluate bonding processes. Joints were fabricated by four processes: (1) inertia (friction) weldings, where the metals are spun and forced together to create the weld; (2) explosive welding, where the metals are impacted together at high velocity; (3) co-extrusion, where the metals are extruded in contact at high temperature to promote diffusion; and (4) swaging, where residual stresses in the metals after a stretching operation maintain forced contact in mutual shear areas. Fifteen joints of each type were prepared and evaluated in a 6.35 cm (2.50 in.) O.D. size, with 0.32 cm (0.13 in.) wall thickness, and 7.6 cm (3.0 in) total length. The joints were tested to evaluate their ability to withstand pressure cycle, thermal cycle, galvanic corrosion and burst tests. Leakage tests and other non-destructive test techniques were used to evaluate the behavior of the joints, and the microstructure of the bond areas was analyzed.

14 CFR 23.693 - Joints.

Code of Federal Regulations, 2011 CFR

2011-01-01

... STANDARDS: NORMAL, UTILITY, ACROBATIC, AND COMMUTER CATEGORY AIRPLANES Design and Construction Control Systems § 23.693 Joints. Control system joints (in push-pull systems) that are subject to angular motion... factor may be reduced to 2.0 for joints in cable control systems. For ball or roller bearings, the...

14 CFR 23.693 - Joints.

Code of Federal Regulations, 2010 CFR

2010-01-01

... STANDARDS: NORMAL, UTILITY, ACROBATIC, AND COMMUTER CATEGORY AIRPLANES Design and Construction Control Systems § 23.693 Joints. Control system joints (in push-pull systems) that are subject to angular motion... factor may be reduced to 2.0 for joints in cable control systems. For ball or roller bearings, the...

14 CFR 23.693 - Joints.

Code of Federal Regulations, 2012 CFR

2012-01-01

... STANDARDS: NORMAL, UTILITY, ACROBATIC, AND COMMUTER CATEGORY AIRPLANES Design and Construction Control Systems § 23.693 Joints. Control system joints (in push-pull systems) that are subject to angular motion... factor may be reduced to 2.0 for joints in cable control systems. For ball or roller bearings, the...

14 CFR 23.693 - Joints.

Code of Federal Regulations, 2014 CFR

2014-01-01

... STANDARDS: NORMAL, UTILITY, ACROBATIC, AND COMMUTER CATEGORY AIRPLANES Design and Construction Control Systems § 23.693 Joints. Control system joints (in push-pull systems) that are subject to angular motion... factor may be reduced to 2.0 for joints in cable control systems. For ball or roller bearings, the...

Quick-connect threaded attachment joint

NASA Technical Reports Server (NTRS)

Lucy, M. H.; Messick, W. R.; Vasquez, P.

1979-01-01

Joint is self-aligning and tightens with only sixty-five degrees of rotation for quick connects and disconnects. Made of injection-molded plastics or cast or machined aluminum, joint can carry wires, tubes, liquids, or gases. When two parts of joint are brought together, their shapes align them. Small projections on male section and slots on female section further aid alignment; slight rotation of male form engages projections in slots. At this point, threads engage and male section is rotated until joint is fully engaged.

The contribution of quasi-joint stiffness of the ankle joint to gait in patients with hemiparesis.

PubMed

Sekiguchi, Yusuke; Muraki, Takayuki; Kuramatsu, Yuko; Furusawa, Yoshihito; Izumi, Shin-Ichi

2012-06-01

The role of ankle joint stiffness during gait in patients with hemiparesis has not been clarified. The purpose of this study was to determine the contribution of quasi-joint stiffness of the ankle joint to spatiotemporal and kinetic parameters regarding gait in patients with hemiparesis due to brain tumor or stroke and healthy individuals. Spatiotemporal and kinetic parameters regarding gait in twelve patients with hemiparesis due to brain tumor or stroke and nine healthy individuals were measured with a 3-dimensional motion analysis system. Quasi-joint stiffness was calculated from the slope of the linear regression of the moment-angle curve of the ankle joint during the second rocker. There was no significant difference in quasi-joint stiffness among both sides of patients and the right side of controls. Quasi-joint stiffness on the paretic side of patients with hemiparesis positively correlated with maximal ankle power (r=0.73, P<0.01) and gait speed (r=0.66, P<0.05). In contrast, quasi-joint stiffness in controls negatively correlated with maximal ankle power (r=-0.73, P<0.05) and gait speed (r=-0.76, P<0.05). Our findings suggested that ankle power during gait might be generated by increasing quasi-joint stiffness in patients with hemiparesis. In contrast, healthy individuals might decrease quasi-joint stiffness to avoid deceleration of forward tilt of the tibia. Our findings might be useful for selecting treatment for increased ankle stiffness due to contracture and spasticity in patients with hemiparesis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Double slotted socket spherical joint

DOEpatents

Bieg, Lothar F.; Benavides, Gilbert L.

2001-05-22

A new class of spherical joints is disclosed. These spherical joints are capable of extremely large angular displacements (full cone angles in excess of 270.degree.), while exhibiting no singularities or dead spots in their range of motion. These joints can improve or simplify a wide range of mechanical devices.

Clinical synovitis in a particular joint is associated with progression of erosions and joint space narrowing in that same joint, but not in patients initially treated with infliximab.

PubMed

Klarenbeek, N B; Güler-Yüksel, M; van der Heijde, D M F M; Hulsmans, H M J; Kerstens, P J S M; Molenaar, T H E; de Sonnaville, P B J; Huizinga, T W J; Dijkmans, B A C; Allaart, C F

2010-12-01

To assess the relationship between joint tenderness, swelling and joint damage progression in individual joints and to evaluate the influence of treatment on these relationships. First-year data of the Behandel Strategieën (BeSt) study were used, in which patients recently diagnosed as having rheumatoid arthritis (RA) were randomly assigned into four different treatment strategies. Baseline and 1-year x-rays of the hands and feet were assessed using the Sharp-van der Heijde score (SHS). With generalised estimating equations, 3-monthly assessments of tender and swollen joints of year 1 were related to erosion progression, joint space narrowing (JSN) progression and total SHS progression at the individual joint level (definition > 0.5 SHS units) in year 1, corrected for potential confounders and within-patient correlation for multiple joints per patient. During year 1, 59% of all 13 959 joints analysed were ever tender and 45% ever swollen, 2.1% showed erosion progression, 1.9% JSN progression and 3.6% SHS progression. Swelling and tenderness were both independently associated with erosion and JSN progression with comparable OR, although with higher OR in the hands than in the feet. Local swelling and tenderness were not associated with local damage progression in patients initially treated with infliximab. Clinical signs of synovitis are associated with erosion and JSN progression in individual joints after 1 year in RA. A disconnect between synovitis and joint damage progression was observed at joint level in patients who were treated with methotrexate and infliximab as initial treatment, confirming the disconnect between synovitis and the development of joint damage in tumour necrosis factor blockers seen at patient level.

Hip joint replacement - slideshow

MedlinePlus

... this page: //medlineplus.gov/ency/presentations/100006.htm Hip joint replacement - series—Normal anatomy To use the ... to slide 5 out of 5 Overview The hip joint is made up of two major parts: ...

Sacroiliac joint pain - aftercare

MedlinePlus

... this page: //medlineplus.gov/ency/patientinstructions/000610.htm Sacroiliac joint pain - aftercare To use the sharing features on this page, please enable JavaScript. The sacroiliac joint (SIJ) is a term used to describe ...

Metacarpophalangeal joint arthroscopy: indications revisited.

PubMed

Choi, Alexander K Y; Chow, Esther C S; Ho, P C; Chow, Y Y

2011-08-01

Arthroscopic surgery has become the gold standard for the diagnosis and treatment of major joint disorders. With advancement in arthroscopic technique, arthroscopy has become feasible in most human joints, even those as small as the finger joints. The metacarpophalangeal joint (MCPJ) can become spacious with simple traction, the intra-articular anatomy is simple, and its major structures can be easily visualized and identified. However, MCPJ arthroscopy has never been popular. This article describes our experience with MCPJ arthroscopy and seeks to establish its role in clinical practice. Copyright © 2011 Elsevier Inc. All rights reserved.

Joint Attention in Autism: Teaching Smiling Coordinated with Gaze to Respond to Joint Attention Bids

ERIC Educational Resources Information Center

Krstovska-Guerrero, Ivana; Jones, Emily A.

2013-01-01

Children with autism demonstrate early deficits in joint attention and expressions of affect. Interventions to teach joint attention have addressed gaze behavior, gestures, and vocalizations, but have not specifically taught an expression of positive affect such as smiling that tends to occur during joint attention interactions. Intervention was…

Sacroiliac joint tuberculosis: surgical management by posterior open-window focal debridement and joint fusion.

PubMed

Zhu, Guo; Jiang, Li-Yuan; Yi, Zhang; Ping, Li; Duan, Chun-Yue; Yong, Cao; Liu, Jin-Yang; Hu, Jian-Zhong

2017-11-29

Sacroiliac joint tuberculosis(SJT) is relatively uncommon, but it may cause severe sacroiliac joint destruction and functional disorder. Few studies in the literature have been presented on SJT, reports of surgical treatment for SJT are even fewer. In this study, we retrospectively reviewed surgical management of patients with severe SJT of 3 different types and proposed to reveal the clinical manifestations and features and aim to determine the efficiency and security of such surgical treatment. We reviewed 17 patients with severe SJT of 3 different types who underwent posterior open-window focal debridement and bone graft for joint fusion. Among them,five patients with anterior sacral abscess had anterior abscess curettage before debridement. Two patients with lumbar vertebral tuberculosis received one-stage posterior tuberculous debridement, interbody fusion and instrumentation. Follow-up was performed 36 months (26 to 45 months) using the following parameters: erythrocyte sedimentation rate(ESR), status of joint bony fusion on CT scan, visual analogue scale (VAS) and the Oswestry Disability Index (ODI). Buttock pain and low back pain were progressively relieved with time. 6 months later, pain was not obvious, and ESR resumed to normal levels within 3 months. Solid fusion of the sacroiliac joint occurred within 12 months in all cases. No complications or recurrence occurred. At final follow-up, all patients had no pain or only minimal discomfort over the affected joint and almost complete functional recovery. Posterior open-window focal debridement and joint fusion is an efficient and secure surgical method to treat severe SJT. If there is an abscess in the front of the sacroiliac joint, anterior abscess curettage should be performed as a supplement.

Jointness for the Rest of Us: Reforming Joint Professional Development

DTIC Science & Technology

2016-06-10

where service capabilities are combined to maximize effectiveness while minimizing vulnerabilities. However, despite the passage of thirty years ...staff of the Joint Advance Warfighting School and the Joint Forces Staff College for their support during the academic year . Special thanks to my...seminar faculty Colonel Chris Rogers, Dr. Mike Pavlec, and Captain Miguel “Boo” Peko for the lessons and laughs that have made this year so enjoyable

12 CFR 347.107 - Joint ventures.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Joint ventures. 347.107 Section 347.107 Banks... INTERNATIONAL BANKING § 347.107 Joint ventures. (a) Joint ventures. If a bank, directly or indirectly, acquires or holds an equity interest in a foreign organization that is a joint venture, and the bank or its...

About the Joint Chiefs of Staff

Science.gov Websites

JCS: Search Home Media News Photos Videos Publications About The Joint Staff Chairman Vice Chairman J8 | Force Structure, Resources & Assessment Contact Joint Staff Structure Home : About About the Joint Chiefs of Staff Download the CJCS Historic Guide The Joint Chiefs of Staff consist of the Chairman

26 CFR 1.6015-1 - Relief from joint and several liability on a joint return.

Code of Federal Regulations, 2010 CFR

2010-04-01

... they claim losses attributable to H's limited partnership interest in Partnership A. In January 2006... 26 Internal Revenue 13 2010-04-01 2010-04-01 false Relief from joint and several liability on a... joint and several liability on a joint return. (a) In general. (1) An individual who qualifies and...

Large displacement spherical joint

DOEpatents

Bieg, Lothar F.; Benavides, Gilbert L.

2002-01-01

A new class of spherical joints has a very large accessible full cone angle, a property which is beneficial for a wide range of applications. Despite the large cone angles, these joints move freely without singularities.

Does Success Of Arthroscopic Laser Surgery In The Knee Joint Warrant Its Extension To "Non-Knee" Joints?

