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Sample records for random fields reveal

  1. Social patterns revealed through random matrix theory

    NASA Astrophysics Data System (ADS)

    Sarkar, Camellia; Jalan, Sarika

    2014-11-01

    Despite the tremendous advancements in the field of network theory, very few studies have taken weights in the interactions into consideration that emerge naturally in all real-world systems. Using random matrix analysis of a weighted social network, we demonstrate the profound impact of weights in interactions on emerging structural properties. The analysis reveals that randomness existing in particular time frame affects the decisions of individuals rendering them more freedom of choice in situations of financial security. While the structural organization of networks remains the same throughout all datasets, random matrix theory provides insight into the interaction pattern of individuals of the society in situations of crisis. It has also been contemplated that individual accountability in terms of weighted interactions remains as a key to success unless segregation of tasks comes into play.

  2. On Pfaffian Random Point Fields

    NASA Astrophysics Data System (ADS)

    Kargin, V.

    2014-02-01

    We study Pfaffian random point fields by using the Moore-Dyson quaternion determinants. First, we give sufficient conditions that ensure that a self-dual quaternion kernel defines a valid random point field, and then we prove a CLT for Pfaffian point fields. The proofs are based on a new quaternion extension of the Cauchy-Binet determinantal identity. In addition, we derive the Fredholm determinantal formulas for the Pfaffian point fields which use the quaternion determinant.

  3. Markov random field surface reconstruction.

    PubMed

    Paulsen, Rasmus R; Baerentzen, Jakob Andreas; Larsen, Rasmus

    2010-01-01

    A method for implicit surface reconstruction is proposed. The novelty in this paper is the adaptation of Markov Random Field regularization of a distance field. The Markov Random Field formulation allows us to integrate both knowledge about the type of surface we wish to reconstruct (the prior) and knowledge about data (the observation model) in an orthogonal fashion. Local models that account for both scene-specific knowledge and physical properties of the scanning device are described. Furthermore, how the optimal distance field can be computed is demonstrated using conjugate gradients, sparse Cholesky factorization, and a multiscale iterative optimization scheme. The method is demonstrated on a set of scanned human heads and, both in terms of accuracy and the ability to close holes, the proposed method is shown to have similar or superior performance when compared to current state-of-the-art algorithms.

  4. Efficient robust conditional random fields.

    PubMed

    Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A

    2015-10-01

    Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.

  5. Defect Detection Using Hidden Markov Random Fields

    SciTech Connect

    Dogandzic, Aleksandar; Eua-anant, Nawanat; Zhang Benhong

    2005-04-09

    We derive an approximate maximum a posteriori (MAP) method for detecting NDE defect signals using hidden Markov random fields (HMRFs). In the proposed HMRF framework, a set of spatially distributed NDE measurements is assumed to form a noisy realization of an underlying random field that has a simple structure with Markovian dependence. Here, the random field describes the defect signals to be estimated or detected. The HMRF models incorporate measurement locations into the statistical analysis, which is important in scenarios where the same defect affects measurements at multiple locations. We also discuss initialization of the proposed HMRF detector and apply to simulated eddy-current data and experimental ultrasonic C-scan data from an inspection of a cylindrical Ti 6-4 billet.

  6. Random field estimation approach to robot dynamics

    NASA Technical Reports Server (NTRS)

    Rodriguez, Guillermo

    1990-01-01

    The difference equations of Kalman filtering and smoothing recursively factor and invert the covariance of the output of a linear state-space system driven by a white-noise process. Here it is shown that similar recursive techniques factor and invert the inertia matrix of a multibody robot system. The random field models are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. They are easier to describe than the models based on classical mechanics, which typically require extensive derivation and manipulation of equations of motion for complex mechanical systems. With the spatially random models, more primitive locally specified computations result in a global collective system behavior equivalent to that obtained with deterministic models. The primary goal of applying random field estimation is to provide a concise analytical foundation for solving robot control and motion planning problems.

  7. Relativistic diffusive motion in random electromagnetic fields

    NASA Astrophysics Data System (ADS)

    Haba, Z.

    2011-08-01

    We show that the relativistic dynamics in a Gaussian random electromagnetic field can be approximated by the relativistic diffusion of Schay and Dudley. Lorentz invariant dynamics in the proper time leads to the diffusion in the proper time. The dynamics in the laboratory time gives the diffusive transport equation corresponding to the Jüttner equilibrium at the inverse temperature β-1 = mc2. The diffusion constant is expressed by the field strength correlation function (Kubo's formula).

  8. Deterministic signal associated with a random field.

    PubMed

    Kim, Taewoo; Zhu, Ruoyu; Nguyen, Tan H; Zhou, Renjie; Edwards, Chris; Goddard, Lynford L; Popescu, Gabriel

    2013-09-01

    Stochastic fields do not generally possess a Fourier transform. This makes the second-order statistics calculation very difficult, as it requires solving a fourth-order stochastic wave equation. This problem was alleviated by Wolf who introduced the coherent mode decomposition and, as a result, space-frequency statistics propagation of wide-sense stationary fields. In this paper we show that if, in addition to wide-sense stationarity, the fields are also wide-sense statistically homogeneous, then monochromatic plane waves can be used as an eigenfunction basis for the cross spectral density. Furthermore, the eigenvalue associated with a plane wave, exp[i(k · r-ωt)], is given by the spatiotemporal power spectrum evaluated at the frequency (k, ω). We show that the second-order statistics of these fields is fully described by the spatiotemporal power spectrum, a real, positive function. Thus, the second-order statistics can be efficiently propagated in the wavevector-frequency representation using a new framework of deterministic signals associated with random fields. Analogous to the complex analytic signal representation of a field, the deterministic signal is a mathematical construct meant to simplify calculations. Specifically, the deterministic signal associated with a random field is defined such that it has the identical autocorrelation as the actual random field. Calculations for propagating spatial and temporal correlations are simplified greatly because one only needs to solve a deterministic wave equation of second order. We illustrate the power of the wavevector-frequency representation with calculations of spatial coherence in the far zone of an incoherent source, as well as coherence effects induced by biological tissues.

  9. Variational Infinite Hidden Conditional Random Fields.

    PubMed

    Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja; Ghahramani, Zoubin

    2015-09-01

    Hidden conditional random fields (HCRFs) are discriminative latent variable models which have been shown to successfully learn the hidden structure of a given classification problem. An Infinite hidden conditional random field is a hidden conditional random field with a countably infinite number of hidden states, which rids us not only of the necessity to specify a priori a fixed number of hidden states available but also of the problem of overfitting. Markov chain Monte Carlo (MCMC) sampling algorithms are often employed for inference in such models. However, convergence of such algorithms is rather difficult to verify, and as the complexity of the task at hand increases the computational cost of such algorithms often becomes prohibitive. These limitations can be overcome by variational techniques. In this paper, we present a generalized framework for infinite HCRF models, and a novel variational inference approach on a model based on coupled Dirichlet Process Mixtures, the HCRF-DPM. We show that the variational HCRF-DPM is able to converge to a correct number of represented hidden states, and performs as well as the best parametric HCRFs-chosen via cross-validation-for the difficult tasks of recognizing instances of agreement, disagreement, and pain in audiovisual sequences. PMID:26353136

  10. Field and intensity correlation in random media

    PubMed

    Sebbah; Pnini; Genack

    2000-11-01

    We have obtained the spectral and spatial field correlation functions, C(E)(Deltaomega) and C(E)(Deltax), respectively, from measurement of the microwave field spectrum at a series of points along a line on the output of a random dielectric medium. C(E)(Deltaomega) and C(E)(Deltax) are shown to be the Fourier transforms, respectively, of the time of flight distribution, obtained from pulsed measurements, and of the specific intensity. Unlike C(E)(Deltaomega), the imaginary part of C(E)(Deltax) is shown to vanish as a result of the isotropy of the correlation function in the output plane. The complex square of the field correlation function gives the short-range or C1 contribution to the intensity correlation function C. Longer-range contributions to the intensity correlation function are obtained directly by subtracting C1 from C and are in good agreement with theory.

  11. Learning Heterogeneous Hidden Markov Random Fields

    PubMed Central

    Liu, Jie; Zhang, Chunming; Burnside, Elizabeth; Page, David

    2014-01-01

    Hidden Markov random fields (HMRFs) are conventionally assumed to be homogeneous in the sense that the potential functions are invariant across different sites. However in some biological applications, it is desirable to make HMRFs heterogeneous, especially when there exists some background knowledge about how the potential functions vary. We formally define heterogeneous HMRFs and propose an EM algorithm whose M-step combines a contrastive divergence learner with a kernel smoothing step to incorporate the background knowledge. Simulations show that our algorithm is effective for learning heterogeneous HMRFs and outperforms alternative binning methods. We learn a heterogeneous HMRF in a real-world study. PMID:25404989

  12. The infinite hidden Markov random field model.

    PubMed

    Chatzis, Sotirios P; Tsechpenakis, Gabriel

    2010-06-01

    Hidden Markov random field (HMRF) models are widely used for image segmentation, as they appear naturally in problems where a spatially constrained clustering scheme is asked for. A major limitation of HMRF models concerns the automatic selection of the proper number of their states, i.e., the number of region clusters derived by the image segmentation procedure. Existing methods, including likelihood- or entropy-based criteria, and reversible Markov chain Monte Carlo methods, usually tend to yield noisy model size estimates while imposing heavy computational requirements. Recently, Dirichlet process (DP, infinite) mixture models have emerged in the cornerstone of nonparametric Bayesian statistics as promising candidates for clustering applications where the number of clusters is unknown a priori; infinite mixture models based on the original DP or spatially constrained variants of it have been applied in unsupervised image segmentation applications showing promising results. Under this motivation, to resolve the aforementioned issues of HMRF models, in this paper, we introduce a nonparametric Bayesian formulation for the HMRF model, the infinite HMRF model, formulated on the basis of a joint Dirichlet process mixture (DPM) and Markov random field (MRF) construction. We derive an efficient variational Bayesian inference algorithm for the proposed model, and we experimentally demonstrate its advantages over competing methodologies.

  13. Role of random electric fields in relaxors

    PubMed Central

    Phelan, Daniel; Stock, Christopher; Rodriguez-Rivera, Jose A.; Chi, Songxue; Leão, Juscelino; Long, Xifa; Xie, Yujuan; Bokov, Alexei A.; Ye, Zuo-Guang; Ganesh, Panchapakesan; Gehring, Peter M.

    2014-01-01

    PbZr1–xTixO3 (PZT) and Pb(Mg1/3Nb2/3)1–xTixO3 (PMN-xPT) are complex lead-oxide perovskites that display exceptional piezoelectric properties for pseudorhombohedral compositions near a tetragonal phase boundary. In PZT these compositions are ferroelectrics, but in PMN-xPT they are relaxors because the dielectric permittivity is frequency dependent and exhibits non-Arrhenius behavior. We show that the nanoscale structure unique to PMN-xPT and other lead-oxide perovskite relaxors is absent in PZT and correlates with a greater than 100% enhancement of the longitudinal piezoelectric coefficient in PMN-xPT relative to that in PZT. By comparing dielectric, structural, lattice dynamical, and piezoelectric measurements on PZT and PMN-xPT, two nearly identical compounds that represent weak and strong random electric field limits, we show that quenched (static) random fields establish the relaxor phase and identify the order parameter. PMID:24449912

  14. Enhanced diffusion in random velocity fields

    NASA Astrophysics Data System (ADS)

    Zumofen, G.; Klafter, J.; Blumen, A.

    1990-10-01

    We study superlinear diffusion in a layered medium containing random velocity fields, where the mean-squared displacement grows as ~tα with α>1 [S. Redner, Physica D 38, 287 (1989)]. For a two-dimensional system with preassigned random velocities in the longitudinal x direction and with diffusional motion in the transversal direction, we determine exactly the asymptotic behavior of the first three nontrivial moments M2m=/m of the displacement. Furthermore, we succeed in relating the diffusional problem to the one-dimensional trapping problem. We then are in a position to analyze the scaling form of the propagator P(x,t)~t-3/4f(x3/4), where the function f(z) obeys a complicated stretched exponential behavior. We also generalize the problem to transverse motion on fractals and ultrametric spaces that leads to α values that interpolate between 1 and 2. We support our theoretical analytical results by simulation calculations.

  15. Modeling stereopsis via Markov random field.

    PubMed

    Ming, Yansheng; Hu, Zhanyi

    2010-08-01

    Markov random field (MRF) and belief propagation have given birth to stereo vision algorithms with top performance. This article explores their biological plausibility. First, an MRF model guided by physiological and psychophysical facts was designed. Typically an MRF-based stereo vision algorithm employs a likelihood function that reflects the local similarity of two regions and a potential function that models the continuity constraint. In our model, the likelihood function is constructed on the basis of the disparity energy model because complex cells are considered as front-end disparity encoders in the visual pathway. Our likelihood function is also relevant to several psychological findings. The potential function in our model is constrained by the psychological finding that the strength of the cooperative interaction minimizing relative disparity decreases as the separation between stimuli increases. Our model is tested on three kinds of stereo images. In simulations on images with repetitive patterns, we demonstrate that our model could account for the human depth percepts that were previously explained by the second-order mechanism. In simulations on random dot stereograms and natural scene images, we demonstrate that false matches introduced by the disparity energy model can be reliably removed using our model. A comparison with the coarse-to-fine model shows that our model is able to compute the absolute disparity of small objects with larger relative disparity. We also relate our model to several physiological findings. The hypothesized neurons of the model are selective for absolute disparity and have facilitative extra receptive field. There are plenty of such neurons in the visual cortex. In conclusion, we think that stereopsis can be implemented by neural networks resembling MRF.

  16. Fusion moves for Markov random field optimization.

    PubMed

    Lempitsky, Victor; Rother, Carsten; Roth, Stefan; Blake, Andrew

    2010-08-01

    The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one possible way of achieving this by using graph cuts to combine pairs of suboptimal labelings or solutions. We call this combination process the fusion move. By employing recently developed graph-cut-based algorithms (so-called QPBO-graph cut), the fusion move can efficiently combine two proposal labelings in a theoretically sound way, which is in practice often globally optimal. We demonstrate that fusion moves generalize many previous graph-cut approaches, which allows them to be used as building blocks within a broader variety of optimization schemes than were considered before. In particular, we propose new optimization schemes for computer vision MRFs with applications to image restoration, stereo, and optical flow, among others. Within these schemes the fusion moves are used 1) for the parallelization of MRF optimization into several threads, 2) for fast MRF optimization by combining cheap-to-compute solutions, and 3) for the optimization of highly nonconvex continuous-labeled MRFs with 2D labels. Our final example is a nonvision MRF concerned with cartographic label placement, where fusion moves can be used to improve the performance of a standard inference method (loopy belief propagation).

  17. Leukocytes segmentation using Markov random fields.

    PubMed

    Reta, C; Gonzalez, J A; Diaz, R; Guichard, J S

    2011-01-01

    The segmentation of leukocytes and their components plays an important role in the extraction of geometric, texture, and morphological characteristics used to diagnose different diseases. This paper presents a novel method to segment leukocytes and their respective nucleus and cytoplasm from microscopic bone marrow leukemia cell images. Our method uses color and texture contextual information of image pixels to extract cellular elements from images, which show heterogeneous color and texture staining and high-cell population. The CIEL ( ∗ ) a ( ∗ ) b ( ∗ ) color space is used to extract color features, whereas a 2D Wold Decomposition model is applied to extract structural and stochastic texture features. The color and texture contextual information is incorporated into an unsupervised binary Markov Random Field segmentation model. Experimental results show the performance of the proposed method on both synthetic and real leukemia cell images. An average accuracy of 95% was achieved in the segmentation of real cell images by comparing those results with manually segmented cell images.

  18. Unmixing hyperspectral images using Markov random fields

    SciTech Connect

    Eches, Olivier; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2011-03-14

    This paper proposes a new spectral unmixing strategy based on the normal compositional model that exploits the spatial correlations between the image pixels. The pure materials (referred to as endmembers) contained in the image are assumed to be available (they can be obtained by using an appropriate endmember extraction algorithm), while the corresponding fractions (referred to as abundances) are estimated by the proposed algorithm. Due to physical constraints, the abundances have to satisfy positivity and sum-to-one constraints. The image is divided into homogeneous distinct regions having the same statistical properties for the abundance coefficients. The spatial dependencies within each class are modeled thanks to Potts-Markov random fields. Within a Bayesian framework, prior distributions for the abundances and the associated hyperparameters are introduced. A reparametrization of the abundance coefficients is proposed to handle the physical constraints (positivity and sum-to-one) inherent to hyperspectral imagery. The parameters (abundances), hyperparameters (abundance mean and variance for each class) and the classification map indicating the classes of all pixels in the image are inferred from the resulting joint posterior distribution. To overcome the complexity of the joint posterior distribution, Markov chain Monte Carlo methods are used to generate samples asymptotically distributed according to the joint posterior of interest. Simulations conducted on synthetic and real data are presented to illustrate the performance of the proposed algorithm.

  19. Is the Non-Dipole Magnetic Field Random?

    NASA Technical Reports Server (NTRS)

    Walker, Andrew D.; Backus, George E.

    1996-01-01

    Statistical modelling of the Earth's magnetic field B has a long history. In particular, the spherical harmonic coefficients of scalar fields derived from B can be treated as Gaussian random variables. In this paper, we give examples of highly organized fields whose spherical harmonic coefficients pass tests for independent Gaussian random variables. The fact that coefficients at some depth may be usefully summarized as independent samples from a normal distribution need not imply that there really is some physical, random process at that depth. In fact, the field can be extremely structured and still be regarded for some purposes as random. In this paper, we examined the radial magnetic field B(sub r) produced by the core, but the results apply to any scalar field on the core-mantle boundary (CMB) which determines B outside the CMB.

  20. Generating functionals for quantum field theories with random potentials

    NASA Astrophysics Data System (ADS)

    Jain, Mudit; Vanchurin, Vitaly

    2016-01-01

    We consider generating functionals for computing correlators in quantum field theories with random potentials. Examples of such theories include cosmological systems in context of the string theory landscape (e.g. cosmic inflation) or condensed matter systems with quenched disorder (e.g. spin glass). We use the so-called replica trick to define two different generating functionals for calculating correlators of the quantum fields averaged over a given distribution of random potentials. The first generating functional is appropriate for calculating averaged (in-out) amplitudes and involves a single replica of fields, but the replica limit is taken to an (unphysical) negative one number of fields outside of the path integral. When the number of replicas is doubled the generating functional can also be used for calculating averaged probabilities (squared amplitudes) using the in-in construction. The second generating functional involves an infinite number of replicas, but can be used for calculating both in-out and in-in correlators and the replica limits are taken to only a zero number of fields. We discuss the formalism in details for a single real scalar field, but the generalization to more fields or to different types of fields is straightforward. We work out three examples: one where the mass of scalar field is treated as a random variable and two where the functional form of interactions is random, one described by a Gaussian random field and the other by a Euclidean action in the field configuration space.

  1. Frequency of encounter of aircraft in a random horizontal field

    NASA Technical Reports Server (NTRS)

    Bird, J. D.; Smith, K. A.

    1976-01-01

    Calculations were made of the frequency of encounter as a function of azimuth of encounter of a passing aircraft with the aircraft in a random planar horizontal field. All the field aircraft moved at a constant speed but in random directions. These calculations included the total frequency of encounter with the aircraft of the field and the frequency of encounter with those aircraft of the field which were encountered in the fore quadrant, in the lateral quadrants, and in the rear quadrant; the calculations were made for various speed ratios of the field aircraft and the passing aircraft.

  2. Listening to the noise: random fluctuations reveal gene network parameters

    SciTech Connect

    Munsky, Brian; Khammash, Mustafa

    2009-01-01

    The cellular environment is abuzz with noise. The origin of this noise is attributed to the inherent random motion of reacting molecules that take part in gene expression and post expression interactions. In this noisy environment, clonal populations of cells exhibit cell-to-cell variability that frequently manifests as significant phenotypic differences within the cellular population. The stochastic fluctuations in cellular constituents induced by noise can be measured and their statistics quantified. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.

  3. Statistical analysis of loopy belief propagation in random fields

    NASA Astrophysics Data System (ADS)

    Yasuda, Muneki; Kataoka, Shun; Tanaka, Kazuyuki

    2015-10-01

    Loopy belief propagation (LBP), which is equivalent to the Bethe approximation in statistical mechanics, is a message-passing-type inference method that is widely used to analyze systems based on Markov random fields (MRFs). In this paper, we propose a message-passing-type method to analytically evaluate the quenched average of LBP in random fields by using the replica cluster variation method. The proposed analytical method is applicable to general pairwise MRFs with random fields whose distributions differ from each other and can give the quenched averages of the Bethe free energies over random fields, which are consistent with numerical results. The order of its computational cost is equivalent to that of standard LBP. In the latter part of this paper, we describe the application of the proposed method to Bayesian image restoration, in which we observed that our theoretical results are in good agreement with the numerical results for natural images.

  4. The space transformation in the simulation of multidimensional random fields

    USGS Publications Warehouse

    Christakos, G.

    1987-01-01

    Space transformations are proposed as a mathematically meaningful and practically comprehensive approach to simulate multidimensional random fields. Within this context the turning bands method of simulation is reconsidered and improved in both the space and frequency domains. ?? 1987.

  5. Subpixel translation-registration of random fields

    NASA Technical Reports Server (NTRS)

    Slud, Eric V.

    1988-01-01

    The author examines both theoretically and through a simulation study the feasibility of identifying the location within a large reference gray-level array of a smaller sensed array to an accuracy finer than one pixel. It is assumed that the sensed image before discretization into pixels consists of a translated, but not rotated, section of the reference image with some superposed noise. The theoretical and empirical results show that when the noise has standard deviation no larger than that of a realistic reference field, the upper quartile of the registration error is on the order of 0.25-0.5 pixels.

  6. Plane-wave decomposition of spatially random fields.

    PubMed

    Nguyen, Tan H; Majeed, Hassaan; Popescu, Gabriel

    2015-04-01

    We investigate the uniqueness of the plane-wave decomposition of temporally deterministic, spatially random fields. Specifically, we consider the decomposition of spatially ergodic and, thus, statistically homogeneous fields. We show that when the spatial power spectrum is injective, the plane waves are the only possible coherent modes. Furthermore, the randomness of such fields originates in the spatial spectral phase, i.e., the phase associated with the coefficients of each plane wave in the expansion. By contrast, the spectral amplitude is deterministic and is specified by the spatial power spectrum. We end with a discussion showing how the results can be translated in full to the time domain.

  7. Multilevel Compression of Random Walks on Networks Reveals Hierarchical Organization in Large Integrated Systems

    PubMed Central

    Rosvall, Martin; Bergstrom, Carl T.

    2011-01-01

    To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation, which reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker as a proxy for real flow on a network, we find regularities in the network that induce this system-wide flow. Finding the shortest multilevel description of the random walker therefore gives us the best hierarchical clustering of the network — the optimal number of levels and modular partition at each level — with respect to the dynamics on the network. With a novel search algorithm, we extract and illustrate the rich multilevel organization of several large social and biological networks. For example, from the global air traffic network we uncover countries and continents, and from the pattern of scientific communication we reveal more than 100 scientific fields organized in four major disciplines: life sciences, physical sciences, ecology and earth sciences, and social sciences. In general, we find shallow hierarchical structures in globally interconnected systems, such as neural networks, and rich multilevel organizations in systems with highly separated regions, such as road networks. PMID:21494658

  8. Rigorously testing multialternative decision field theory against random utility models.

    PubMed

    Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg

    2014-06-01

    Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions.

  9. Barkhausen noise in the random field Ising magnet Nd2Fe14B

    NASA Astrophysics Data System (ADS)

    Xu, J.; Silevitch, D. M.; Dahmen, K. A.; Rosenbaum, T. F.

    2015-07-01

    With sintered needles aligned and a magnetic field applied transverse to its easy axis, the rare-earth ferromagnet Nd2Fe14B becomes a room-temperature realization of the random field Ising model. The transverse field tunes the pinning potential of the magnetic domains in a continuous fashion. We study the magnetic domain reversal and avalanche dynamics between liquid helium and room temperatures at a series of transverse fields using a Barkhausen noise technique. The avalanche size and energy distributions follow power-law behavior with a cutoff dependent on the pinning strength dialed in by the transverse field, consistent with theoretical predictions for Barkhausen avalanches in disordered materials. A scaling analysis reveals two regimes of behavior: one at low temperature and high transverse field, where the dynamics are governed by the randomness, and the second at high temperature and low transverse field, where thermal fluctuations dominate the dynamics.

  10. Synchronization and Spin-Flop Transitions for a Mean-Field XY Model in Random Field

    NASA Astrophysics Data System (ADS)

    Collet, Francesca; Ruszel, Wioletta

    2016-08-01

    We characterize the phase space for the infinite volume limit of a ferromagnetic mean-field XY model in a random field pointing in one direction with two symmetric values. We determine the stationary solutions and detect possible phase transitions in the interaction strength for fixed random field intensity. We show that at low temperature magnetic ordering appears perpendicularly to the field. The latter situation corresponds to a spin-flop transition.

  11. Ubiquity of, and geostatistics for, nonstationary increment random fields

    NASA Astrophysics Data System (ADS)

    O'Malley, Daniel; Cushman, John H.

    2013-07-01

    Nonstationary random fields such as fractional Brownian motion and fractional Lévy motion have been studied extensively in the hydrology literature. On the other hand, random fields that have nonstationary increments have seen little study. A mathematical argument is presented that demonstrates processes with stationary increments are the exception and processes with nonstationary increments are far more abundant. The abundance of nonstationary increment processes has important implications, e.g., in kriging where a translation-invariant variogram implicitly assumes stationarity of the increments. An approach to kriging for processes with nonstationary increments is presented and accompanied by some numerical results.

  12. The spectral expansion of the elasticity random field

    SciTech Connect

    Malyarenko, Anatoliy; Ostoja-Starzewski, Martin

    2014-12-10

    We consider a deformable body that occupies a region D in the plane. In our model, the body’s elasticity tensor H(x) is the restriction to D of a second-order mean-square continuous random field. Under translation, the expected value and the correlation tensor of the field H(x) do not change. Under action of an arbitrary element k of the orthogonal group O(2), they transform according to the reducible orthogonal representation k ⟼ S{sup 2}(S{sup 2}(k)) of the above group. We find the spectral expansion of the correlation tensor R(x) of the elasticity field as well as the expansion of the field itself in terms of stochastic integrals with respect to a family of orthogonal scattered random measures.

  13. Probability Statements Extraction with Constrained Conditional Random Fields.

    PubMed

    Deleris, Léa A; Jochim, Charles

    2016-01-01

    This paper investigates how to extract probability statements from academic medical papers. In previous work we have explored traditional classification methods which led to numerous false negatives. This current work focuses on constraining classification output obtained from a Conditional Random Field (CRF) model to allow for domain knowledge constraints. Our experimental results indicate constraining leads to a significant improvement in performance. PMID:27577439

  14. A Multisite Cluster Randomized Field Trial of Open Court Reading

    ERIC Educational Resources Information Center

    Borman, Geoffrey D.; Dowling, N. Maritza; Schneck, Carrie

    2008-01-01

    In this article, the authors report achievement outcomes of a multisite cluster randomized field trial of Open Court Reading 2005 (OCR), a K-6 literacy curriculum published by SRA/McGraw-Hill. The participants are 49 first-grade through fifth-grade classrooms from predominantly minority and poor contexts across the nation. Blocking by grade level…

  15. Random vectorial fields representing the local structure of turbulence

    NASA Astrophysics Data System (ADS)

    Chevillard, Laurent; Robert, Raoul; Vargas, Vincent

    2011-12-01

    We propose a method to build up a random homogeneous, isotropic and incompressible turbulent velocity field that mimics turbulence in the inertial range. The underlying Gaussian field is given by a modified Biot-Savart law. The long range correlated nature of turbulence is then incorporated heuristically using a non linear transformation inspired by the recent fluid deformation imposed by the Euler equations. The resulting velocity field shows a non vanishing mean energy transfer towards the small scales and realistic alignment properties of vorticity with the eigenframe of the deformation rate.

  16. Cosmological fluctuations of a random field and radiation fluid

    SciTech Connect

    Bastero-Gil, Mar; Berera, Arjun; Moss, Ian G.; Ramos, Rudnei O. E-mail: ab@ph.ed.ac.uk E-mail: rudnei@uerj.br

    2014-05-01

    A generalization of the random fluid hydrodynamic fluctuation theory due to Landau and Lifshitz is applied to describe cosmological fluctuations in systems with radiation and scalar fields. The viscous pressures, parametrized in terms of the bulk and shear viscosity coefficients, and the respective random fluctuations in the radiation fluid are combined with the stochastic and dissipative scalar evolution equation. This results in a complete set of equations describing the perturbations in both scalar and radiation fluids. These derived equations are then studied, as an example, in the context of warm inflation. Similar treatments can be done for other cosmological early universe scenarios involving thermal or statistical fluctuations.

  17. Nonstationary random acoustic and electromagnetic fields as wave diffusion processes

    NASA Astrophysics Data System (ADS)

    Arnaut, L. R.

    2007-07-01

    We investigate the effects of relatively rapid variations of the boundaries of an overmoded cavity on the stochastic properties of its interior acoustic or electromagnetic field. For quasi-static variations, this field can be represented as an ideal incoherent and statistically homogeneous isotropic random scalar or vector field, respectively. A physical model is constructed showing that the field dynamics can be characterized as a generalized diffusion process. The Langevin-It\\hato and Fokker-Planck equations are derived and their associated statistics and distributions for the complex analytic field, its magnitude and energy density are computed. The energy diffusion parameter is found to be proportional to the square of the ratio of the standard deviation of the source field to the characteristic time constant of the dynamic process, but is independent of the initial energy density, to first order. The energy drift vanishes in the asymptotic limit. The time-energy probability distribution is in general not separable, as a result of nonstationarity. A general solution of the Fokker-Planck equation is obtained in integral form, together with explicit closed-form solutions for several asymptotic cases. The findings extend known results on statistics and distributions of quasi-stationary ideal random fields (pure diffusions), which are retrieved as special cases. A summary of selected results in this paper appeared in [1].

  18. Extreme value statistics of smooth Gaussian random fields

    NASA Astrophysics Data System (ADS)

    Colombi, Stéphane; Davis, Olaf; Devriendt, Julien; Prunet, Simon; Silk, Joe

    2011-07-01

    We consider the Gumbel or extreme value statistics describing the distribution function pG(νmax) of the maximum values of a random field ν within patches of fixed size. We present, for smooth Gaussian random fields in two and three dimensions, an analytical estimate of pG which is expected to hold in a regime where local maxima of the field are moderately high and weakly clustered. When the patch size becomes sufficiently large, the negative of the logarithm of the cumulative extreme value distribution is simply equal to the average of the Euler characteristic of the field in the excursion ν≥νmax inside the patches. The Gumbel statistics therefore represents an interesting alternative probe of the genus as a test of non-Gaussianity, e.g. in cosmic microwave background temperature maps or in 3D galaxy catalogues. It can be approximated, except in the remote positive tail, by a negative Weibull-type form, converging slowly to the expected Gumbel-type form for infinitely large patch size. Convergence is facilitated when large-scale correlations are weaker. We compare the analytic predictions to numerical experiments for the case of a scale-free Gaussian field in two dimensions, achieving impressive agreement between approximate theory and measurements. We also discuss the generalization of our formalism to non-Gaussian fields.

  19. Weak scattering of scalar and electromagnetic random fields

    NASA Astrophysics Data System (ADS)

    Tong, Zhisong

    This dissertation encompasses several studies relating to the theory of weak potential scattering of scalar and electromagnetic random, wide-sense statistically stationary fields from various types of deterministic or random linear media. The proposed theory is largely based on the first Born approximation for potential scattering and on the angular spectrum representation of fields. The main focus of the scalar counterpart of the theory is made on calculation of the second-order statistics of scattered light fields in cases when the scattering medium consists of several types of discrete particles with deterministic or random potentials. It is shown that the knowledge of the correlation properties for the particles of the same and different types, described with the newly introduced pair-scattering matrix, is crucial for determining the spectral and coherence states of the scattered radiation. The approach based on the pair-scattering matrix is then used for solving an inverse problem of determining the location of an "alien" particle within the scattering collection of "normal" particles, from several measurements of the spectral density of scattered light. Weak scalar scattering of light from a particulate medium in the presence of optical turbulence existing between the scattering centers is then approached using the combination of the Born's theory for treating the light interaction with discrete particles and the Rytov's theory for light propagation in extended turbulent medium. It is demonstrated how the statistics of scattered radiation depend on scattering potentials of particles and the power spectra of the refractive index fluctuations of turbulence. This theory is of utmost importance for applications involving atmospheric and oceanic light transmission. The second part of the dissertation includes the theoretical procedure developed for predicting the second-order statistics of the electromagnetic random fields, such as polarization and linear momentum

  20. Simulation of Radar Rainfall Fields: A Random Error Model

    NASA Astrophysics Data System (ADS)

    Aghakouchak, A.; Habib, E.; Bardossy, A.

    2008-12-01

    Precipitation is a major input in hydrological and meteorological models. It is believed that uncertainties due to input data will propagate in modeling hydrologic processes. Stochastically generated rainfall data are used as input to hydrological and meteorological models to assess model uncertainties and climate variability in water resources systems. The superposition of random errors of different sources is one of the main factors in uncertainty of radar estimates. One way to express these uncertainties is to stochastically generate random error fields to impose them on radar measurements in order to obtain an ensemble of radar rainfall estimates. In the method introduced here, the random error consists of two components: purely random error and dependent error on the indicator variable. Model parameters of the error model are estimated using a heteroscedastic maximum likelihood model in order to account for variance heterogeneity in radar rainfall error estimates. When reflectivity values are considered, the exponent and multiplicative factor of the Z-R relationship are estimated simultaneously with the model parameters. The presented model performs better compared to the previous approaches that generally result in unaccounted heteroscedasticity in error fields and thus radar ensemble.

  1. Contextual modeling of functional MR images with conditional random fields.

    PubMed

    Wang, Yang; Rajapakse, Jagath C

    2006-06-01

    This paper presents a conditional random field (CRF) approach to fuse contextual dependencies in functional magnetic resonance imaging (fMRI) data for the detection of brain activation. The interactions among both activation (activated/inactive) labels and observed data of brain voxels are unified in a probabilistic framework based on the CRF, where the interaction strength can be adaptively adjusted in terms of the data similarity of neighboring sites. Compared to earlier detection methods, including statistical parametric mapping and Markov random field, the proposed method avoids the suppression of high frequency information and relaxes the strong assumption of conditional independence of observed data. Experimental results show that the proposed approach effectively integrates contextual constraints within the detection process and robustly detects brain activities from fMRI data.

  2. Random point fields for paraparticles of any order

    NASA Astrophysics Data System (ADS)

    Tamura, Hiroshi; Ito, Keiichi R.

    2007-02-01

    Random point fields which describe gases consisting of paraparticles of any order p ɛN are given by means of the canonical ensemble approach. The analysis for the cases of the parafermion gases are discussed in full detail and it is shown that the partition functions are pth power of that of the usual (i.e., p =1) fermion. The same is true for parabosons.

  3. Computation of image spatial entropy using quadrilateral Markov random field.

    PubMed

    Razlighi, Qolamreza R; Kehtarnavaz, Nasser; Nosratinia, Aria

    2009-12-01

    Shannon entropy is a powerful tool in image analysis, but its reliable computation from image data faces an inherent dimensionality problem that calls for a low-dimensional and closed form model for the pixel value distributions. The most promising such models are Markovian, however, the conventional Markov random field is hampered by noncausality and its causal versions are also not free of difficulties. For example, the Markov mesh random field has its own limitations due to the strong diagonal dependency in its local neighboring system. A new model, named quadrilateral Markov random field (QMRF) is introduced in this paper in order to overcome these limitations. A property of QMRF with neighboring size of 2 is then used to decompose an image prior into a product of 2-D joint pdfs in which they are estimated using a joint histogram under the homogeneity assumption. In addition, the paper includes an extension of the introduced method to the computation of image spatial mutual information. Comparisons on synthesized images as well as two applications with real images are presented to motivate the developments in this paper and demonstrate the advantages in the performance of the introduced method over the existing ones.

  4. A ferromagnet in a continuously tunable random field.

    PubMed

    Silevitch, D M; Bitko, D; Brooke, J; Ghosh, S; Aeppli, G; Rosenbaum, T F

    2007-08-01

    Most physical and biological systems are disordered, even though the majority of theoretical models treat disorder as a weak perturbation. One particularly simple system is a ferromagnet approaching its Curie temperature, T(C), where all of the spins associated with partially filled atomic shells acquire parallel orientation. With the addition of disorder by way of chemical substitution, the Curie point is suppressed, but no qualitatively new phenomena appear in bulk measurements as long as the disorder is truly random on the atomic scale and not so large as to eliminate ferromagnetism entirely. Here we report the discovery that a simply measured magnetic response is singular above the Curie temperature of a model, disordered magnet, and that the associated singularity grows to an anomalous divergence at T(C). The origin of the singular response is the random internal field induced by an external magnetic field transverse to the favoured direction for magnetization. The fact that ferromagnets can be studied easily and with high precision using bulk susceptibility and a large variety of imaging tools will not only advance fundamental studies of the random field problem, but also suggests a mechanism for tuning the strength of domain wall pinning, the key to applications.

  5. Markov-random-field modeling for linear seismic tomography.

    PubMed

    Kuwatani, Tatsu; Nagata, Kenji; Okada, Masato; Toriumi, Mitsuhiro

    2014-10-01

    We apply the Markov-random-field model to linear seismic tomography and propose a method to estimate the hyperparameters for the smoothness and the magnitude of the noise. Optimal hyperparameters can be determined analytically by minimizing the free energy function, which is defined by marginalizing the evaluation function. In synthetic inversion tests under various settings, the assumed velocity structures are successfully reconstructed, which shows the effectiveness and robustness of the proposed method. The proposed mathematical framework can be applied to inversion problems in various fields in the natural sciences.

  6. Markov-random-field modeling for linear seismic tomography

    NASA Astrophysics Data System (ADS)

    Kuwatani, Tatsu; Nagata, Kenji; Okada, Masato; Toriumi, Mitsuhiro

    2014-10-01

    We apply the Markov-random-field model to linear seismic tomography and propose a method to estimate the hyperparameters for the smoothness and the magnitude of the noise. Optimal hyperparameters can be determined analytically by minimizing the free energy function, which is defined by marginalizing the evaluation function. In synthetic inversion tests under various settings, the assumed velocity structures are successfully reconstructed, which shows the effectiveness and robustness of the proposed method. The proposed mathematical framework can be applied to inversion problems in various fields in the natural sciences.

  7. Ising nanowire with random field at surface; its unconventional effects

    NASA Astrophysics Data System (ADS)

    Kaneyoshi, T.

    2016-10-01

    The phase diagrams and temperature dependences of total magnetization mT in an Ising nanowire with a random magnetic field at the surface are studied by the uses of the effective-field theory with correlations. Many unconventional and novel phenomena have been obtained in them, although one section of the system is consisted of one spin-1/2 surface shell atom and one spin-1/2 core atom and they are coupled with a positive or a negative shell-core exchange interaction.

  8. Statistical Downscaling Based on Spartan Spatial Random Fields

    NASA Astrophysics Data System (ADS)

    Hristopulos, Dionissios

    2010-05-01

    Stochastic methods of space-time interpolation and conditional simulation have been used in statistical downscaling approaches to increase the resolution of measured fields. One of the popular interpolation methods in geostatistics is kriging, also known as optimal interpolation in data assimilation. Kriging is a stochastic, linear interpolator which incorporates time/space variability by means of the variogram function. However, estimation of the variogram from data involves various assumptions and simplifications. At the same time, the high numerical complexity of kriging makes it difficult to use for very large data sets. We present a different approach based on the so-called Spartan Spatial Random Fields (SSRFs). SSRFs were motivated from classical field theories of statistical physics [1]. The SSRFs provide a different approach of parametrizing spatial dependence based on 'effective interactions,' which can be formulated based on general statistical principles or even incorporate physical constraints. This framework leads to a broad family of covariance functions [2], and it provides new perspectives in covariance parameter estimation and interpolation [3]. A significant advantage offered by SSRFs is reduced numerical complexity, which can lead to much faster codes for spatial interpolation and conditional simulation. In addition, on grids composed of rectangular cells, the SSRF representation leads to an explicit expression for the precision matrix (the inverse covariance). Therefore SSRFs could provide useful models of error covariance for data assimilation methods. We use simulated and real data to demonstrate SSRF properties and downscaled fields. keywords: interpolation, conditional simulation, precision matrix References [1] Hristopulos, D.T., 2003. Spartan Gibbs random field models for geostatistical applications, SIAM Journal in Scientific Computation, 24, 2125-2162. [2] Hristopulos, D.T., Elogne, S. N. 2007. Analytic properties and covariance

  9. Localization of disordered bosons and magnets in random fields

    SciTech Connect

    Yu, Xiaoquan; Müller, Markus

    2013-10-15

    We study localization properties of disordered bosons and spins in random fields at zero temperature. We focus on two representatives of different symmetry classes, hard-core bosons (XY magnets) and Ising magnets in random transverse fields, and contrast their physical properties. We describe localization properties using a locator expansion on general lattices. For 1d Ising chains, we find non-analytic behavior of the localization length as a function of energy at ω=0, ξ{sup −1}(ω)=ξ{sup −1}(0)+A|ω|{sup α}, with α vanishing at criticality. This contrasts with the much smoother behavior predicted for XY magnets. We use these results to approach the ordering transition on Bethe lattices of large connectivity K, which mimic the limit of high dimensionality. In both models, in the paramagnetic phase with uniform disorder, the localization length is found to have a local maximum at ω=0. For the Ising model, we find activated scaling at the phase transition, in agreement with infinite randomness studies. In the Ising model long range order is found to arise due to a delocalization and condensation initiated at ω=0, without a closing mobility gap. We find that Ising systems establish order on much sparser (fractal) subgraphs than XY models. Possible implications of these results for finite-dimensional systems are discussed. -- Highlights: •Study of localization properties of disordered bosons and spins in random fields. •Comparison between XY magnets (hard-core bosons) and Ising magnets. •Analysis of the nature of the magnetic transition in strong quenched disorder. •Ising magnets: activated scaling, no closing mobility gap at the transition. •Ising order emerges on sparser (fractal) support than XY order.

  10. Global diffusion of cosmic rays in random magnetic fields

    NASA Astrophysics Data System (ADS)

    Snodin, A. P.; Shukurov, A.; Sarson, G. R.; Bushby, P. J.; Rodrigues, L. F. S.

    2016-04-01

    The propagation of charged particles, including cosmic rays, in a partially ordered magnetic field is characterized by a diffusion tensor whose components depend on the particle's Larmor radius RL and the degree of order in the magnetic field. Most studies of the particle diffusion presuppose a scale separation between the mean and random magnetic fields (e.g. there being a pronounced minimum in the magnetic power spectrum at intermediate scales). Scale separation is often a good approximation in laboratory plasmas, but not in most astrophysical environments such as the interstellar medium (ISM). Modern simulations of the ISM have numerical resolution of the order of 1 pc, so the Larmor radius of the cosmic rays that dominate in energy density is at least 106 times smaller than the resolved scales. Large-scale simulations of cosmic ray propagation in the ISM thus rely on oversimplified forms of the diffusion tensor. We take the first steps towards a more realistic description of cosmic ray diffusion for such simulations, obtaining direct estimates of the diffusion tensor from test particle simulations in random magnetic fields (with the Larmor radius scale being fully resolved), for a range of particle energies corresponding to 10-2 ≲ RL/lc ≲ 103, where lc is the magnetic correlation length. We obtain explicit expressions for the cosmic ray diffusion tensor for RL/lc ≪ 1, that might be used in a sub-grid model of cosmic ray diffusion. The diffusion coefficients obtained are closely connected with existing transport theories that include the random walk of magnetic lines.

  11. Utilizing Gaussian Markov random field properties of Bayesian animal models.

    PubMed

    Steinsland, Ingelin; Jensen, Henrik

    2010-09-01

    In this article, we demonstrate how Gaussian Markov random field properties give large computational benefits and new opportunities for the Bayesian animal model. We make inference by computing the posteriors for important quantitative genetic variables. For the single-trait animal model, a nonsampling-based approximation is presented. For the multitrait model, we set up a robust and fast Markov chain Monte Carlo algorithm. The proposed methodology was used to analyze quantitative genetic properties of morphological traits of a wild house sparrow population. Results for single- and multitrait models were compared.

  12. PREDICTION INTERVALS FOR INTEGRALS OF GAUSSIAN RANDOM FIELDS

    PubMed Central

    De Oliveira, Victor; Kone, Bazoumana

    2014-01-01

    Methodology is proposed for the construction of prediction intervals for integrals of Gaussian random fields over bounded regions (called block averages in the geostatistical literature) based on observations at a finite set of sampling locations. Two bootstrap calibration algorithms are proposed, termed indirect and direct, aimed at improving upon plug-in prediction intervals in terms of coverage probability. A simulation study is carried out that illustrates the effectiveness of both procedures, and these procedures are applied to estimate block averages of chromium traces in a potentially contaminated region in Switzerland. PMID:25431507

  13. Markov random fields for static foreground classification in surveillance systems

    NASA Astrophysics Data System (ADS)

    Fitzsimons, Jack K.; Lu, Thomas T.

    2014-09-01

    We present a novel technique for classifying static foreground in automated airport surveillance systems between abandoned and removed objects by representing the image as a Markov Random Field. The proposed algorithm computes and compares the net probability of the region of interest before and after the event occurs, hence finding which fits more naturally with their respective backgrounds. Having tested on a dataset from the PETS 2006, PETS 2007, AVSS20074, CVSG, VISOR, CANDELA and WCAM datasets, the algorithm has shown capable of matching the results of the state-of-the-art, is highly parallel and has a degree of robustness to noise and illumination changes.

  14. Parsing Citations in Biomedical Articles Using Conditional Random Fields

    PubMed Central

    Zhang, Qing; Cao, Yong-Gang; Yu, Hong

    2011-01-01

    Citations are used ubiquitously in biomedical full-text articles and play an important role for representing both the rhetorical structure and the semantic content of the articles. As a result, text mining systems will significantly benefit from a tool that automatically extracts the content of a citation. In this study, we applied the supervised machine-learning algorithms Conditional Random Fields (CRFs) to automatically parse a citation into its fields (e.g., Author, Title, Journal, and Year). With a subset of html format open-access PubMed Central articles, we report an overall 97.95% F1-score. The citation parser can be accessed at: http://www.cs.uwm.edu/~qing/projects/cithit/index.html. PMID:21419403

  15. Correlated continuous-time random walks in external force fields

    NASA Astrophysics Data System (ADS)

    Magdziarz, Marcin; Metzler, Ralf; Szczotka, Wladyslaw; Zebrowski, Piotr

    2012-05-01

    We study the anomalous diffusion of a particle in an external force field whose motion is governed by nonrenewal continuous time random walks with correlated waiting times. In this model the current waiting time Ti is equal to the previous waiting time Ti-1 plus a small increment. Based on the associated coupled Langevin equations the force field is systematically introduced. We show that in a confining potential the relaxation dynamics follows power-law or stretched exponential pattern, depending on the model parameters. The process obeys a generalized Einstein-Stokes-Smoluchowski relation and observes the second Einstein relation. The stationary solution is of Boltzmann-Gibbs form. The case of an harmonic potential is discussed in some detail. We also show that the process exhibits aging and ergodicity breaking.

  16. Random field Ising model and community structure in complex networks

    NASA Astrophysics Data System (ADS)

    Son, S.-W.; Jeong, H.; Noh, J. D.

    2006-04-01

    We propose a method to determine the community structure of a complex network. In this method the ground state problem of a ferromagnetic random field Ising model is considered on the network with the magnetic field Bs = +∞, Bt = -∞, and Bi≠s,t=0 for a node pair s and t. The ground state problem is equivalent to the so-called maximum flow problem, which can be solved exactly numerically with the help of a combinatorial optimization algorithm. The community structure is then identified from the ground state Ising spin domains for all pairs of s and t. Our method provides a criterion for the existence of the community structure, and is applicable equally well to unweighted and weighted networks. We demonstrate the performance of the method by applying it to the Barabási-Albert network, Zachary karate club network, the scientific collaboration network, and the stock price correlation network. (Ising, Potts, etc.)

  17. Measuring marine oil spill extent by Markov Random Fields

    NASA Astrophysics Data System (ADS)

    Moctezuma, Miguel; Parmiggiani, Flavio; Lopez Lopez, Ludwin

    2014-10-01

    The Deepwater Horizon oil spill of the Gulf of Mexico in the spring of 2010 was the largest accidental marine oil spill in the history of the petroleum industry. An immediate request, after the accident, was to detect the oil slick and to measure its extent: SAR images were the obvious tool to be employed for the task. This paper presents a processing scheme based on Markov Random Fields (MRF) theory. MRF theory describes the global information by probability terms involving local neighborhood representations of the SAR backscatter data. The random degradation introduced by speckle noise is dealt with a pre-processing stage which applies a nonlinear diffusion filter. Spatial context attributes are structured by the Bayes equation derived from a Maximum-A-Posteriori (MAP) estimation. The probability terms define an objective function of a MRF model whose goal is to detect contours and fine structures. The markovian segmentation problem is solved with a numerical optimization method. The scheme was applied to an Envisat/ASAR image over the Gulf of Mexico of May 9, 2010, when the oil spill was already fully developed. The final result was obtained with 51 recursion cycles, where, at each step, the segmentation consists of a 3-class label field (open sea and two oil slick thicknesses). Both the MRF model and the parameters of the stochastic optimization procedure will be provided, together with the area measurement of the two kinds of oil slick.

  18. Internetwork magnetic field as revealed by two-dimensional inversions

    NASA Astrophysics Data System (ADS)

    Danilovic, S.; van Noort, M.; Rempel, M.

    2016-09-01

    Context. Properties of magnetic field in the internetwork regions are still fairly unknown because of rather weak spectropolarimetric signals. Aims: We address the matter by using the two-dimensional (2D) inversion code, which is able to retrieve the information on smallest spatial scales up to the diffraction limit, while being less susceptible to noise than most of the previous methods used. Methods: Performance of the code and the impact of various effects on the retrieved field distribution is tested first on the realistic magneto-hydrodynamic (MHD) simulations. The best inversion scenario is then applied to the real data obtained by Spectropolarimeter (SP) on board Hinode. Results: Tests on simulations show that: (1) the best choice of node position ensures a decent retrieval of all parameters; (2) the code performs well for different configurations of magnetic field; (3) slightly different noise levels or slightly different defocus included in the spatial point spread function (PSF) produces no significant effect on the results; and (4) temporal integration shifts the field distribution to a stronger, more horizontally inclined field. Conclusions: Although the contribution of the weak field is slightly overestimated owing to noise, 2D inversions are able to recover well the overall distribution of the magnetic field strength. Application of the 2D inversion code on the Hinode SP internetwork observations reveals a monotonic field strength distribution. The mean field strength at optical depth unity is ~ 130 G. At higher layers, field strength drops as the field becomes more horizontal. Regarding the distribution of the field inclination, tests show that we cannot directly retrieve it with the observations and tools at hand, however, the obtained distributions are consistent with those expected from simulations with a quasi-isotropic field inclination after accounting for observational effects.

  19. Distributed estimation of a parametric field with random sensor placements

    NASA Astrophysics Data System (ADS)

    Alkhweldi, Marwan; Cao, Zhicheng; Schmid, Natalia A.

    2015-05-01

    This paper considers a problem of distributed function estimation in the case when sensor locations are modeled as Gaussian random variables. We consider a scenario where sensors are deployed in clusters with cluster centers known a priori (or estimated by a high performance GPS) and the average quadratic spread of sensors around the cluster center also known. Distributed sensors make noisy observations about an unknown parametric field generated by a physical object of interest (for example, magnetic field generated by a ferrous object and sensed by a network of magnetometers). Each sensor then performs local signal processing of its noisy observation and sends it to a central processor (called fusion center) in the wireless sensor network over parallel channels corrupted by fading and additive noise. The central processor combines the set of received signals to form an estimate of the unknown parametric field. In our numerical analysis, we involve a field shaped as a Gaussian bell. We experiment with the size of sensor clusters and with their number. A mean square error between the estimated parameters of the field and the true parameters used in simulations is involved as a performance measure. It can be shown that a relatively good estimate of the field can be obtained with only a small number of clusters. As the number of clusters increases, the estimation performance steadily improves. The results also indicate that, on the average, the number of clusters has more impact on the performance than the number of sensors per cluster, given the same size of the total network.

  20. Fuzzy Markov random fields versus chains for multispectral image segmentation.

    PubMed

    Salzenstein, Fabien; Collet, Christophe

    2006-11-01

    This paper deals with a comparison of recent statistical models based on fuzzy Markov random fields and chains for multispectral image segmentation. The fuzzy scheme takes into account discrete and continuous classes which model the imprecision of the hidden data. In this framework, we assume the dependence between bands and we express the general model for the covariance matrix. A fuzzy Markov chain model is developed in an unsupervised way. This method is compared with the fuzzy Markovian field model previously proposed by one of the authors. The segmentation task is processed with Bayesian tools, such as the well-known MPM (Mode of Posterior Marginals) criterion. Our goal is to compare the robustness and rapidity for both methods (fuzzy Markov fields versus fuzzy Markov chains). Indeed, such fuzzy-based procedures seem to be a good answer, e.g., for astronomical observations when the patterns present diffuse structures. Moreover, these approaches allow us to process missing data in one or several spectral bands which correspond to specific situations in astronomy. To validate both models, we perform and compare the segmentation on synthetic images and raw multispectral astronomical data.

  1. Fuzzy Markov random fields versus chains for multispectral image segmentation.

    PubMed

    Salzenstein, Fabien; Collet, Christophe

    2006-11-01

    This paper deals with a comparison of recent statistical models based on fuzzy Markov random fields and chains for multispectral image segmentation. The fuzzy scheme takes into account discrete and continuous classes which model the imprecision of the hidden data. In this framework, we assume the dependence between bands and we express the general model for the covariance matrix. A fuzzy Markov chain model is developed in an unsupervised way. This method is compared with the fuzzy Markovian field model previously proposed by one of the authors. The segmentation task is processed with Bayesian tools, such as the well-known MPM (Mode of Posterior Marginals) criterion. Our goal is to compare the robustness and rapidity for both methods (fuzzy Markov fields versus fuzzy Markov chains). Indeed, such fuzzy-based procedures seem to be a good answer, e.g., for astronomical observations when the patterns present diffuse structures. Moreover, these approaches allow us to process missing data in one or several spectral bands which correspond to specific situations in astronomy. To validate both models, we perform and compare the segmentation on synthetic images and raw multispectral astronomical data. PMID:17063681

  2. Submodular Relaxation for Inference in Markov Random Fields.

    PubMed

    Osokin, Anton; Vetrov, Dmitry P

    2015-07-01

    In this paper we address the problem of finding the most probable state of a discrete Markov random field (MRF), also known as the MRF energy minimization problem. The task is known to be NP-hard in general and its practical importance motivates numerous approximate algorithms. We propose a submodular relaxation approach (SMR) based on a Lagrangian relaxation of the initial problem. Unlike the dual decomposition approach of Komodakis et al. [29] SMR does not decompose the graph structure of the initial problem but constructs a submodular energy that is minimized within the Lagrangian relaxation. Our approach is applicable to both pairwise and high-order MRFs and allows to take into account global potentials of certain types. We study theoretical properties of the proposed approach and evaluate it experimentally.

  3. A Markov random field approach for microstructure synthesis

    NASA Astrophysics Data System (ADS)

    Kumar, A.; Nguyen, L.; DeGraef, M.; Sundararaghavan, V.

    2016-03-01

    We test the notion that many microstructures have an underlying stationary probability distribution. The stationary probability distribution is ubiquitous: we know that different windows taken from a polycrystalline microstructure are generally ‘statistically similar’. To enable computation of such a probability distribution, microstructures are represented in the form of undirected probabilistic graphs called Markov Random Fields (MRFs). In the model, pixels take up integer or vector states and interact with multiple neighbors over a window. Using this lattice structure, algorithms are developed to sample the conditional probability density for the state of each pixel given the known states of its neighboring pixels. The sampling is performed using reference experimental images. 2D microstructures are artificially synthesized using the sampled probabilities. Statistical features such as grain size distribution and autocorrelation functions closely match with those of the experimental images. The mechanical properties of the synthesized microstructures were computed using the finite element method and were also found to match the experimental values.

  4. Phase unwrapping using region-based markov random field model.

    PubMed

    Dong, Ying; Ji, Jim

    2010-01-01

    Phase unwrapping is a classical problem in Magnetic Resonance Imaging (MRI), Interferometric Synthetic Aperture Radar and Sonar (InSAR/InSAS), fringe pattern analysis, and spectroscopy. Although many methods have been proposed to address this problem, robust and effective phase unwrapping remains a challenge. This paper presents a novel phase unwrapping method using a region-based Markov Random Field (MRF) model. Specifically, the phase image is segmented into regions within which the phase is not wrapped. Then, the phase image is unwrapped between different regions using an improved Highest Confidence First (HCF) algorithm to optimize the MRF model. The proposed method has desirable theoretical properties as well as an efficient implementation. Simulations and experimental results on MRI images show that the proposed method provides similar or improved phase unwrapping than Phase Unwrapping MAx-flow/min-cut (PUMA) method and ZpM method.

  5. Causal Markov random field for brain MR image segmentation.

    PubMed

    Razlighi, Qolamreza R; Orekhov, Aleksey; Laine, Andrew; Stern, Yaakov

    2012-01-01

    We propose a new Bayesian classifier, based on the recently introduced causal Markov random field (MRF) model, Quadrilateral MRF (QMRF). We use a second order inhomogeneous anisotropic QMRF to model the prior and likelihood probabilities in the maximum a posteriori (MAP) classifier, named here as MAP-QMRF. The joint distribution of QMRF is given in terms of the product of two dimensional clique distributions existing in its neighboring structure. 20 manually labeled human brain MR images are used to train and assess the MAP-QMRF classifier using the jackknife validation method. Comparing the results of the proposed classifier and FreeSurfer on the Dice overlap measure shows an average gain of 1.8%. We have performed a power analysis to demonstrate that this increase in segmentation accuracy substantially reduces the number of samples required to detect a 5% change in volume of a brain region.

  6. Multiple testing for neuroimaging via hidden Markov random field.

    PubMed

    Shu, Hai; Nan, Bin; Koeppe, Robert

    2015-09-01

    Traditional voxel-level multiple testing procedures in neuroimaging, mostly p-value based, often ignore the spatial correlations among neighboring voxels and thus suffer from substantial loss of power. We extend the local-significance-index based procedure originally developed for the hidden Markov chain models, which aims to minimize the false nondiscovery rate subject to a constraint on the false discovery rate, to three-dimensional neuroimaging data using a hidden Markov random field model. A generalized expectation-maximization algorithm for maximizing the penalized likelihood is proposed for estimating the model parameters. Extensive simulations show that the proposed approach is more powerful than conventional false discovery rate procedures. We apply the method to the comparison between mild cognitive impairment, a disease status with increased risk of developing Alzheimer's or another dementia, and normal controls in the FDG-PET imaging study of the Alzheimer's Disease Neuroimaging Initiative.