NASA Astrophysics Data System (ADS)

Smith, Chadwick F.; Johansen, W. Edward; Vangness, C. Thomas; Yamaguchi, Ken; McEleney, Emmett T.; Bales, Peter

1987-03-01

One of the authors has performed 162 arthroscopic laser surgeries in the knee joint without any major complication. Other investigators have recently proposed diagnostic arthroscopy and arthroscopic surgery for "non-knee" joints. The authors have proposed that arthroscopic laser surgery he extended to "non-knee" joints. The authors have performed arthroscopic laser surgery on "non-knee" joints of twelve cadavers. One of the authors have performed one successful arthroscopic surgery on a shoulder joint with only a minor, transient complication of subcutaneous emphysema. Is laser arthroscopic surgery safe and effective in "non-knee" joints? The evolving answer appears to be a qualified "Yes," which needs to be verified by a multicenter trial.

Estimation of Time-Varying, Intrinsic and Reflex Dynamic Joint Stiffness during Movement. Application to the Ankle Joint

PubMed Central

Guarín, Diego L.; Kearney, Robert E.

2017-01-01

Dynamic joint stiffness determines the relation between joint position and torque, and plays a vital role in the control of posture and movement. Dynamic joint stiffness can be quantified during quasi-stationary conditions using disturbance experiments, where small position perturbations are applied to the joint and the torque response is recorded. Dynamic joint stiffness is composed of intrinsic and reflex mechanisms that act and change together, so that nonlinear, mathematical models and specialized system identification techniques are necessary to estimate their relative contributions to overall joint stiffness. Quasi-stationary experiments have demonstrated that dynamic joint stiffness is heavily modulated by joint position and voluntary torque. Consequently, during movement, when joint position and torque change rapidly, dynamic joint stiffness will be Time-Varying (TV). This paper introduces a new method to quantify the TV intrinsic and reflex components of dynamic joint stiffness during movement. The algorithm combines ensemble and deterministic approaches for estimation of TV systems; and uses a TV, parallel-cascade, nonlinear system identification technique to separate overall dynamic joint stiffness into intrinsic and reflex components from position and torque records. Simulation studies of a stiffness model, whose parameters varied with time as is expected during walking, demonstrated that the new algorithm accurately tracked the changes in dynamic joint stiffness using as little as 40 gait cycles. The method was also used to estimate the intrinsic and reflex dynamic ankle stiffness from an experiment with a healthy subject during which ankle movements were imposed while the subject maintained a constant muscle contraction. The method identified TV stiffness model parameters that predicted the measured torque very well, accounting for more than 95% of its variance. Moreover, both intrinsic and reflex dynamic stiffness were heavily modulated through the

Hip and knee joints are more stabilized than driven during the stance phase of gait: an analysis of the 3D angle between joint moment and joint angular velocity.

PubMed

Dumas, R; Cheze, L

2008-08-01

Joint power is commonly used in orthopaedics, ergonomics or sports analysis but its clinical interpretation remains controversial. Some basic principles on muscle actions and energy transfer have been proposed in 2D. The decomposition of power on 3 axes, although questionable, allows the same analysis in 3D. However, these basic principles have been widely criticized, mainly because bi-articular muscles must be considered. This requires a more complex computation in order to determine how the individual muscle force contributes to drive the joint. Conversely, with simple 3D inverse dynamics, the analysis of both joint moment and angular velocity directions is essential to clarify when the joint moment can contribute or not to drive the joint. The present study evaluates the 3D angle between the joint moment and the joint angular velocity and investigates when the hip, knee and ankle joints are predominantly driven (angle close to 0 degrees and 180 degrees ) or stabilized (angle close to 90 degrees ) during gait. The 3D angle curves show that the three joints are never fully but only partially driven and that the hip and knee joints are mainly stabilized during the stance phase. The notion of stabilization should be further investigated, especially for subjects with motion disorders or prostheses.

Swivel Joint For Liquid Nitrogen

NASA Technical Reports Server (NTRS)

Milner, James F.

1988-01-01

Swivel joint allows liquid-nitrogen pipe to rotate through angle of 100 degree with respect to mating pipe. Functions without cracking hard foam insulation on lines. Pipe joint rotates on disks so mechanical stress not transmitted to thick insulation on pipes. Inner disks ride on fixed outer disks. Disks help to seal pressurized liquid nitrogen flowing through joint.

The Standard Joint Unit.

PubMed

Casajuana Kögel, Cristina; Balcells-Olivero, María Mercedes; López-Pelayo, Hugo; Miquel, Laia; Teixidó, Lídia; Colom, Joan; Nutt, David John; Rehm, Jürgen; Gual, Antoni

2017-07-01

Reliable data on cannabis quantities is required to improve assessment of cannabis consumption for epidemiological analysis and clinical assessment, consequently a Standard Joint Unit (SJU) based on quantity of 9-Tetrahydrocannabinol (9-THC) has been established. Naturalistic study of a convenience sample recruited from February 2015-June 2016 in universities, leisure spaces, mental health services and cannabis clubs in Barcelona. Adults, reporting cannabis use in the last 60 days, without cognitive impairment or language barriers, answered a questionnaire on cannabis use and were asked to donate a joint to further determine their 9-THC and Cannabidiol (CBD) content. 492 participants donated 315 valid joints. Donators were on average 29 years old, mostly men (77%), single (75%), with at least secondary studies (73%) and in active employment (63%). Marijuana joints (N=232) contained a median of 6.56mg of 9-THC (Interquartile range-IQR=10,22) and 0.02mg of CBD (IQR=0.02); hashish joints (N=83) a median of 7.94mg of 9-THC (IQR=10,61) and 3.24mg of CBD (IQR=3.21). Participants rolled 4 joints per gram of cannabis and paid 5€ per gram (median values). Consistent 9-THC-content in joints lead to a SJU of 7mg of 9-THC, the integer number closest to the median values shared by both cannabis types. Independently if marijuana or hashish, 1 SJU = 1 joint = 0.25 g of cannabis = 7 mg of 9-THC. For CBD, only hashish SJU contained relevant levels. Similarly to the Standard Drink Unit for alcohol, the SJU is useful for clinical, epidemiological and research purposes. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

NASA Astrophysics Data System (ADS)

Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu

2018-02-01

A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.

Temporo mandibular joint ankylosis.

PubMed

Vasconcelos, Belmiro Cavalcanti do Egito; Porto, Gabriela Granja; Bessa-Nogueira, Ricardo Viana

2008-01-01

Ankylosis may be defined as joint surfaces fusion. The treatment of temporomandibular joint ankylosis poses a significant challenge because of the high recurrence rate. The aim of this study is to report six cases treated by joint reconstruction, evaluate the results of these surgeries and review the literature. The sample in this retrospective study was obtained from the records of the university hospital, patients who had to undergo ankylosis treatment by alloplastic or autogenous graft between March 2001 and October 2005. Pre - and post-operative assessment included a throughout history and physical examination to determine the cause of ankylosis, the Maximum mouth opening (MMO), etiology and type of ankylosis, recurrence rate and presence of facial nerve paralysis. The mean MMO in the pre-operative period was 9.6 mm (0 mm to 17 mm) and in the post-operative period it was of 31.33 mm (14 mm to 41 mm), there was no facial nerve paralysis and there was recurrence in just one case. The joint reconstruction with alloplastic or autogenous grafts for the ankylosis treatment proved to be efficient in relation to the post-operative MMO, recurrence and joint function.

Minimally invasive arthrodesis for chronic sacroiliac joint dysfunction using the SImmetry SI Joint Fusion system.

PubMed

Miller, Larry E; Block, Jon E

2014-01-01

Chronic sacroiliac (SI) joint-related low back pain (LBP) is a common, yet under-diagnosed and undertreated condition due to difficulties in accurate diagnosis and highly variable treatment practices. In patients with debilitating SI-related LBP for at least 6 months duration who have failed conservative management, arthrodesis is a viable option. The SImmetry(®) SI Joint Fusion System is a novel therapy for SI joint fusion, not just fixation, which utilizes a minimally invasive surgical approach, instrumented fixation for immediate stability, and joint preparation with bone grafting for a secure construct in the long term. The purpose of this report is to describe the minimally invasive SI Joint Fusion System, including patient selection criteria, implant characteristics, surgical technique, postoperative recovery, and biomechanical testing results. Advantages and limitations of this system will be discussed.

Unloading joints to treat osteoarthritis, including joint distraction.

PubMed

Lafeber, Floris P J G; Intema, Femke; Van Roermund, Peter M; Marijnissen, Anne C A

2006-09-01

Patients are increasingly becoming interested in nonpharmacologic approaches to manage their osteoarthritis. This review examines the recent literature on the potential beneficial effects of unloading joints in the treatment of osteoarthritis, with a focus on joint distraction. Mechanical factors are involved in the development and progression of osteoarthritis. If "loading" is a major cause in development and progression of osteoarthritis, then "unloading" may be able to prevent progression. There is evidence that unloading may be effective in reducing pain and slowing down structural damage. This review describes unloading by footwear and bracing (nonsurgical), unloading by osteotomy (surgical), and has a focus on unloading by joint distraction. Excellent reviews in all these three fields have been published over the past few years. Recent studies argue for the usefulness of a biomechanical approach to improve function and possibly reduce disease progression in osteoarthritis. To improve patient function and possibly reduce disease progression, a biomechanical approach should be considered in treating patients with osteoarthritis. Further research (appropriate high-quality clinical trials) and analysis (clinical as well as preclinical and fundamental) are still necessary, however, to understand, validate, and refine the different approaches of unloading to treat osteoarthritis.

Joint design of QC-LDPC codes for coded cooperation system with joint iterative decoding

NASA Astrophysics Data System (ADS)

Zhang, Shunwai; Yang, Fengfan; Tang, Lei; Ejaz, Saqib; Luo, Lin; Maharaj, B. T.

2016-03-01

In this paper, we investigate joint design of quasi-cyclic low-density-parity-check (QC-LDPC) codes for coded cooperation system with joint iterative decoding in the destination. First, QC-LDPC codes based on the base matrix and exponent matrix are introduced, and then we describe two types of girth-4 cycles in QC-LDPC codes employed by the source and relay. In the equivalent parity-check matrix corresponding to the jointly designed QC-LDPC codes employed by the source and relay, all girth-4 cycles including both type I and type II are cancelled. Theoretical analysis and numerical simulations show that the jointly designed QC-LDPC coded cooperation well combines cooperation gain and channel coding gain, and outperforms the coded non-cooperation under the same conditions. Furthermore, the bit error rate performance of the coded cooperation employing jointly designed QC-LDPC codes is better than those of random LDPC codes and separately designed QC-LDPC codes over AWGN channels.

The joint venture alternative to mergers.

PubMed

Enders, R J

1995-02-01

However, while a joint venture may be "safe" from antitrust challenge, it is not without some practical difficulties, especially with respect to consolidating services at one location or jointly offering services provided at multiple facilities. These practical concerns include: 1. Who will exercise operational management of the joint venture? 2. How will the joint venture deal with different pricing for services that will be provided at multiple locations? 3. What criteria will be used to decide the location at which consolidated tertiary services will be offered? 4. In what circumstances can the joint venture be unwound, either in its entirety or as to discrete functions? When clinical services have been consolidated at one location, there is an appropriate concern by the other hospital that it will be unable to provide or re-enter the market for those services if the joint venture dissolves. These operational concerns, of course, are not addressed in the Consent Decree. Thus, even if a joint venture relationship survives antitrust scrutiny, the parties must still negotiate and resolve these operational issues in order for the joint venture to be viable.

Innervation of the Anterior Sacroiliac Joint.

PubMed

Cox, Marcus; Ng, Garrett; Mashriqi, Faizullah; Iwanaga, Joe; Alonso, Fernando; Tubbs, Kevin; Loukas, Marios; Oskouian, Rod J; Tubbs, R Shane

2017-11-01

Sacroiliac joint pain can be disabling and recalcitrant to medical therapy. The innervation of this joint is poorly understood, especially its anterior aspect. Therefore, the present cadaveric study was performed to better elucidate this anatomy. Twenty-four cadaveric sides underwent dissection of the anterior sacroiliac joint, with special attention given to any branches from regional nerves to this joint. No femoral, obturator, or lumbosacral trunk branches destined to the anterior sacroiliac joint were identified in the 24 sides. In 20 sides, one or two small branches (less than 0.5 mm in diameter) were found to arise from the L4 ventral ramus (10%), the L5 ventral ramus (80%), or simultaneously from both the L4 and L5 ventral rami (10%). The length of the branches ranged from 5 to 31 mm (mean, 14 mm). All these branches arose from the posterior part of the nerves and traveled to the anterior surface of the sacroiliac joint. No statistical significance was found between sides or sexes. An improved knowledge of the innervation of the anterior sacroiliac joint might decrease suffering in patients with chronic sacroiliac joint pain. Copyright © 2017 Elsevier Inc. All rights reserved.