  7. CAUSAL MARKOV RANDOM FIELD FOR BRAIN MR IMAGE SEGMENTATION

    PubMed Central

    Razlighi, Qolamreza R.; Orekhov, Aleksey; Laine, Andrew; Stern, Yaakov

    2013-01-01

    We propose a new Bayesian classifier, based on the recently introduced causal Markov random field (MRF) model, Quadrilateral MRF (QMRF). We use a second order inhomogeneous anisotropic QMRF to model the prior and likelihood probabilities in the maximum a posteriori (MAP) classifier, named here as MAP-QMRF. The joint distribution of QMRF is given in terms of the product of two dimensional clique distributions existing in its neighboring structure. 20 manually labeled human brain MR images are used to train and assess the MAP-QMRF classifier using the jackknife validation method. Comparing the results of the proposed classifier and FreeSurfer on the Dice overlap measure shows an average gain of 1.8%. We have performed a power analysis to demonstrate that this increase in segmentation accuracy substantially reduces the number of samples required to detect a 5% change in volume of a brain region. PMID:23366607

  8. Phase unwrapping using region-based markov random field model.

    PubMed

    Dong, Ying; Ji, Jim

    2010-01-01

    Phase unwrapping is a classical problem in Magnetic Resonance Imaging (MRI), Interferometric Synthetic Aperture Radar and Sonar (InSAR/InSAS), fringe pattern analysis, and spectroscopy. Although many methods have been proposed to address this problem, robust and effective phase unwrapping remains a challenge. This paper presents a novel phase unwrapping method using a region-based Markov Random Field (MRF) model. Specifically, the phase image is segmented into regions within which the phase is not wrapped. Then, the phase image is unwrapped between different regions using an improved Highest Confidence First (HCF) algorithm to optimize the MRF model. The proposed method has desirable theoretical properties as well as an efficient implementation. Simulations and experimental results on MRI images show that the proposed method provides similar or improved phase unwrapping than Phase Unwrapping MAx-flow/min-cut (PUMA) method and ZpM method. PMID:21096819

  9. Multiple testing for neuroimaging via hidden Markov random field.

    PubMed

    Shu, Hai; Nan, Bin; Koeppe, Robert

    2015-09-01

    Traditional voxel-level multiple testing procedures in neuroimaging, mostly p-value based, often ignore the spatial correlations among neighboring voxels and thus suffer from substantial loss of power. We extend the local-significance-index based procedure originally developed for the hidden Markov chain models, which aims to minimize the false nondiscovery rate subject to a constraint on the false discovery rate, to three-dimensional neuroimaging data using a hidden Markov random field model. A generalized expectation-maximization algorithm for maximizing the penalized likelihood is proposed for estimating the model parameters. Extensive simulations show that the proposed approach is more powerful than conventional false discovery rate procedures. We apply the method to the comparison between mild cognitive impairment, a disease status with increased risk of developing Alzheimer's or another dementia, and normal controls in the FDG-PET imaging study of the Alzheimer's Disease Neuroimaging Initiative. PMID:26012881

  10. Markov random-field-based anomaly screening algorithm

    NASA Astrophysics Data System (ADS)

    Bello, Martin G.

    1995-06-01

    A novel anomaly screening algorithm is described which makes use of a regression diagnostic associated with the fitting of Markov Random Field (MRF) models. This regression diagnostic quantifies the extent to which a given neighborhood of pixels is atypical, relative to local background characteristics. The screening algorithm consists first in the calculation of an MRF-based anomoly statistic values. Next, 'blob' features, such as pixel count and maximal pixel intensity are calculated, and ranked over the image, in order to 'filter' the blobs to some final subset of most likely candidates. Receiver operating characteristics obtained from applying the above described screening algorithm to the detection of minelike targets in high- and low-frequency side-scan sonar imagery are presented together with results obtained from other screening algorithms for comparison, demonstrating performance comparable to trained human operators. In addition, real-time implementation considerations associated with each algorithmic component of the described procedure are identified.

  11. Glaucoma progression detection using nonlocal Markov random field prior.

    PubMed

    Belghith, Akram; Bowd, Christopher; Medeiros, Felipe A; Balasubramanian, Madhusudhanan; Weinreb, Robert N; Zangwill, Linda M

    2014-10-01

    Glaucoma is neurodegenerative disease characterized by distinctive changes in the optic nerve head and visual field. Without treatment, glaucoma can lead to permanent blindness. Therefore, monitoring glaucoma progression is important to detect uncontrolled disease and the possible need for therapy advancement. In this context, three-dimensional (3-D) spectral domain optical coherence tomography (SD-OCT) has been commonly used in the diagnosis and management of glaucoma patients. We present a new framework for detection of glaucoma progression using 3-D SD-OCT images. In contrast to previous works that use the retinal nerve fiber layer thickness measurement provided by commercially available instruments, we consider the whole 3-D volume for change detection. To account for the spatial voxel dependency, we propose the use of the Markov random field (MRF) model as a prior for the change detection map. In order to improve the robustness of the proposed approach, a nonlocal strategy was adopted to define the MRF energy function. To accommodate the presence of false-positive detection, we used a fuzzy logic approach to classify a 3-D SD-OCT image into a "non-progressing" or "progressing" glaucoma class. We compared the diagnostic performance of the proposed framework to the existing methods of progression detection.

  12. Learning dynamic hybrid Markov random field for image labeling.

    PubMed

    Zhou, Quan; Zhu, Jun; Liu, Wenyu

    2013-06-01

    Using shape information has gained increasing concerns in the task of image labeling. In this paper, we present a dynamic hybrid Markov random field (DHMRF), which explicitly captures middle-level object shape and low-level visual appearance (e.g., texture and color) for image labeling. Each node in DHMRF is described by either a deformable template or an appearance model as visual prototype. On the other hand, the edges encode two types of intersections: co-occurrence and spatial layered context, with respect to the labels and prototypes of connected nodes. To learn the DHMRF model, an iterative algorithm is designed to automatically select the most informative features and estimate model parameters. The algorithm achieves high computational efficiency since a branch-and-bound schema is introduced to estimate model parameters. Compared with previous methods, which usually employ implicit shape cues, our DHMRF model seamlessly integrates color, texture, and shape cues to inference labeling output, and thus produces more accurate and reliable results. Extensive experiments validate its superiority over other state-of-the-art methods in terms of recognition accuracy and implementation efficiency on: 1) the MSRC 21-class dataset, and 2) the lotus hill institute 15-class dataset.

  13. A Markov Random Field Groupwise Registration Framework for Face Recognition.

    PubMed

    Liao, Shu; Shen, Dinggang; Chung, Albert C S

    2014-04-01

    In this paper, we propose a new framework for tackling face recognition problem. The face recognition problem is formulated as groupwise deformable image registration and feature matching problem. The main contributions of the proposed method lie in the following aspects: (1) Each pixel in a facial image is represented by an anatomical signature obtained from its corresponding most salient scale local region determined by the survival exponential entropy (SEE) information theoretic measure. (2) Based on the anatomical signature calculated from each pixel, a novel Markov random field based groupwise registration framework is proposed to formulate the face recognition problem as a feature guided deformable image registration problem. The similarity between different facial images are measured on the nonlinear Riemannian manifold based on the deformable transformations. (3) The proposed method does not suffer from the generalizability problem which exists commonly in learning based algorithms. The proposed method has been extensively evaluated on four publicly available databases: FERET, CAS-PEAL-R1, FRGC ver 2.0, and the LFW. It is also compared with several state-of-the-art face recognition approaches, and experimental results demonstrate that the proposed method consistently achieves the highest recognition rates among all the methods under comparison.

  14. A Markov Random Field Groupwise Registration Framework for Face Recognition

    PubMed Central

    Liao, Shu; Shen, Dinggang; Chung, Albert C.S.

    2014-01-01

    In this paper, we propose a new framework for tackling face recognition problem. The face recognition problem is formulated as groupwise deformable image registration and feature matching problem. The main contributions of the proposed method lie in the following aspects: (1) Each pixel in a facial image is represented by an anatomical signature obtained from its corresponding most salient scale local region determined by the survival exponential entropy (SEE) information theoretic measure. (2) Based on the anatomical signature calculated from each pixel, a novel Markov random field based groupwise registration framework is proposed to formulate the face recognition problem as a feature guided deformable image registration problem. The similarity between different facial images are measured on the nonlinear Riemannian manifold based on the deformable transformations. (3) The proposed method does not suffer from the generalizability problem which exists commonly in learning based algorithms. The proposed method has been extensively evaluated on four publicly available databases: FERET, CAS-PEAL-R1, FRGC ver 2.0, and the LFW. It is also compared with several state-of-the-art face recognition approaches, and experimental results demonstrate that the proposed method consistently achieves the highest recognition rates among all the methods under comparison. PMID:25506109

  15. Conditional random fields for pattern recognition applied to structured data

    DOE PAGESBeta

    Burr, Tom; Skurikhin, Alexei

    2015-07-14

    Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features between parts of the modelmore » are often correlated. Therefore, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.« less

  16. GAUSSIAN RANDOM FIELD: PHYSICAL ORIGIN OF SERSIC PROFILES

    SciTech Connect

    Cen, Renyue

    2014-08-01

    While the Sersic profile family provides adequate fits for the surface brightness profiles of observed galaxies, its physical origin is unknown. We show that if the cosmological density field is seeded by random Gaussian fluctuations, as in the standard cold dark matter model, galaxies with steep central profiles have simultaneously extended envelopes of shallow profiles in the outskirts, whereas galaxies with shallow central profiles are accompanied by steep density profiles in the outskirts. These properties are in accord with those of the Sersic profile family. Moreover, galaxies with steep central profiles form their central regions in smaller denser subunits that possibly merge subsequently, which naturally leads to the formation of bulges. In contrast, galaxies with shallow central profiles form their central regions in a coherent fashion without significant substructure, a necessary condition for disk galaxy formation. Thus, the scenario is self-consistent with respect to the correlation between observed galaxy morphology and the Sersic index. We further predict that clusters of galaxies should display a similar trend, which should be verifiable observationally.

  17. Infinite hidden conditional random fields for human behavior analysis.

    PubMed

    Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja

    2013-01-01

    Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time. PMID:24808217

  18. Wavelet variance analysis for random fields on a regular lattice.

    PubMed

    Mondal, Debashis; Percival, Donald B

    2012-02-01

    There has been considerable recent interest in using wavelets to analyze time series and images that can be regarded as realizations of certain 1-D and 2-D stochastic processes on a regular lattice. Wavelets give rise to the concept of the wavelet variance (or wavelet power spectrum), which decomposes the variance of a stochastic process on a scale-by-scale basis. The wavelet variance has been applied to a variety of time series, and a statistical theory for estimators of this variance has been developed. While there have been applications of the wavelet variance in the 2-D context (in particular, in works by Unser in 1995 on wavelet-based texture analysis for images and by Lark and Webster in 2004 on analysis of soil properties), a formal statistical theory for such analysis has been lacking. In this paper, we develop the statistical theory by generalizing and extending some of the approaches developed for time series, thus leading to a large-sample theory for estimators of 2-D wavelet variances. We apply our theory to simulated data from Gaussian random fields with exponential covariances and from fractional Brownian surfaces. We demonstrate that the wavelet variance is potentially useful for texture discrimination. We also use our methodology to analyze images of four types of clouds observed over the southeast Pacific Ocean.

  19. Conditional random fields for pattern recognition applied to structured data

    SciTech Connect

    Burr, Tom; Skurikhin, Alexei

    2015-07-14

    Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.

  20. On random field Completely Automated Public Turing Test to Tell Computers and Humans Apart generation.

    PubMed

    Kouritzin, Michael A; Newton, Fraser; Wu, Biao

    2013-04-01

    Herein, we propose generating CAPTCHAs through random field simulation and give a novel, effective and efficient algorithm to do so. Indeed, we demonstrate that sufficient information about word tests for easy human recognition is contained in the site marginal probabilities and the site-to-nearby-site covariances and that these quantities can be embedded directly into certain conditional probabilities, designed for effective simulation. The CAPTCHAs are then partial random realizations of the random CAPTCHA word. We start with an initial random field (e.g., randomly scattered letter pieces) and use Gibbs resampling to re-simulate portions of the field repeatedly using these conditional probabilities until the word becomes human-readable. The residual randomness from the initial random field together with the random implementation of the CAPTCHA word provide significant resistance to attack. This results in a CAPTCHA, which is unrecognizable to modern optical character recognition but is recognized about 95% of the time in a human readability study.

  1. The Sherrington-Kirkpatrick spin glass model in the presence of a random field with a joint Gaussian probability density function for the exchange interactions and random fields

    NASA Astrophysics Data System (ADS)

    Hadjiagapiou, Ioannis A.

    2014-03-01

    The magnetic systems with disorder form an important class of systems, which are under intensive studies, since they reflect real systems. Such a class of systems is the spin glass one, which combines randomness and frustration. The Sherrington-Kirkpatrick Ising spin glass with random couplings in the presence of a random magnetic field is investigated in detail within the framework of the replica method. The two random variables (exchange integral interaction and random magnetic field) are drawn from a joint Gaussian probability density function characterized by a correlation coefficient ρ. The thermodynamic properties and phase diagrams are studied with respect to the natural parameters of both random components of the system contained in the probability density. The de Almeida-Thouless line is explored as a function of temperature, ρ and other system parameters. The entropy for zero temperature as well as for non zero temperatures is partly negative or positive, acquiring positive branches as h0 increases.

  2. Theory and generation of conditional, scalable sub-Gaussian random fields

    NASA Astrophysics Data System (ADS)

    Panzeri, M.; Riva, M.; Guadagnini, A.; Neuman, S. P.

    2016-03-01

    Many earth and environmental (as well as a host of other) variables, Y, and their spatial (or temporal) increments, ΔY, exhibit non-Gaussian statistical scaling. Previously we were able to capture key aspects of such non-Gaussian scaling by treating Y and/or ΔY as sub-Gaussian random fields (or processes). This however left unaddressed the empirical finding that whereas sample frequency distributions of Y tend to display relatively mild non-Gaussian peaks and tails, those of ΔY often reveal peaks that grow sharper and tails that become heavier with decreasing separation distance or lag. Recently we proposed a generalized sub-Gaussian model (GSG) which resolves this apparent inconsistency between the statistical scaling behaviors of observed variables and their increments. We presented an algorithm to generate unconditional random realizations of statistically isotropic or anisotropic GSG functions and illustrated it in two dimensions. Most importantly, we demonstrated the feasibility of estimating all parameters of a GSG model underlying a single realization of Y by analyzing jointly spatial moments of Y data and corresponding increments, ΔY. Here, we extend our GSG model to account for noisy measurements of Y at a discrete set of points in space (or time), present an algorithm to generate conditional realizations of corresponding isotropic or anisotropic random fields, introduce two approximate versions of this algorithm to reduce CPU time, and explore them on one and two-dimensional synthetic test cases.

  3. MRFalign: protein homology detection through alignment of Markov random fields.

    PubMed

    Ma, Jianzhu; Wang, Sheng; Wang, Zhiyong; Xu, Jinbo

    2014-03-01

    Sequence-based protein homology detection has been extensively studied and so far the most sensitive method is based upon comparison of protein sequence profiles, which are derived from multiple sequence alignment (MSA) of sequence homologs in a protein family. A sequence profile is usually represented as a position-specific scoring matrix (PSSM) or an HMM (Hidden Markov Model) and accordingly PSSM-PSSM or HMM-HMM comparison is used for homolog detection. This paper presents a new homology detection method MRFalign, consisting of three key components: 1) a Markov Random Fields (MRF) representation of a protein family; 2) a scoring function measuring similarity of two MRFs; and 3) an efficient ADMM (Alternating Direction Method of Multipliers) algorithm aligning two MRFs. Compared to HMM that can only model very short-range residue correlation, MRFs can model long-range residue interaction pattern and thus, encode information for the global 3D structure of a protein family. Consequently, MRF-MRF comparison for remote homology detection shall be much more sensitive than HMM-HMM or PSSM-PSSM comparison. Experiments confirm that MRFalign outperforms several popular HMM or PSSM-based methods in terms of both alignment accuracy and remote homology detection and that MRFalign works particularly well for mainly beta proteins. For example, tested on the benchmark SCOP40 (8353 proteins) for homology detection, PSSM-PSSM and HMM-HMM succeed on 48% and 52% of proteins, respectively, at superfamily level, and on 15% and 27% of proteins, respectively, at fold level. In contrast, MRFalign succeeds on 57.3% and 42.5% of proteins at superfamily and fold level, respectively. This study implies that long-range residue interaction patterns are very helpful for sequence-based homology detection. The software is available for download at http://raptorx.uchicago.edu/download/. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5. PMID:24675572

  4. MAGNETIC FIELD LINE RANDOM WALK IN ISOTROPIC TURBULENCE WITH ZERO MEAN FIELD

    SciTech Connect

    Sonsrettee, W.; Ruffolo, D.; Snodin, A. P.; Wongpan, P.; Subedi, P.; Matthaeus, W. H.; Chuychai, P. E-mail: david.ruf@mahidol.ac.th E-mail: pat.wongpan@postgrad.otago.ac.nz E-mail: prasub@udel.edu

    2015-01-01

    In astrophysical plasmas, magnetic field lines often guide the motions of thermal and non-thermal particles. The field line random walk (FLRW) is typically considered to depend on the Kubo number R = (b/B {sub 0})(ℓ{sub ∥}/ℓ ) for rms magnetic fluctuation b, large-scale mean field B {sub 0}, and parallel and perpendicular coherence scales ℓ{sub ∥} and ℓ , respectively. Here we examine the FLRW when R → ∞ by taking B {sub 0} → 0 for finite b{sub z} (fluctuation component along B {sub 0}), which differs from the well-studied route with b{sub z} = 0 or b{sub z} << B {sub 0} as the turbulence becomes quasi-two-dimensional (quasi-2D). Fluctuations with B {sub 0} = 0 are typically isotropic, which serves as a reasonable model of interstellar turbulence. We use a non-perturbative analytic framework based on Corrsin's hypothesis to determine closed-form solutions for the asymptotic field line diffusion coefficient for three versions of the theory, which are directly related to the k {sup –1} or k {sup –2} moment of the power spectrum. We test these theories by performing computer simulations of the FLRW, obtaining the ratio of diffusion coefficients for two different parameterizations of a field line. Comparing this with theoretical ratios, the random ballistic decorrelation version of the theory agrees well with the simulations. All results exhibit an analog to Bohm diffusion. In the quasi-2D limit, previous works have shown that Corrsin-based theories deviate substantially from simulation results, but here we find that as B {sub 0} → 0, they remain in reasonable agreement. We conclude that their applicability is limited not by large R, but rather by quasi-two-dimensionality.

  5. One-dimensional random field Ising model and discrete stochastic mappings

    SciTech Connect

    Behn, U.; Zagrebnov, V.A.

    1987-06-01

    Previous results relating the one-dimensional random field Ising model to a discrete stochastic mapping are generalized to a two-valued correlated random (Markovian) field and to the case of zero temperature. The fractal dimension of the support of the invariant measure is calculated in a simple approximation and its dependence on the physical parameters is discussed.

  6. Fernique-type inequalities and moduli of continuity for anisotropic Gaussian random fields.

    PubMed

    Meerschaert, Mark M; Wang, Wensheng; Xiao, Yimin

    2012-08-01

    This paper is concerned with sample path properties of anisotropic Gaussian random fields. We establish Fernique-type inequalities and utilize them to study the global and local moduli of continuity for anisotropic Gaussian random fields. Applications to fractional Brownian sheets and to the solutions of stochastic partial differential equations are investigated.

  7. Fernique-type inequalities and moduli of continuity for anisotropic Gaussian random fields

    PubMed Central

    Meerschaert, Mark M.; Wang, Wensheng; Xiao, Yimin

    2013-01-01

    This paper is concerned with sample path properties of anisotropic Gaussian random fields. We establish Fernique-type inequalities and utilize them to study the global and local moduli of continuity for anisotropic Gaussian random fields. Applications to fractional Brownian sheets and to the solutions of stochastic partial differential equations are investigated. PMID:24825922

  8. Magnetic Field Line Random Walk in Isotropic Turbulence with Varying Mean Field

    NASA Astrophysics Data System (ADS)

    Sonsrettee, W.; Subedi, P.; Ruffolo, D.; Matthaeus, W. H.; Snodin, A. P.; Wongpan, P.; Chuychai, P.; Rowlands, G.; Vyas, S.

    2016-08-01

    In astrophysical plasmas, the magnetic field line random walk (FLRW) plays an important role in guiding particle transport. The FLRW behavior is scaled by the Kubo number R=(b/{B}0)({{\\ell }}\\parallel /{{\\ell }}\\perp ) for rms magnetic fluctuation b, large-scale mean field {{\\boldsymbol{B}}}0, and coherence scales parallel ({{\\ell }}\\parallel ) and perpendicular ({{\\ell }}\\perp ) to {{\\boldsymbol{B}}}0. Here we use a nonperturbative analytic framework based on Corrsin’s hypothesis, together with direct computer simulations, to examine the R-scaling of the FLRW for varying B 0 with finite b and isotropic fluctuations with {{\\ell }}\\parallel /{{\\ell }}\\perp =1, instead of the well-studied route of varying {{\\ell }}\\parallel /{{\\ell }}\\perp for b \\ll {B}0. The FLRW for isotropic magnetic fluctuations is also of astrophysical interest regarding transport processes in the interstellar medium. With a mean field, fluctuations may have variance anisotropy, so we consider limiting cases of isotropic variance and transverse variance (with b z = 0). We obtain analytic theories, and closed-form solutions for extreme cases. Padé approximants are provided to interpolate all versions of theory and simulations to any B 0. We demonstrate that, for isotropic turbulence, Corrsin-based theories generally work well, and with increasing R there is a transition from quasilinear to Bohm diffusion. This holds even with b z = 0, when different routes to R\\to ∞ are mathematically equivalent; in contrast with previous studies, we find that a Corrsin-based theory with random ballistic decorrelation works well even up to R = 400, where the effects of trapping are barely perceptible in simulation results.

  9. Detection and characterization of regulatory elements using probabilistic conditional random field and hidden Markov models.

    PubMed

    Wang, Hongyan; Zhou, Xiaobo

    2013-04-01

    By altering the electrostatic charge of histones or providing binding sites to protein recognition molecules, Chromatin marks have been proposed to regulate gene expression, a property that has motivated researchers to link these marks to cis-regulatory elements. With the help of next generation sequencing technologies, we can now correlate one specific chromatin mark with regulatory elements (e.g. enhancers or promoters) and also build tools, such as hidden Markov models, to gain insight into mark combinations. However, hidden Markov models have limitation for their character of generative models and assume that a current observation depends only on a current hidden state in the chain. Here, we employed two graphical probabilistic models, namely the linear conditional random field model and multivariate hidden Markov model, to mark gene regions with different states based on recurrent and spatially coherent character of these eight marks. Both models revealed chromatin states that may correspond to enhancers and promoters, transcribed regions, transcriptional elongation, and low-signal regions. We also found that the linear conditional random field model was more effective than the hidden Markov model in recognizing regulatory elements, such as promoter-, enhancer-, and transcriptional elongation-associated regions, which gives us a better choice.

  10. Random field disorder and charge order driven quantum oscillations in cuprates

    NASA Astrophysics Data System (ADS)

    Russo, Antonio; Chakravarty, Sudip

    2016-03-01

    In the pseudogap regime of the cuprates, a period-2 charge order breaks a Z2 symmetry, reflecting a broken translational symmetry. Therefore, the interaction of charge order and quenched disorder due to potential scattering, can, in principle, be treated as a random field Ising model. A numerical analysis of the ground state of such a random field Ising model reveals local, glassy dynamics in both two and three dimensions. The dynamics are treated in the glassy limit as a heat bath which couples to the itinerant electrons, leading to an unusual electronic non-Fermi-liquid. If the dynamics are strong enough, the electron spectral function has no quasiparticle peak and the effective mass diverges at the Fermi surface, precluding quantum oscillations. In contrast to charge density, d -density wave order (reflecting staggered circulating currents) does not directly couple to potential disorder, allowing it to support quantum oscillations. At fourth order in Landau theory, there is a term consisting of the square of the d -density wave order parameter, and the square of the charge order. This coupling could induce parasitic charge order, which may be weak enough for the Fermi liquid behavior to remain uncorrupted. Here, we argue that this distinction must be made clear, as one interprets quantum oscillations in cuprates.

  11. Detection and characterization of regulatory elements using probabilistic conditional random field and hidden Markov models.

    PubMed

    Wang, Hongyan; Zhou, Xiaobo

    2013-04-01

    By altering the electrostatic charge of histones or providing binding sites to protein recognition molecules, Chromatin marks have been proposed to regulate gene expression, a property that has motivated researchers to link these marks to cis-regulatory elements. With the help of next generation sequencing technologies, we can now correlate one specific chromatin mark with regulatory elements (e.g. enhancers or promoters) and also build tools, such as hidden Markov models, to gain insight into mark combinations. However, hidden Markov models have limitation for their character of generative models and assume that a current observation depends only on a current hidden state in the chain. Here, we employed two graphical probabilistic models, namely the linear conditional random field model and multivariate hidden Markov model, to mark gene regions with different states based on recurrent and spatially coherent character of these eight marks. Both models revealed chromatin states that may correspond to enhancers and promoters, transcribed regions, transcriptional elongation, and low-signal regions. We also found that the linear conditional random field model was more effective than the hidden Markov model in recognizing regulatory elements, such as promoter-, enhancer-, and transcriptional elongation-associated regions, which gives us a better choice. PMID:23237214

  12. The application of the Gibbs-Bogoliubov-Feynman inequality in mean field calculations for Markov random fields.

    PubMed

    Zhang, J

    1996-01-01

    The Gibbs-Bogoliubov-Feynman (GBF) inequality of statistical mechanics is adopted, with an information-theoretic interpretation, as a general optimization framework for deriving and examining various mean field approximations for Markov random fields (MRF's). The efficacy of this approach is demonstrated through the compound Gauss-Markov (CGM) model, comparisons between different mean field approximations, and experimental results in image restoration.

  13. Wegner estimates, Lifshitz tails, and Anderson localization for Gaussian random magnetic fields

    NASA Astrophysics Data System (ADS)

    Ueki, Naomasa

    2016-07-01

    The Wegner estimate for the Hamiltonian of the Anderson model for the special Gaussian random magnetic field is extended to more general magnetic fields. The Lifshitz tail upper bounds of the integrated density of states as analyzed by Nakamura are reviewed and extended so that Gaussian random magnetic fields can be treated. By these and multiscale analysis, the Anderson localization at low energies is proven.

  14. Spectral expansions of homogeneous and isotropic tensor-valued random fields

    NASA Astrophysics Data System (ADS)

    Malyarenko, Anatoliy; Ostoja-Starzewski, Martin

    2016-06-01

    We establish spectral expansions of tensor-valued homogeneous and isotropic random fields in terms of stochastic integrals with respect to orthogonal scattered random measures previously known only for the case of tensor rank 0. The fields under consideration take values in the 3-dimensional Euclidean space {E^3} and in the space {S^2(E^3)} of symmetric rank 2 tensors over {E^3}. We find a link between the theory of random fields and the theory of finite-dimensional convex compact sets. These random fields furnish stepping-stone for models of rank 1 and rank 2 tensor-valued fields in continuum physics, such as displacement, velocity, stress, strain, providing appropriate conditions (such as the governing equation or positive-definiteness) are imposed.

  15. Spatio-temporal contextual classification based on Markov random field model. [for thematic mapping

    NASA Technical Reports Server (NTRS)

    Jeon, Byeungwoo; Landgrebe, D. A.

    1991-01-01

    A contextural classifier based on a Markov random field model, which can utilize both spatial and temporal contexts, is investigated. Spatial and temporal neighbors are defined, and the class assignment of each pixel is assumed to be dependent only on the measurement vectors of itself and those of its spatial and temporal neighbors according to the Markov random field property. Only interpixel class dependency context is used in the classification. The joint prior probability of the classes of each pixel and its spatial and temporal neighbors are modeled by a Gibbs random field. The classification is performed in a recursive manner. Experiments with multi-temporal Thematic Mapper data show promising results.

  16. Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.

    SciTech Connect

    Heasler, Patrick G.

    2008-09-30

    This report develops a random field model that describes gas plumes in LWIR remote sensing images. The random field model serves as a prior distribution that can be combined with LWIR data to produce a posterior that determines the probability that a gas plume exists in the scene and also maps the most probable location of any plume. The random field model is intended to work with a single pixel regression estimator--a regression model that estimates gas concentration on an individual pixel basis.

  17. Detection and inpainting of facial wrinkles using texture orientation fields and Markov random field modeling.

    PubMed

    Batool, Nazre; Chellappa, Rama

    2014-09-01

    Facial retouching is widely used in media and entertainment industry. Professional software usually require a minimum level of user expertise to achieve the desirable results. In this paper, we present an algorithm to detect facial wrinkles/imperfection. We believe that any such algorithm would be amenable to facial retouching applications. The detection of wrinkles/imperfections can allow these skin features to be processed differently than the surrounding skin without much user interaction. For detection, Gabor filter responses along with texture orientation field are used as image features. A bimodal Gaussian mixture model (GMM) represents distributions of Gabor features of normal skin versus skin imperfections. Then, a Markov random field model is used to incorporate the spatial relationships among neighboring pixels for their GMM distributions and texture orientations. An expectation-maximization algorithm then classifies skin versus skin wrinkles/imperfections. Once detected automatically, wrinkles/imperfections are removed completely instead of being blended or blurred. We propose an exemplar-based constrained texture synthesis algorithm to inpaint irregularly shaped gaps left by the removal of detected wrinkles/imperfections. We present results conducted on images downloaded from the Internet to show the efficacy of our algorithms.

  18. Nonstationary elementary-field light randomly triggered by Poisson impulses.

    PubMed

    Fernández-Pousa, Carlos R

    2013-05-01

    A stochastic theory of nonstationary light describing the random emission of elementary pulses is presented. The emission is governed by a nonhomogeneous Poisson point process determined by a time-varying emission rate. The model describes, in the appropriate limits, stationary, cyclostationary, locally stationary, and pulsed radiation, and reduces to a Gaussian theory in the limit of dense emission rate. The first- and second-order coherence theories are solved after the computation of second- and fourth-order correlation functions by use of the characteristic function. The ergodicity of second-order correlations under various types of detectors is explored and a number of observables, including optical spectrum, amplitude, and intensity correlations, are analyzed. PMID:23695325

  19. Statistical properties of the Fraunhofer diffraction field produced by random fractals.

    PubMed

    Uno, K; Uozumi, J; Asakura, T

    1993-05-20

    First-order statistical properties of the speckle field and its intensity in the Fraunhofer diffraction region that is produced by random Koch fractals are investigated by means of computer simulations in comparison with the ordinary fully developed speckle.

  20. Phase diagram of the random-field Ising system Fe{sub 0.60}Zn{sub 0.40}F{sub 2} at intense fields

    SciTech Connect

    Montenegro, F.C.; Lima, K.A.; Torikachvili, M.S.; Lacerda, A.H.

    1997-10-01

    The critical and irreversibility phase boundaries of the d = 3 diluted uniaxial antiferromagnet Fe{sub 0.60}Zn{sub 0.40}F{sub 2} have been determined under strong external magnetic fields by means of magnetization measurements. The data reveal that the random-field-induced glassy phase, previously observed in the upper part of the (H,T) phase diagram for highly diluted samples (x {approx_equal} 0.3), is extended to higher values of x.

  1. Synchronization in the random-field Kuramoto model on complex networks.

    PubMed

    Lopes, M A; Lopes, E M; Yoon, S; Mendes, J F F; Goltsev, A V

    2016-07-01

    We study the impact of random pinning fields on the emergence of synchrony in the Kuramoto model on complete graphs and uncorrelated random complex networks. We consider random fields with uniformly distributed directions and homogeneous and heterogeneous (Gaussian) field magnitude distribution. In our analysis, we apply the Ott-Antonsen method and the annealed-network approximation to find the critical behavior of the order parameter. In the case of homogeneous fields, we find a tricritical point above which a second-order phase transition gives place to a first-order phase transition when the network is either fully connected or scale-free with the degree exponent γ>5. Interestingly, for scale-free networks with 2<γ≤5, the phase transition is of second-order at any field magnitude, except for degree distributions with γ=3 when the transition is of infinite order at K_{c}=0 independent of the random fields. Contrary to the Ising model, even strong Gaussian random fields do not suppress the second-order phase transition in both complete graphs and scale-free networks, although the fields increase the critical coupling for γ>3. Our simulations support these analytical results. PMID:27575149

  2. Synchronization in the random-field Kuramoto model on complex networks

    NASA Astrophysics Data System (ADS)

    Lopes, M. A.; Lopes, E. M.; Yoon, S.; Mendes, J. F. F.; Goltsev, A. V.

    2016-07-01

    We study the impact of random pinning fields on the emergence of synchrony in the Kuramoto model on complete graphs and uncorrelated random complex networks. We consider random fields with uniformly distributed directions and homogeneous and heterogeneous (Gaussian) field magnitude distribution. In our analysis, we apply the Ott-Antonsen method and the annealed-network approximation to find the critical behavior of the order parameter. In the case of homogeneous fields, we find a tricritical point above which a second-order phase transition gives place to a first-order phase transition when the network is either fully connected or scale-free with the degree exponent γ >5 . Interestingly, for scale-free networks with 2 <γ ≤5 , the phase transition is of second-order at any field magnitude, except for degree distributions with γ =3 when the transition is of infinite order at Kc=0 independent of the random fields. Contrary to the Ising model, even strong Gaussian random fields do not suppress the second-order phase transition in both complete graphs and scale-free networks, although the fields increase the critical coupling for γ >3 . Our simulations support these analytical results.

  3. Computationally tractable stochastic image modeling based on symmetric Markov mesh random fields.

    PubMed

    Yousefi, Siamak; Kehtarnavaz, Nasser; Cao, Yan

    2013-06-01

    In this paper, the properties of a new class of causal Markov random fields, named symmetric Markov mesh random field, are initially discussed. It is shown that the symmetric Markov mesh random fields from the upper corners are equivalent to the symmetric Markov mesh random fields from the lower corners. Based on this new random field, a symmetric, corner-independent, and isotropic image model is then derived which incorporates the dependency of a pixel on all its neighbors. The introduced image model comprises the product of several local 1D density and 2D joint density functions of pixels in an image thus making it computationally tractable and practically feasible by allowing the use of histogram and joint histogram approximations to estimate the model parameters. An image restoration application is also presented to confirm the effectiveness of the model developed. The experimental results demonstrate that this new model provides an improved tool for image modeling purposes compared to the conventional Markov random field models.

  4. Cauchy-Laguerre Two-Matrix Model and the Meijer-G Random Point Field

    NASA Astrophysics Data System (ADS)

    Bertola, M.; Gekhtman, M.; Szmigielski, J.

    2014-02-01

    We apply the general theory of Cauchy biorthogonal polynomials developed in Bertola et al. (Commun Math Phys 287(3):983-1014, 2009) and Bertola et al. (J Approx Th 162(4):832-867, 2010) to the case associated with Laguerre measures. In particular, we obtain explicit formulae in terms of Meijer-G functions for all key objects relevant to the study of the corresponding biorthogonal polynomials and the Cauchy two-matrix model associated with them. The central theorem we prove is that a scaling limit of the correlation functions for eigenvalues near the origin exists, and is given by a new determinantal two-level random point field, the Meijer-G random field. We conjecture that this random point field leads to a novel universality class of random fields parametrized by exponents of Laguerre weights. We express the joint distributions of the smallest eigenvalues in terms of suitable Fredholm determinants and evaluate them numerically. We also show that in a suitable limit, the Meijer-G random field converges to the Bessel random field and hence the behavior of the eigenvalues of one of the two matrices converges to the one of the Laguerre ensemble.

  5. Modelling Potential Field Sources in the Gelibolu Peninsula (Western Turkey) Using a Markov Random Field Approach

    NASA Astrophysics Data System (ADS)

    Albora, A. Muhittin; Ucan, Osman N.; Aydogan, Davut

    2007-05-01

    In this study, a Markov Random Field (MRF) approach is used to locate source boundary positions which are difficult to identify from Bouguer gravity and magnetic maps. As a generalized form of Markov Chains, the MRF approach is an unsupervised statistical model based algorithm and is applied to the analysis of images, particularly in the detection of visual patterns or textures. Here, we present a dynamic programming based on the MRF approach for boundary detection of noisy and super-positioned potential anomalies, which are produced by various geological structures. In the MRF method, gravity and magnetic maps are considered as two-dimensional (2-D) images with a matrix composed of N 1 × N 2 pixels. Each pixel value of the matrix is optimized in real time with no a priori processing by using two parameter sets; average steering vector (θ) and quantization level (M). They carry information about the correlation of neighboring pixels and the locality of their connections. We have chosen MRF as a processing approach for geophysical data since it is an unsupervised, efficient model for image enhancement, border detection and separation of 2-D potential anomalies. The main benefit of MRF is that an average steering vector and a quantization level are enough in evaluation of the potential anomaly maps. We have compared the MRF method to noise implemented synthetic potential field anomalies. After satisfactory results were found, the method has been applied to gravity and magnetic anomaly maps of Gelibolu Peninsula in Western Turkey. Here, we have observed Anafartalar thrust fault and another parallel fault northwest of Anafartalar thrust fault. We have modeled a geological structure including a lateral fault, which results in a higher susceptibility and anomaly amplitude increment. We have shown that the MRF method is effective to detect the broad-scale geological structures in the Gelibolu Peninsula, and thus to delineate the complex tectonic structure of Gelibolu

  6. Combining Monte Carlo and mean-field-like methods for inference in hidden Markov random fields.

    PubMed

    Forbes, Florence; Fort, Gersende

    2007-03-01

    Issues involving missing data are typical settings where exact inference is not tractable as soon as nontrivial interactions occur between the missing variables. Approximations are required, and most of them are based either on simulation methods or on deterministic variational methods. While variational methods provide fast and reasonable approximate estimates in many scenarios, simulation methods offer more consideration of important theoretical issues such as accuracy of the approximation and convergence of the algorithms but at a much higher computational cost. In this work, we propose a new class of algorithms that combine the main features and advantages of both simulation and deterministic methods and consider applications to inference in hidden Markov random fields (HMRFs). These algorithms can be viewed as stochastic perturbations of variational expectation maximization (VEM) algorithms, which are not tractable for HMRF. We focus more specifically on one of these perturbations and we prove their (almost sure) convergence to the same limit set as the limit set of VEM. In addition, experiments on synthetic and real-world images show that the algorithm performance is very close and sometimes better than that of other existing simulation-based and variational EM-like algorithms.

  7. The simulation of groundwater flow velocity random fields by the method of partitioning and randomization of the spectrum

    NASA Astrophysics Data System (ADS)

    Konecny, Franz; Fürst, Josef

    2007-02-01

    Due to the heterogeneity of aquifers, groundwater flow velocity fields can be viewed as vector random fields (v.r.f.). For the application of Monte Carlo methods to investigate problems of pollutant transport, the efficient generation of v.r.f. with prescribed covariance structure is an important task. The subject of this paper is the simulation of v.r.f. with a given spectral tensor. We adopt a method that combines two principles: spectral domain partitioning and spectrum randomization (SDP/SR). The SR principle allows to reproduce exactly the covariance structure of the v.r.f., which is of particular importance for Monte Carlo simulation, such as random walk particle tracking. Following this methodology, replicates of the v.r.f. can be generated using a cosine series. Once the coefficients of the series were determined, the v.r.f. can be computed at any point of its domain by mere evaluation of the cosine terms. The method does not require a computational grid and is computationally more efficient than, e.g., Gaussian conditioning.

  8. Random walk study of electron motion in helium in crossed electromagnetic fields

    NASA Technical Reports Server (NTRS)

    Englert, G. W.

    1972-01-01

    Random walk theory, previously adapted to electron motion in the presence of an electric field, is extended to include a transverse magnetic field. In principle, the random walk approach avoids mathematical complexity and concomitant simplifying assumptions and permits determination of energy distributions and transport coefficients within the accuracy of available collisional cross section data. Application is made to a weakly ionized helium gas. Time of relaxation of electron energy distribution, determined by the random walk, is described by simple expressions based on energy exchange between the electron and an effective electric field. The restrictive effect of the magnetic field on electron motion, which increases the required number of collisions per walk to reach a terminal steady state condition, as well as the effect of the magnetic field on electron transport coefficients and mean energy can be quite adequately described by expressions involving only the Hall parameter.

  9. Faraday effect in rippled graphene: Magneto-optics and random gauge fields

    NASA Astrophysics Data System (ADS)

    Schiefele, Jürgen; Martin-Moreno, Luis; Guinea, Francisco

    2016-07-01

    A beam of linearly polarized light transmitted through magnetically biased graphene can have its axis of polarization rotated by several degrees after passing the graphene sheet. This large Faraday effect is due to the action of the magnetic field on graphene's charge carriers. As deformations of the graphene membrane result in pseudomagnetic fields acting on the charge carriers, the effect of random mesoscopic corrugations (ripples) can be described as the exposure of graphene to a random pseudomagnetic field. We aim to clarify the interplay of these typically sample inherent fields with the external magnetic bias field and the resulting effect on the Faraday rotation. In principle, random gauge disorder can be identified from a combination of Faraday angle and optical spectroscopy measurements.

  10. Long term field evaluation reveals HLB resistance in Citrus relatives

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Citrus huanglongbing (HLB) is a destructive disease with no known cure. To identify sources of HLB resistance in the subfamily Aurantioideae to which citrus belongs, we conducted a six-year field trial under natural disease challenge conditions in an HLB endemic region. The study included 65 Citrus ...

  11. Random-field-induced order in a bosonic t-J model

    NASA Astrophysics Data System (ADS)

    Kuno, Yoshihito; Mori, Takamasa; Ichinose, Ikuo

    2014-08-01

    In this paper, we study the effect of a random quenched external field for spin order and also multiple Bose-Einstein condensation (BEC). This system is realized by the cold atomic gases in an optical lattice. In particular, we are interested in the strong-repulsion region of the two-component gases for which the bosonic t-J model is a good effective model. In the bosonic t-J model, a long-range order of the pseudo-spin and also BEC of atoms appear quite naturally as in the fermion t-J model for the high-temperature superconducting materials. Random Raman scattering between two internal states of a single atom plays a role of the random external field, and we study its effects on the pseudo-spin order and the BEC by means of quantum Monte-Carlo simulations. The random external field breaks a continuous U(1) symmetry existing in the original bosonic t-J model and it induces new orders, named random-field-induced order (RFIO). We show a phase diagram of the bosonic t-J model with the random external magnetic field and study the robustness of the RFIO states. We also study topological excitations like vortices and the domain wall in the RFIO state. Finally, we point out the possibility of a quantum bit by the RFIO.

  12. Tuning of random lasers by means of external magnetic fields based on the Voigt effect

    NASA Astrophysics Data System (ADS)

    Ghasempour Ardakani, Abbas; Mahdavi, Seyed Mohammad; Bahrampour, Ali Reza

    2013-04-01

    It has been proposed that emission spectrum of random lasers with magnetically active semiconductor constituents can be made tunable by external magnetic fields. By employing the FDTD method, the spectral intensity and spatial distribution of electric field are calculated in the presence of an external magnetic field. It is numerically shown that due to the magneto-optical Voigt effect, the emission spectrum of a semiconductor-based random laser can be made tunable by adjusting the external magnetic field. The effect of magnetic field on the localization length of the laser modes is investigated. It is also shown that the spatial distribution of electric field exhibited remarkable modification with variation of magnetic field.

  13. Near-membrane protein dynamics revealed by evanescent field microscopy

    NASA Astrophysics Data System (ADS)

    Bezzerides, Vassilios J.; Clapham, David E.

    2004-05-01

    Evanescent Field (EF) microscopy is used to investigate the spatial and temporal dynamics of proteins in living cells. A genetically engineered ion channel fused to a fluorescent tag is expressed in cells and imaged with an objective-based EF microscope. Images are obtained from a CCD and analyzed to determine fluorescence and velocity of individual protein containing vesicles. An inverse correlation between fluorescent intensity and average motility provides a method for determination of membrane localization. Stimulation and subsequent decrease in ion channel activity is correlated with loss of protein from membrane as shown by EF microscopy and patch-clamp electrophysiology.

  14. Phase Correlations at Neighboring Intensity Critical Points in Gaussian Random Wave Fields

    NASA Astrophysics Data System (ADS)

    Freund, Isaac

    1998-11-01

    Phase correlations are studied for neighboring critical points of the intensity in an isotropic Gaussian random wave field. Significant correlations and anticorrelations are found that extend out to at least the fifth nearest neighbors. A theoretical interpretation of the empirical data is attempted within the framework of the phase autocorrelation and the probability-density functions of extended two-dimensional random phase fields. It is found, however, that adaptations of these theoretical models are unable to account satisfactorily, or even qualitatively, for the extensive phase correlations that are present in these fields.

  15. Phase diagram of the classical Heisenberg model in a trimodal random field distribution

    NASA Astrophysics Data System (ADS)

    Santos-Filho, A.; Albuquerque, D. F. de; Santos-Filho, J. B.; Batista, T. S. Araujo

    2016-11-01

    The classical spin 1 / 2 Heisenberg model on a simple cubic lattice, with fluctuating bond interactions between nearest neighbors and in the presence of a random magnetic field, is investigated by effective field theory based on two-spin cluster. The random field is drawn from the asymmetric and anisotropic trimodal probability distribution. The fluctuating bond is extracted from the symmetric and anisotropic bimodal probability. We estimate the transition temperatures, and the phase diagram in the Tc- h, Tc- p and Tc - α planes. We observe that the temperature of the tricritical point decreases with the increase of disorder in exchange interactions until the system ceases to display tricritical behavior. The disorder of the interactions and reentrant phenomena depends on the trimodal distribution of the random field.

  16. Revealing the Properties of the Frontier Fields Galaxies

    NASA Astrophysics Data System (ADS)

    Wise, John

    2014-10-01

    The HST campaign Frontier Fields will discover an even larger sample of galaxies at redshifts greater than 6. We propose to make observational predictions for this high-redshift population, using a suite of high-resolution cosmological simulations, that will enable the correlation between key observables and the physical properties of the first galaxies in the universe. These simulations will have finished before Cycle 22, and this proposal focuses on the analysis of the simulated galaxies. The primary goal of this proposal is to constrain the following properties: {1} star formation histories and stellar populations, {2} nebular emission and dust extinction, {3} the faint end of the luminosity function, {4} cosmic variance, and {5} galaxy morphology and structure. We will make all of the analysis data products publicly available. We will also provide a Markov Chain Monte Carlo tool to the public that will calculate the most likely galaxy properties, such as stellar mass, metallicity, and ages, given a redshift, half-light radius, and magnitudes/spectra.

  17. Simulation of quantum random walks using the interference of a classical field

    SciTech Connect

    Jeong, H.; Paternostro, M.; Kim, M.S.

    2004-01-01

    We suggest a theoretical scheme for the simulation of quantum random walks on a line using beam splitters, phase shifters, and photodetectors. Our model enables us to simulate a quantum random walk using of the wave nature of classical light fields. Furthermore, the proposed setup allows the analysis of the effects of decoherence. The transition from a pure mean-photon-number distribution to a classical one is studied varying the decoherence parameters.

  18. Probability distributions of random electromagnetic fields in the presence of a semi-infinite isotropic medium

    NASA Astrophysics Data System (ADS)

    Arnaut, L. R.

    2007-06-01

    Using a transverse electric/transverse magnetic decomposition for an angular plane wave spectrum of random electromagnetic waves and matched boundary conditions, we derive the probability density function for the energy density of the vector electric field in the presence of a semi-infinite isotropic medium. The theoretical analysis is illustrated with calculations and results for good electric conductors and for a lossless dielectric half-space. The influence of the permittivity and conductivity on the intensity, polarization state, statistical distribution, and standard deviation of the field is investigated, both for incident plus reflected fields and for refracted fields. External refraction is found to result in compression of the fluctuations of the random field. Several applications of the theory are discussed.

  19. Identifying protein interaction subnetworks by a bagging Markov random field-based method.

    PubMed

    Chen, Li; Xuan, Jianhua; Riggins, Rebecca B; Wang, Yue; Clarke, Robert

    2013-01-01

    Identification of differentially expressed subnetworks from protein-protein interaction (PPI) networks has become increasingly important to our global understanding of the molecular mechanisms that drive cancer. Several methods have been proposed for PPI subnetwork identification, but the dependency among network member genes is not explicitly considered, leaving many important hub genes largely unidentified. We present a new method, based on a bagging Markov random field (BMRF) framework, to improve subnetwork identification for mechanistic studies of breast cancer. The method follows a maximum a posteriori principle to form a novel network score that explicitly considers pairwise gene interactions in PPI networks, and it searches for subnetworks with maximal network scores. To improve their robustness across data sets, a bagging scheme based on bootstrapping samples is implemented to statistically select high confidence subnetworks. We first compared the BMRF-based method with existing methods on simulation data to demonstrate its improved performance. We then applied our method to breast cancer data to identify PPI subnetworks associated with breast cancer progression and/or tamoxifen resistance. The experimental results show that not only an improved prediction performance can be achieved by the BMRF approach when tested on independent data sets, but biologically meaningful subnetworks can also be revealed that are relevant to breast cancer and tamoxifen resistance.

  20. Automated torso organ segmentation from 3D CT images using conditional random field

    NASA Astrophysics Data System (ADS)

    Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Misawa, Kazunari; Mori, Kensaku

    2016-03-01

    This paper presents a segmentation method for torso organs using conditional random field (CRF) from medical images. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. In this paper, we propose an organ segmentation method using structured output learning which is based on probabilistic graphical model. The proposed method utilizes CRF on three-dimensional grids as probabilistic graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weight parameters of the CRF using stochastic gradient descent algorithm and estimate organ labels for a given image by maximum a posteriori (MAP) estimation. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 6.6%. The DICE coefficients of right lung, left lung, heart, liver, spleen, right kidney, and left kidney are 0.94, 0.92, 0.65, 0.67, 0.36, 0.38, and 0.37, respectively.

  1. Dynamics of Crowd Behaviors: From Complex Plane to Quantum Random Fields

    NASA Astrophysics Data System (ADS)

    Ivancevic, Vladimir G.; Reid, Darryn J.

    2015-11-01

    The following sections are included: * Complex Plane Dynamics of Crowds and Groups * Introduction * Complex-Valued Dynamics of Crowd and Group Behaviors * Kähler Geometry of Crowd and Group Dynamics * Computer Simulations of Crowds and Croups Dynamics * Braids of Agents' Behaviors in the Complex Plane * Hilbert-Space Control of Crowds and Groups Dynamics * Quantum Random Fields: A Unique Framework for Simulation, Optimization, Control and Learning * Introduction * Adaptive Quantum Oscillator * Optimization and Learning on Banach and Hilbert Spaces * Appendix * Complex-Valued Image Processing * Linear Integral Equations * Riemann-Liouville Fractional Calculus * Rigorous Geometric Quantization * Supervised Machine-Learning Methods * First-Order Logic and Quantum Random Fields

  2. A mechanism of long-range order induced by random fields: Effective anisotropy created by defects

    NASA Astrophysics Data System (ADS)

    Berzin, A. A.; Morosov, A. I.; Sigov, A. S.

    2016-09-01

    A microscopic mechanism of the long-range order in two-dimensional space induced by random local fields of crystal defects has been found. The impurity-induced effective anisotropy has been shown to arise in the system due to anisotropic distribution of impurity-induced random local field directions in the n-dimensional space of vector order parameter with the O( n) symmetry. The expression for the effective anisotropy constant has been obtained. A weak anisotropy of the "easy axis" type transforms the X- Y model and the Heisenberg model to the class of Ising models, and brings into long-range order existence in the system.

  3. Analysis of spanning avalanches in the two-dimensional nonequilibrium zero-temperature random-field Ising model.

    PubMed

    Spasojević, Djordje; Janićević, Sanja; Knežević, Milan

    2014-01-01

    We present a numerical analysis of spanning avalanches in a two-dimensional (2D) nonequilibrium zero-temperature random field Ising model. Finite-size scaling analysis, performed for distribution of the average number of spanning avalanches per single run, spanning avalanche size distribution, average size of spanning avalanche, and contribution of spanning avalanches to magnetization jump, is augmented by analysis of spanning field (i.e., field triggering spanning avalanche), which enabled us to collapse averaged magnetization curves below critical disorder. Our study, based on extensive simulations of sufficiently large systems, reveals the dominant role of subcritical 2D-spanning avalanches in model behavior below and at the critical disorder. Other types of avalanches influence finite systems, but their contribution for large systems remains small or vanish.

  4. ``Avalanches'' in the ground state of the 3D Gaussian random field Ising model driven by an external field

    NASA Astrophysics Data System (ADS)

    Frontera, Carlos; Vives, Eduard

    2002-08-01

    We present a numerical study of the exact ground states of the 3D Gaussian random field Ising model (G-RFIM) with an applied external field B. We combine a max-flow min-cut algorithm with an optimal procedure for determining all the ground states when B is swept from -∞ to ∞. The magnetization of finite lattices ( L3) is studied as a function of the degree of disorder in the system σ (standard deviation of the Gaussian random fields). The magnetization evolves as a sequence of jumps or "avalanches" with a certain size s. The statistical distribution p( s) becomes a power law p( s)˜ s- τ for a certain degree of disorder σc( L). The extrapolation of the results to L→∞ renders σc≃2.4±0.1 and τ≃1.70±0.07.

  5. Magnetic field line random walk in models and simulations of reduced magnetohydrodynamic turbulence

    SciTech Connect

    Snodin, A. P.; Ruffolo, D.; Oughton, S.; Servidio, S.; Matthaeus, W. H.

    2013-12-10

    The random walk of magnetic field lines is examined numerically and analytically in the context of reduced magnetohydrodynamic (RMHD) turbulence, which provides a useful description of plasmas dominated by a strong mean field, such as in the solar corona. A recently developed non-perturbative theory of magnetic field line diffusion is compared with the diffusion coefficients obtained by accurate numerical tracing of magnetic field lines for both synthetic models and direct numerical simulations of RMHD. Statistical analysis of an ensemble of trajectories confirms the applicability of the theory, which very closely matches the numerical field line diffusion coefficient as a function of distance z along the mean magnetic field for a wide range of the Kubo number R. This theory employs Corrsin's independence hypothesis, sometimes thought to be valid only at low R. However, the results demonstrate that it works well up to R = 10, both for a synthetic RMHD model and an RMHD simulation. The numerical results from the RMHD simulation are compared with and without phase randomization, demonstrating a clear effect of coherent structures on the field line random walk for a very low Kubo number.

  6. Theory of weak scattering of stochastic electromagnetic fields from deterministic and random media

    SciTech Connect

    Tong Zhisong; Korotkova, Olga

    2010-09-15

    The theory of scattering of scalar stochastic fields from deterministic and random media is generalized to the electromagnetic domain under the first-order Born approximation. The analysis allows for determining the changes in spectrum, coherence, and polarization of electromagnetic fields produced on their propagation from the source to the scattering volume, interaction with the scatterer, and propagation from the scatterer to the far field. An example of scattering of a field produced by a {delta}-correlated partially polarized source and scattered from a {delta}-correlated medium is provided.

  7. Sensitivity of Lagrangian coherent structure identification to flow field resolution and random errors

    NASA Astrophysics Data System (ADS)

    Olcay, Ali B.; Pottebaum, Tait S.; Krueger, Paul S.

    2010-03-01

    The effect of spatial and temporal resolutions and random errors on identification of Lagrangian coherent structures (LCSs) from Eulerian velocity fields is evaluated using two canonical flows: a two-dimensional vortex pair and a vortex ring formed by transient ejection of a jet from a tube. The flow field for the vortex pair case was steady and obtained analytically while the transient vortex ring flow was simulated using computational fluid dynamics. To evaluate resolution and random error effects, the flow fields were degraded by locally smoothing the flow and sampling it on a sparser grid to reduce spatial resolution, adding Gaussian distributed random noise to provide random errors, and/or subsampling the time series of vector fields to reduce the temporal resolution (the latter applying only for the vortex ring case). The degradation methods were meant to emulate distortions and errors introduced in common flow measurement methods such as digital particle image velocimetry. Comparing the LCS corresponding to the vortex boundary (separatrix) obtained from the degraded velocity fields with the true separatrix (obtained analytically for the vortex pair case or from high resolution, noise-free velocity fields for the vortex ring case) showed that noise levels as low as 5%-10% of the vortex velocity can cause the separatrix to significantly deviate from its true location in a random fashion, but the "mean" location still remained close to the true location. Temporal and spatial resolution degradations were found to primarily affect transient portions of the flow with strong spatial gradients. Significant deviations in the location of the separatrix were observed even for spatial resolutions as high as 2% of the jet diameter for the vortex ring case.

  8. Spin relaxation of a diffusively moving carrier in a random hyperfine field

    NASA Astrophysics Data System (ADS)

    Roundy, R. C.; Raikh, M. E.

    2014-11-01

    Relaxation, , of the average spin of a carrier in a course of hops over sites hosting random hyperfine fields is studied theoretically. In low dimensions, d =1 ,2 , the decay of average spin with time is nonexponential at all times. The origin of the effect is that for d =1 ,2 a typical random-walk trajectory exhibits numerous self-intersections. Multiple visits of the carrier to the same site accelerates the relaxation since the corresponding partial rotations of spin during these visits add up. Another consequence of self-intersections of the random-walk trajectories is that, in all dimensions, the average, , becomes sensitive to a weak magnetic field directed along z . Our analytical predictions are complemented by the numerical simulations of . The scenario of acceleration of spin relaxation due to returns applies also to the non-Markovian decoherence of a qubit surrounded by multiple fluctuators.

  9. Random Field Driven Spatial Complexity at the Mott Transition in VO2

    NASA Astrophysics Data System (ADS)

    Carlson, Erica; Liu, Shuo; Phillabaum, Benjamin; Dahmen, Karin; Vidhyadhiraja, Narsimhamurthy; Qazilbash, Mumtaz; Basov, Dimitri

    We report the first application of critical cluster techniques to the Mott metal-insulator transition in vanadium dioxide. We show that the geometric properties of the metallic and insulating puddles observed by scanning near-field infrared microscopy are consistent with the system passing near criticality of the random field Ising model as temperature is varied. The resulting large barriers to equilibrium may be the source of the unusually robust hysteresis phenomena associated with the metal-insulator transition in this system.

  10. Maximum a posteriori blind image deconvolution with Huber-Markov random-field regularization.

    PubMed

    Xu, Zhimin; Lam, Edmund Y

    2009-05-01

    We propose a maximum a posteriori blind deconvolution approach using a Huber-Markov random-field model. Compared with the conventional maximum-likelihood method, our algorithm not only suppresses noise effectively but also significantly alleviates the artifacts produced by the deconvolution process. The performance of this method is demonstrated by computer simulations.

  11. Effects of Academic Vocabulary Instruction for Linguistically Diverse Adolescents: Evidence from a Randomized Field Trial

    ERIC Educational Resources Information Center

    Lesaux, Nonie K.; Kieffer, Michael J.; Kelley, Joan G.; Harris, Julie Russ

    2014-01-01

    We conducted a randomized field trial to test an academic vocabulary intervention designed to bolster the language and literacy skills of linguistically diverse sixth-grade students (N = 2,082; n = 1,469 from a home where English is not the primary language), many demonstrating low achievement, enrolled in 14 urban middle schools. The 20-week…

  12. What Works Clearinghouse Quick Review: "Information and College Access: Evidence from a Randomized Field Experiment"

    ERIC Educational Resources Information Center

    What Works Clearinghouse, 2013

    2013-01-01

    "Information and College Access: Evidence From a Randomized Field Experiment" examined the impact of offering an online informational video and financial aid materials to high school students on: (1) their postsecondary aspirations, (2) the accuracy of their understanding of financial aid availability, and (3) the accuracy of their estimates of…

  13. The Role of Treatment Fidelity on Outcomes during a Randomized Field Trial of an Autism Intervention

    ERIC Educational Resources Information Center

    Mandell, David S; Stahmer, Aubyn C; Shin, Sujie; Xie, Ming; Reisinger, Erica; Marcus, Steven C

    2013-01-01

    This randomized field trial comparing Strategies for Teaching based on Autism Research and Structured Teaching enrolled educators in 33 kindergarten-through-second-grade autism support classrooms and 119 students, aged 5-8 years in the School District of Philadelphia. Students were assessed at the beginning and end of the academic year using the…

  14. Effects of a Voluntary Summer Reading Intervention on Reading Achievement: Results from a Randomized Field Trial

    ERIC Educational Resources Information Center

    Kim, James S.

    2006-01-01

    The effects of a voluntary summer reading intervention were assessed in a randomized field trial involving 552 students in 10 schools. In this study, fourth-grade children received eight books to read during their summer vacation and were encouraged by their teachers to practice oral reading at home with a family member and to use comprehension…

  15. Test of crossover scaling in the two-dimensional random-field Ising model

    NASA Astrophysics Data System (ADS)

    Binder, K.

    1984-05-01

    The random-field-induced rounding of the specific-heat singularity observed in transfer-matrix calculations of two-dimensional Ising models by Morgenstern, Binder, and Hornreich is interpreted in terms of the Fishman-Aharony scaling theory. Results qualitatively similar to recent experimental work on Rb2Co0.85Mg0.15F4 are obtained.