Bolted joints in graphite-epoxy composites

NASA Technical Reports Server (NTRS)

Hart-Smith, L. J.

1976-01-01

All-graphite/epoxy laminates and hybrid graphite-glass/epoxy laminates were tested. The tests encompassed a range of geometries for each laminate pattern to cover the three basic failure modes - net section tension failure through the bolt hole, bearing and shearout. Static tensile and compressive loads were applied. A constant bolt diameter of 6.35 mm (0.25 in.) was used in the tests. The interaction of stress concentrations associated with multi-row bolted joints was investigated by testing single- and double-row bolted joints and open-hole specimens in tension. For tension loading, linear interaction was found to exist between the bearing stress reacted at a given bolt hole and the remaining tension stress running by that hole to be reacted elsewhere. The interaction under compressive loading was found to be non-linear. Comparative tests were run using single-lap bolted joints and double-lap joints with pin connection. Both of these joint types exhibited lower strengths than were demonstrated by the corresponding double-lap joints. The analysis methods developed here for single bolt joints are shown to be capable of predicting the behavior of multi-row joints.

Space Station alpha joint bearing

NASA Technical Reports Server (NTRS)

Everman, Michael R.; Jones, P. Alan; Spencer, Porter A.

1987-01-01

Perhaps the most critical structural system aboard the Space Station is the Solar Alpha Rotary Joint which helps align the power generation system with the sun. The joint must provide structural support and controlled rotation to the outboard transverse booms as well as power and data transfer across the joint. The Solar Alpha Rotary Joint is composed of two transition sections and an integral, large diameter bearing. Alpha joint bearing design presents a particularly interesting problem because of its large size and need for high reliability, stiffness, and on orbit maintability. The discrete roller bearing developed is a novel refinement to cam follower technology. It offers thermal compensation and ease of on-orbit maintenance that are not found in conventional rolling element bearings. How the bearing design evolved is summarized. Driving requirements are reviewed, alternative concepts assessed, and the selected design is described.

[Application of joint reconstruction with autogenous coronoid process graft to treat temporomandibular joint ankylosis].

PubMed

Xie, Qing-tiao; Huang, Xuan-ping; Jiang, Xian-fang; Yang, Yuan-yuan; Li, Hua; Lin, Xi

2013-08-01

To evaluate the clinical effect of joint reconstruction by using autogenous coronoid process graft to treat temporomandibular joint(TMJ) ankylosis. Nine cases of TMJ ankylosis from September 2008 to September 2010 were surgically treated by joint reconstruction with autogenous coronoid process graft, using autogenous articular disc or prosthodontic membrane as interpositional material. Mouth opening, occlusion and cone beam CT(CBCT) were used for evaluation before and after surgery. Satisfactory mouth opening was achieved in all patients and no one got occlusal changes or reankylosis during follow-up. CBCT showed that coronoid process graft reached bone union with the ramus and turned to be round. It is effective to cure TMJ ankylosis through joint reconstruction with autogenous coronoid process graft.

Phase 1 Program Joint Report

NASA Technical Reports Server (NTRS)

Nield, George C. (Editor); Vorobiev, Pavel Mikhailovich (Editor)

1999-01-01

This report consists of inputs from each of the Phase I Program Joint Working Groups. The Working Groups were tasked to describe the organizational structure and work processes that they used during the program, joint accomplishments, lessons learned, and applications to the International Space Station Program. This report is a top-level joint reference document that contains information of interest to both countries.

Self-Alining Quick-Connect Joint

NASA Technical Reports Server (NTRS)

Lucy, M. H.

1983-01-01

Quick connect tapered joint used with minimum manipulation and force. Split ring retainer holds locking ring in place. Minimal force required to position male in female joint, at which time split-ring retainers are triggered to release split locking rings. Originally developed to assemble large space structures, joint is simple, compact, strong, lightweight, self alining, and has no loose parts.

Feature-extracted joint transform correlation.

PubMed

Alam, M S

1995-12-10

A new technique for real-time optical character recognition that uses a joint transform correlator is proposed. This technique employs feature-extracted patterns for the reference image to detect a wide range of characters in one step. The proposed technique significantly enhances the processing speed when compared with the presently available joint transform correlator architectures and shows feasibility for multichannel joint transform correlation.

Cancer risk among patients with finger and hand joint and temporo-mandibular joint prostheses in Denmark.

PubMed

Fryzek, J P; Mellemkjaer, L; McLaughlin, J K; Blot, W J; Olsen, J H

1999-05-31

The use of artificial joint implants has risen greatly over the past years. However, few investigations of the cancer risk associated with implants have been performed. We investigated cancer risk in patients with finger and hand joint and temporo-mandibular (TMJ) joint implants. A nationwide cohort in Denmark of patients with finger and hand joint prostheses (n = 858) or TMJ implants (n = 389) was followed from January 1, 1977, to December 31, 1995, to evaluate any potential cancer risks subsequent to receiving these implants. Standardized incidence ratios (SIRs) for all cancers were 1.0 (95% CI = 0.8-1.2) for the finger and hand joint cohort and 1.1 (95% CI = 0.8-1.7) for the TMJ cohort. A significant risk for non-Hodgkin's lymphoma was found in the finger and hand joint cohort (SIR = 3.8, 95% CI = 1.5-7.8). When the finger and hand joint cohort was stratified by diagnosis of rheumatoid arthritis, the excess risk was seen only in the group with rheumatoid arthritis. This is consistent with past studies, which have found an association between rheumatoid arthritis and non-Hodgkin's lymphoma. Our results provide evidence that the cancer risk for patients with finger and hand joint prostheses and TMJ implants is similar to that for the general population.

JointMMCC: Joint Maximum-Margin Classification and Clustering of Imaging Data

PubMed Central

Filipovych, Roman; Resnick, Susan M.; Davatzikos, Christos

2012-01-01

A number of conditions are characterized by pathologies that form continuous or nearly-continuous spectra spanning from the absence of pathology to very pronounced pathological changes (e.g., normal aging, Mild Cognitive Impairment, Alzheimer's). Moreover, diseases are often highly heterogeneous with a number of diagnostic subcategories or subconditions lying within the spectra (e.g., Autism Spectrum Disorder, schizophrenia). Discovering coherent subpopulations of subjects within the spectrum of pathological changes may further our understanding of diseases, and potentially identify subconditions that require alternative or modified treatment options. In this paper, we propose an approach that aims at identifying coherent subpopulations with respect to the underlying MRI in the scenario where the condition is heterogeneous and pathological changes form a continuous spectrum. We describe a Joint Maximum-Margin Classification and Clustering (JointMMCC) approach that jointly detects the pathologic population via semi-supervised classification, as well as disentangles heterogeneity of the pathological cohort by solving a clustering subproblem. We propose an efficient solution to the non-convex optimization problem associated with JointMMCC. We apply our proposed approach to an MRI study of aging, and identify coherent subpopulations (i.e., clusters) of cognitively less stable adults. PMID:22328179

Minimally invasive arthrodesis for chronic sacroiliac joint dysfunction using the SImmetry SI Joint Fusion system

PubMed Central

Miller, Larry E; Block, Jon E

2014-01-01

Chronic sacroiliac (SI) joint-related low back pain (LBP) is a common, yet under-diagnosed and undertreated condition due to difficulties in accurate diagnosis and highly variable treatment practices. In patients with debilitating SI-related LBP for at least 6 months duration who have failed conservative management, arthrodesis is a viable option. The SImmetry® SI Joint Fusion System is a novel therapy for SI joint fusion, not just fixation, which utilizes a minimally invasive surgical approach, instrumented fixation for immediate stability, and joint preparation with bone grafting for a secure construct in the long term. The purpose of this report is to describe the minimally invasive SI Joint Fusion System, including patient selection criteria, implant characteristics, surgical technique, postoperative recovery, and biomechanical testing results. Advantages and limitations of this system will be discussed. PMID:24851059

HMA Longitudinal Joint Evaluation and Construction

DOT National Transportation Integrated Search

2011-02-01

Longitudinal joint quality is essential to the successful performance of asphalt pavements. A number of states have begun to implement longitudinal joint specifications, and most are based on determinations of density. However, distress at the joint ...

The volume of the human knee joint.

PubMed

Matziolis, Georg; Roehner, Eric; Windisch, Christoph; Wagner, Andreas

2015-10-01

Despite its clinical relevance, particularly in septic knee surgery, the volume of the human knee joint has not been established to date. Therefore, the objective of this study was to determine knee joint volume and whether or not it is dependent on sex or body height. Sixty-one consecutive patients (joints) who were due to undergo endoprosthetic joint replacement were enrolled in this prospective study. During the operation, the joint volume was determined by injecting saline solution until a pressure of 200 mmHg was achieved in the joint. The average volume of all knee joints was 131 ± 53 (40-290) ml. The volume was not found to be dependent on sex, but it was dependent on the patients' height (R = 0.312, p = 0.014). This enabled an estimation of the joint volume according to V = 1.6 height - 135. The considerable inter-individual variance of the knee joint volume would suggest that it should be determined or at least estimated according to body height if the joint volume has consequences for the diagnostics or therapy of knee disorders.

Method of forming a joint

DOEpatents

Butt, Darryl Paul; Cutler, Raymond Ashton; Rynders, Steven Walton; Carolan, Michael Francis

2006-08-22

A method of joining at least two sintered bodies to form a composite structure, including providing a first multicomponent metallic oxide having a perovskitic or fluorite crystal structure; providing a second sintered body including a second multicomponent metallic oxide having a crystal structure of the same type as the first; and providing at an interface a joint material containing at least one metal oxide containing at least one metal identically contained in at least one of the first and second multicomponent metallic oxides. The joint material is free of cations of Si, Ge, Sn, Pb, P and Te and has a melting point below the sintering temperatures of both sintered bodies. The joint material is heated to a temperature above the melting point of the metal oxide(s) and below the sintering temperatures of the sintered bodies to form the joint. Structures containing such joints are also disclosed.

RSRM Nozzle-to-Case Joint J-leg Development

NASA Technical Reports Server (NTRS)

Albrechtsen, Kevin U.; Eddy, Norman F.; Ewing, Mark E.; McGuire, John R.

2003-01-01

Since the beginning of the Space Shuttle Reusable Solid Rocket Motor (RSRM) program, nozzle-to-case joint polysulfide adhesive gas paths have occurred on several flight motors. These gas paths have allowed hot motor gases to reach the wiper O-ring. Even though these motors continue to fly safely with this condition, a desire was to reduce such occurrences. The RSRM currently uses a J-leg joint configuration on case field joints and igniter inner and outer joints. The J-leg joint configuration has been successfully demonstrated on numerous RSRM flight and static test motors, eliminating hot gas intrusion to the critical O-ring seals on these joints. Using the proven technology demonstrated on the case field joints and igniter joints, a nozzle-to-case joint J-leg design was developed for implementation on RSRM flight motors. This configuration provides an interference fit with nozzle fixed housing phenolics at assembly, with a series of pressurization gaps incorporated outboard of the joint mating surface to aid in joint pressurization and to eliminate any circumferential flow in this region. The joint insulation is bonded to the nozzle phenolics using the same pressure sensitive adhesive used in the case field joints and igniter joints. An enhancement to the nozzle-to-case joint J-leg configuration is the implementation of a carbon rope thermal barrier. The thermal barrier is located downstream of the joint bondline and is positioned within the joint in a manner where any hot gas intrusion into the joint passes through the thermal barrier, reducing gas temperatures to a level that would not affect O-rings downstream of the thermal barrier. This paper discusses the processes used in reaching a final nozzle-to-case joint J-leg design, provides structural and thermal results in support of the design, and identifies fabrication techniques and demonstrations used in arriving at the final configuration.

Rotary Joints With Electrical Connections

NASA Technical Reports Server (NTRS)

Osborn, F. W.

1986-01-01

Power and data transmitted on many channels. Two different rotary joints equipped with electrical connections between rotating and stationary parts. One joint transmits axial thrust and serves as interface between spinning and nonspinning parts of Galileo spacecraft. Other is scanning (limitedrotation) joint that aims scientific instruments from nonspinning part. Selected features of both useful to designers of robots, advanced production equipment, and remotely controlled instruments.

Prosthetic Joint Infections

PubMed Central

Aslam, Saima; Darouiche, Rabih O.

2012-01-01

Prosthetic joint infections represent a major therapeutic challenge for both healthcare providers and patients. This paper reviews the predisposing factors, pathogenesis, microbiology, diagnosis, treatment and prophylaxis of prosthetic joint infection. The most optimal management strategy should be identified based on a number of considerations including type and duration of infection, antimicrobial susceptibility of the infecting pathogen, condition of infected tissues and bone stock, patient wishes and functional status. PMID:22847032

Common Bolted Joint Analysis Tool

NASA Technical Reports Server (NTRS)

Imtiaz, Kauser

2011-01-01

Common Bolted Joint Analysis Tool (comBAT) is an Excel/VB-based bolted joint analysis/optimization program that lays out a systematic foundation for an inexperienced or seasoned analyst to determine fastener size, material, and assembly torque for a given design. Analysts are able to perform numerous what-if scenarios within minutes to arrive at an optimal solution. The program evaluates input design parameters, performs joint assembly checks, and steps through numerous calculations to arrive at several key margins of safety for each member in a joint. It also checks for joint gapping, provides fatigue calculations, and generates joint diagrams for a visual reference. Optimum fastener size and material, as well as correct torque, can then be provided. Analysis methodology, equations, and guidelines are provided throughout the solution sequence so that this program does not become a "black box:" for the analyst. There are built-in databases that reduce the legwork required by the analyst. Each step is clearly identified and results are provided in number format, as well as color-coded spelled-out words to draw user attention. The three key features of the software are robust technical content, innovative and user friendly I/O, and a large database. The program addresses every aspect of bolted joint analysis and proves to be an instructional tool at the same time. It saves analysis time, has intelligent messaging features, and catches operator errors in real time.

Adhesive-bonded scarf and stepped-lap joints

NASA Technical Reports Server (NTRS)

Hart-Smith, L. J.

1973-01-01

Continuum mechanics solutions are derived for the static load-carrying capacity of scarf and stepped-lap adhesive-bonded joints. The analyses account for adhesive plasticity and adherend stiffness imbalance and thermal mismatch. The scarf joint solutions include a simple algebraic formula which serves as a close lower bound, within a small fraction of a per cent of the true answer for most practical geometries and materials. Digital computer programs were developed and, for the stepped-lap joints, the critical adherend and adhesive stresses are computed for each step. The scarf joint solutions exhibit grossly different behavior from that for double-lap joints for long overlaps inasmuch as that the potential bond shear strength continues to increase with indefinitely long overlaps on the scarf joints. The stepped-lap joint solutions exhibit some characteristics of both the scarf and double-lap joints. The stepped-lap computer program handles arbitrary (different) step lengths and thickness and the solutions obtained have clarified potentially weak design details and the remedies. The program has been used effectively to optimize the joint proportions.

Dynamic Analyses Including Joints Of Truss Structures

NASA Technical Reports Server (NTRS)

Belvin, W. Keith

1991-01-01

Method for mathematically modeling joints to assess influences of joints on dynamic response of truss structures developed in study. Only structures with low-frequency oscillations considered; only Coulomb friction and viscous damping included in analysis. Focus of effort to obtain finite-element mathematical models of joints exhibiting load-vs.-deflection behavior similar to measured load-vs.-deflection behavior of real joints. Experiments performed to determine stiffness and damping nonlinearities typical of joint hardware. Algorithm for computing coefficients of analytical joint models based on test data developed to enable study of linear and nonlinear effects of joints on global structural response. Besides intended application to large space structures, applications in nonaerospace community include ground-based antennas and earthquake-resistant steel-framed buildings.

Joint contact forces can be reduced by improving joint moment symmetry in below-knee amputee gait simulations.

PubMed

Koelewijn, Anne D; van den Bogert, Antonie J

2016-09-01

Despite having a fully functional knee and hip in both legs, asymmetries in joint moments of the knee and hip are often seen in gait of persons with a unilateral transtibial amputation (TTA), possibly resulting in excessive joint loading. We hypothesize that persons with a TTA can walk with more symmetric joint moments at the cost of increased effort or abnormal kinematics. The hypothesis was tested using predictive simulations of gait. Open loop controls of one gait cycle were found by solving an optimization problem that minimizes a combination of walking effort and tracking error in joint angles, ground reaction force and gait cycle duration. A second objective was added to penalize joint moment asymmetry, creating a multi-objective optimization problem. A Pareto front was constructed by changing the weights of the objectives and three solutions were analyzed to study the effect of increasing joint moment symmetry. When the optimization placed more weight on moment symmetry, walking effort increased and kinematics became less normal, confirming the hypothesis. TTA gait improved with a moderate increase in joint moment symmetry. At a small cost of effort and abnormal kinematics, the peak hip extension moment in the intact leg was decreased significantly, and so was the joint contact force in the knee and hip. Additional symmetry required a significant increase in walking effort and the joint contact forces in both hips became significantly higher than in able-bodied gait. Copyright © 2016 Elsevier B.V. All rights reserved.

77 FR 39560 - International Joint Commission

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-03

... DEPARTMENT OF STATE [Public Notice 7945] International Joint Commission International Joint Commission Invites Public Comment on Upper Great Lakes Report The International Joint Commission (IJC) announced today that it is inviting public comment on the final report of its International Upper Great...

Joint torques in a freely walking insect reveal distinct functions of leg joints in propulsion and posture control

PubMed Central

2016-01-01

Determining the mechanical output of limb joints is critical for understanding the control of complex motor behaviours such as walking. In the case of insect walking, the neural infrastructure for single-joint control is well described. However, a detailed description of the motor output in form of time-varying joint torques is lacking. Here, we determine joint torques in the stick insect to identify leg joint function in the control of body height and propulsion. Torques were determined by measuring whole-body kinematics and ground reaction forces in freely walking animals. We demonstrate that despite strong differences in morphology and posture, stick insects show a functional division of joints similar to other insect model systems. Propulsion was generated by strong depression torques about the coxa–trochanter joint, not by retraction or flexion/extension torques. Torques about the respective thorax–coxa and femur–tibia joints were often directed opposite to fore–aft forces and joint movements. This suggests a posture-dependent mechanism that counteracts collapse of the leg under body load and directs the resultant force vector such that strong depression torques can control both body height and propulsion. Our findings parallel propulsive mechanisms described in other walking, jumping and flying insects, and challenge current control models of insect walking. PMID:26791608

Early Osteoarthritis of the Trapeziometacarpal Joint Is Not Associated With Joint Instability during Typical Isometric Loading

PubMed Central

Halilaj, Eni; Moore, Douglas C.; Patel, Tarpit K.; Ladd, Amy L.; Weiss, Arnold-Peter C.; Crisco, Joseph J.

2015-01-01

The saddle-shaped trapeziometacarpal (TMC) joint contributes importantly to the function of the human thumb. A balance between mobility and stability is essential in this joint, which experiences high loads and is prone to osteoarthritis (OA). Since instability is considered a risk factor for TMC OA, we assessed TMC joint instability during the execution of three isometric functional tasks (key pinch, jar grasp, and jar twist) in 76 patients with early TMC OA and 44 asymptomatic controls. Computed tomography images were acquired while subjects held their hands relaxed and while they applied 80% of their maximum effort for each task. Six degree-of-freedom rigid body kinematics of the metacarpal with respect to the trapezium from the unloaded to the loaded task positions were computed in terms of a TMC joint coordinate system. Joint instability was expressed as a function of the metacarpal translation and the applied force. We found that the TMC joint was more unstable during a key pinch task than during a jar grasp or a jar twist task. Sex, age, and early OA did not have an effect on TMC joint instability, suggesting that instability during these three tasks is not a predisposing factor in TMC OA. PMID:25941135

Improved Automatically Locking/Unlocking Orthotic Knee Joint

NASA Technical Reports Server (NTRS)

Weddendorf, Bruce

1995-01-01

Proposed orthotic knee joint improved version of one described in "Automatically Locking/Unlocking Orthotic Knee Joint" (MFS-28633). Locks automatically upon initial application of radial force (wearer's weight) and unlocks automatically, but only when all loads (radial force and bending) relieved. Joints lock whenever wearer applies weight to knee at any joint angle between full extension and 45 degree bend. Both devices offer increased safety and convenience relative to conventional orthotic knee joints.

Real-Time Visualization of Joint Cavitation

PubMed Central

Rowe, Lindsay

2015-01-01

Cracking sounds emitted from human synovial joints have been attributed historically to the sudden collapse of a cavitation bubble formed as articular surfaces are separated. Unfortunately, bubble collapse as the source of joint cracking is inconsistent with many physical phenomena that define the joint cracking phenomenon. Here we present direct evidence from real-time magnetic resonance imaging that the mechanism of joint cracking is related to cavity formation rather than bubble collapse. In this study, ten metacarpophalangeal joints were studied by inserting the finger of interest into a flexible tube tightened around a length of cable used to provide long-axis traction. Before and after traction, static 3D T1-weighted magnetic resonance images were acquired. During traction, rapid cine magnetic resonance images were obtained from the joint midline at a rate of 3.2 frames per second until the cracking event occurred. As traction forces increased, real-time cine magnetic resonance imaging demonstrated rapid cavity inception at the time of joint separation and sound production after which the resulting cavity remained visible. Our results offer direct experimental evidence that joint cracking is associated with cavity inception rather than collapse of a pre-existing bubble. These observations are consistent with tribonucleation, a known process where opposing surfaces resist separation until a critical point where they then separate rapidly creating sustained gas cavities. Observed previously in vitro, this is the first in-vivo macroscopic demonstration of tribonucleation and as such, provides a new theoretical framework to investigate health outcomes associated with joint cracking. PMID:25875374

Joint Disorders - Multiple Languages

MedlinePlus

... a new window. Arabic (العربية) Expand Section Home Care After Total Joint Replacement - العربية (Arabic) Bilingual PDF Health Information Translations Bosnian (bosanski) Expand Section Home Care After Total Joint Replacement - bosanski (Bosnian) Bilingual PDF Health Information ...

15 CFR 296.8 - Joint venture agreement.

Code of Federal Regulations, 2011 CFR

2011-01-01

... OF STANDARDS AND TECHNOLOGY, DEPARTMENT OF COMMERCE NIST EXTRAMURAL PROGRAMS TECHNOLOGY INNOVATION PROGRAM General § 296.8 Joint venture agreement. NIST shall not issue a TIP award to a joint venture and... joint venture agreement has been executed by all of the joint venture members and approved by NIST. ...

15 CFR 296.8 - Joint venture agreement.

Code of Federal Regulations, 2012 CFR

2012-01-01

... OF STANDARDS AND TECHNOLOGY, DEPARTMENT OF COMMERCE NIST EXTRAMURAL PROGRAMS TECHNOLOGY INNOVATION PROGRAM General § 296.8 Joint venture agreement. NIST shall not issue a TIP award to a joint venture and... joint venture agreement has been executed by all of the joint venture members and approved by NIST. ...

15 CFR 296.8 - Joint venture agreement.

Code of Federal Regulations, 2013 CFR

2013-01-01

... OF STANDARDS AND TECHNOLOGY, DEPARTMENT OF COMMERCE NIST EXTRAMURAL PROGRAMS TECHNOLOGY INNOVATION PROGRAM General § 296.8 Joint venture agreement. NIST shall not issue a TIP award to a joint venture and... joint venture agreement has been executed by all of the joint venture members and approved by NIST. ...

15 CFR 296.8 - Joint venture agreement.

Code of Federal Regulations, 2014 CFR

2014-01-01

... OF STANDARDS AND TECHNOLOGY, DEPARTMENT OF COMMERCE NIST EXTRAMURAL PROGRAMS TECHNOLOGY INNOVATION PROGRAM General § 296.8 Joint venture agreement. NIST shall not issue a TIP award to a joint venture and... joint venture agreement has been executed by all of the joint venture members and approved by NIST. ...

15 CFR 296.8 - Joint venture agreement.

Code of Federal Regulations, 2010 CFR

2010-01-01

... OF STANDARDS AND TECHNOLOGY, DEPARTMENT OF COMMERCE NIST EXTRAMURAL PROGRAMS TECHNOLOGY INNOVATION PROGRAM General § 296.8 Joint venture agreement. NIST shall not issue a TIP award to a joint venture and... joint venture agreement has been executed by all of the joint venture members and approved by NIST. ...

Second-site prosthetic joint infection in patients with multiple prosthetic joints.