  16. Random transposon mutagenesis of the Saccharopolyspora erythraea genome reveals additional genes influencing erythromycin biosynthesis.

    PubMed

    Fedashchin, Andrij; Cernota, William H; Gonzalez, Melissa C; Leach, Benjamin I; Kwan, Noelle; Wesley, Roy K; Weber, J Mark

    2015-11-01

    A single cycle of strain improvement was performed in Saccharopolyspora erythraea mutB and 15 genotypes influencing erythromycin production were found. Genotypes generated by transposon mutagenesis appeared in the screen at a frequency of ~3%. Mutations affecting central metabolism and regulatory genes were found, as well as hydrolases, peptidases, glycosyl transferases and unknown genes. Only one mutant retained high erythromycin production when scaled-up from micro-agar plug fermentations to shake flasks. This mutant had a knockout of the cwh1 gene (SACE_1598), encoding a cell-wall-associated hydrolase. The cwh1 knockout produced visible growth and morphological defects on solid medium. This study demonstrated that random transposon mutagenesis uncovers strain improvement-related genes potentially useful for strain engineering. PMID:26468041

  17. Testing Random-Detector-Efficiency Countermeasure in a Commercial System Reveals a Breakable Unrealistic Assumption

    NASA Astrophysics Data System (ADS)

    Huang, Anqi; Sajeed, Shihan; Chaiwongkhot, Poompong; Soucarros, Mathilde; Legre, Matthieu; Makarov, Vadim

    2016-11-01

    In the last decade, efforts have been made to reconcile theoretical security with realistic imperfect implementations of quantum key distribution (QKD). Implementable countermeasures are proposed to patch the discovered loopholes. However, certain countermeasures are not as robust as would be expected. In this paper, we present a concrete example of ID Quantique's random-detector-efficiency countermeasure against detector blinding attacks. As a third-party tester, we have found that the first industrial implementation of this countermeasure is effective against the original blinding attack, but not immune to a modified blinding attack. Then, we implement and test a later full version of this countermeasure containing a security proof [C. C. W. Lim et al., IEEE Journal of Selected Topics in Quantum Electronics, 21, 6601305 (2015)]. We find that it is still vulnerable against the modified blinding attack, because an assumption about hardware characteristics on which the proof relies fails in practice.

  18. Thermal Non-equilibrium Revealed by Periodic Pulses of Random Amplitudes in Solar Coronal Loops

    NASA Astrophysics Data System (ADS)

    Auchère, F.; Froment, C.; Bocchialini, K.; Buchlin, E.; Solomon, J.

    2016-08-01

    We recently detected variations in extreme ultraviolet intensity in coronal loops repeating with periods of several hours. Models of loops including stratified and quasi-steady heating predict the development of a state of thermal non-equilibrium (TNE): cycles of evaporative upflows at the footpoints followed by falling condensations at the apex. Based on Fourier and wavelet analysis, we demonstrate that the observed periodic signals are indeed not signatures of vibrational modes. Instead, superimposed on the power law expected from the stochastic background emission, the power spectra of the time series exhibit the discrete harmonics and continua expected from periodic trains of pulses of random amplitudes. These characteristics reinforce our earlier interpretation of these pulsations as being aborted TNE cycles.

  19. New constraints on modelling the random magnetic field of the MW

    NASA Astrophysics Data System (ADS)

    Beck, Marcus C.; Beck, Alexander M.; Beck, Rainer; Dolag, Klaus; Strong, Andrew W.; Nielaba, Peter

    2016-05-01

    We extend the description of the isotropic and anisotropic random component of the small-scale magnetic field within the existing magnetic field model of the Milky Way from Jansson & Farrar, by including random realizations of the small-scale component. Using a magnetic-field power spectrum with Gaussian random fields, the NE2001 model for the thermal electrons and the Galactic cosmic-ray electron distribution from the current GALPROP model we derive full-sky maps for the total and polarized synchrotron intensity as well as the Faraday rotation-measure distribution. While previous work assumed that small-scale fluctuations average out along the line-of-sight or which only computed ensemble averages of random fields, we show that these fluctuations need to be carefully taken into account. Comparing with observational data we obtain not only good agreement with 408 MHz total and WMAP7 22 GHz polarized intensity emission maps, but also an improved agreement with Galactic foreground rotation-measure maps and power spectra, whose amplitude and shape strongly depend on the parameters of the random field. We demonstrate that a correlation length of 0≈22 pc (05 pc being a 5σ lower limit) is needed to match the slope of the observed power spectrum of Galactic foreground rotation-measure maps. Using multiple realizations allows us also to infer errors on individual observables. We find that previously-used amplitudes for random and anisotropic random magnetic field components need to be rescaled by factors of ≈0.3 and 0.6 to account for the new small-scale contributions. Our model predicts a rotation measure of -2.8±7.1 rad/m2 and 04.4±11. rad/m2 for the north and south Galactic poles respectively, in good agreement with observations. Applying our model to deflections of ultra-high-energy cosmic rays we infer a mean deflection of ≈3.5±1.1 degree for 60 EeV protons arriving from CenA.

  20. Some remarks on p-spin interaction models in a random field

    NASA Astrophysics Data System (ADS)

    Haddad, T. A. S.; Vieira, A. P.; Salinas, S. R.

    2004-10-01

    We present some calculations for the thermodynamic behavior of mean-field ferromagnetic p-spin interaction models in the presence of quenched random fields. For both Ising and spherical spin variables, we use the law of large numbers, without recourse to the replica trick, to obtain a free-energy functional in terms of the order parameter and an extra non-ordering density. In the spherical limit, we show that the transition is continuous for p=2, but turns into first order for p⩾3, regardless of the probability distribution of the random fields. In the Ising case, for p=2, we recover previously known results. The free-energy functional obtained in this treatment can be used as a starting point for a dynamical study of these models.

  1. The dispersive evolution of charged-particle bunches in random magnetic fields

    NASA Technical Reports Server (NTRS)

    Earl, J. A.

    1985-01-01

    Shortly after a strongly anisotropic beam of charged particles is injected along a guiding magnetic field on which is superimposed a small random conponent, the particle density can be represented by a Gaussian profile whose center moves with the coherent velocity and whose width increases with time at a rate controlled by the coefficient of dispersion. Both parameters depend upon the mean free path, which characterizes scattering by the random fields, and the focusing length, which characterizes spatial variations of the guiding field. These dependencies are known explicitly for the coherent velocity. Formulae for coefficient of dispersion are available only in the limits of very weak and very strong focusing. A new expression for coefficient of dispersion, which spans this gap, is presented.

  2. Characterization of a random anisotropic conductivity field with Karhunen-Loeve methods

    SciTech Connect

    Cherry, Matthew R.; Sabbagh, Harold S.; Pilchak, Adam L.; Knopp, Jeremy S.

    2014-02-18

    While parametric uncertainty quantification for NDE models has been addressed in recent years, the problem of stochastic field parameters such as spatially distributed electrical conductivity has only been investigated minimally in the last year. In that work, the authors treated the field as a one-dimensional random process and Karhunen-Loeve methods were used to discretize this process to make it amenable to UQ methods such as ANOVA expansions. In the present work, we will treat the field as a two dimensional random process, and the eigenvalues and eigenfunctions of the integral operator will be determined via Galerkin methods. The Karhunen-Loeve methods is extended to two dimensions and implemented to represent this process. Several different choices for basis functions will be discussed, as well as convergence criteria for each. The methods are applied to correlation functions collected over electron backscatter data from highly micro textured Ti-7Al.

  3. Controlling dispersion forces between small particles with artificially created random light fields

    PubMed Central

    Brügger, Georges; Froufe-Pérez, Luis S.; Scheffold, Frank; José Sáenz, Juan

    2015-01-01

    Appropriate combinations of laser beams can be used to trap and manipulate small particles with optical tweezers as well as to induce significant optical binding forces between particles. These interaction forces are usually strongly anisotropic depending on the interference landscape of the external fields. This is in contrast with the familiar isotropic, translationally invariant, van der Waals and, in general, Casimir–Lifshitz interactions between neutral bodies arising from random electromagnetic waves generated by equilibrium quantum and thermal fluctuations. Here we show, both theoretically and experimentally, that dispersion forces between small colloidal particles can also be induced and controlled using artificially created fluctuating light fields. Using optical tweezers as a gauge, we present experimental evidence for the predicted isotropic attractive interactions between dielectric microspheres induced by laser-generated, random light fields. These light-induced interactions open a path towards the control of translationally invariant interactions with tuneable strength and range in colloidal systems. PMID:26096622

  4. Methods for testing theory and evaluating impact in randomized field trials

    PubMed Central

    Brown, C. Hendricks; Wang, Wei; Kellam, Sheppard G.; Muthén, Bengt O.; Petras, Hanno; Toyinbo, Peter; Poduska, Jeanne; Ialongo, Nicholas; Wyman, Peter A.; Chamberlain, Patricia; Sloboda, Zili; MacKinnon, David P.; Windham, Amy

    2008-01-01

    Randomized field trials provide unique opportunities to examine the effectiveness of an intervention in real world settings and to test and extend both theory of etiology and theory of intervention. These trials are designed not only to test for overall intervention impact but also to examine how impact varies as a function of individual level characteristics, context, and across time. Examination of such variation in impact requires analytical methods that take into account the trial’s multiple nested structure and the evolving changes in outcomes over time. The models that we describe here merge multilevel modeling with growth modeling, allowing for variation in impact to be represented through discrete mixtures—growth mixture models—and nonparametric smooth functions—generalized additive mixed models. These methods are part of an emerging class of multilevel growth mixture models, and we illustrate these with models that examine overall impact and variation in impact. In this paper, we define intent-to-treat analyses in group-randomized multilevel field trials and discuss appropriate ways to identify, examine, and test for variation in impact without inflating the Type I error rate. We describe how to make causal inferences more robust to misspecification of covariates in such analyses and how to summarize and present these interactive intervention effects clearly. Practical strategies for reducing model complexity, checking model fit, and handling missing data are discussed using six randomized field trials to show how these methods may be used across trials randomized at different levels. PMID:18215473

  5. MODEL OF THE FIELD LINE RANDOM WALK EVOLUTION AND APPROACH TO ASYMPTOTIC DIFFUSION IN MAGNETIC TURBULENCE

    SciTech Connect

    Snodin, A. P.; Ruffolo, D.; Matthaeus, W. H. E-mail: david.ruf@mahidol.ac.th

    2013-01-01

    The turbulent random walk of magnetic field lines plays an important role in the transport of plasmas and energetic particles in a wide variety of astrophysical situations, but most theoretical work has concentrated on determination of the asymptotic field line diffusion coefficient. Here we consider the evolution with distance of the field line random walk using a general ordinary differential equation (ODE), which for most cases of interest in astrophysics describes a transition from free streaming to asymptotic diffusion. By challenging theories of asymptotic diffusion to also describe the evolution, one gains insight on how accurately they describe the random walk process. Previous theoretical work has effectively involved closure of the ODE, often by assuming Corrsin's hypothesis and a Gaussian displacement distribution. Approaches that use quasilinear theory and prescribe the mean squared displacement ({Delta}x {sup 2}) according to free streaming (random ballistic decorrelation, RBD) or asymptotic diffusion (diffusive decorrelation, DD) can match computer simulation results, but only over specific parameter ranges, with no obvious 'marker' of the range of validity. Here we make use of a unified description in which the ODE determines ({Delta}x {sup 2}) self-consistently, providing a natural transition between the assumptions of RBD and DD. We find that the minimum kurtosis of the displacement distribution provides a good indicator of whether the self-consistent ODE is applicable, i.e., inaccuracy of the self-consistent ODE is associated with non-Gaussian displacement distributions.

  6. A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

    NASA Astrophysics Data System (ADS)

    Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

    2016-07-01

    A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of field and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.

  7. Random walk of magnetic field lines in dynamical turbulence: A field line tracing method. I. Slab turbulence

    SciTech Connect

    Shalchi, A.

    2010-08-15

    To study the wandering of magnetic field lines is an important subject in theoretical physics. Results of field line random walk theories can be applied in plasma physics as well as astrophysics. Previous investigations are based on magnetostatic models. These models have been used in analytical work as well as in computer simulations to warrant mathematical and numerical tractability. To replace the magnetostatic model by a dynamical turbulence model is a difficult task. In the present article, a field line tracing method is used to describe field line wandering in dynamical magnetic turbulence. As examples different models are employed, namely, the plasma wave model, the damping model of dynamical turbulence, and the random sweeping model. It is demonstrated that the choice of the turbulence model has a very strong influence on the field line structure. It seems that if dynamical turbulence effects are included, Markovian diffusion can be found for other forms of the wave spectrum as in the magnetostatic model. Therefore, the results of the present paper are useful to specify turbulence models. As a further application we consider charged particle transport at early times.

  8. Planetary science. Low-altitude magnetic field measurements by MESSENGER reveal Mercury's ancient crustal field.

    PubMed

    Johnson, Catherine L; Phillips, Roger J; Purucker, Michael E; Anderson, Brian J; Byrne, Paul K; Denevi, Brett W; Feinberg, Joshua M; Hauck, Steven A; Head, James W; Korth, Haje; James, Peter B; Mazarico, Erwan; Neumann, Gregory A; Philpott, Lydia C; Siegler, Matthew A; Tsyganenko, Nikolai A; Solomon, Sean C

    2015-05-22

    Magnetized rocks can record the history of the magnetic field of a planet, a key constraint for understanding its evolution. From orbital vector magnetic field measurements of Mercury taken by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft at altitudes below 150 kilometers, we have detected remanent magnetization in Mercury's crust. We infer a lower bound on the average age of magnetization of 3.7 to 3.9 billion years. Our findings indicate that a global magnetic field driven by dynamo processes in the fluid outer core operated early in Mercury's history. Ancient field strengths that range from those similar to Mercury's present dipole field to Earth-like values are consistent with the magnetic field observations and with the low iron content of Mercury's crust inferred from MESSENGER elemental composition data. PMID:25953822

  9. Planetary science. Low-altitude magnetic field measurements by MESSENGER reveal Mercury's ancient crustal field.

    PubMed

    Johnson, Catherine L; Phillips, Roger J; Purucker, Michael E; Anderson, Brian J; Byrne, Paul K; Denevi, Brett W; Feinberg, Joshua M; Hauck, Steven A; Head, James W; Korth, Haje; James, Peter B; Mazarico, Erwan; Neumann, Gregory A; Philpott, Lydia C; Siegler, Matthew A; Tsyganenko, Nikolai A; Solomon, Sean C

    2015-05-22

    Magnetized rocks can record the history of the magnetic field of a planet, a key constraint for understanding its evolution. From orbital vector magnetic field measurements of Mercury taken by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft at altitudes below 150 kilometers, we have detected remanent magnetization in Mercury's crust. We infer a lower bound on the average age of magnetization of 3.7 to 3.9 billion years. Our findings indicate that a global magnetic field driven by dynamo processes in the fluid outer core operated early in Mercury's history. Ancient field strengths that range from those similar to Mercury's present dipole field to Earth-like values are consistent with the magnetic field observations and with the low iron content of Mercury's crust inferred from MESSENGER elemental composition data.

  10. On Polynomial Lieb-Robinson Bounds for the XY Chain in a Decaying Random Field

    NASA Astrophysics Data System (ADS)

    Gebert, Martin; Lemm, Marius

    2016-08-01

    We consider the isotropic XY quantum spin chain in a random external field in the z direction, with single site distributions given by i.i.d. random variables times the critical decaying envelope j^{-1/2}. Our motivation is the study of many-body localization. We investigate transport properties in terms of polynomial Lieb-Robinson (PLR) bounds. We prove a zero-velocity PLR bound for large disorder strength λ and for small λ we show a partial converse, which suggests the existence of a transition to non-trivial transport in the model.

  11. Lengths of ferroelectric domains: The role of defects and random fields

    NASA Astrophysics Data System (ADS)

    Voelker, Uwe; Dinges, Kai; Heine, Urs; Betzler, Klaus

    2010-06-01

    Using noncollinear optical second-harmonic generation, the characteristic lengths of ferroelectric domains in strontium-barium niobate are determined. The role of the domain geometry in the random quasiphase matching process involved is elucidated by model calculations on different domain arrangements. The calculations prove that the domain geometries—especially the domain lengths—strongly affect the angular distribution of the generated second-harmonic light. The evaluation of the measured angular distributions in crystals with different doping concentrations shows that the domain lengths are distinctly albeit not drastically influenced by the dopant-induced random electric or strain fields.

  12. Analysis and Prediction of the Critical Regions of Antimicrobial Peptides Based on Conditional Random Fields

    PubMed Central

    Chang, Kuan Y.; Lin, Tung-pei; Shih, Ling-Yi; Wang, Chien-Kuo

    2015-01-01

    Antimicrobial peptides (AMPs) are potent drug candidates against microbes such as bacteria, fungi, parasites, and viruses. The size of AMPs ranges from less than ten to hundreds of amino acids. Often only a few amino acids or the critical regions of antimicrobial proteins matter the functionality. Accurately predicting the AMP critical regions could benefit the experimental designs. However, no extensive analyses have been done specifically on the AMP critical regions and computational modeling on them is either non-existent or settled to other problems. With a focus on the AMP critical regions, we thus develop a computational model AMPcore by introducing a state-of-the-art machine learning method, conditional random fields. We generate a comprehensive dataset of 798 AMPs cores and a low similarity dataset of 510 representative AMP cores. AMPcore could reach a maximal accuracy of 90% and 0.79 Matthew’s correlation coefficient on the comprehensive dataset and a maximal accuracy of 83% and 0.66 MCC on the low similarity dataset. Our analyses of AMP cores follow what we know about AMPs: High in glycine and lysine, but low in aspartic acid, glutamic acid, and methionine; the abundance of α-helical structures; the dominance of positive net charges; the peculiarity of amphipathicity. Two amphipathic sequence motifs within the AMP cores, an amphipathic α-helix and an amphipathic π-helix, are revealed. In addition, a short sequence motif at the N-terminal boundary of AMP cores is reported for the first time: arginine at the P(-1) coupling with glycine at the P1 of AMP cores occurs the most, which might link to microbial cell adhesion. PMID:25803302

  13. Directed random walks and constraint programming reveal active pathways in hepatocyte growth factor signaling.

    PubMed

    Kittas, Aristotelis; Delobelle, Aurélien; Schmitt, Sabrina; Breuhahn, Kai; Guziolowski, Carito; Grabe, Niels

    2016-01-01

    An effective means to analyze mRNA expression data is to take advantage of established knowledge from pathway databases, using methods such as pathway-enrichment analyses. However, pathway databases are not case-specific and expression data could be used to infer gene-regulation patterns in the context of specific pathways. In addition, canonical pathways may not always describe the signaling mechanisms properly, because interactions can frequently occur between genes in different pathways. Relatively few methods have been proposed to date for generating and analyzing such networks, preserving the causality between gene interactions and reasoning over the qualitative logic of regulatory effects. We present an algorithm (MCWalk) integrated with a logic programming approach, to discover subgraphs in large-scale signaling networks by random walks in a fully automated pipeline. As an exemplary application, we uncover the signal transduction mechanisms in a gene interaction network describing hepatocyte growth factor-stimulated cell migration and proliferation from gene-expression measured with microarray and RT-qPCR using in-house perturbation experiments in a keratinocyte-fibroblast co-culture. The resulting subgraphs illustrate possible associations of hepatocyte growth factor receptor c-Met nodes, differentially expressed genes and cellular states. Using perturbation experiments and Answer Set programming, we are able to select those which are more consistent with the experimental data. We discover key regulator nodes by measuring the frequency with which they are traversed when connecting signaling between receptors and significantly regulated genes and predict their expression-shift consistently with the measured data. The Java implementation of MCWalk is publicly available under the MIT license at: https://bitbucket.org/akittas/biosubg.

  14. Comparison of Haemophilus parasuis reference strains and field isolates by using random amplified polymorphic DNA and protein profiles

    PubMed Central

    2012-01-01

    Background Haemophilus parasuis is the causative agent of Glässer’s disease and is a pathogen of swine in high-health status herds. Reports on serotyping of field strains from outbreaks describe that approximately 30% of them are nontypeable and therefore cannot be traced. Molecular typing methods have been used as alternatives to serotyping. This study was done to compare random amplified polymorphic DNA (RAPD) profiles and whole cell protein (WCP) lysate profiles as methods for distinguishing H. parasuis reference strains and field isolates. Results The DNA and WCP lysate profiles of 15 reference strains and 31 field isolates of H. parasuis were analyzed using the Dice and neighbor joining algorithms. The results revealed unique and reproducible DNA and protein profiles among the reference strains and field isolates studied. Simpson’s index of diversity showed significant discrimination between isolates when three 10mer primers were combined for the RAPD method and also when both the RAPD and WCP lysate typing methods were combined. Conclusions The RAPD profiles seen among the reference strains and field isolates did not appear to change over time which may reflect a lack of DNA mutations in the genes of the samples. The recent field isolates had different WCP lysate profiles than the reference strains, possibly because the number of passages of the type strains may affect their protein expression. PMID:22703293

  15. Random fields generation on the GPU with the spectral turning bands method

    NASA Astrophysics Data System (ADS)

    Hunger, L.; Cosenza, B.; Kimeswenger, S.; Fahringer, T.

    2014-08-01

    Random field (RF) generation algorithms are of paramount importance for many scientific domains, such as astrophysics, geostatistics, computer graphics and many others. Some examples are the generation of initial conditions for cosmological simulations or hydrodynamical turbulence driving. In the latter a new random field is needed every time-step. Current approaches commonly make use of 3D FFT (Fast Fourier Transform) and require the whole generated field to be stored in memory. Moreover, they are limited to regular rectilinear meshes and need an extra processing step to support non-regular meshes. In this paper, we introduce TBARF (Turning BAnd Random Fields), a RF generation algorithm based on the turning band method that is optimized for massively parallel hardware such as GPUs. Our algorithm replaces the 3D FFT with a lower order, one-dimensional FFT followed by a projection step, and is further optimized with loop unrolling and blocking. We show that TBARF can easily generate RF on non-regular (non uniform) meshes and can afford mesh sizes bigger than the available GPU memory by using a streaming, out-of-core approach. TBARF is 2 to 5 times faster than the traditional methods when generating RFs with more than 16M cells. It can also generate RF on non-regular meshes, and has been successfully applied to two real case scenarios: planetary nebulae and cosmological simulations.

  16. Analytic Theory and Numerical Study of the Magnetic Field Line Random Walk in Reduced Magnetohydrodynamic Turbulence

    NASA Astrophysics Data System (ADS)

    Ruffolo, D. J.; Snodin, A. P.; Oughton, S.; Servidio, S.; Matthaeus, W. H.

    2013-12-01

    The random walk of magnetic field lines is examined analytically and numerically in the context of reduced magnetohydrodynamic (RMHD) turbulence, which provides a useful description of plasmas dominated by a strong mean field, such as in the solar corona. A nonperturbative theory of magnetic field line diffusion [1] is compared with the diffusion coefficients obtained by accurate numerical tracing of magnetic field lines for both synthetic models and direct numerical simulations of RMHD. Statistical analysis of an ensemble of trajectories confirms the applicability of the theory, which very closely matches the numerical field line diffusion coefficient as a function of distance z along the mean magnetic field for a wide range of the Kubo number R. The theory employs Corrsin's independence hypothesis, sometimes thought to be valid only at low R. However, the results demonstrate that it works well up to R=10, both for a synthetic RMHD model and an RMHD simulation. The numerical results from RMHD simulation are compared with and without phase randomization, demonstrating an effect of coherent structures on the field line random walk for low Kubo number. Partially supported by a postdoctoral fellowship from Mahidol University, the Thailand Research Fund, POR Calabria FSE-2007/2013, the US NSF (AGS-1063439 and SHINE AGS-1156094), NASA (Heliophysics Theory NNX08AI47G & NNX11AJ44G), by the Solar Probe Plus Project through the ISIS Theory team, by the MMS Theory and Modeling team, and by EU Marie Curie Project FP7 PIRSES-2010-269297 'Turboplasmas' at Università della Calabria. [1] D. Ruffolo and W. H. Matthaeus, Phys. Plasmas, 20, 012308 (2013).

  17. A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

    DOE PAGESBeta

    Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

    2016-07-20

    A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

  18. A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

    PubMed

    Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

    2016-06-01

    Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs.

  19. Synthesis of cervical tissue second harmonic generation images using Markov random field modeling.

    PubMed

    Yousefi, S; Kehtarnavaz, N; Gholipour, A

    2011-01-01

    This paper presents a statistical image modeling approach based on Markov random field to synthesize cervical tissue second harmonic generation (SHG) images. Binary images representing fiber and pore areas of the cervix tissue are first obtained from SHG images using an image processing pipeline consisting of noise removal, contrast enhancement and optimal thresholding. These binary images are modeled using a Markov random field whose parameters are estimated via the least squares method. The parameters are then used to synthesize fiber and pore areas of cervical tissue in the form of binary images. The effectiveness of the synthesis is demonstrated by reporting the classification outcome for two classes of cervical SHG images collected from mice at two different stages of normal pregnancy. The developed synthesis allows generation of realistic fiber and pore area binary images for cervical tissue studies.

  20. On the convergence of EM-like algorithms for image segmentation using Markov random fields.

    PubMed

    Roche, Alexis; Ribes, Delphine; Bach-Cuadra, Meritxell; Krüger, Gunnar

    2011-12-01

    Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.

  1. Quantum correlations and dynamics from classical random fields valued in complex Hilbert spaces

    SciTech Connect

    Khrennikov, Andrei

    2010-08-15

    One of the crucial differences between mathematical models of classical and quantum mechanics (QM) is the use of the tensor product of the state spaces of subsystems as the state space of the corresponding composite system. (To describe an ensemble of classical composite systems, one uses random variables taking values in the Cartesian product of the state spaces of subsystems.) We show that, nevertheless, it is possible to establish a natural correspondence between the classical and the quantum probabilistic descriptions of composite systems. Quantum averages for composite systems (including entangled) can be represented as averages with respect to classical random fields. It is essentially what Albert Einstein dreamed of. QM is represented as classical statistical mechanics with infinite-dimensional phase space. While the mathematical construction is completely rigorous, its physical interpretation is a complicated problem. We present the basic physical interpretation of prequantum classical statistical field theory in Sec. II. However, this is only the first step toward real physical theory.

  2. Quantum correlations of three-qubit states driven by a classical random external field

    NASA Astrophysics Data System (ADS)

    Guo, Youneng; Fang, Maofa; Zhang, Shiyang; Liu, Xiang

    2015-03-01

    In this paper, we exploit the notions of tripartite quantum discord {{D}(3)}, tripartite negativity {{N}(3)}, and entanglement witnesses (EWs), respectively, as a measure of quantum correlations in a model of three noninteracting qubits subject to a classical random external field. We compare the dynamics of {{D}(3)} with that of entanglement for the initial entangled pure or mixed GHZ- and W-type states. We find that the quantum correlations dynamics depend on the input configuration of the purity of the initial states. The results show that {{D}(3)} may be more robust than entanglement and no sudden death of the {{D}(3)} occurs, whereas entanglement displays periodically sudden death and revivals in the regions for GHZ- and W-type states driven by a classical random external field. Furthermore, we also show that the survival partial entanglement can be detected by means of the suitable EWs.

  3. Possible Statistics of Two Coupled Random Fields: Application to Passive Scalar

    NASA Technical Reports Server (NTRS)

    Dubrulle, B.; He, Guo-Wei; Bushnell, Dennis M. (Technical Monitor)

    2000-01-01

    We use the relativity postulate of scale invariance to derive the similarity transformations between two coupled scale-invariant random elds at different scales. We nd the equations leading to the scaling exponents. This formulation is applied to the case of passive scalars advected i) by a random Gaussian velocity field; and ii) by a turbulent velocity field. In the Gaussian case, we show that the passive scalar increments follow a log-Levy distribution generalizing Kraichnan's solution and, in an appropriate limit, a log-normal distribution. In the turbulent case, we show that when the velocity increments follow a log-Poisson statistics, the passive scalar increments follow a statistics close to log-Poisson. This result explains the experimental observations of Ruiz et al. about the temperature increments.

  4. A heuristic for the distribution of point counts for random curves over a finite field

    PubMed Central

    Achter, Jeffrey D.; Erman, Daniel; Kedlaya, Kiran S.; Wood, Melanie Matchett; Zureick-Brown, David

    2015-01-01

    How many rational points are there on a random algebraic curve of large genus g over a given finite field ? We propose a heuristic for this question motivated by a (now proven) conjecture of Mumford on the cohomology of moduli spaces of curves; this heuristic suggests a Poisson distribution with mean q+1+1/(q−1). We prove a weaker version of this statement in which g and q tend to infinity, with q much larger than g. PMID:25802415

  5. Percolation in sign-symmetric random fields: topological aspects and numerical modeling

    PubMed

    Milovanov; Zimbardo

    2000-07-01

    The topology of percolation in random scalar fields psi(x) with sign symmetry [i.e., that the statistical properties of the functions psi(x) and -psi(x) are identical] is analyzed. Based on methods of general topology, we show that the zero set psi(x)=0 of the n-dimensional (n>/=2) sign-symmetric random field psi(x) contains a (connected) percolating subset under the condition |nablapsi(x)| not equal0 everywhere except in domains of negligible measure. The fractal geometry of percolation is analyzed in more detail in the particular case of the two-dimensional (n=2) fields psi(x). The improved Alexander-Orbach conjecture [Phys. Rev. E 56, 2437 (1997)] is applied analytically to obtain estimates of the main fractal characteristics of the percolating fractal sets generated by the horizontal "cuts," psi(x)=h, of the field psi(x). These characteristics are the Hausdorff fractal dimension of the set, D, and the index of connectivity, straight theta. We advocate an unconventional approach to studying the geometric properties of fractals, which involves methods of homotopic topology. It is shown that the index of connectivity, straight theta, of a fractal set is the topological invariant of this set, i.e., it remains unchanged under the homeomorphic deformations of the fractal. This issue is explicitly used in our study to find the Hausdorff fractal dimension of the single isolevels of the field psi(x), as well as the related geometric quantities. The results obtained are analyzed numerically in the particular case when the random field psi(x) is given by a fractional Brownian surface whose topological properties recover well the main assumptions of our consideration.