PubMed

Clesham, Kevin; Hughes, Andrew J; O' hEireamhoin, Sven; Fleming, Catherine; Murphy, Colin G

2018-04-10

Prosthetic joint infections (PJIs) are among the most serious complications in arthroplasty. A second-site PJI in patients with multiple prosthetic joints increases morbidity, with many requiring further revision procedures. We aimed to establish why some patients with multiple joints develop second-site infections. Our institution's arthroplasty database was reviewed from 2004 to 2017. All PJIs were identified, and all patients with more than one prosthetic joint in situ were included. We recorded risk factors, causative organisms, number of procedures and length of stay. Forty-four patients meeting the criteria were identified. Four patients (9.1%) developed second-site infection. Eight patients (18.2%) developed re-infection of the primary PJI. Positive MRSA carrier status and PJI of a total knee replacement were associated with an increased risk of a second episode of infection. Patients who developed further infection had more frequent admission and longer lengths of stay than isolated PJIs. Higher morbidity and use of hospital resources are associated with this cohort of patients. PJIs in total knee replacements and positive MRSA status are associated with higher rates of second infection. Identifying this vulnerable cohort of patients at an early stage is critical to ensure measures are taken to reduce the risks of further infection.

Structural analysis of Aircraft fuselage splice joint

NASA Astrophysics Data System (ADS)

Udaya Prakash, R.; Kumar, G. Raj; Vijayanandh, R.; Senthil Kumar, M.; Ramganesh, T.

2016-09-01

In Aviation sector, composite materials and its application to each component are one of the prime factors of consideration due to the high strength to weight ratio, design flexibility and non-corrosive so that the composite materials are widely used in the low weight constructions and also it can be treated as a suitable alternative to metals. The objective of this paper is to estimate and compare the suitability of a composite skin joint in an aircraft fuselage with different joints by simulating the displacement, normal stress, vonmises stress and shear stress with the help of numerical solution methods. The reference Z-stringer component of this paper is modeled by CATIA and numerical simulation is carried out by ANSYS has been used for splice joint presents in the aircraft fuselage with three combinations of joints such as riveted joint, bonded joint and hybrid joint. Nowadays the stringers are using to avoid buckling of fuselage skin, it has joined together by rivets and they are connected end to end by splice joint. Design and static analysis of three-dimensional models of joints such as bonded, riveted and hybrid are carried out and results are compared.

Dorsoradial capsulodesis for trapeziometacarpal joint instability.

PubMed

Rayan, Ghazi; Do, Viet

2013-02-01

We describe an alternative method for treating chronic trapeziometacarpal (TM) joint instability after acute injury or chronic repetitive use of the thumb by performing a dorsoradial capsulodesis procedure. The procedure is done by imbricating the redundant TM joint dorsoradial ligament and capsule after reducing the joint by pronating the thumb. The dorsoradial capsulodesis is a reasonable reconstructive option for chronic TM joint instability and subluxation. Copyright © 2013 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

Fluoroscopic Sacroiliac Joint Injection: Is Oblique Angulation Really Necessary?

PubMed

Khuba, Sandeep; Agarwal, Anil; Gautam, Sujeet; Kumar, Sanjay

2016-01-01

The conventional technique for sacroiliac (SI) joint injection involves aligning the anterior and posterior aspects of the SI joint under fluoroscopic guidance and then entering the SI joint in the most caudal aspect. We wish to highlight that there is no added advantage to aligning both the anterior and posterior joint lines of the SI joint as it is time consuming, associated with additional radiation exposure, and may make the entry into the posterior SI joint technically more difficult. Observational study. Pain Clinic, Department of Anesthesiology. With the patient lying prone on fluoroscopy table, SI joint injection is performed with a 22 G, 10 cm spinal needle in a true anteroposterior (AP) view, where anterior and posterior SI joint spaces are seen as separate entities, where the medial joint space represents the posterior SI joint and the lateral joint space represents the anterior SI joint. The distal 1 cm of the medial joint space is entered under AP view. If the SI joint is seen as a straight line rather than 2 joint spaces in the AP view then the image intensifier of the fluoroscope was tilted cranially to elongate the image of the lower part of the posterior SI joint, thus facilitating entry into this part of the joint which was confirmed by administering 0.3 to 0.5 mL of radiopaque contrast medium. Sixty SI joints of 58 patients were injected under an AP fluoroscopic view. Forty-two (70%) SI joints were seen as 2 separate medial and lateral joint spaces and were entered in distal 1 cm of the medial joint space. In 18 (30%) joints seen as a straight line rather than 2 separate spaces, the image intensifier of the fluoroscope was tilted cranially to elongate the image of the lower part of the posterior SI joint and then the SI joint was entered in its distal 1 cm. Confirmation of entry into the SI joint was confirmed by with 0.3 to 0.5 mL of radiopaque contrast medium. In 4 cases the joints did not show the correct radiopaque contrast spread (3/42 and 1

Development of Vision Based Multiview Gait Recognition System with MMUGait Database

PubMed Central

Ng, Hu; Tan, Wooi-Haw; Tong, Hau-Lee

2014-01-01

This paper describes the acquisition setup and development of a new gait database, MMUGait. This database consists of 82 subjects walking under normal condition and 19 subjects walking with 11 covariate factors, which were captured under two views. This paper also proposes a multiview model-based gait recognition system with joint detection approach that performs well under different walking trajectories and covariate factors, which include self-occluded or external occluded silhouettes. In the proposed system, the process begins by enhancing the human silhouette to remove the artifacts. Next, the width and height of the body are obtained. Subsequently, the joint angular trajectories are determined once the body joints are automatically detected. Lastly, crotch height and step-size of the walking subject are determined. The extracted features are smoothened by Gaussian filter to eliminate the effect of outliers. The extracted features are normalized with linear scaling, which is followed by feature selection prior to the classification process. The classification experiments carried out on MMUGait database were benchmarked against the SOTON Small DB from University of Southampton. Results showed correct classification rate above 90% for all the databases. The proposed approach is found to outperform other approaches on SOTON Small DB in most cases. PMID:25143972

Increased expression of damage-associated molecular patterns (DAMPs) in osteoarthritis of human knee joint compared to hip joint.

PubMed

Rosenberg, John H; Rai, Vikrant; Dilisio, Matthew F; Sekundiak, Todd D; Agrawal, Devendra K

2017-12-01

Osteoarthritis (OA) is a degenerative disease characterized by the destruction of cartilage. The greatest risk factors for the development of OA include age and obesity. Recent studies suggest the role of inflammation in the pathogenesis of OA. The two most common locations for OA to occur are in the knee and hip joints. The knee joint experiences more mechanical stress, cartilage degeneration, and inflammation than the hip joint. This could contribute to the increased incidence of OA in the knee joint. Damage-associated molecular patterns (DAMPs), including high-mobility group box-1, receptor for advanced glycation end products, and alarmins (S100A8 and S100A9), are released in the joint in response to stress-mediated chondrocyte and cartilage damage. This facilitates increased cartilage degradation and inflammation in the joint. Studies have documented the role of DAMPs in the pathogenesis of OA; however, the comparison of DAMPs and its influence on OA has not been discussed. In this study, we compared the DAMPs between OA knee and hip joints and found a significant difference in the levels of DAMPs expressed in the knee joint compared to the hip joint. The increased levels of DAMPs suggest a difference in the underlying pathogenesis of OA in the knee and the hip and highlights DAMPs as potential therapeutic targets for OA in the future.

49 CFR 213.351 - Rail joints.

Code of Federal Regulations, 2011 CFR

2011-10-01

... replaced. (d) Each rail shall be bolted with at least two bolts at each joint. (e) Each joint bar shall be... in this subpart. (f) No rail shall have a bolt hole which is torch cut or burned. (g) No joint bar shall be reconfigured by torch cutting. ...

Objective Assessment of Joint Stiffness: A Clinically Oriented Hardware and Software Device with an Application to the Shoulder Joint.

PubMed

McQuade, Kevin; Price, Robert; Liu, Nelson; Ciol, Marcia A

2012-08-30

Examination of articular joints is largely based on subjective assessment of the "end-feel" of the joint in response to manually applied forces at different joint orientations. This technical report aims to describe the development of an objective method to examine joints in general, with specific application to the shoulder, and suitable for clinical use. We adapted existing hardware and developed laptop-based software to objectively record the force/displacement behavior of the glenohumeral joint during three common manual joint examination tests with the arm in six positions. An electromagnetic tracking system recorded three-dimensional positions of sensors attached to a clinician examiner and a patient. A hand-held force transducer recorded manually applied translational forces. The force and joint displacement were time-synchronized and the joint stiffness was calculated as a quantitative representation of the joint "end-feel." A methodology and specific system checks were developed to enhance clinical testing reproducibility and precision. The device and testing protocol were tested on 31 subjects (15 with healthy shoulders, and 16 with a variety of shoulder impairments). Results describe the stiffness responses, and demonstrate the feasibility of using the device and methods in clinical settings.

Joint Newspaper Operating Agreements.

ERIC Educational Resources Information Center

Parsons, Marie

The number of competing daily newspapers in American cities has dwindled until only about 50 cities boast two papers. Of the newspapers in those cities, 23 now maintain separate editorial operations but have joint printing, advertising, and circulation departments. The concept of joint operation is 50 years old, dating from the Depression years…

Strength evaluation of socket joints

NASA Technical Reports Server (NTRS)

Rash, Larry C.

1994-01-01

This report documents the development of a set of equations that can be used to provide a relatively simple solution for identifying the strength of socket joints and for most cases avoid the need of more lengthy analyses. The analytical approach was verified by comparison of the contact load distributions to results obtained from a finite element analysis. The contacting surfaces for the specific joint in this analysis are in the shape of frustrums of a cone and are representative of the tapered surfaces in the socket-type joints used to join segments of model support systems for wind tunnels. The results are in the form of equations that can be used to determine the contact loads and stresses in the joint from the given geometry and externally applied loads. Equations were determined to define the bending moments and stresses along the length of the joints based on strength and materials principles. The results have also been programmed for a personal computer and a copy of the program is included.

37 CFR 1.45 - Joint inventors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... joint application under 35 U.S.C. 116. If multiple inventors are named in a provisional application... disclosed in the provisional application and the provisional application will be considered to be a joint... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Joint inventors. 1.45 Section...

BIOMECHANICS AND PATHOMECHANICS OF THE PATELLOFEMORAL JOINT

PubMed Central

2016-01-01

The patellofemoral joint is a joint that can be an area of concern for athletes of various sports and ages. The joint is somewhat complex with multiple contact points and numerous tissues that attach to the patella. Joint forces are variable and depend on the degree of knee flexion and whether the foot is in contact with the ground. The sports medicine specialist must have a good working knowledge of the anatomy and biomechanics of the patellofemoral joint in order to treat it effectively. PMID:27904787

Geared Electromechanical Rotary Joint

NASA Technical Reports Server (NTRS)

Vranish, John M.

1994-01-01

Geared rotary joint provides low-noise ac or dc electrical contact between electrical subsystems rotating relative to each other. Designed to overcome some disadvantages of older electromechanical interfaces, especially intermittency of sliding-contact and rolling-contact electromechanical joints. Hollow, springy planetary gears provide continuous, redundant, low-noise electrical contact between inner and outer gears.

Temporal gene expression profiling of the rat knee joint capsule during immobilization-induced joint contractures.

PubMed

Wong, Kayleigh; Sun, Fangui; Trudel, Guy; Sebastiani, Paola; Laneuville, Odette

2015-05-26

Contractures of the knee joint cause disability and handicap. Recovering range of motion is recognized by arthritic patients as their preference for improved health outcome secondary only to pain management. Clinical and experimental studies provide evidence that the posterior knee capsule prevents the knee from achieving full extension. This study was undertaken to investigate the dynamic changes of the joint capsule transcriptome during the progression of knee joint contractures induced by immobilization. We performed a microarray analysis of genes expressed in the posterior knee joint capsule following induction of a flexion contracture by rigidly immobilizing the rat knee joint over a time-course of 16 weeks. Fold changes of expression values were measured and co-expressed genes were identified by clustering based on time-series analysis. Genes associated with immobilization were further analyzed to reveal pathways and biological significance and validated by immunohistochemistry on sagittal sections of knee joints. Changes in expression with a minimum of 1.5 fold changes were dominated by a decrease in expression for 7732 probe sets occurring at week 8 while the expression of 2251 probe sets increased. Clusters of genes with similar profiles of expression included a total of 162 genes displaying at least a 2 fold change compared to week 1. Functional analysis revealed ontology categories corresponding to triglyceride metabolism, extracellular matrix and muscle contraction. The altered expression of selected genes involved in the triglyceride biosynthesis pathway; AGPAT-9, and of the genes P4HB and HSP47, both involved in collagen synthesis, was confirmed by immunohistochemistry. Gene expression in the knee joint capsule was sensitive to joint immobility and provided insights into molecular mechanisms relevant to the pathophysiology of knee flexion contractures. Capsule responses to immobilization was dynamic and characterized by modulation of at least three

Conarticular congruence of the hominoid subtalar joint complex with implications for joint function in Plio-Pleistocene hominins.