  6. Lossy cutset coding of bilevel images based on Markov random fields.

    PubMed

    Reyes, Matthew G; Neuhoff, David L; Pappas, Thrasyvoulos N

    2014-04-01

    An effective, low complexity method for lossy compression of scenic bilevel images, called lossy cutset coding, is proposed based on a Markov random field model. It operates by losslessly encoding pixels in a square grid of lines, which is a cutset with respect to a Markov random field model, and preserves key structural information, such as borders between black and white regions. Relying on the Markov random field model, the decoder takes a MAP approach to reconstructing the interior of each grid block from the pixels on its boundary, thereby creating a piecewise smooth image that is consistent with the encoded grid pixels. The MAP rule, which reduces to finding the block interiors with fewest black-white transitions, is directly implementable for the most commonly occurring block boundaries, thereby avoiding the need for brute force or iterative solutions. Experimental results demonstrate that the new method is computationally simple, outperforms the current lossy compression technique most suited to scenic bilevel images, and provides substantially lower rates than lossless techniques, e.g., JBIG, with little loss in perceived image quality.

  7. Fluorescence microscopy image noise reduction using a stochastically-connected random field model

    PubMed Central

    Haider, S. A.; Cameron, A.; Siva, P.; Lui, D.; Shafiee, M. J.; Boroomand, A.; Haider, N.; Wong, A.

    2016-01-01

    Fluorescence microscopy is an essential part of a biologist’s toolkit, allowing assaying of many parameters like subcellular localization of proteins, changes in cytoskeletal dynamics, protein-protein interactions, and the concentration of specific cellular ions. A fundamental challenge with using fluorescence microscopy is the presence of noise. This study introduces a novel approach to reducing noise in fluorescence microscopy images. The noise reduction problem is posed as a Maximum A Posteriori estimation problem, and solved using a novel random field model called stochastically-connected random field (SRF), which combines random graph and field theory. Experimental results using synthetic and real fluorescence microscopy data show the proposed approach achieving strong noise reduction performance when compared to several other noise reduction algorithms, using quantitative metrics. The proposed SRF approach was able to achieve strong performance in terms of signal-to-noise ratio in the synthetic results, high signal to noise ratio and contrast to noise ratio in the real fluorescence microscopy data results, and was able to maintain cell structure and subtle details while reducing background and intra-cellular noise. PMID:26884148

  8. Spectral turning bands for efficient Gaussian random fields generation on GPUs and accelerators

    NASA Astrophysics Data System (ADS)

    Hunger, L.; Cosenza, B.; Kimeswenger, S.; Fahringer, T.

    2015-11-01

    A random field (RF) is a set of correlated random variables associated with different spatial locations. RF generation algorithms are of crucial importance for many scientific areas, such as astrophysics, geostatistics, computer graphics, and many others. Current approaches commonly make use of 3D fast Fourier transform (FFT), which does not scale well for RF bigger than the available memory; they are also limited to regular rectilinear meshes. We introduce random field generation with the turning band method (RAFT), an RF generation algorithm based on the turning band method that is optimized for massively parallel hardware such as GPUs and accelerators. Our algorithm replaces the 3D FFT with a lower-order, one-dimensional FFT followed by a projection step and is further optimized with loop unrolling and blocking. RAFT can easily generate RF on non-regular (non-uniform) meshes and efficiently produce fields with mesh sizes bigger than the available device memory by using a streaming, out-of-core approach. Our algorithm generates RF with the correct statistical behavior and is tested on a variety of modern hardware, such as NVIDIA Tesla, AMD FirePro and Intel Phi. RAFT is faster than the traditional methods on regular meshes and has been successfully applied to two real case scenarios: planetary nebulae and cosmological simulations.

  9. Schwinger-Dyson equations in large-N quantum field theories and nonlinear random processes

    SciTech Connect

    Buividovich, P. V.

    2011-02-15

    We propose a stochastic method for solving Schwinger-Dyson equations in large-N quantum field theories. Expectation values of single-trace operators are sampled by stationary probability distributions of the so-called nonlinear random processes. The set of all the histories of such processes corresponds to the set of all planar diagrams in the perturbative expansions of the expectation values of singlet operators. We illustrate the method on examples of the matrix-valued scalar field theory and the Weingarten model of random planar surfaces on the lattice. For theories with compact field variables, such as sigma models or non-Abelian lattice gauge theories, the method does not converge in the physically most interesting weak-coupling limit. In this case one can absorb the divergences into a self-consistent redefinition of expansion parameters. A stochastic solution of the self-consistency conditions can be implemented as a 'memory' of the random process, so that some parameters of the process are estimated from its previous history. We illustrate this idea on the two-dimensional O(N) sigma model. The extension to non-Abelian lattice gauge theories is discussed.

  10. Lack of adaptation to random conflicting force fields of variable magnitude.

    PubMed

    Gupta, Rahul; Ashe, James

    2007-01-01

    The concept of internal models has been used to explain how the brain learns and stores a variety of motor behaviors. A large body of work has shown that conflicting internal models could not be learned simultaneously; this suggests either a limited capacity or the unstable nature of short-term motor memories. However, it has been recently shown that multiple conflicting internal models of motor behavior could be acquired simultaneously if associated with appropriate contextual cues and random presentations. We re-examined this issue in a more complex environment in which the magnitude of the conflicting fields could vary randomly. Human subjects failed to show any evidence of learning the force fields themselves or the magnitude of the forces experienced, even with extended practice. Subjects did adapt to the applied perturbation when the field strength was kept constant but still did not form internal models. Our results show that neither random presentation nor specific contextual cues are sufficient for learning conflicting internal models when the magnitude of the forces is also unpredictable. The data suggest that multiple conflicting internal models cannot be learned in all environments, and provide support for the unstable nature or limited capacity of motor memories.

  11. Random Field Driven Spatial Complexity at the Mott Transition in VO2

    NASA Astrophysics Data System (ADS)

    Liu, Shuo; Phillabaum, B.; Carlson, E. W.; Dahmen, K. A.; Vidhyadhiraja, N. S.; Qazilbash, M. M.; Basov, D. N.

    2016-01-01

    We report the first application of critical cluster techniques to the Mott metal-insulator transition in vanadium dioxide. We show that the geometric universal properties of the metallic and insulating puddles observed by scanning near-field infrared microscopy are consistent with the system passing near criticality of the random field Ising model as temperature is varied. The resulting large barriers to equilibrium may be the source of the unusually robust hysteresis phenomena associated with the metal-insulator transition in this system.

  12. Phase transitions of Ising mixed spin 1 and 3/2 with random crystal field distribution

    NASA Astrophysics Data System (ADS)

    Sabri, S.; EL Falaki, M.; EL Yadari, M.; Benyoussef, A.; EL Kenz, A.

    2016-10-01

    The thermal and magnetic properties of the mixed spin-1 and spin-3/2 in the presence of the random crystal field are studied within the mean field approach based on the Bogoliubov inequality for the Gibbs free energy. The model exhibits first, second order transitions, a tricritical point, triple point and an isolated critical end point. It is found that the system displays simple and double compensation temperatures, five topologies of the phase diagrams. A re-entrant phenomenon is also discussed and the thermal dependences of total magnetization according to extended Neel classification have been also given.

  13. Anomalous diffusion and Levy random walk of magnetic field lines in three dimensional turbulence

    SciTech Connect

    Zimbardo, G.; Veltri, P.; Basile, G.; Principato, S.

    1995-07-01

    The transport of magnetic field lines is studied numerically where three dimensional (3-D) magnetic fluctuations, with a power law spectrum, and periodic over the simulation box are superimposed on an average uniform magnetic field. The weak and the strong turbulence regime, {delta}{ital B}{similar_to}{ital B}{sub 0}, are investigated. In the weak turbulence case, magnetic flux tubes are separated from each other by percolating layers in which field lines undergo a chaotic motion. In this regime the field lines may exhibit Levy, rather than Gaussian, random walk, changing from Levy flights to trapped motion. The anomalous diffusion laws {l_angle}{Delta}{ital x}{sup 2}{sub {ital i}}{r_angle}{proportional_to}{ital s}{sup {alpha}} with {alpha}{gt}1 and {alpha}{lt}1, are obtained for a number of cases, and the non-Gaussian character of the field line random walk is pointed out by computing the kurtosis. Increasing the fluctuation level, and, therefore stochasticity, normal diffusion ({alpha}{congruent}1) is recovered and the kurtoses reach their Gaussian value. However, the numerical results show that neither the quasi-linear theory nor the two dimensional percolation theory can be safely extrapolated to the considered 3-D strong turbulence regime. {copyright} {ital 1995} {ital American} {ital Institute} {ital of} {ital Physics}.

  14. Multi-fidelity modelling via recursive co-kriging and Gaussian–Markov random fields

    PubMed Central

    Perdikaris, P.; Venturi, D.; Royset, J. O.; Karniadakis, G. E.

    2015-01-01

    We propose a new framework for design under uncertainty based on stochastic computer simulations and multi-level recursive co-kriging. The proposed methodology simultaneously takes into account multi-fidelity in models, such as direct numerical simulations versus empirical formulae, as well as multi-fidelity in the probability space (e.g. sparse grids versus tensor product multi-element probabilistic collocation). We are able to construct response surfaces of complex dynamical systems by blending multiple information sources via auto-regressive stochastic modelling. A computationally efficient machine learning framework is developed based on multi-level recursive co-kriging with sparse precision matrices of Gaussian–Markov random fields. The effectiveness of the new algorithms is demonstrated in numerical examples involving a prototype problem in risk-averse design, regression of random functions, as well as uncertainty quantification in fluid mechanics involving the evolution of a Burgers equation from a random initial state, and random laminar wakes behind circular cylinders. PMID:26345079

  15. Critical and umbilical points of a non-Gaussian random field

    NASA Astrophysics Data System (ADS)

    Beuman, T. H.; Turner, A. M.; Vitelli, V.

    2013-07-01

    Random fields in nature often have, to a good approximation, Gaussian characteristics. For such fields, the number of maxima and minima are the same. Furthermore, the relative densities of umbilical points, topological defects which can be classified into three types, have certain fixed values. Phenomena described by nonlinear laws can, however, give rise to a non-Gaussian contribution, causing a deviation from these universal values. We consider a random surface, whose height is given by a nonlinear function of a Gaussian field. We find that, as a result of the non-Gaussianity, the density of maxima and minima no longer match and we calculate the relative imbalance between the two. We also calculate the change in the relative density of umbilics. This allows us not only to detect a perturbation, but to determine its size as well. This geometric approach offers an independent way of detecting non-Gaussianity, which even works in cases where the field itself can not be probed directly.

  16. Spatial-Temporal Conditional Random Fields Crop Classification from Terrasar-X Images

    NASA Astrophysics Data System (ADS)

    Kenduiywoa, B. K.; Bargiel, D.; Soergel, U.

    2015-03-01

    The rapid increase in population in the world has propelled pressure on arable land. Consequently, the food basket has continuously declined while global demand for food has grown twofold. There is need to monitor and update agriculture land-cover to support food security measures. This study develops a spatial-temporal approach using conditional random fields (CRF) to classify co-registered images acquired in two epochs. We adopt random forest (RF) as CRF association potential and introduce a temporal potential for mutual crop phenology information exchange between spatially corresponding sites in two epochs. An important component of temporal potential is a transitional matrix that bears intra- and inter-class changes between considered epochs. Conventionally, one matrix has been used in the entire image thereby enforcing stationary transition probabilities in all sites. We introduce a site dependent transition matrix to incorporate phenology information from images. In our study, images are acquired within a vegetation season, thus perceived spectral changes are due to crop phenology. To exploit this phenomena, we develop a novel approach to determine site-wise transition matrix using conditional probabilities computed from two corresponding temporal sites. Conditional probability determines transitions between classes in different epochs and thus we used it to propagate crop phenology information. Classification results show that our approach improved crop discrimination in all epochs compared to state-of-the-art mono-temporal approaches (RF and CRF monotemporal) and existing multi-temporal markov random fields approach by Liu et al. (2008).

  17. Proteomics Analysis with a Nano Random Forest Approach Reveals Novel Functional Interactions Regulated by SMC Complexes on Mitotic Chromosomes*

    PubMed Central

    Ohta, Shinya; Montaño-Gutierrez, Luis F.; de Lima Alves, Flavia; Ogawa, Hiromi; Toramoto, Iyo; Sato, Nobuko; Morrison, Ciaran G.; Takeda, Shunichi; Hudson, Damien F.; Earnshaw, William C.

    2016-01-01

    Packaging of DNA into condensed chromosomes during mitosis is essential for the faithful segregation of the genome into daughter nuclei. Although the structure and composition of mitotic chromosomes have been studied for over 30 years, these aspects are yet to be fully elucidated. Here, we used stable isotope labeling with amino acids in cell culture to compare the proteomes of mitotic chromosomes isolated from cell lines harboring conditional knockouts of members of the condensin (SMC2, CAP-H, CAP-D3), cohesin (Scc1/Rad21), and SMC5/6 (SMC5) complexes. Our analysis revealed that these complexes associate with chromosomes independently of each other, with the SMC5/6 complex showing no significant dependence on any other chromosomal proteins during mitosis. To identify subtle relationships between chromosomal proteins, we employed a nano Random Forest (nanoRF) approach to detect protein complexes and the relationships between them. Our nanoRF results suggested that as few as 113 of 5058 detected chromosomal proteins are functionally linked to chromosome structure and segregation. Furthermore, nanoRF data revealed 23 proteins that were not previously suspected to have functional interactions with complexes playing important roles in mitosis. Subsequent small-interfering-RNA-based validation and localization tracking by green fluorescent protein-tagging highlighted novel candidates that might play significant roles in mitotic progression. PMID:27231315

  18. The spectrum of random magnetic fields in the mean field dynamo theory of the Galactic magnetic field

    NASA Technical Reports Server (NTRS)

    Kulsrud, Russell M.; Anderson, Stephen W.

    1992-01-01

    The fluctuation spectrum that must arise in a mean field dynamo generation of galactic fields if the initial field is weak is considered. A kinetic equation for its evolution is derived and solved. The spectrum evolves by transfer of energy from one magnetic mode to another by interaction with turbulent velocity modes. This kinetic equation is valid in the limit that the rate of evolution of the magnetic modes is slower than the reciprocal decorrelation time of the turbulent modes. This turns out to be the case by a factor greater than 3. Most of the fluctuation energy concentrates on small scales, shorter than the hydrodynamic turbulent scales. The fluctuation energy builds up to equipartition with the turbulent energy in times that are short compared to the e-folding time of the mean field. The turbulence becomes strongly modified before the dynamo amplification starts. Thus, the kinematic assumption of the mean dynamo theory is invalid. Thus, the galactic field must have a primordial origin, although it may subsequently be modified by dynamo action.

  19. Certified randomness from a two-level system in a relativistic quantum field

    NASA Astrophysics Data System (ADS)

    Thinh, Le Phuc; Bancal, Jean-Daniel; Martín-Martínez, Eduardo

    2016-08-01

    Randomness is an indispensable resource in modern science and information technology. Fortunately, an experimentally simple procedure exists to generate randomness with well-characterized devices: measuring a quantum system in a basis complementary to its preparation. Towards realizing this goal one may consider using atoms or superconducting qubits, promising candidates for quantum information processing. However, their unavoidable interaction with the electromagnetic field affects their dynamics. At large time scales, this can result in decoherence. Smaller time scales in principle avoid this problem, but may not be well analyzed under the usual rotating wave and single mode approximation (RWA and SMA) which break the relativistic nature of quantum field theory. Here, we use a fully relativistic analysis to quantify the information that an adversary with access to the field could get on the result of an atomic measurement. Surprisingly, we find that the adversary's guessing probability is not minimized for atoms initially prepared in the ground state (an intuition derived from the RWA and SMA model).

  20. Karhunen-Loève expansion revisited for vector-valued random fields: Scaling, errors and optimal basis.

    NASA Astrophysics Data System (ADS)

    Perrin, G.; Soize, C.; Duhamel, D.; Funfschilling, C.

    2013-06-01

    Due to scaling effects, when dealing with vector-valued random fields, the classical Karhunen-Loève expansion, which is optimal with respect to the total mean square error, tends to favorize the components of the random field that have the highest signal energy. When these random fields are to be used in mechanical systems, this phenomenon can introduce undesired biases for the results. This paper presents therefore an adaptation of the Karhunen-Loève expansion that allows us to control these biases and to minimize them. This original decomposition is first analyzed from a theoretical point of view, and is then illustrated on a numerical example.

  1. A Bayesian approach for inverse modeling, data assimilation, and conditional simulation of spatial random fields

    NASA Astrophysics Data System (ADS)

    Rubin, Yoram; Chen, Xingyuan; Murakami, Haruko; Hahn, Melanie

    2010-10-01

    This paper addresses the inverse problem in spatially variable fields such as hydraulic conductivity in groundwater aquifers or rainfall intensity in hydrology. Common to all these problems is the existence of a complex pattern of spatial variability of the target variables and observations, the multiple sources of data available for characterizing the fields, the complex relations between the observed and target variables and the multiple scales and frequencies of the observations. The method of anchored distributions (MAD) that we propose here is a general Bayesian method of inverse modeling of spatial random fields that addresses this complexity. The central elements of MAD are a modular classification of all relevant data and a new concept called "anchors." Data types are classified by the way they relate to the target variable, as either local or nonlocal and as either direct or indirect. Anchors are devices for localization of data: they are used to convert nonlocal, indirect data into local distributions of the target variables. The target of the inversion is the derivation of the joint distribution of the anchors and structural parameters, conditional to all measurements, regardless of scale or frequency of measurement. The structural parameters describe large-scale trends of the target variable fields, whereas the anchors capture local inhomogeneities. Following inversion, the joint distribution of anchors and structural parameters is used for generating random fields of the target variable(s) that are conditioned on the nonlocal, indirect data through their anchor representation. We demonstrate MAD through a detailed case study that assimilates point measurements of the conductivity with head measurements from natural gradient flow. The resulting statistical distributions of the parameters are non-Gaussian. Similarly, the moments of the estimates of the hydraulic head are non-Gaussian. We provide an extended discussion of MAD vis à vis other inversion

  2. The effect of random alpha-fluctuations and the global properties of the solar magnetic field

    NASA Astrophysics Data System (ADS)

    Hoyng, P.; Schmitt, D.; Teuben, L. J. W.

    1994-09-01

    We study the effect of rapid random fluctuations in the dynamo parameter alpha in a simple axisymmetric mean-field dynamo. The model is 1D; it is a shell with latitude-dependent fields. Radial turbulent diffusion is modeled by a prescribed factor ikr r in the field potentials. We consider mainly linear models. The fluctuations excite overtones of the fundamental mode which are otherwise damped. Butterfly diagrams and frequency spectra Sl(nu) of the Legendre expansion coefficients cl(t) of the toroidal mean field (B(theta, t) = Sigmalcl(t)Pl(cos(theta))) are compared with observations of the solar magnetic field. The results are: (1). The model accounts for the observed relative phases of the coefficients cl(t) for odd l at the frequency per 22 yr of the fundamental mode, and potentially also for their relative amplitudes. (2). The spectra Sl(nu) are broad and featureless for even l, while for odd l the frequency per 22 yr of the fundamental mode dominates. (3). Butterfly diagrams have a solar-type structure for 1 less than or approximately = kR less than or approximately = 5 (R = position of the bottom of the convection zone). (4). The amplitudes of the eigenmodes are shown to behave as randomly excited coupled oscillators. (5). In the latitude region where the dynamo operates the local fluctuations in (u dot del-V x u)tauc are approximately 60 to 70 times larger than the mean value of (u dot del-V x u)tauc, and the fluctuations in alpha are 6 to 7 times larger than the mean value of alpha.

  3. Separable Markov random field model and its applications in low level vision.

    PubMed

    Sun, Jian; Tappen, Marshall F

    2013-01-01

    This brief proposes a continuously-valued Markov random field (MRF) model with separable filter bank, denoted as MRFSepa, which significantly reduces the computational complexity in the MRF modeling. In this framework, we design a novel gradient-based discriminative learning method to learn the potential functions and separable filter banks. We learn MRFSepa models with 2-D and 3-D separable filter banks for the applications of gray-scale/color image denoising and color image demosaicing. By implementing MRFSepa model on graphics processing unit, we achieve real-time image denoising and fast image demosaicing with high-quality results.

  4. Theory of Distribution Estimation of Hyperparameters in Markov Random Field Models

    NASA Astrophysics Data System (ADS)

    Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato

    2016-06-01

    We investigated the performance of distribution estimation of hyperparameters in Markov random field models proposed by Nakanishi-Ohno et al., http://doi.org/10.1088/1751-8113/47/4/045001, J. Phys. A 47, 045001 (2014) when used to evaluate the confidence of data. We analytically calculated the configurational average, with respect to data, of the negative logarithm of the posterior distribution, which is called free energy based on an analogy with statistical mechanics. This configurational average of free energy shrinks as the amount of data increases. Our results theoretically confirm the numerical results from that previous study.

  5. Pixel partition method using Markov random field for measurements of closely spaced objects by optical sensors

    NASA Astrophysics Data System (ADS)

    Wang, Xueying; Li, Jun; Sheng, Weidong; An, Wei; Du, Qinfeng

    2015-10-01

    ABSTRACT In Space-based optical system, during the tracking for closely spaced objects (CSOs), the traditional method with a constant false alarm rate(CFAR) detecting brings either more clutter measurements or the loss of target information. CSOs can be tracked as Extended targets because their features on optical sensor's pixel-plane. A pixel partition method under the framework of Markov random field(MRF) is proposed, simulation results indicate: the method proposed provides higher pixel partition performance than traditional method, especially when the signal-noise-rate is poor.

  6. Conditional Random Field-Based Offline Map Matching for Indoor Environments.

    PubMed

    Bataineh, Safaa; Bahillo, Alfonso; Díez, Luis Enrique; Onieva, Enrique; Bataineh, Ikram

    2016-01-01

    In this paper, we present an offline map matching technique designed for indoor localization systems based on conditional random fields (CRF). The proposed algorithm can refine the results of existing indoor localization systems and match them with the map, using loose coupling between the existing localization system and the proposed map matching technique. The purpose of this research is to investigate the efficiency of using the CRF technique in offline map matching problems for different scenarios and parameters. The algorithm was applied to several real and simulated trajectories of different lengths. The results were then refined and matched with the map using the CRF algorithm. PMID:27537892

  7. Conditional Random Field-Based Offline Map Matching for Indoor Environments

    PubMed Central

    Bataineh, Safaa; Bahillo, Alfonso; Díez, Luis Enrique; Onieva, Enrique; Bataineh, Ikram

    2016-01-01

    In this paper, we present an offline map matching technique designed for indoor localization systems based on conditional random fields (CRF). The proposed algorithm can refine the results of existing indoor localization systems and match them with the map, using loose coupling between the existing localization system and the proposed map matching technique. The purpose of this research is to investigate the efficiency of using the CRF technique in offline map matching problems for different scenarios and parameters. The algorithm was applied to several real and simulated trajectories of different lengths. The results were then refined and matched with the map using the CRF algorithm. PMID:27537892

  8. High-Frequency Waves in a Random Distribution of Metallic Nanoparticles in an External Magnetic Field

    NASA Astrophysics Data System (ADS)

    Moradi, Afshin

    2016-09-01

    Propagation of magnetoplasma waves at an angle to a static magnetic field is studied for a random distribution of spherical metallic nanoparticles. A general analytical expression for dispersion relation of the system is derived and useful expressions are obtained in the limiting cases. It is found that the interaction between longitudinal and transverse modes leads to coupled modes in the vicinity of the frequency √ {f + ξ } {ω _p}, where ξ is the ratio of the volume occupied by all the nanoparticles to the entire volume, ωp the plasma frequency of electrons inside a nanoparticle, and f a geometrical factor of order unity (1/3 for spherical nanoparticles).

  9. The phase diagrams of a ferromagnetic thin film in a random magnetic field

    NASA Astrophysics Data System (ADS)

    Zaim, N.; Zaim, A.; Kerouad, M.

    2016-10-01

    In this paper, the magnetic properties and the phase diagrams of a ferromagnetic thin film with a thickness N in a random magnetic field (RMF) are investigated by using the Monte Carlo simulation technique based on the Metropolis algorithm. The effects of the RMF and the surface exchange interaction on the critical behavior are studied. A variety of multicritical points such as tricritical points, isolated critical points, and triple points are obtained. It is also found that the double reentrant phenomenon can appear for appropriate values of the system parameters.

  10. Robust phase sensitive inversion recovery imaging using a Markov random field model.

    PubMed

    Garach, Ravindra M; Ji, Jim X; Ying, Lei; Ma, Jingfei

    2004-01-01

    This paper presents a novel method for phase sensitive inversion recovery (PSIR) imaging for improved T/sub 1/ contrast. This method models the phase of the complex magnetic resonance image using a statistical model based on Markov random fields. A computationally efficient optimization method is developed. Computer simulations and in-vivo brain imaging experiments show that the proposed method can produce PSIR images with enhanced T/sub 1/ contrast and it is robust against high levels of data noise even when rapid phase variations are presented.

  11. Markov random field and Gaussian mixture for segmented MRI-based partial volume correction in PET.

    PubMed

    Bousse, Alexandre; Pedemonte, Stefano; Thomas, Benjamin A; Erlandsson, Kjell; Ourselin, Sébastien; Arridge, Simon; Hutton, Brian F

    2012-10-21

    In this paper we propose a segmented magnetic resonance imaging (MRI) prior-based maximum penalized likelihood deconvolution technique for positron emission tomography (PET) images. The model assumes the existence of activity classes that behave like a hidden Markov random field (MRF) driven by the segmented MRI. We utilize a mean field approximation to compute the likelihood of the MRF. We tested our method on both simulated and clinical data (brain PET) and compared our results with PET images corrected with the re-blurred Van Cittert (VC) algorithm, the simplified Guven (SG) algorithm and the region-based voxel-wise (RBV) technique. We demonstrated our algorithm outperforms the VC algorithm and outperforms SG and RBV corrections when the segmented MRI is inconsistent (e.g. mis-segmentation, lesions, etc) with the PET image.

  12. Glassy phases and driven response of the phase-field-crystal model with random pinning.

    PubMed

    Granato, E; Ramos, J A P; Achim, C V; Lehikoinen, J; Ying, S C; Ala-Nissila, T; Elder, K R

    2011-09-01

    We study the structural correlations and the nonlinear response to a driving force of a two-dimensional phase-field-crystal model with random pinning. The model provides an effective continuous description of lattice systems in the presence of disordered external pinning centers, allowing for both elastic and plastic deformations. We find that the phase-field crystal with disorder assumes an amorphous glassy ground state, with only short-ranged positional and orientational correlations, even in the limit of weak disorder. Under increasing driving force, the pinned amorphous-glass phase evolves into a moving plastic-flow phase and then, finally, a moving smectic phase. The transverse response of the moving smectic phase shows a vanishing transverse critical force for increasing system sizes. PMID:22060323

  13. An exact solution of solute transport by one-dimensional random velocity fields

    USGS Publications Warehouse

    Cvetkovic, V.D.; Dagan, G.; Shapiro, A.M.

    1991-01-01

    The problem of one-dimensional transport of passive solute by a random steady velocity field is investigated. This problem is representative of solute movement in porous media, for example, in vertical flow through a horizontally stratified formation of variable porosity with a constant flux at the soil surface. Relating moments of particle travel time and displacement, exact expressions for the advection and dispersion coefficients in the Focker-Planck equation are compared with the perturbation results for large distances. The first- and second-order approximations for the dispersion coefficient are robust for a lognormal velocity field. The mean Lagrangian velocity is the harmonic mean of the Eulerian velocity for large distances. This is an artifact of one-dimensional flow where the continuity equation provides for a divergence free fluid flux, rather than a divergence free fluid velocity. ?? 1991 Springer-Verlag.

  14. Deviations from the mean-field predictions for the phase behaviour of random copolymers melts

    NASA Astrophysics Data System (ADS)

    Houdayer, J.; Müller, M.

    2002-06-01

    We investigate the phase behaviour of random copolymers melts via large-scale Monte Carlo simulations. We observe macrophase separation into A- and B-rich phases as predicted by the mean-field theory only for systems with a very large correlation λ of blocks along the polymer chains, far away from the Lifshitz point. For smaller values of λ, we find that a locally segregated, disordered microemulsion-like structure gradually forms as the temperature decreases. As we increase the number of blocks in the polymers, the region of macrophase separation further shrinks. The results of our Monte Carlo simulation are in agreement with a Ginzburg criterium, which suggests that the mean-field theory becomes worse as the number of blocks in polymers increases.

  15. Efficient Semantic Segmentation of Man-Made Scenes Using Fully-Connected Conditional Random Field

    NASA Astrophysics Data System (ADS)

    Li, Weihao; Yang, Michael Ying

    2016-06-01

    In this paper we explore semantic segmentation of man-made scenes using fully connected conditional random field (CRF). Images of man-made scenes display strong contextual dependencies in the spatial structures. Fully connected CRFs can model long-range connections within the image of man-made scenes and make use of contextual information of scene structures. The pairwise edge potentials of fully connected CRF models are defined by a linear combination of Gaussian kernels. Using filter-based mean field algorithm, the inference is very efficient. Our experimental results demonstrate that fully connected CRF performs better than previous state-of-the-art approaches on both eTRIMS dataset and LabelMeFacade dataset.

  16. Glassy phases and driven response of the phase-field-crystal model with random pinning.

    PubMed

    Granato, E; Ramos, J A P; Achim, C V; Lehikoinen, J; Ying, S C; Ala-Nissila, T; Elder, K R

    2011-09-01

    We study the structural correlations and the nonlinear response to a driving force of a two-dimensional phase-field-crystal model with random pinning. The model provides an effective continuous description of lattice systems in the presence of disordered external pinning centers, allowing for both elastic and plastic deformations. We find that the phase-field crystal with disorder assumes an amorphous glassy ground state, with only short-ranged positional and orientational correlations, even in the limit of weak disorder. Under increasing driving force, the pinned amorphous-glass phase evolves into a moving plastic-flow phase and then, finally, a moving smectic phase. The transverse response of the moving smectic phase shows a vanishing transverse critical force for increasing system sizes.