PubMed

Prang, Thomas C

2016-07-01

The purpose of this study is to test the hypothesis that conarticular surfaces areas and curvatures are correlates of mobility at the hominoid talocalcaneal and talonavicular joints. Articular surface areas and curvatures of the talonavicular, anterior talocalcaneal, and posterior talocalcaneal joints were quantified using a total of 425 three-dimensional surface models of extant hominoid and fossil hominin tali, calcanei, and naviculars. Quadric surface fitting was used to calculate curvatures, pairwise comparisons were used to evaluate statistical differences between taxa, and regression was used to test for the effects of allometry. Pairwise comparisons show that the distributions of values for joint curvature indices follow the predicted arboreal-terrestrial morphocline in hominoid primates with no effect of body mass (PGLS p > 0.05). OH 8 (Homo habilis) and LB 1 (Homo floresiensis) can be accommodated within the range of human variation for the talonavicular joint, whereas MH2 (Australopithecus sediba) falls within the ranges of variation for Pan troglodytes and Gorilla gorilla in measures of posterior talocalcaneal joint congruity. Joint curvature indices are better discriminators than joint surface area indices, which may reflect a greater contribution of rotation, rather than translation, to joint movement in plantigrade taxa due to discrepancies in conarticular congruence and the "convex-concave" rule. The pattern of joint congruence in Au. sediba contributes to other data on the foot and ankle suggesting that the lateral side of the foot was more mobile than the medial side, which is consistent with suggestions of increased medial weight transfer associated with hyperpronation. Am J Phys Anthropol 160:446-457, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Functional outcome from sacroiliac joint prolotherapy in patients with sacroiliac joint instability.

PubMed

Hoffman, Martin D; Agnish, Vikram

2018-04-01

Examine the effectiveness of sacroiliac (SI) joint prolotherapy for SI joint instability, and characterize the patients most likely to benefit from this treatment. Retrospective cohort study. Department of Veterans Affairs outpatient physical medicine clinic. Patients referred for low back pain and diagnosed with SI joint instability received a series of three SI joint prolotherapy injections (15% dextrose in lidocaine) at approximately a one-month interval. The outcome of those completing treatment was retrospectively examined, and characteristics were compared between those with at least a minimum clinically important improvement and those without improvement. Patients completed the Oswestry Disability Index (ODI) before treatment was initiated, immediately preceding each prolotherapy injection, and at 3-4 month follow-up. Of 103 treated patients returning for post-treatment follow-up at a median of 117 days, 24 (23%) showed a minimum clinically important improvement despite a median of 2 years with low back pain and a mean (±SD) pre-intervention ODI of 54 ± 15 points. Much of the improvement was evident after the initial prolotherapy injection, and a 15-point improvement in ODI prior to the second prolotherapy injection had a sensitivity of 92% and specificity of 80% for determining which patients would improve. A satisfactory proportion of patients with symptomatic SI joint instability as an etiology of low back pain can have clinically meaningful functional gains with prolotherapy treatment. The patients who are not likely to improve with prolotherapy are generally evident by lack of improvement following the initial prolotherapy injection. Published by Elsevier Ltd.

Comparison of the use of a notched wedge joint vs. traditional butt joints in Connecticut : phase 1 report.

DOT National Transportation Integrated Search

2008-05-14

Performance of Hot Mix Asphalt (HMA) longitudinal joints have been an : item of increasing scrutiny in Connecticut. The traditional butt joint : has typically been the method used in Connecticut. These joints have : been reportedly opening up creatin...

The sacroiliac joint: anatomy, physiology and clinical significance.

PubMed

Forst, Stacy L; Wheeler, Michael T; Fortin, Joseph D; Vilensky, Joel A

2006-01-01

The sacroiliac joint (SIJ) is a putative source of low back pain. The objective of this article is to provide clinicians with a concise review of SIJ structure and function, diagnostic indicators of SIJ-mediated pain, and therapeutic considerations. The SIJ is a true diarthrodial joint with unique characteristics not typically found in other diarthrodial joints. The joint differs with others in that it has fibrocartilage in addition to hyaline cartilage, there is discontinuity of the posterior capsule, and articular surfaces have many ridges and depressions. The sacroiliac joint is well innervated. Histological analysis of the sacroiliac joint has verified the presence of nerve fibers within the joint capsule and adjoining ligaments. It has been variously described that the sacroiliac joint receives its innervation from the ventral rami of L4 and L5, the superior gluteal nerve, and the dorsal rami of L5, S1, and S2, or that it is almost exclusively derived from the sacral dorsal rami. Even though the sacroiliac joint is a known putative source of low back and lower extremity pain, there are few findings that are pathognomonic of sacroiliac joint pain. The controlled diagnostic blocks utilizing the International Association for the Study of Pain (IASP) criteria demonstrated the prevalence of pain of sacroiliac joint origin in 19% to 30% of the patients suspected to have sacroiliac joint pain. Conservative management includes manual medicine techniques, pelvic stabilization exercises to allow dynamic postural control, and muscle balancing of the trunk and lower extremities. Interventional treatments include sacroiliac joint, intra-articular joint injections, radiofrequency neurotomy, prolotherapy, cryotherapy, and surgical treatment. The evidence for intra-articular injections and radiofrequency neurotomy has been shown to be limited in managing sacroiliac joint pain.

Design and clinical outcome of a novel 3D-printed prosthetic joint replacement for the human temporomandibular joint.

PubMed

Ackland, David; Robinson, Dale; Lee, Peter Vee Sin; Dimitroulis, George

2018-05-11

Stock prosthetic temporomandibular joint replacements come in limited sizes, and do not always encompass the joint anatomy that presents clinically. The aims of this study were twofold. Firstly, to design a personalized prosthetic total joint replacement for the treatment of a patient's end-stage temporomandibular joint osteoarthritis, to implant the prosthesis into the patient, and assess clinical outcome 12-months post-operatively; and secondly, to evaluate the influence of changes in prosthetic condyle geometry on implant load response during mastication. A 48-year-old female patient with Grade-5 osteoarthritis to the left temporomandibular joint was recruited, and a prosthesis developed to match the native temporomandibular joint anatomy. The prosthesis was 3D printed, sterilized and implanted into the patient, and pain and function measured 12-months post-operatively. The prosthesis load response during a chewing-bite and maximum-force bite was evaluated using a personalized multi-body musculoskeletal model. Simulations were performed after perturbing condyle thickness, neck length and head sphericity. Increases in prosthetic condyle neck length malaligned the mandible and perturbed temporomandibular joint force. Changes in condylar component thickness greatly influenced fixation screw stress response, while a more eccentric condylar head increased prosthetic joint-contact loading. Post-operatively, the prosthetic temporomandibular joint surgery reduced patient pain from 7/10 to 1/10 on a visual analog scale, and increased intercisal opening distance from 22 mm to 38 mm. This study demonstrates effectiveness of a personalized prosthesis that may ultimately be adapted to treat a wide-range of end-stage temporomandibular joint conditions, and highlights sensitivity of prosthesis load response to changes in condylar geometry. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nikolaus Rüdinger (1832-1896), His Description of Joint Innervation in 1857, and the History of Surgical Joint Denervation.

PubMed

Gohritz, Andreas; Kaiser, Erich; Guggenheim, Merlin; Dellon, Arnold Lee

2018-01-01

 Selective joint denervation has become a reliable palliative treatment, especially for painful joints in the upper and lower extremity.  This article highlights the life and work of Nikolaus Rüdinger (1832-1896) who first described joint innervation which became the basis of later techniques of surgical joint denervation. The historical evolution of this method is outlined.  Rüdinger made a unique career from apprentice barber to military surgeon and anatomy professor in Munich, Germany. His first description of articular innervation of temporomandibular, shoulder, elbow, wrist, finger, sacroiliac, hip, knee, ankle, foot, and toe joints in 1857 stimulated the subsequent history of surgical joint denervation. Comparing his investigations with modern joint denervation methods, developed by pioneers like Albrecht Wilhelm or A. Lee Dellon, shows his great exactitude and anatomical correspondence despite different current terminology. Clinical series of modern surgical joint denervations reveal success rates of up to 80% with reliable long-term results.  The history of joint denervation with Rüdinger as its important protagonist offers inspiring insights into the evolution of surgical techniques and exemplifies the value of descriptive functional anatomy, even if surgical application may not have been realized until a century later. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

30 CFR 36.24 - Engine joints.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Engine joints. 36.24 Section 36.24 Mineral... Construction and Design Requirements § 36.24 Engine joints. (a) Cylinder head. The joint between the cylinder head and block of the engine shall be fitted with a metal or metal-clad gasket satisfactory to MSHA...

30 CFR 36.24 - Engine joints.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Engine joints. 36.24 Section 36.24 Mineral... Construction and Design Requirements § 36.24 Engine joints. (a) Cylinder head. The joint between the cylinder head and block of the engine shall be fitted with a metal or metal-clad gasket satisfactory to MSHA...

30 CFR 36.24 - Engine joints.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Engine joints. 36.24 Section 36.24 Mineral... Construction and Design Requirements § 36.24 Engine joints. (a) Cylinder head. The joint between the cylinder head and block of the engine shall be fitted with a metal or metal-clad gasket satisfactory to MSHA...

30 CFR 36.24 - Engine joints.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Engine joints. 36.24 Section 36.24 Mineral... Construction and Design Requirements § 36.24 Engine joints. (a) Cylinder head. The joint between the cylinder head and block of the engine shall be fitted with a metal or metal-clad gasket satisfactory to MSHA...

30 CFR 36.24 - Engine joints.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Engine joints. 36.24 Section 36.24 Mineral... Construction and Design Requirements § 36.24 Engine joints. (a) Cylinder head. The joint between the cylinder head and block of the engine shall be fitted with a metal or metal-clad gasket satisfactory to MSHA...

46 CFR 385.38 - Joint funding.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 8 2012-10-01 2012-10-01 false Joint funding. 385.38 Section 385.38 Shipping MARITIME... AGREEMENTS REGULATIONS General Policies § 385.38 Joint funding. (a) Pursuant to section 10(c) of the Act, MarAd is authorized to participate in joint funded projects with other Federal agencies in any funding...

46 CFR 385.38 - Joint funding.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 8 2013-10-01 2013-10-01 false Joint funding. 385.38 Section 385.38 Shipping MARITIME... AGREEMENTS REGULATIONS General Policies § 385.38 Joint funding. (a) Pursuant to section 10(c) of the Act, MarAd is authorized to participate in joint funded projects with other Federal agencies in any funding...

46 CFR 385.38 - Joint funding.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 8 2014-10-01 2014-10-01 false Joint funding. 385.38 Section 385.38 Shipping MARITIME... AGREEMENTS REGULATIONS General Policies § 385.38 Joint funding. (a) Pursuant to section 10(c) of the Act, MarAd is authorized to participate in joint funded projects with other Federal agencies in any funding...

46 CFR 385.38 - Joint funding.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 8 2010-10-01 2010-10-01 false Joint funding. 385.38 Section 385.38 Shipping MARITIME... AGREEMENTS REGULATIONS General Policies § 385.38 Joint funding. (a) Pursuant to section 10(c) of the Act, MarAd is authorized to participate in joint funded projects with other Federal agencies in any funding...

46 CFR 385.38 - Joint funding.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 8 2011-10-01 2011-10-01 false Joint funding. 385.38 Section 385.38 Shipping MARITIME... AGREEMENTS REGULATIONS General Policies § 385.38 Joint funding. (a) Pursuant to section 10(c) of the Act, MarAd is authorized to participate in joint funded projects with other Federal agencies in any funding...

Development Requirements for Spacesuit Elbow Joint

NASA Technical Reports Server (NTRS)

Peters, Benjamin

2017-01-01

Functional Requirements for spacesuit elbow joint:1) The system is a conformal, single-axis spacesuit pressurized joint that encloses the elbow joint of the suited user and uses a defined interface to connect to the suit systems on either side of the joint.2) The system shall be designed to bear the loads incurred from the internal pressure of the system, as well as the expected loads induced by the user while enabling the user move the joint through the required range of motion. The joint torque of the system experienced by the user shall remain at or below the required specification for the entire range of motion.3) The design shall be constructed, at a minimum, as a two-layer system. The internal, air-tight layer shall be referred to as the bladder, and the layer on the unpressurized side of the bladder shall be referred to as the restraint. The design of the system may include additional features or layers, such as axial webbing, to meet the overall requirements of the design.

Inflammation is more distinct in temporomandibular joint osteoarthritis compared to the knee joint.

PubMed

Vos, Lukas M; Kuijer, Roel; Huddleston Slater, James J R; Bulstra, Sjoerd K; Stegenga, Boudewijn

2014-01-01

Most of the current understanding of articular cartilage maintenance and degradation is derived from large load-bearing synovial joints, in particular the knee joint. The aim of this study was to identify valuable degradation markers for cartilage degradation in the temporomandibular joint (TMJ) by comparing the relative concentrations of carboxyterminal telopeptides of collagen types I and II (CTX-I and CTX-II), cartilage oligomeric matrix protein (COMP), and prostaglandin E2 (PGE2) in synovial fluid (SF) of TMJ and knee joints with cartilage degradation. In this cross-sectional comparative study, participants were recruited from the University Medical Center Groningen, The Netherlands. Patients with TMJ osteoarthritis were compared with patients with knee osteoarthritis. The outcome variables were the relative SF concentrations of CTX-I, CTX-II, COMP, and PGE2. An independent samples Mann-Whitney U test was used to compare the relative concentrations. Thirty consecutive patients (9 male, 21 female; mean age, 40.1 yr; standard deviation, 15.3 yr) with TMJ osteoarthritis and 31 consecutive patients (20 male, 11 female; mean age, 37.4 yr; standard deviation, 13.7 yr) who were scheduled for arthroscopy of the knee joint participated in this study. Significant differences were found between relative concentrations of COMP (P = .000) and PGE2 (P = .005), and no significant differences were found between relative concentrations of CTX-I (P = .720) and CTX-II (P = .242). Relative SF concentrations of COMP and PGE2 showed significant differences between the TMJ and the knee joint, suggesting that there are differences in pathophysiology and that the inflammatory component may be more distinct in the TMJ. Copyright © 2014 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

The Joint Chiefs of Staff Video Collections

Science.gov Websites

Senior Enlisted Advisor Joint Staff History Joint Staff Inspector General Joint Staff Structure Origin of J8 | Force Structure, Resources & Assessment Contact Home : Media : Videos Featured Videos Gen

Shoulder Joint For Protective Suit

NASA Technical Reports Server (NTRS)

Kosmo, Joseph J.; Smallcombe, Richard D.

1994-01-01

Shoulder joint allows full range of natural motion: wearer senses little or no resisting force or torque. Developed for space suit, joint offers advantages in protective garments for underwater work, firefighting, or cleanup of hazardous materials.

49 CFR 213.121 - Rail joints.

Code of Federal Regulations, 2010 CFR

2010-10-01

... the rail on which it is applied. (b) If a joint bar on Classes 3 through 5 track is cracked, broken... at each joint in Classes 2 through 5 track, and with at least one bolt in Class 1 track. (e) In the... accommodate expansion and contraction due to temperature variations. When no-slip, joint-to-rail contact...

Joint Chiefs of Staff > Directorates > J3 | Operations

Science.gov Websites

Joint Staff Structure Joint Staff Inspector General Origin of Joint Concepts U.S. Code | Joint Chiefs of J8 | Force Structure, Resources & Assessment Contact J3 Operations Home : Directorates : J3

Experimental cryo-irrigation of the knee joint.

PubMed

Chen, S C; Helal, B; Revell, P A; Brocklehurst, R; Currey, H L

1986-10-01

Experiments have been carried out to test the feasibility of using cryo-irrigation as a means of ablating the synovium in the rheumatoid knee joint. Cryo-irrigation was performed by a cooling machine and pump, which circulated cold 200/10 centistoke (cSt) silicone through the knee joint of rabbits anaesthetised with intravenous (IV) 'Saffan'. Fluid left the joint at -5 to -10 degrees C. Sixteen normal New Zealand rabbits received cryo-irrigation of one knee joint for 10-20 minutes and were killed at one day, and one, two, and 12 weeks thereafter. Judged by radioactive sulphate incorporation there was no impairment of chondrocyte function in the articular cartilage of irrigated joints. Histological examination showed mild synovitis and some loss of staining of superficial cartilage in 6/16 irrigated joints (v 1/16 control joints). Similar treatment of rabbit joints in which the Glynn model of synovitis had been induced showed marked reduction of synovitis 14-45 days after silicone treatment. Nine of 26 animals in which synovitis was induced in both knees and cryo-irrigation performed in one knee died either immediately postoperatively or during the next week. These deaths remain unexplained. A single dog received cryo-irrigation of one knee (-6 to -9 degrees C for 22 min) and remained perfectly well up to sacrifice at six months, when the joint appeared histologically completely normal.

Joint Laxity in Preschool Children Born Preterm.

PubMed

Romeo, Domenico M; Velli, Chiara; Lucibello, Simona; Ferrantini, Gloria; Leo, Giuseppina; Brogna, Claudia; Cota, Francesco; Ricci, Daniela; Gallini, Francesca; Romagnoli, Costantino; Vento, Giovanni; Mercuri, Eugenio

2018-06-01

To evaluate the prevalence of joint laxity in children born preterm assessed in the first 2 years, the relationship between joint laxity and motor performance at preschool age, and possible changes over time in a subgroup of children followed longitudinally. The revised scale of Beighton Score was used to evaluate joint laxity in a population of 132 preschool children born preterm between 24 and 32 weeks of gestational age. All were assessed for joint laxity between 12 and 24 months of age. Children also performed the Movement Assessment Battery for Children-Second Edition between the age of 3 years and 6 months and 4 years; the age at onset of independent walking also was recorded. The total Beighton Score ranged between 0 and 8. Twenty percent of the cohort showed joint laxity. No differences related to sex or gestational age were observed. Children born preterm with joint laxity achieved later independent walking and achieved lower scores on Movement Assessment Battery for Children-Second Edition than those without joint laxity. In 76 children born preterm, an assessment for joint laxity was repeated once between 25 and 36 months and again after >36 months. No statistically significant difference was observed between the 3 assessments. The Beighton Score can be used to assess generalized joint laxity in children born preterm. As the presence of joint laxity influenced motor competences, the possibility to early identify these infants in the first 2 years is of interest to benefit from early intervention and potentially improve gross motor skills and coordination. Copyright © 2018 Elsevier Inc. All rights reserved.

Temporomandibular joint involvement caused by Borrelia Burgdorferi.

PubMed

Lesnicar, Gorazd; Zerdoner, Danijel

2007-12-01

Lyme borreliosis is an endemic disease in Slovenia with an incidence of around 150 patients per 100,000 inhabitants. Although the large joints are most typically affected in Lyme borreliosis, there are also periods of disease activity with arthritis or arthralgias involving smaller joints, including the temporo-mandibular joint. During the years between 2000 and 2003, two patients with Lyme borreliosis affecting the temporo-mandibular joints were treated. The patients presented with fatigue and pain in diverse muscle groups accompanied by arthralgia, which was most pronounced in the temporomandibular joint area. None of the patients were febrile or had joint effusions. Both patients were examined by means of biochemical and serological examinations for Borrelia burgdorferi using ELISA assay and Western blot test (both for IgM and IgG), plain radiographs, MR and CT scans, and scinti-scan of the temporo-mandibular joints They both had positive serum markers for an acute B. burgdorferi infection and were treated with intravenous ceftriaxone. None of the patients had clinical or laboratory signs of chronic Lyme disease activity two and four years following therapy, respectively. Roentgenographic and nuclear magnetic resonance imaging of the temporo-mandibular joints had not shown any persistent sign of acute inflammation. There are only few reports of patients with manifest temporo-mandibular joint involvement of Lyme borreliosis in the literature. This report emphasizes the importance of differential diagnosis of acute temporo-mandibular joint arthralgia, of early diagnosis of Lyme borreliosis, and of the necessity for prompt antibiotic treatment.

Anatomy of the pelvic joints--a review.

PubMed

Dietrichs, E

1991-01-01

In adults, after the os ilium, os ischii and os pubis have joined together by ossification to form the os coxae, there is usually one joint between the hip bones ventrally (the pubic symphysis) and several more complex joints between the hip bones and os sacrum dorsally (sacroiliac, "axial sacroiliac" and accessory sacroiliac joints). These joints carry the weight of the upper part of the body, but they shall also enable pelvic distention during labour. Pathological conditions in these joints are common, and increased knowledge concerning their normal antomy is important for better understanding of these conditions.

Management of acromioclavicular joint injuries.

PubMed

Li, Xinning; Ma, Richard; Bedi, Asheesh; Dines, David M; Altchek, David W; Dines, Joshua S

2014-01-01

Acromioclavicular joint injuries are among the most common shoulder girdle injuries in athletes and most commonly result from a direct force to the acromion with the arm in an adducted position. Acromioclavicular joint injuries often present with associated injuries to the glenohumeral joint, including an increased incidence of superior labrum anterior posterior (SLAP) tears that may warrant further evaluation and treatment. Anteroposterior stability of the acromioclavicular joint is conferred by the capsule and acromioclavicular ligaments, of which the posterior and superior ligaments are the strongest. Superior-inferior stability is maintained by the coracoclavicular (conoid and trapezoid) ligaments. Type-I or type-II acromioclavicular joint injuries have been treated with sling immobilization, early shoulder motion, and physical therapy, with favorable outcomes. Return to activity can occur when normal shoulder motion and strength are obtained and the shoulder is asymptomatic as compared with the contralateral normal extremity. The management of type-III injuries remains controversial and is individualized. While a return to the previous level of functional activity with nonsurgical treatment has been documented in a number of case series, surgical reduction and coracoclavicular ligament reconstruction has been associated with a favorable outcome and can be considered in patients who place high functional demands on their shoulders or in athletes who participate in overhead sports. Surgical management is indicated for high-grade (≥type IV) acromioclavicular joint injuries to achieve anatomic reduction of the acromioclavicular joint, reconstruction of the coracoclavicular ligaments, and repair of the deltotrapezial fascia. Outcomes after surgical reconstruction of the coracoclavicular ligaments have been satisfactory with regard to achieving pain relief and return to functional activities, but further improvements in the biomechanical strength of these

Longitudinal joint specifications and performance.

DOT National Transportation Integrated Search

2012-08-01

Deterioration of longitudinal joints is widely recognized as one of the major factors contributing to failure of asphalt pavements. Finding : ways to improve the durability of longitudinal joints will lead to improved service lives and lower life cyc...

Photonic Waveguide Choke Joint with Non-Absorptive Loading

NASA Technical Reports Server (NTRS)

Wollack, Edward J. (Inventor); U-Yen, Kongpop (Inventor); Chuss, David T. (Inventor)

2016-01-01

A waveguide choke joint includes a first array of pillars positioned on a substrate, each pillar in the first array of pillars having a first size and configured to receive an input plane wave at a first end of the choke joint. The choke joint has a second end configured to transmit the input plane wave away from the choke joint. The choke joint further includes a second array of pillars positioned on the substrate between the first array of pillars and the second end of the choke joint. Each pillar in the second array of pillars has a second size. The choke joint also has a third array of pillars positioned on the substrate between the second array and the second end of the choke joint. Each pillar in the third array of pillars has a third size.

Shading aboveground L-joint and lap-joint tests : comparison of white pine and sugar maple test assemblies

Treesearch

Carol A. Clausen; Daniel L. Lindner

2011-01-01

Five-year performance ratings are presented for two types of untreated, uncoated wood joints (L and lap) in aboveground tests under shaded conditions. The effect of shading on moisture entrapment in pine and maple L and lap joints was evaluated in a moderate decay zone (Madison, Wisconsin). Variations were observed between wood species, visual ratings, joint type,...

Pressure relief and other joint rehabilitation techniques

DOT National Transportation Integrated Search

1987-02-01

A study of four major concrete pavement joint rehabilitation techniques has been conducted, including: pressure relief joints, full-depth repairs, partial-depth repairs and joint resealing. The products of this research include the following for each...

Hypermobile joints

MedlinePlus

... Hypermobility syndrome Images Hypermobile joints References Ball JW, Dains JE, Flynn JA, Solomon BS, Stewart RW. Musculoskeletal system. In: Ball JW, Dains JE, Flynn JA, Solomon BS, Stewart RW, eds. ...