  17. The diffusive idealization of charged particle transport in random magnetic fields

    NASA Technical Reports Server (NTRS)

    Earl, J. A.

    1974-01-01

    The transport of charged particles diffusing in a random magnetic field parallel to a relatively large guiding field is presented. The same coefficient of diffusion is obtained by three methods. Two corrections must be added to the expression in which the diffusive flux is proportional to the gradient of the density. Explicit expressions are given for a characteristic time and a characteristic length which describe the corrections. The well known divergence of the coefficient of diffusion, which is implied by the quasilinear analysis of pitch angle scattering, does not occur if the scattering rate is finite at 90 deg pitch angle. This effect is illustrated by formulas which give the coefficient of diffusion when the quasilinear expression is perturbed by a variable amount of isotropic scattering.

  18. Disorder-induced enhancement and critical scaling of spontaneous magnetization in random-field quantum spin systems

    NASA Astrophysics Data System (ADS)

    Bera, Anindita; Rakshit, Debraj; Lewenstein, Maciej; SenDe, Aditi; Sen, Ujjwal; Wehr, Jan

    2016-07-01

    We investigate the effect of a unidirectional quenched random field on the anisotropic quantum spin-1/2 X Y model, which magnetizes spontaneously in the absence of the random field. We adopt a mean-field approach for this analysis. In general, the models considered have Ising symmetry, and as such they exhibit ferromagnetic order in two and three dimensions in the presence of not too large disorder. Even in the special case when the model without disorder has U(1 ) symmetry, a small U(1 ) -symmetry-breaking random field induces ferromagnetic long-range order in two dimensions. The mean-field approach, consequently, provides a rather good qualitative and even quantitative description when applied not too close to the criticality. We show that spontaneous magnetization persists even in the presence of the random field, but the magnitude of magnetization gets suppressed due to disorder, and the system magnetizes in the directions parallel and transverse to the random field. Our results are obtained via analytical calculations within a perturbative framework and by numerical simulations. Interestingly, we show that it is possible to enhance a component of magnetization in the presence of the disorder field provided that we apply an additional constant field in the X Y plane. Moreover, we derive generalized expressions for the critical temperature and the scalings of the magnetization near the critical point for the X Y spin system with arbitrary fixed quantum spin angular momentum.

  19. Document ink bleed-through removal with two hidden Markov random fields and a single observation field.

    PubMed

    Wolf, Christian

    2010-03-01

    We present a new method for blind document bleed-through removal based on separate Markov Random Field (MRF) regularization for the recto and for the verso side, where separate priors are derived from the full graph. The segmentation algorithm is based on Bayesian Maximum a Posteriori (MAP) estimation. The advantages of this separate approach are the adaptation of the prior to the contents creation process (e.g., superimposing two handwritten pages), and the improvement of the estimation of the recto pixels through an estimation of the verso pixels covered by recto pixels; moreover, the formulation as a binary labeling problem with two hidden labels per pixels naturally leads to an efficient optimization method based on the minimum cut/maximum flow in a graph. The proposed method is evaluated on scanned document images from the 18th century, showing an improvement of character recognition results compared to other restoration methods.

  20. Classification method for disease risk mapping based on discrete hidden Markov random fields.

    PubMed

    Charras-Garrido, Myriam; Abrial, David; Goër, Jocelyn De; Dachian, Sergueï; Peyrard, Nathalie

    2012-04-01

    Risk mapping in epidemiology enables areas with a low or high risk of disease contamination to be localized and provides a measure of risk differences between these regions. Risk mapping models for pooled data currently used by epidemiologists focus on the estimated risk for each geographical unit. They are based on a Poisson log-linear mixed model with a latent intrinsic continuous hidden Markov random field (HMRF) generally corresponding to a Gaussian autoregressive spatial smoothing. Risk classification, which is necessary to draw clearly delimited risk zones (in which protection measures may be applied), generally must be performed separately. We propose a method for direct classified risk mapping based on a Poisson log-linear mixed model with a latent discrete HMRF. The discrete hidden field (HF) corresponds to the assignment of each spatial unit to a risk class. The risk values attached to the classes are parameters and are estimated. When mapping risk using HMRFs, the conditional distribution of the observed field is modeled with a Poisson rather than a Gaussian distribution as in image segmentation. Moreover, abrupt changes in risk levels are rare in disease maps. The spatial hidden model should favor smoothed out risks, but conventional discrete Markov random fields (e.g. the Potts model) do not impose this. We therefore propose new potential functions for the HF that take into account class ordering. We use a Monte Carlo version of the expectation-maximization algorithm to estimate parameters and determine risk classes. We illustrate the method's behavior on simulated and real data sets. Our method appears particularly well adapted to localize high-risk regions and estimate the corresponding risk levels.

  1. Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

    PubMed

    Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

    2009-09-01

    A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

  2. A New Markov Random Field Segmentation Method for Breast Lesion Segmentation in MR images.

    PubMed

    Azmi, Reza; Norozi, Narges

    2011-07-01

    Breast cancer is a major public health problem for women in the Iran and many other parts of the world. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a pivotal role in breast cancer care, including detection, diagnosis, and treatment monitoring. But segmentation of these images which is seriously affected by intensity inhomogeneities created by radio-frequency coils is a challenging task. Markov Random Field (MRF) is used widely in medical image segmentation especially in MR images. It is because this method can model intensity inhomogeneities occurring in these images. But this method has two critical weaknesses: Computational complexity and sensitivity of the results to the models parameters. To overcome these problems, in this paper, we present Improved-Markov Random Field (I-MRF) method for breast lesion segmentation in MR images. Unlike the conventional MRF, in the proposed approach, we don't use the Iterative Conditional Mode (ICM) method or Simulated Annealing (SA) for class membership estimation of each pixel (lesion and non-lesion). The prior distribution of the class membership is modeled as a ratio of two conditional probability distributions in a neighborhood which is defined for each pixel: probability distribution of similar pixels and non-similar ones. Since our proposed approach don't use an iterative method for maximizing the posterior probability, above mentioned problems are solved. Experimental results show that performance of segmentation in this approach is higher than conventional MRF in terms of accuracy, precision, and Computational complexity.

  3. A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping.

    PubMed

    Baptista, Helena; Mendes, Jorge M; MacNab, Ying C; Xavier, Miguel; Caldas-de-Almeida, José

    2016-08-01

    Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated determinant factors do not vary systematically in space, and the similarity is defined by "similarity" with respect to the associated disease determinant factors. The neighbourhood-based GMRF and the similarity-based GRF are compared and accessed via a simulation study and by two case studies, using new data on alcohol abuse in Portugal collected by the World Mental Health Survey Initiative and the well-known lip cancer data in Scotland. In the presence of disease data with no evidence of positive spatial correlation, the simulation study showed a consistent gain in efficiency from the similarity-based GRF, compared with the adjacency-based GMRF with the determinant risk factors as covariate. This new approach broadens the scope of the existing conditional autocorrelation models.

  4. Markov random field model-based edge-directed image interpolation.

    PubMed

    Li, Min; Nguyen, Truong Q

    2008-07-01

    This paper presents an edge-directed image interpolation algorithm. In the proposed algorithm, the edge directions are implicitly estimated with a statistical-based approach. In opposite to explicit edge directions, the local edge directions are indicated by length-16 weighting vectors. Implicitly, the weighting vectors are used to formulate geometric regularity (GR) constraint (smoothness along edges and sharpness across edges) and the GR constraint is imposed on the interpolated image through the Markov random field (MRF) model. Furthermore, under the maximum a posteriori-MRF framework, the desired interpolated image corresponds to the minimal energy state of a 2-D random field given the low-resolution image. Simulated annealing methods are used to search for the minimal energy state from the state space. To lower the computational complexity of MRF, a single-pass implementation is designed, which performs nearly as well as the iterative optimization. Simulation results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity. Compared to traditional methods and other edge-directed interpolation methods, the proposed method improves the subjective quality of the interpolated edges while maintaining a high PSNR level.

  5. Automatic segmentation of breast MR images through a Markov random field statistical model.

    PubMed

    Ribes, S; Didierlaurent, D; Decoster, N; Gonneau, E; Risser, L; Feillel, V; Caselles, O

    2014-10-01

    An algorithm dedicated to automatic segmentation of breast magnetic resonance images is presented in this paper. Our approach is based on a pipeline that includes a denoising step and statistical segmentation. The noise removal preprocessing relies on an anisotropic diffusion scheme, whereas the statistical segmentation is conducted through a Markov random field model. The continuous updating of all parameters governing the diffusion process enables automatic denoising, and the partial volume effect is also addressed during the labeling step. To assess the relevance, the Jaccard similarity coefficient was computed. Experiments were conducted on synthetic data and breast magnetic resonance images extracted from a high-risk population. The relevance of the approach for the dataset is highlighted, and we demonstrate accuracy superior to that of traditional clustering algorithms. The results emphasize the benefits of both denoising guided by input data and the inclusion of spatial dependency through a Markov random field. For example, the Jaccard coefficient for the clinical data was increased by 114%, 109%, and 140% with respect to a K-means algorithm and, respectively, for the adipose, glandular and muscle and skin components. Moreover, the agreement between the manual segmentations provided by an experienced radiologist and the automatic segmentations performed with this algorithm was good, with Jaccard coefficients equal to 0.769, 0.756, and 0.694 for the above-mentioned classes.

  6. Does Encouragement Matter in Improving Gender Imbalances in Technical Fields? Evidence from a Randomized Controlled Trial.

    PubMed

    Unkovic, Cait; Sen, Maya; Quinn, Kevin M

    2016-01-01

    Does encouragement help address gender imbalances in technical fields? We present the results of one of the first and largest randomized controlled trials on the topic. Using an applied statistics conference in the social sciences as our context, we randomly assigned half of a pool of 3,945 graduate students to receive two personalized emails encouraging them to apply (n = 1,976) and the other half to receive nothing (n = 1,969). We find a robust, positive effect associated with this simple intervention and suggestive evidence that women responded more strongly than men. However, we find that women's conference acceptance rates are higher within the control group than in the treated group. This is not the case for men. The reason appears to be that female applicants in the treated group solicited supporting letters at lower rates. Our findings therefore suggest that "low dose" interventions may promote diversity in STEM fields but may also have the potential to expose underlying disparities when used alone or in a non-targeted way.

  7. Seeking mathematics success for college students: a randomized field trial of an adapted approach

    NASA Astrophysics Data System (ADS)

    Gula, Taras; Hoessler, Carolyn; Maciejewski, Wes

    2015-11-01

    Many students enter the Canadian college system with insufficient mathematical ability and leave the system with little improvement. Those students who enter with poor mathematics ability typically take a developmental mathematics course as their first and possibly only mathematics course. The educational experiences that comprise a developmental mathematics course vary widely and are, too often, ineffective at improving students' ability. This trend is concerning, since low mathematics ability is known to be related to lower rates of success in subsequent courses. To date, little attention has been paid to the selection of an instructional approach to consistently apply across developmental mathematics courses. Prior research suggests that an appropriate instructional method would involve explicit instruction and practising mathematical procedures linked to a mathematical concept. This study reports on a randomized field trial of a developmental mathematics approach at a college in Ontario, Canada. The new approach is an adaptation of the JUMP Math program, an explicit instruction method designed for primary and secondary school curriculae, to the college learning environment. In this study, a subset of courses was assigned to JUMP Math and the remainder was taught in the same style as in the previous years. We found consistent, modest improvement in the JUMP Math sections compared to the non-JUMP sections, after accounting for potential covariates. The findings from this randomized field trial, along with prior research on effective education for developmental mathematics students, suggest that JUMP Math is a promising way to improve college student outcomes.

  8. Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

    PubMed

    Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

    2009-09-01

    A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms. PMID:19446435

  9. Single-image super-resolution based on Markov random field and contourlet transform

    NASA Astrophysics Data System (ADS)

    Wu, Wei; Liu, Zheng; Gueaieb, Wail; He, Xiaohai

    2011-04-01

    Learning-based methods are well adopted in image super-resolution. In this paper, we propose a new learning-based approach using contourlet transform and Markov random field. The proposed algorithm employs contourlet transform rather than the conventional wavelet to represent image features and takes into account the correlation between adjacent pixels or image patches through the Markov random field (MRF) model. The input low-resolution (LR) image is decomposed with the contourlet transform and fed to the MRF model together with the contourlet transform coefficients from the low- and high-resolution image pairs in the training set. The unknown high-frequency components/coefficients for the input low-resolution image are inferred by a belief propagation algorithm. Finally, the inverse contourlet transform converts the LR input and the inferred high-frequency coefficients into the super-resolved image. The effectiveness of the proposed method is demonstrated with the experiments on facial, vehicle plate, and real scene images. A better visual quality is achieved in terms of peak signal to noise ratio and the image structural similarity measurement.

  10. Does Encouragement Matter in Improving Gender Imbalances in Technical Fields? Evidence from a Randomized Controlled Trial

    PubMed Central

    Unkovic, Cait; Sen, Maya; Quinn, Kevin M.

    2016-01-01

    Does encouragement help address gender imbalances in technical fields? We present the results of one of the first and largest randomized controlled trials on the topic. Using an applied statistics conference in the social sciences as our context, we randomly assigned half of a pool of 3,945 graduate students to receive two personalized emails encouraging them to apply (n = 1,976) and the other half to receive nothing (n = 1,969). We find a robust, positive effect associated with this simple intervention and suggestive evidence that women responded more strongly than men. However, we find that women’s conference acceptance rates are higher within the control group than in the treated group. This is not the case for men. The reason appears to be that female applicants in the treated group solicited supporting letters at lower rates. Our findings therefore suggest that “low dose” interventions may promote diversity in STEM fields but may also have the potential to expose underlying disparities when used alone or in a non-targeted way. PMID:27097315

  11. Does Encouragement Matter in Improving Gender Imbalances in Technical Fields? Evidence from a Randomized Controlled Trial.

    PubMed

    Unkovic, Cait; Sen, Maya; Quinn, Kevin M

    2016-01-01

    Does encouragement help address gender imbalances in technical fields? We present the results of one of the first and largest randomized controlled trials on the topic. Using an applied statistics conference in the social sciences as our context, we randomly assigned half of a pool of 3,945 graduate students to receive two personalized emails encouraging them to apply (n = 1,976) and the other half to receive nothing (n = 1,969). We find a robust, positive effect associated with this simple intervention and suggestive evidence that women responded more strongly than men. However, we find that women's conference acceptance rates are higher within the control group than in the treated group. This is not the case for men. The reason appears to be that female applicants in the treated group solicited supporting letters at lower rates. Our findings therefore suggest that "low dose" interventions may promote diversity in STEM fields but may also have the potential to expose underlying disparities when used alone or in a non-targeted way. PMID:27097315

  12. Genetic relationship of 32 cell lines of Euplotes octocarinatus species complex revealed by random amplified polymorphic DNA (RAPD) fingerprinting.

    PubMed

    Möllenbeck, M

    1999-12-01

    Random amplified polymorphic DNA (RAPD) fingerprinting was used in this study to determine the genetic relationship of different cell lines of the hypotrichous ciliate Euplotes octocarinatus. Stocks isolated from different habitats in the USA, and from a group of genetically recombined laboratory strains, were characterized. Band-sharing indices (D) for all possible pairwise comparisons revealed a remarkable genetic diversity between the different cell lines. Investigation of the genetic structure in natural populations found diversity--although to a different extent--in all populations investigated. No clonal structure could be observed, as proposed for several protozoa and recently shown for E. daidaleos. These findings suggest frequent conjugation in the population of E. octocarinatus. No correlation between the genetic relationship of cell lines from different habitats and the distance between the corresponding sampling locations was found. Once separated geographically, the exchange of genetic material between populations appears to be nearly impossible. Therefore, these groups tend to separate into sibling species. The data generally support the occurrence of different syngens in the E. octocarinatus species complex. This finding is in accordance with our observation that the morphological 'species' of E. octocarinatus consists of several syngens or sibling species, similar to findings for the Paramecium aurelia-, Tetrahymena pyriformis- and E. vannus- species complexes. PMID:10722304

  13. Quantile estimation to derive optimized test thresholds for random field statistics.

    PubMed

    Hinrichs, H; Scholz, M; Noesselt, T; Heinze, H J

    2005-08-01

    We present a numerical method to estimate the true threshold values in random fields needed to determine the significance of apparent signals observed in noisy images. To accomplish this, a quantile estimation algorithm is applied to derive the threshold with a predefined confidence interval from a large number of simulated random fields. Also, a computationally efficient method for generating a random field simulation is presented using resampling techniques. Applying these techniques, thresholds have been determined for a large variety of parameter settings (smoothness, voxel size, brain shape, type of statistics). By means of interpolation techniques, thresholds for additional arbitrary settings can be quickly derived without the need to run individual simulations. Compared to the parametric approach of Worsley et al. (1996) (Worsley, K.J., Marrett, S., Neelin P., Vandal, A.C., Friston, K.J., Evans, A.C., 1996. A unified statistical approach for determining significant signals in images of cerebral activation. Hum. Brain Mapp. 4, 58-73) and Friston et al. (1991) (Friston, K.J., Frith, C.D., Liddle, P.F., Frackowiak, R.S. 1991. Comparing functional (PET) images: the assessment of significant change. J. Cereb. Blood Flow Metab. 11(4), 690-699), and to the Bonferroni approach, these optimized thresholds lead to higher levels of significance (i.e., lower p values) with a specific amount of activation especially with fields of moderate smoothness (i.e., with a relative full width half maximum between 2 and 6). Alternatively, the threshold for a specified level of significance can be lowered. This improved statistical sensitivity is illustrated by the analysis of an actual event related functional magnetic resonance data set, and its limitations are tested by determining the false positive rate with experimental MR noise data. The grid of estimated threshold values as well as the interpolation algorithm to derive thresholds for arbitrary parameter settings are made

  14. Local Autoencoding for Parameter Estimation in a Hidden Potts-Markov Random Field.

    PubMed

    Song, Sanming; Si, Bailu; Herrmann, J Michael; Feng, Xisheng

    2016-05-01

    A local-autoencoding (LAE) method is proposed for the parameter estimation in a Hidden Potts-Markov random field model. Due to sampling cost, Markov chain Monte Carlo methods are rarely used in real-time applications. Like other heuristic methods, LAE is based on a conditional independence assumption. It adapts, however, the parameters in a block-by-block style with a simple Hebbian learning rule. Experiments with given label fields show that the LAE is able to converge in far less time than required for a scan. It is also possible to derive an estimate for LAE based on a Cramer–Rao bound that is similar to the classical maximum pseudolikelihood method. As a general algorithm, LAE can be used to estimate the parameters in anisotropic label fields. Furthermore, LAE is not limited to the classical Potts model and can be applied to other types of Potts models by simple label field transformations and straightforward learning rule extensions. Experimental results on image segmentations demonstrate the efficiency and generality of the LAE algorithm.

  15. Local Autoencoding for Parameter Estimation in a Hidden Potts-Markov Random Field.

    PubMed

    Song, Sanming; Si, Bailu; Herrmann, J Michael; Feng, Xisheng

    2016-05-01

    A local-autoencoding (LAE) method is proposed for the parameter estimation in a Hidden Potts-Markov random field model. Due to sampling cost, Markov chain Monte Carlo methods are rarely used in real-time applications. Like other heuristic methods, LAE is based on a conditional independence assumption. It adapts, however, the parameters in a block-by-block style with a simple Hebbian learning rule. Experiments with given label fields show that the LAE is able to converge in far less time than required for a scan. It is also possible to derive an estimate for LAE based on a Cramer–Rao bound that is similar to the classical maximum pseudolikelihood method. As a general algorithm, LAE can be used to estimate the parameters in anisotropic label fields. Furthermore, LAE is not limited to the classical Potts model and can be applied to other types of Potts models by simple label field transformations and straightforward learning rule extensions. Experimental results on image segmentations demonstrate the efficiency and generality of the LAE algorithm. PMID:27019491

  16. Spin dynamics of polarons and polaron pairs in a random hyperfine field

    NASA Astrophysics Data System (ADS)

    Roundy, Robert C.

    Spin-dependent recombination of polaron pairs and spin relaxation of a single polaron are the most fundamental processes are responsible for the performance of organic spintronics-based devices such as light-emitting diodes and organic spin valves. In organic materials, with no spin-orbit coupling, both processes are due to random hyperfine fields created by protons neighboring the polaron sites. The essence of spin-dependent recombination is that in order to recombine the pair must be in the singlet state. Hyperfine fields acting on the electron and hole govern the spin-dynamics of localized pairs during the waiting time for recombination. We demonstrate that for certain domain of trapping configurations of hyperfine fields, crossover to the singlet state is quenched. This leads to the blocking of current. The phenomenon of organic magnetoresistance (OMAR) is described by counting the weights of trapping configurations as a function of magnetic field. This explains the universality of the lineshapes of the OMAR curves. In finite samples incomplete averaging over the hyperfine fields gives rise to mesoscopic fluctuations of the current response. We also demonstrate that under the condition of magnetic resonance, new trapping configurations emerge. This leads to nontrivial evolution of current through the sample with microwave power. When discussing spin-relaxation two questions can be asked: (a) How does the local spin polarization decay as a function of distance from the spin-polarized injector? (b) How does the injected spin decay as a function of time after spatial averaging? With regard to (a), we demonstrate that, while decaying exponentially on average, local spin-polarization exhibits giant fluctuations from point to point. Concerning (b), we find that for a spin-carrier which moves diffusively in low dimensions the decay is faster than a simple exponent. The underlying physics for both findings is that in describing spin evolution it is necessary to add up

  17. A Markov random field-based approach for joint estimation of differentially expressed genes in mouse transcriptome data.

    PubMed

    Lin, Zhixiang; Li, Mingfeng; Sestan, Nenad; Zhao, Hongyu

    2016-04-01

    The statistical methodology developed in this study was motivated by our interest in studying neurodevelopment using the mouse brain RNA-Seq data set, where gene expression levels were measured in multiple layers in the somatosensory cortex across time in both female and male samples. We aim to identify differentially expressed genes between adjacent time points, which may provide insights on the dynamics of brain development. Because of the extremely small sample size (one male and female at each time point), simple marginal analysis may be underpowered. We propose a Markov random field (MRF)-based approach to capitalizing on the between layers similarity, temporal dependency and the similarity between sex. The model parameters are estimated by an efficient EM algorithm with mean field-like approximation. Simulation results and real data analysis suggest that the proposed model improves the power to detect differentially expressed genes than simple marginal analysis. Our method also reveals biologically interesting results in the mouse brain RNA-Seq data set.

  18. A Poisson Random Field Framework Bridges Micro- To Macroscopic Scales In Microbial Transport

    NASA Astrophysics Data System (ADS)

    Yeghiazarian, L.; Safwat, A.; Shuster, W.; Samorodnitsky, G.; Whiteaker, T. L.; Maidment, D. R.

    2014-12-01

    Understanding microbial fate and transport in surface water and making accurate predictions is a formidable task. Evidence from experimental and observational studies unequivocally points to temporal and spatial variability in microbial distributions with significant correlation structure; and to the critical role of processes at the microscopic level. The temporal and spatial variability in microbial distributions arises from inherently random environmental factors and processes. Many cannot be described accurately using deterministic methods, necessitating a stochastic approach to microbial modeling. At the same time, microbial tracking studies identified significant spatial and temporal correlations in microbial distributions in streams, and highlighted the necessity of including microbial interactions with sediments, settling and re-suspension in models of microbial transport. Such understanding must be gained from microscopic, particle-scale research, because microdynamic interactions ultimately give rise to phenomena on higher scales. The challenge then is to be able to describe microbial behavior in probabilistic terms to take care of random drivers, while incorporating processes on microscopic scale and bridging the gap to macroscopic entities like concentrations that are used in watershed management. We have derived a stochastic modeling paradigm that bridges microscopic processes to macroscopic manifestation of microbial behavior in time and space, where the Markov behavior of individual microbes collectively translates into a non-homogeneous Poisson random field that describes microbial population dynamics. The Poisson framework is applied to a mixed-use watershed and implemented within ArcGIS, which makes a wealth of geographic, topologic, soil and other information, as well as data from national and regional datasets, instantly available. Probabilities of exceeding microbial safety thresholds are then obtained at any point in time and space in the

  19. Stochastic generation of explicit pore structures by thresholding Gaussian random fields

    NASA Astrophysics Data System (ADS)

    Hyman, Jeffrey D.; Winter, C. Larrabee

    2014-11-01

    We provide a description and computational investigation of an efficient method to stochastically generate realistic pore structures. Smolarkiewicz and Winter introduced this specific method in pores resolving simulation of Darcy flows (Smolarkiewicz and Winter, 2010 [1]) without giving a complete formal description or analysis of the method, or indicating how to control the parameterization of the ensemble. We address both issues in this paper. The method consists of two steps. First, a realization of a correlated Gaussian field, or topography, is produced by convolving a prescribed kernel with an initial field of independent, identically distributed random variables. The intrinsic length scales of the kernel determine the correlation structure of the topography. Next, a sample pore space is generated by applying a level threshold to the Gaussian field realization: points are assigned to the void phase or the solid phase depending on whether the topography over them is above or below the threshold. Hence, the topology and geometry of the pore space depend on the form of the kernel and the level threshold. Manipulating these two user prescribed quantities allows good control of pore space observables, in particular the Minkowski functionals. Extensions of the method to generate media with multiple pore structures and preferential flow directions are also discussed. To demonstrate its usefulness, the method is used to generate a pore space with physical and hydrological properties similar to a sample of Berea sandstone.

  20. Turbulence generation by a shock wave interacting with a random density inhomogeneity field

    NASA Astrophysics Data System (ADS)

    Huete Ruiz de Lira, C.

    2010-12-01

    When a planar shock wave interacts with a random pattern of pre-shock density non-uniformities, it generates an anisotropic turbulent velocity/vorticity field. This turbulence plays an important role in the early stages of the mixing process in a compressed fluid. This situation emerges naturally in a shock interaction with weakly inhomogeneous deuterium-wicked foam targets in inertial confinement fusion and with density clumps/clouds in astrophysics. We present an exact small-amplitude linear theory describing such an interaction. It is based on the exact theory of time and space evolution of the perturbed quantities behind a corrugated shock front for a single-mode pre-shock non-uniformity. Appropriate mode averaging in two dimensions results in closed analytical expressions for the turbulent kinetic energy, degree of anisotropy of velocity and vorticity fields in the shocked fluid, shock amplification of the density non-uniformity and sonic energy flux radiated downstream. These explicit formulae are further simplified in the important asymptotic limits of weak/strong shocks and highly compressible fluids. A comparison with the related problem of a shock interacting with a pre-shock isotropic vorticity field is also presented.

  1. A NOVEL EMISSION SPECTRUM FROM A RELATIVISTIC ELECTRON MOVING IN A RANDOM MAGNETIC FIELD

    SciTech Connect

    Teraki, Yuto; Takahara, Fumio

    2011-07-10

    We numerically calculate the radiation spectrum from relativistic electrons moving in small-scale turbulent magnetic fields expected in high-energy astrophysical sources. Such a radiation spectrum is characterized by the strength parameter a = {lambda}{sub B} e|B|/mc {sup 2}, where {lambda}{sub B} is the length scale of the turbulent field. When a is much larger than the Lorentz factor of a radiating electron {gamma}, synchrotron radiation is realized, while a << 1 corresponds to the so-called jitter radiation regime. Because for 1 < a < {gamma} we cannot use either approximations, we should have recourse to the Lienard-Wiechert potential to evaluate the radiation spectrum, which is performed in this Letter. We generate random magnetic fields assuming Kolmogorov turbulence, inject monoenergetic electrons, solve the equation of motion, and calculate the radiation spectrum. We perform numerical calculations for several values of a with {gamma} = 10. We obtain various types of spectra ranging between jitter radiation and synchrotron radiation. For a {approx} 7, the spectrum takes a novel shape which had not been noticed up to now. It is like a synchrotron spectrum in the middle energy region, but in the low frequency region it is a broken power law and in the high frequency region an extra power-law component appears beyond the synchrotron cutoff. We give a physical explanation of these features.

  2. Automatic white matter lesion segmentation using contrast enhanced FLAIR intensity and Markov Random Field.

    PubMed

    Roy, Pallab Kanti; Bhuiyan, Alauddin; Janke, Andrew; Desmond, Patricia M; Wong, Tien Yin; Abhayaratna, Walter P; Storey, Elsdon; Ramamohanarao, Kotagiri

    2015-10-01

    White matter lesions (WMLs) are small groups of dead cells that clump together in the white matter of brain. In this paper, we propose a reliable method to automatically segment WMLs. Our method uses a novel filter to enhance the intensity of WMLs. Then a feature set containing enhanced intensity, anatomical and spatial information is used to train a random forest classifier for the initial segmentation of WMLs. Following that a reliable and robust edge potential function based Markov Random Field (MRF) is proposed to obtain the final segmentation by removing false positive WMLs. Quantitative evaluation of the proposed method is performed on 24 subjects of ENVISion study. The segmentation results are validated against the manual segmentation, performed under the supervision of an expert neuroradiologist. The results show a dice similarity index of 0.76 for severe lesion load, 0.73 for moderate lesion load and 0.61 for mild lesion load. In addition to that we have compared our method with three state of the art methods on 20 subjects of Medical Image Computing and Computer Aided Intervention Society's (MICCAI's) MS lesion challenge dataset, where our method shows better segmentation accuracy compare to the state of the art methods. These results indicate that the proposed method can assist the neuroradiologists in assessing the WMLs in clinical practice.

  3. Hyperspectral image clustering method based on artificial bee colony algorithm and Markov random fields

    NASA Astrophysics Data System (ADS)

    Sun, Xu; Yang, Lina; Gao, Lianru; Zhang, Bing; Li, Shanshan; Li, Jun

    2015-01-01

    Center-oriented hyperspectral image clustering methods have been widely applied to hyperspectral remote sensing image processing; however, the drawbacks are obvious, including the over-simplicity of computing models and underutilized spatial information. In recent years, some studies have been conducted trying to improve this situation. We introduce the artificial bee colony (ABC) and Markov random field (MRF) algorithms to propose an ABC-MRF-cluster model to solve the problems mentioned above. In this model, a typical ABC algorithm framework is adopted in which cluster centers and iteration conditional model algorithm's results are considered as feasible solutions and objective functions separately, and MRF is modified to be capable of dealing with the clustering problem. Finally, four datasets and two indices are used to show that the application of ABC-cluster and ABC-MRF-cluster methods could help to obtain better image accuracy than conventional methods. Specifically, the ABC-cluster method is superior when used for a higher power of spectral discrimination, whereas the ABC-MRF-cluster method can provide better results when used for an adjusted random index. In experiments on simulated images with different signal-to-noise ratios, ABC-cluster and ABC-MRF-cluster showed good stability.