Bone alterations are associated with ankle osteoarthritis joint pain

PubMed Central

Nakamura, Yukio; Uchiyama, Shigeharu; Kamimura, Mikio; Komatsu, Masatoshi; Ikegami, Shota; Kato, Hiroyuki

2016-01-01

The etiology of ankle osteoarthritis (OA) is largely unknown. We analyzed 24 ankle OA of 21 patients diagnosed by plain radiographs using magnetic resonance imaging (MRI). Ankle joint pain disappeared in 22 out of 24 joints by conservative treatment. MRI bone signal changes in and around the ankle joints were observed in 22 of 24 joints. Bone signal changes along the joint line were seen in 10 of 11 joints as a Kellgren-Lawrence (KL) grade of II to IV. Such signal changes were witnessed in only 4 of 13 joints with KL grade 0 or I. In the talocrural joint, bone alterations occurred in both tibia and talus bones through the joint line in cases of KL grade III or IV, while focal bone alterations were present in the talus only in KL grade I or II cases. Sixteen of 24 joints exhibited intraosseous bone signal changes, which tended to correspond to joint pain of any ankle OA stage. Our results suggest that bone alterations around the ankle joint might be one of the etiologies of OA and associated with ankle joint pain. PMID:26776564

Bone alterations are associated with ankle osteoarthritis joint pain.

PubMed

Nakamura, Yukio; Uchiyama, Shigeharu; Kamimura, Mikio; Komatsu, Masatoshi; Ikegami, Shota; Kato, Hiroyuki

2016-01-18

The etiology of ankle osteoarthritis (OA) is largely unknown. We analyzed 24 ankle OA of 21 patients diagnosed by plain radiographs using magnetic resonance imaging (MRI). Ankle joint pain disappeared in 22 out of 24 joints by conservative treatment. MRI bone signal changes in and around the ankle joints were observed in 22 of 24 joints. Bone signal changes along the joint line were seen in 10 of 11 joints as a Kellgren-Lawrence (KL) grade of II to IV. Such signal changes were witnessed in only 4 of 13 joints with KL grade 0 or I. In the talocrural joint, bone alterations occurred in both tibia and talus bones through the joint line in cases of KL grade III or IV, while focal bone alterations were present in the talus only in KL grade I or II cases. Sixteen of 24 joints exhibited intraosseous bone signal changes, which tended to correspond to joint pain of any ankle OA stage. Our results suggest that bone alterations around the ankle joint might be one of the etiologies of OA and associated with ankle joint pain.

Longitudinal joint treatment : construction report.

DOT National Transportation Integrated Search

2000-05-01

Maine highways have been showing signs of longitudinal joint failure for a number of : years. In an effort to reduce the amount of joint failures the Maine Department of : Transportation (MDOT) is currently evaluating two projects. One project is mon...

A nondestructive, reproducible method of measuring joint reaction force at the distal radioulnar joint.

PubMed

Canham, Colin D; Schreck, Michael J; Maqsoodi, Noorullah; Doolittle, Madison; Olles, Mark; Elfar, John C

2015-06-01

To develop a nondestructive method of measuring distal radioulnar joint (DRUJ) joint reaction force (JRF) that preserves all periarticular soft tissues and more accurately reflects in vivo conditions. Eight fresh-frozen human cadaveric limbs were obtained. A threaded Steinmann pin was placed in the middle of the lateral side of the distal radius transverse to the DRUJ. A second pin was placed into the middle of the medial side of the distal ulna colinear to the distal radial pin. Specimens were mounted onto a tensile testing machine using a custom fixture. A uniaxial distracting force was applied across the DRUJ while force and displacement were simultaneously measured. Force-displacement curves were generated and a best-fit polynomial was solved to determine JRF. All force-displacement curves demonstrated an initial high slope where relatively large forces were required to distract the joint. This ended with an inflection point followed by a linear area with a low slope, where small increases in force generated larger amounts of distraction. Each sample was measured 3 times and there was high reproducibility between repeated measurements. The average baseline DRUJ JRF was 7.5 N (n = 8). This study describes a reproducible method of measuring DRUJ reaction forces that preserves all periarticular stabilizing structures. This technique of JRF measurement may also be suited for applications in the small joints of the wrist and hand. Changes in JRF can alter native joint mechanics and lead to pathology. Reliable methods of measuring these forces are important for determining how pathology and surgical interventions affect joint biomechanics. Copyright © 2015 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

QM-8 field joint protection system, volume 7

NASA Technical Reports Server (NTRS)

Hale, Elgie

1989-01-01

The pre-launch functioning data of the Field Joint Protection System (JPS) used on QM-8 are presented. Also included is the post fire condition of the JPS components following the test firing of the motor. The JPS components are: field joint heaters; field joint sensors; field joint moisture seal; moisture seal kevlar retaining straps; field joint external extruded cork insulation; vent valve; power cables; and igniter heater.

DEMES rotary joint: theories and applications

NASA Astrophysics Data System (ADS)

Wang, Shu; Hao, Zhaogang; Li, Mingyu; Huang, Bo; Sun, Lining; Zhao, Jianwen

2017-04-01

As a kind of dielectric elastomer actuators, dielectric elastomer minimum energy structure (DEMES) can realize large angular deformations by small voltage-induced strains, which make them an attractive candidate for use as biomimetic robotics. Considering the rotary joint is a basic and common component of many biomimetic robots, we have been fabricated rotary joint by DEMES and developed its performances in the past two years. In this paper, we have discussed the static analysis, dynamics analysis and some characteristics of the DEMES rotary joint. Based on theoretical analysis, some different applications of the DEMES rotary joint were presented, such as a flapping wing, a biomimetic fish and a two-legged walker. All of the robots are fabricated by DEMES rotary joint and can realize some basic biomimetic motions. Comparing with traditional rigid robot, the robot based on DEMES is soft and light, so it has advantage on the collision-resistant.

Shear joint capability versus bolt clearance

NASA Technical Reports Server (NTRS)

Lee, H. M.

1992-01-01

The results of a conservative analysis approach into the determination of shear joint strength capability for typical space-flight hardware as a function of the bolt-hole clearance specified in the design are presented. These joints are comprised of high-strength steel fasteners and abutments constructed of aluminum alloys familiar to the aerospace industry. A general analytical expression was first arrived at which relates bolt-hole clearance to the bolt shear load required to place all joint fasteners into a shear transferring position. Extension of this work allowed the analytical development of joint load capability as a function of the number of fasteners, shear strength of the bolt, bolt-hole clearance, and the desired factor of safety. Analysis results clearly indicate that a typical space-flight hardware joint can withstand significant loading when less than ideal bolt hole clearances are used in the design.

BLOC-1 is required for selective membrane protein trafficking from endosomes to primary cilia

PubMed Central

2017-01-01

Primary cilia perceive the extracellular environment through receptors localized in the ciliary membrane, but mechanisms directing specific proteins to this domain are poorly understood. To address this question, we knocked down proteins potentially important for ciliary membrane targeting and determined how this affects the ciliary trafficking of fibrocystin, polycystin-2, and smoothened. Our analysis showed that fibrocystin and polycystin-2 are dependent on IFT20, GMAP210, and the exocyst complex, while smoothened delivery is largely independent of these components. In addition, we found that polycystin-2, but not smoothened or fibrocystin, requires the biogenesis of lysosome-related organelles complex-1 (BLOC-1) for ciliary delivery. Consistent with the role of BLOC-1 in sorting from the endosome, we find that disrupting the recycling endosome reduces ciliary polycystin-2 and causes its accumulation in the recycling endosome. This is the first demonstration of a role for BLOC-1 in ciliary assembly and highlights the complexity of pathways taken to the cilium. PMID:28576874

Design and fabrication of realistic adhesively bonded joints

NASA Technical Reports Server (NTRS)

Shyprykevich, P.

1983-01-01

Eighteen bonded joint test specimens representing three different designs of a composite wing chordwise bonded splice were designed and fabricated using current aircraft industry practices. Three types of joints (full wing laminate penetration, two side stepped; midthickness penetration, one side stepped; and partial penetration, scarfed) were analyzed using state of the art elastic joint analysis modified for plastic behavior of the adhesive. The static tensile fail load at room temperature was predicted to be: (1) 1026 kN/m (5860 1b/in) for the two side stepped joint; (2) 925 kN/m (5287 1b/in) for the one side stepped joint; and (3) 1330 kN/m (7600 1b/in) for the scarfed joint. All joints were designed to fail in the adhesive.

Joint Airspace Control, Doctrine Update 10-06

DTIC Science & Technology

2010-05-20

Doctrine Update 10-06 Joint Publication 3-52, Joint Airspace Control JP 3-52 provides joint doctrine for airspace control across the full range...identification, combined operations, and unmanned aerial vehicle If you want read the complete new doctrine document, dated 20 May 2010, click here: JP 3-52...Joint Airspace Control. For more information, visit the LeMay Center for Doctrine Development and Education, call us at DSN 493-7442, or e-mail

Evaluation of Asphalt Bridge Deck Joint Systems.

DOT National Transportation Integrated Search

2009-12-01

Asphaltic Plug Joint is an expansion joint that is used for new and rehabilitated bridges. It provides a smooth and watertight surface free of debris; and offers simple, easy and staged construction. Asphaltic plug joint can be repaired segmentally a...

Joint imaging in polymyalgia rheumatica

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Duffy, J.D.; Wahner, H.W.; Hunder, G.G.

1976-08-01

Technetium pertechnetate joint scintigrams were abnormal in 24 of 25 patients with polymyalgia rheumatica, in all 16 with rheumatoid arthritis, in 4 of 13 with nonarticular rheumatism, but in none of 26 control patients. Abnormal uptake in polymyalgia patients was commonest in shoulders and was less likely to be symmetric than in patients with rheumatoid arthritis, in whom distal joint abnormalities predominated. The pattern of abnormal uptake in polymyalgia rheumatica was not different in those with biopsy-proved giant cell arteritis. Correlation between symptoms and abnormal scintigrams was 72%, and abnormal uptake was present in 81% of joints of patients havingmore » physical abnormalities. Biopsy showed lymphocytic synovitis in the knee of one patient. After treatment the number of abnormal joints declined. These findings suggest that synovitis is common in polymyalgia rheumatica, and that it may account for some or most of the symptoms in this condition.« less

In Vivo Measurement of Glenohumeral Joint Contact Patterns

NASA Astrophysics Data System (ADS)

Bey, Michael J.; Kline, Stephanie K.; Zauel, Roger; Kolowich, Patricia A.; Lock, Terrence R.

2009-12-01

The objectives of this study were to describe a technique for measuring in-vivo glenohumeral joint contact patterns during dynamic activities and to demonstrate application of this technique. The experimental technique calculated joint contact patterns by combining CT-based 3D bone models with joint motion data that were accurately measured from biplane x-ray images. Joint contact patterns were calculated for the repaired and contralateral shoulders of 20 patients who had undergone rotator cuff repair. Significant differences in joint contact patterns were detected due to abduction angle and shoulder condition (i.e., repaired versus contralateral). Abduction angle had a significant effect on the superior/inferior contact center position, with the average joint contact center of the repaired shoulder 12.1% higher on the glenoid than the contralateral shoulder. This technique provides clinically relevant information by calculating in-vivo joint contact patterns during dynamic conditions and overcomes many limitations associated with conventional techniques for quantifying joint mechanics.

49 CFR 236.752 - Joint, rail, insulated.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Joint, rail, insulated. 236.752 Section 236.752 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION... Joint, rail, insulated. A joint in which electrical insulation is provided between adjoining rails. ...

Adaptive plasticity in mammalian masticatory joints

NASA Astrophysics Data System (ADS)

Ravosa, Matthew J.; Kunwar, Ravinder; Nicholson, Elisabeth K.; Klopp, Emily B.; Pinchoff, Jessie; Stock, Stuart R.; Stack, M. Sharon; Hamrick, Mark W.

2006-08-01

Genetically similar white rabbits raised on diets of different mechanical properties, as well as wild-type and myostatin-deficient mice raised on similar diets, were compared to assess the postweaning effects of elevated masticatory loads due to increased jaw-adductor muscle and bite forces on the proportions and properties of the mandibular symphysis and temporomandibular joint (TMJ). Microcomputed tomography (microCT) was used to quantify bone structure at a series of equidistant external and internal sites in coronal sections for a series of joint locations. Discriminant function analyses and non-parametric ANOVAs were used to characterize variation in biomineralization within and between loading cohorts. In both species, long-term excessive loading results in larger joint proportions, thicker articular and cortical bone, and increased biomineralization of hard tissues. Such adaptive plasticity appears designed to maintain the postnatal integrity of masticatory joint systems for a primary loading environment(s). This behavioral signal may be increasingly mitigated in older organisms by the interplay between adaptive and degradative joint tissue responses.

Excluding joint probabilities from quantum theory

NASA Astrophysics Data System (ADS)