  4. T-->0 mean-field population dynamics approach for the random 3-satisfiability problem.

    PubMed

    Zhou, Haijun

    2008-06-01

    During the past decade, phase-transition phenomena in the random 3-satisfiability ( 3 -SAT) problem has been intensively studied by statistical physics methods. In this work, we study the random 3 -SAT problem by the mean-field first-step replica-symmetry-broken cavity theory at the limit of temperature T-->0 . The reweighting parameter y of the cavity theory is allowed to approach infinity together with the inverse temperature beta with fixed ratio r=ybeta . Focusing on the system's space of satisfiable configurations, we carry out extensive population dynamics simulations using the technique of importance sampling, and we obtain the entropy density s(r) and complexity Sigma(r) of zero-energy clusters at different r values. We demonstrate that the population dynamics may reach different fixed points with different types of initial conditions. By knowing the trends of s(r) and Sigma(r) with r , we can judge whether a certain type of initial condition is appropriate at a given r value. This work complements and confirms the results of several other very recent theoretical studies. PMID:18643331

  5. Automatic white matter lesion segmentation using contrast enhanced FLAIR intensity and Markov Random Field.

    PubMed

    Roy, Pallab Kanti; Bhuiyan, Alauddin; Janke, Andrew; Desmond, Patricia M; Wong, Tien Yin; Abhayaratna, Walter P; Storey, Elsdon; Ramamohanarao, Kotagiri

    2015-10-01

    White matter lesions (WMLs) are small groups of dead cells that clump together in the white matter of brain. In this paper, we propose a reliable method to automatically segment WMLs. Our method uses a novel filter to enhance the intensity of WMLs. Then a feature set containing enhanced intensity, anatomical and spatial information is used to train a random forest classifier for the initial segmentation of WMLs. Following that a reliable and robust edge potential function based Markov Random Field (MRF) is proposed to obtain the final segmentation by removing false positive WMLs. Quantitative evaluation of the proposed method is performed on 24 subjects of ENVISion study. The segmentation results are validated against the manual segmentation, performed under the supervision of an expert neuroradiologist. The results show a dice similarity index of 0.76 for severe lesion load, 0.73 for moderate lesion load and 0.61 for mild lesion load. In addition to that we have compared our method with three state of the art methods on 20 subjects of Medical Image Computing and Computer Aided Intervention Society's (MICCAI's) MS lesion challenge dataset, where our method shows better segmentation accuracy compare to the state of the art methods. These results indicate that the proposed method can assist the neuroradiologists in assessing the WMLs in clinical practice. PMID:26398564

  6. Pulsed electromagnetic fields on postmenopausal osteoporosis in Southwest China: a randomized, active-controlled clinical trial.

    PubMed

    Liu, Hui-Fang; Yang, Lin; He, Hong-Chen; Zhou, Jun; Liu, Ying; Wang, Chun-Yan; Wu, Yuan-Chao; He, Cheng-Qi

    2013-05-01

    A randomized, active-controlled clinical trial was conducted to examine the effect of pulsed electromagnetic fields (PEMFs) on women with postmenopausal osteoporosis (PMO) in southwest China. Forty-four participants were randomly assigned to receive alendronate or one course of PEMFs treatment. The primary endpoint was the mean percentage change in bone mineral density of the lumbar spine (BMDL), and secondary endpoints were the mean percentage changes in left proximal femur bone mineral density (BMDF), serum 25OH vitamin D3 (25(OH)D) concentrations, total lower-extremity manual muscle test (LE MMT) score, and Berg Balance Scale (BBS) score. The BMDL, BMDF, total LE MMT score and BBS score were recorded at baseline, 5, 12, and 24 weeks. Serum concentrations of 25(OH)D were measured at baseline and 5 weeks. Using a mixed linear model, there was no significant treatment difference between the two groups in the BMDL, BMDF, total LE MMT score, and BBS score (P ≥ 0.05). For 25(OH)D concentrations, the effects were also comparable between the two groups (P ≥ 0.05) with the Mann-Whitney's U-test. These results suggested that a course of PEMFs treatment with specific parameters was as effective as alendronate in treating PMO within 24 weeks.

  7. A Markov random field approach for modeling spatio-temporal evolution of microstructures

    NASA Astrophysics Data System (ADS)

    Acar, Pinar; Sundararaghavan, Veera

    2016-10-01

    The following problem is addressed: ‘Can one synthesize microstructure evolution over a large area given experimental movies measured over smaller regions?’ Our input is a movie of microstructure evolution over a small sample window. A Markov random field (MRF) algorithm is developed that uses this data to estimate the evolution of microstructure over a larger region. Unlike the standard microstructure reconstruction problem based on stationary images, the present algorithm is also able to reconstruct time-evolving phenomena such as grain growth. Such an algorithm would decrease the cost of full-scale microstructure measurements by coupling mathematical estimation with targeted small-scale spatiotemporal measurements. The grain size, shape and orientation distribution statistics of synthesized polycrystalline microstructures at different times are compared with the original movie to verify the method.

  8. Markov random field model for segmenting large populations of lipid vesicles from micrographs.

    PubMed

    Zupanc, Jernej; Drobne, Damjana; Ster, Branko

    2011-12-01

    Giant unilamellar lipid vesicles, artificial replacements for cell membranes, are a promising tool for in vitro assessment of interactions between products of nanotechnologies and biological membranes. However, the effect of nanoparticles can not be derived from observations on a single specimen, vesicle populations should be observed instead. We propose an adaptation of the Markov random field image segmentation model which allows detection and segmentation of numerous vesicles in micrographs. The reliability of this model with different lighting, blur, and noise characteristics of micrographs is examined and discussed. Moreover, the automatic segmentation is tested on micrographs with thousands of vesicles and the result is compared to that of manual segmentation. The segmentation step presented is part of a methodology we are developing for bio-nano interaction assessment studies on lipid vesicles.

  9. Automatic prone to supine haustral fold matching in CT colonography using a Markov random field model.

    PubMed

    Hampshire, Thomas; Roth, Holger; Hu, Mingxing; Boone, Darren; Slabaugh, Greg; Punwani, Shonit; Halligan, Steve; Hawkes, David

    2011-01-01

    CT colonography is routinely performed with the patient prone and supine to differentiate fixed colonic pathology from mobile faecal residue. We propose a novel method to automatically establish correspondence. Haustral folds are detected using a graph cut method applied to a surface curvature-based metric, where image patches are generated using endoluminal CT colonography surface rendering. The intensity difference between image pairs, along with additional neighbourhood information to enforce geometric constraints, are used with a Markov Random Field (MRF) model to estimate the fold labelling assignment. The method achieved fold matching accuracy of 83.1% and 88.5% with and without local colonic collapse. Moreover, it improves an existing surface-based registration algorithm, decreasing mean registration error from 9.7mm to 7.7mm in cases exhibiting collapse.

  10. Segmentation of the right ventricle using diffusion maps and Markov random fields.

    PubMed

    Moolan-Feroze, Oliver; Mirmehdi, Majid; Hamilton, Mark; Bucciarelli-Ducci, Chiara

    2014-01-01

    Accurate automated segmentation of the right ventricle is difficult due in part to the large shape variation found between patients. We explore the ability of manifold learning based shape models to represent the complexity of shape variation found within an RV dataset as compared to a typical PCA based model. This is empirically evaluated with the manifold model displaying a greater ability to represent complex shapes. Furthermore, we present a combined manifold shape model and Markov Random Field Segmentation framework. The novelty of this method is the iterative generation of targeted shape priors from the manifold using image information and a current estimate of the segmentation; a process that can be seen as a traversal across the manifold. We apply our method to the independently evaluated MICCAI 2012 RV Segmentation Challenge data set. Our method performs similarly or better than the state-of-the-art methods.

  11. MRFy: Remote Homology Detection for Beta-Structural Proteins Using Markov Random Fields and Stochastic Search.

    PubMed

    Daniels, Noah M; Gallant, Andrew; Ramsey, Norman; Cowen, Lenore J

    2015-01-01

    We introduce MRFy, a tool for protein remote homology detection that captures beta-strand dependencies in the Markov random field. Over a set of 11 SCOP beta-structural superfamilies, MRFy shows a 14 percent improvement in mean Area Under the Curve for the motif recognition problem as compared to HMMER, 25 percent improvement as compared to RAPTOR, 14 percent improvement as compared to HHPred, and a 18 percent improvement as compared to CNFPred and RaptorX. MRFy was implemented in the Haskell functional programming language, and parallelizes well on multi-core systems. MRFy is available, as source code as well as an executable, from http://mrfy.cs.tufts.edu/.

  12. Nakagami Markov random field as texture model for ultrasound RF envelope image.

    PubMed

    Bouhlel, N; Sevestre-Ghalila, S

    2009-06-01

    The aim of this paper is to propose a new Markov random field (MRF) model for the backscattered ultrasonic echo in order to get information about backscatter characteristics, such as the scatterer density, amplitude and spacing. The model combines the Nakagami distribution that describes the envelope of backscattered echo with spatial interaction using MRF. In this paper, the parameters of the model and the estimation parameter method are introduced. Computer simulation using ultrasound radio-frequency (RF) simulator and experiments on choroidal malignant melanoma have been undertaken to test the validity of the model. The relationship between the parameters of MRF model and the backscatter characteristics has been established. Furthermore, the ability of the model to distinguish between normal and abnormal tissue has been proved. All the results can show the success of the model.

  13. Hysteresis in random-field Ising model on a Bethe lattice with a mixed coordination number

    NASA Astrophysics Data System (ADS)

    Shukla, Prabodh; Thongjaomayum, Diana

    2016-06-01

    We study zero-temperature hysteresis in the random-field Ising model on a Bethe lattice where a fraction c of the sites have coordination number z = 4 while the remaining fraction 1-c have z = 3. Numerical simulations as well as probabilistic methods are used to show the existence of critical hysteresis for all values of c\\gt 0. This extends earlier results for c = 0 and c = 1 to the entire range 0≤slant c≤slant 1, and provides new insight in non-equilibrium critical phenomena. Our analysis shows that a spanning avalanche can occur on a lattice even in the absence of a spanning cluster of z = 4 sites.

  14. Broadcast News Story Segmentation Using Conditional Random Fields and Multimodal Features

    NASA Astrophysics Data System (ADS)

    Wang, Xiaoxuan; Xie, Lei; Lu, Mimi; Ma, Bin; Chng, Eng Siong; Li, Haizhou

    In this paper, we propose integration of multimodal features using conditional random fields (CRFs) for the segmentation of broadcast news stories. We study story boundary cues from lexical, audio and video modalities, where lexical features consist of lexical similarity, chain strength and overall cohesiveness; acoustic features involve pause duration, pitch, speaker change and audio event type; and visual features contain shot boundaries, anchor faces and news title captions. These features are extracted in a sequence of boundary candidate positions in the broadcast news. A linear-chain CRF is used to detect each candidate as boundary/non-boundary tags based on the multimodal features. Important interlabel relations and contextual feature information are effectively captured by the sequential learning framework of CRFs. Story segmentation experiments show that the CRF approach outperforms other popular classifiers, including decision trees (DTs), Bayesian networks (BNs), naive Bayesian classifiers (NBs), multilayer perception (MLP), support vector machines (SVMs) and maximum entropy (ME) classifiers.

  15. Sign language recognition with the Kinect sensor based on conditional random fields.

    PubMed

    Yang, Hee-Deok

    2015-01-01

    Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D) space. In this research, we use 3D depth information from hand motions, generated from Microsoft's Kinect sensor and apply a hierarchical conditional random field (CRF) that recognizes hand signs from the hand motions. The proposed method uses a hierarchical CRF to detect candidate segments of signs using hand motions, and then a BoostMap embedding method to verify the hand shapes of the segmented signs. Experiments demonstrated that the proposed method could recognize signs from signed sentence data at a rate of 90.4%. PMID:25609039

  16. Trapping, percolation, and anomalous diffusion of particles in a two-dimensional random field

    SciTech Connect

    Avellaneda, M.; Apelian, C. ); Elliott, F. Jr. )

    1993-09-01

    The authors analyze the advection of particles in a velocity field with Hamiltonian H(x,y) = [bar V][sub 1]y-[bar V][sub 2]x + W[sub 1](y) - W[sub 2](x), where W[sub i], i=1,2, are random functions with stationary, independent increments. In the absence of molecular diffusion, the particle dynamics are sensitive to the streamline topology, which depends on the mean-to-fluctuations ratio p=max([vert bar][bar V][sub 1][vert bar]/[bar U];[vert bar][bar V][sub 2][vert bar]/[bar U]), with [bar U] = [[vert bar]W'[sub 1][vert bar][sup 2

  17. Bayesian Clustering Using Hidden Markov Random Fields in Spatial Population Genetics

    PubMed Central

    François, Olivier; Ancelet, Sophie; Guillot, Gilles

    2006-01-01

    We introduce a new Bayesian clustering algorithm for studying population structure using individually geo-referenced multilocus data sets. The algorithm is based on the concept of hidden Markov random field, which models the spatial dependencies at the cluster membership level. We argue that (i) a Markov chain Monte Carlo procedure can implement the algorithm efficiently, (ii) it can detect significant geographical discontinuities in allele frequencies and regulate the number of clusters, (iii) it can check whether the clusters obtained without the use of spatial priors are robust to the hypothesis of discontinuous geographical variation in allele frequencies, and (iv) it can reduce the number of loci required to obtain accurate assignments. We illustrate and discuss the implementation issues with the Scandinavian brown bear and the human CEPH diversity panel data set. PMID:16888334

  18. Large-Scale Magnetic Field Generation by Randomly Forced Shearing Waves

    NASA Astrophysics Data System (ADS)

    Heinemann, T.; McWilliams, J. C.; Schekochihin, A. A.

    2011-12-01

    A rigorous theory for the generation of a large-scale magnetic field by random nonhelically forced motions of a conducting fluid combined with a linear shear is presented in the analytically tractable limit of low magnetic Reynolds number (Rm) and weak shear. The dynamo is kinematic and due to fluctuations in the net (volume-averaged) electromotive force. This is a minimal proof-of-concept quasilinear calculation aiming to put the shear dynamo, a new effect recently found in numerical experiments, on a firm theoretical footing. Numerically observed scalings of the wave number and growth rate of the fastest-growing mode, previously not understood, are derived analytically. The simplicity of the model suggests that shear dynamo action may be a generic property of sheared magnetohydrodynamic turbulence.

  19. Evaluating Consumer m-Health Services for Promoting Healthy Eating: A Randomized Field Experiment

    PubMed Central

    Kato-Lin, Yi-Chin; Padman, Rema; Downs, Julie; Abhishek, Vibhanshu

    2015-01-01

    Mobile apps have great potential to deliver promising interventions to engage consumers and change their health-related behaviors, such as healthy eating. Currently, the interventions for promoting healthy eating are either too onerous to keep consumers engaged or too restrictive to keep consumers connected with healthcare professionals. In addition, while social media allows individuals to receive information from many sources, it is unclear how peer support interacts with professional support in the context of such interventions. This study proposes and evaluates three mobile-enabled interventions to address these challenges. We examine their effects on user engagement and food choices via a 4-month randomized field experiment. Mixed models provide strong evidence of the positive effect of image-based dietitian support and negative effects of peer support, and moderate evidence of the positive effects of mobile-based visual diary, highlighting the value of mobile apps for delivering advanced interventions to engage users and facilitate behavior change. PMID:26958294

  20. Incorporating conditional random fields and active learning to improve sentiment identification.

    PubMed

    Zhang, Kunpeng; Xie, Yusheng; Yang, Yi; Sun, Aaron; Liu, Hengchang; Choudhary, Alok

    2014-10-01

    Many machine learning, statistical, and computational linguistic methods have been developed to identify sentiment of sentences in documents, yielding promising results. However, most of state-of-the-art methods focus on individual sentences and ignore the impact of context on the meaning of a sentence. In this paper, we propose a method based on conditional random fields to incorporate sentence structure and context information in addition to syntactic information for improving sentiment identification. We also investigate how human interaction affects the accuracy of sentiment labeling using limited training data. We propose and evaluate two different active learning strategies for labeling sentiment data. Our experiments with the proposed approach demonstrate a 5%-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods.

  1. High energy X-ray phase and dark-field imaging using a random absorption mask

    NASA Astrophysics Data System (ADS)

    Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal

    2016-07-01

    High energy X-ray imaging has unique advantage over conventional X-ray imaging, since it enables higher penetration into materials with significantly reduced radiation damage. However, the absorption contrast in high energy region is considerably low due to the reduced X-ray absorption cross section for most materials. Even though the X-ray phase and dark-field imaging techniques can provide substantially increased contrast and complementary information, fabricating dedicated optics for high energies still remain a challenge. To address this issue, we present an alternative X-ray imaging approach to produce transmission, phase and scattering signals at high X-ray energies by using a random absorption mask. Importantly, in addition to the synchrotron radiation source, this approach has been demonstrated for practical imaging application with a laboratory-based microfocus X-ray source. This new imaging method could be potentially useful for studying thick samples or heavy materials for advanced research in materials science.

  2. Theory of Distribution Estimation of Hyperparameters in Markov Random Field Models

    NASA Astrophysics Data System (ADS)

    Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato

    2016-06-01

    We investigated the performance of distribution estimation of hyperparameters in Markov random field models proposed by Nakanishi-Ohno et al., J. Phys. A 47, 045001 (2014) when used to evaluate the confidence of data. We analytically calculated the configurational average, with respect to data, of the negative logarithm of the posterior distribution, which is called free energy based on an analogy with statistical mechanics. This configurational average of free energy shrinks as the amount of data increases. Our results theoretically confirm the numerical results from that previous study.

  3. Long-range random transverse-field Ising model in three dimensions

    NASA Astrophysics Data System (ADS)

    Kovács, István A.; Juhász, Róbert; Iglói, Ferenc

    2016-05-01

    We consider the random transverse-field Ising model in d =3 dimensions with long-range ferromagnetic interactions which decay as a power α >d with the distance. Using a variant of the strong-disorder renormalization group method we study numerically the phase-transition point from the paramagnetic side. We find that the fixed point controlling the transition is of the strong-disorder type, and based on experience with other similar systems, we expect the results to be qualitatively correct, but probably not asymptotically exact. The distribution of the (sample dependent) pseudocritical points is found to scale with 1 /lnL , L being the linear size of the sample. Similarly, the critical magnetization scales with (lnL) χ/Ld and the excitation energy behaves as L-α. Using extreme-value statistics we argue that extrapolating from the ferromagnetic side the magnetization approaches a finite limiting value and thus the transition is of mixed order.

  4. Smoothing Parameter Estimation for Markov Random Field Classification of non-Gaussian Distribution Image

    NASA Astrophysics Data System (ADS)

    Aghighi, H.; Trindet, J.; Wang, K.; Tarabalka, Y.; Lim, S.

    2014-09-01

    In the context of remote sensing image classification, Markov random fields (MRFs) have been used to combine both spectral and contextual information. The MRFs use a smoothing parameter to balance the contribution of the spectral versus spatial energies, which is often defined empirically. This paper proposes a framework to estimate the smoothing parameter using the probability estimates from support vector machines and the spatial class co-occurrence distribution. Furthermore, we construct a spatially weighted parameter to preserve the edges by using seven different edge detectors. The performance of the proposed methods is evaluated on two hyperspectral datasets recorded by the AVIRIS and ROSIS and a simulated ALOS PALSAR image. The experimental results demonstrated that the estimated smoothing parameter is optimal and produces a classified map with high accuracy. Moreover, we found that the Canny-based edge probability map preserved the contours better than others.

  5. Metabolomics reveals the metabolic shifts following an intervention with rye bread in postmenopausal women- a randomized control trial

    PubMed Central

    2012-01-01

    Background Epidemiological studies have consistently shown that whole grain (WG) cereals can protect against the development of chronic diseases, but the underlying mechanism is not fully understood. Among WG products, WG rye is considered even more potent because of its unique discrepancy in postprandial insulin and glucose responses known as the rye factor. In this study, an NMR-based metabolomics approach was applied to study the metabolic effects of WG rye as a tool to determine the beneficial effects of WG rye on human health. Methods Thirty-three postmenopausal Finnish women with elevated serum total cholesterol (5.0-8.5 mmol/L) and BMI of 20–33 kg/m2 consumed a minimum of 20% of their daily energy intake as high fiber WG rye bread (RB) or refined wheat bread (WB) in a randomized, controlled, crossover design with two 8-wk intervention periods separated by an 8-wk washout period. At the end of each intervention period, fasting serum was collected for NMR-based metabolomics and the analysis of cholesterol fractions. Multilevel partial least squares discriminant analysis was used for paired comparisons of multivariate data. Results The metabolomics analysis of serum showed lower leucine and isoleucine and higher betaine and N,N-dimethylglycine levels after RB than WB intake. To further investigate the metabolic effects of RB, the serum cholesterol fractions were measured. Total- and LDL-cholesterol levels were higher after RB intake than after WB (p<0.05). Conclusions This study revealed favorable shifts in branched amino acid and single carbon metabolism and an unfavorable shift in serum cholesterol levels after RB intake in postmenopausal women, which should be considered for evaluating health beneficial effects of rye products. PMID:23088297

  6. Crop Type Mapping from a Sequence of Terrasar-X Images with Dynamic Conditional Random Fields

    NASA Astrophysics Data System (ADS)

    Kenduiywo, B. K.; Bargiel, D.; Soergel, U.

    2016-06-01

    Crop phenology is dynamic as it changes with times of the year. Such biophysical processes also look spectrally different to remote sensing satellites. Some crops may depict similar spectral properties if their phenology coincide, but differ later when their phenology diverge. Thus, conventional approaches that select only images from phenological stages where crops are distinguishable for classification, have low discrimination. In contrast, stacking images within a cropping season limits discrimination to a single feature space that can suffer from overlapping classes. Since crop backscatter varies with time, it can aid discrimination. Therefore, our main objective is to develop a crop sequence classification method using multitemporal TerraSAR-X images. We adopt first order markov assumption in undirected temporal graph sequence. This property is exploited to implement Dynamic Conditional Random Fields (DCRFs). Our DCRFs model has a repeated structure of temporally connected Conditional Random Fields (CRFs). Each node in the sequence is connected to its predecessor via conditional probability matrix. The matrix is computed using posterior class probabilities from association potential. This way, there is a mutual temporal exchange of phenological information observed in TerraSAR-X images. When compared to independent epoch classification, the designed DCRF model improved crop discrimination at each epoch in the sequence. However, government, insurers, agricultural market traders and other stakeholders are interested in the quantity of a certain crop in a season. Therefore, we further develop a DCRF ensemble classifier. The ensemble produces an optimal crop map by maximizing over posterior class probabilities selected from the sequence based on maximum F1-score and weighted by correctness. Our ensemble technique is compared to standard approach of stacking all images as bands for classification using Maximum Likelihood Classifier (MLC) and standard CRFs. It

  7. Bayesian Markov Random Field analysis for protein function prediction based on network data.

    PubMed

    Kourmpetis, Yiannis A I; van Dijk, Aalt D J; Bink, Marco C A M; van Ham, Roeland C H J; ter Braak, Cajo J F

    2010-02-24

    Inference of protein functions is one of the most important aims of modern biology. To fully exploit the large volumes of genomic data typically produced in modern-day genomic experiments, automated computational methods for protein function prediction are urgently needed. Established methods use sequence or structure similarity to infer functions but those types of data do not suffice to determine the biological context in which proteins act. Current high-throughput biological experiments produce large amounts of data on the interactions between proteins. Such data can be used to infer interaction networks and to predict the biological process that the protein is involved in. Here, we develop a probabilistic approach for protein function prediction using network data, such as protein-protein interaction measurements. We take a Bayesian approach to an existing Markov Random Field method by performing simultaneous estimation of the model parameters and prediction of protein functions. We use an adaptive Markov Chain Monte Carlo algorithm that leads to more accurate parameter estimates and consequently to improved prediction performance compared to the standard Markov Random Fields method. We tested our method using a high quality S. cereviciae validation network with 1622 proteins against 90 Gene Ontology terms of different levels of abstraction. Compared to three other protein function prediction methods, our approach shows very good prediction performance. Our method can be directly applied to protein-protein interaction or coexpression networks, but also can be extended to use multiple data sources. We apply our method to physical protein interaction data from S. cerevisiae and provide novel predictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and we evaluate the predictions using the available literature.

  8. A Randomized, Controlled Field Trial for the Prevention of Jellyfish Stings With a Topical Sting Inhibitor

    PubMed Central

    Boulware, David R.

    2007-01-01

    Background Jellyfish stings are a common occurrence among ocean goers worldwide with an estimated 150 million envenomations annually. Fatalities and hospitalizations occur annually, particularly in the Indo-Pacific regions. A new topical jellyfish sting inhibitor based on the mucous coating of the clown fish prevents 85% of jellyfish stings in laboratory settings. The field effectiveness is unknown. The objective is to evaluate the field efficacy of the jellyfish sting inhibitor, Safe Sea™. Methods A double-blind, randomized, placebo-controlled trial occurred at the Dry Tortugas National Park, FL, USA and Sapodilla Cayes, Belize. Participants were healthy volunteers planning to snorkel for 30 to 45 minutes. Ten minutes prior to swimming, each participant was directly observed applying a blinded sample of Safe Sea (Nidaria Technology Ltd, Jordan Valley, Israel) to one side of their body and a blinded sample of Coppertone® (Schering-Plough, Kenilworth, NJ, USA) to the contralateral side as placebo control. Masked 26 g samples of both Safe Sea SPF15 and Coppertone® SPF15 were provided in identical containers to achieve 2 mg/cm2 coverage. Sides were randomly chosen by participants. The incidence of jellyfish stings was the main outcome measure. This was assessed by participant interview and examination as subjects exited the water. Results A total of 82 observed water exposures occurred. Thirteen jellyfish stings occurred during the study period for a 16% incidence. Eleven jellyfish stings occurred with placebo, two with the sting inhibitor, resulting in a relative risk reduction of 82% (95% confidence interval: 21%–96%; p = 0.02). No seabather’s eruption or side effects occurred. Conclusions Safe Sea is a topical barrier cream effective at preventing >80% jellyfish stings under real-world conditions. PMID:16706948

  9. Spin-glass phase transition and behavior of nonlinear susceptibility in the Sherrington-Kirkpatrick model with random fields

    NASA Astrophysics Data System (ADS)

    Morais, C. V.; Zimmer, F. M.; Lazo, M. J.; Magalhães, S. G.; Nobre, F. D.

    2016-06-01

    The behavior of the nonlinear susceptibility χ3 and its relation to the spin-glass transition temperature Tf in the presence of random fields are investigated. To accomplish this task, the Sherrington-Kirkpatrick model is studied through the replica formalism, within a one-step replica-symmetry-breaking procedure. In addition, the dependence of the Almeida-Thouless eigenvalue λAT (replicon) on the random fields is analyzed. Particularly, in the absence of random fields, the temperature Tf can be traced by a divergence in the spin-glass susceptibility χSG, which presents a term inversely proportional to the replicon λAT. As a result of a relation between χSG and χ3, the latter also presents a divergence at Tf, which comes as a direct consequence of λAT=0 at Tf. However, our results show that, in the presence of random fields, χ3 presents a rounded maximum at a temperature T* which does not coincide with the spin-glass transition temperature Tf (i.e., T*>Tf for a given applied random field). Thus, the maximum value of χ3 at T* reflects the effects of the random fields in the paramagnetic phase instead of the nontrivial ergodicity breaking associated with the spin-glass phase transition. It is also shown that χ3 still maintains a dependence on the replicon λAT, although in a more complicated way as compared with the case without random fields. These results are discussed in view of recent observations in the LiHoxY1 -xF4 compound.

  10. INSTRUCTIONAL CONFERENCE ON THE THEORY OF STOCHASTIC PROCESSES: On the general theory of random fields on the plane

    NASA Astrophysics Data System (ADS)

    Gushchin, A. A.

    1982-12-01

    CONTENTSIntroduction § 1. Basic notation and definitions § 2. The Doléans measure and increasing fields § 3. Theorems on predictable projections. Decomposition of weak submartingales § 4. Weakly predictable random fields § 5. Theorems on weakly predictable projections § 6. Decomposition of strong martingales References

  11. Class-specific weighting for Markov random field estimation: application to medical image segmentation.

    PubMed

    Monaco, James P; Madabhushi, Anant

    2012-12-01

    Many estimation tasks require Bayesian classifiers capable of adjusting their performance (e.g. sensitivity/specificity). In situations where the optimal classification decision can be identified by an exhaustive search over all possible classes, means for adjusting classifier performance, such as probability thresholding or weighting the a posteriori probabilities, are well established. Unfortunately, analogous methods compatible with Markov random fields (i.e. large collections of dependent random variables) are noticeably absent from the literature. Consequently, most Markov random field (MRF) based classification systems typically restrict their performance to a single, static operating point (i.e. a paired sensitivity/specificity). To address this deficiency, we previously introduced an extension of maximum posterior marginals (MPM) estimation that allows certain classes to be weighted more heavily than others, thus providing a means for varying classifier performance. However, this extension is not appropriate for the more popular maximum a posteriori (MAP) estimation. Thus, a strategy for varying the performance of MAP estimators is still needed. Such a strategy is essential for several reasons: (1) the MAP cost function may be more appropriate in certain classification tasks than the MPM cost function, (2) the literature provides a surfeit of MAP estimation implementations, several of which are considerably faster than the typical Markov Chain Monte Carlo methods used for MPM, and (3) MAP estimation is used far more often than MPM. Consequently, in this paper we introduce multiplicative weighted MAP (MWMAP) estimation-achieved via the incorporation of multiplicative weights into the MAP cost function-which allows certain classes to be preferred over others. This creates a natural bias for specific classes, and consequently a means for adjusting classifier performance. Similarly, we show how this multiplicative weighting strategy can be applied to the MPM

  12. Class-specific weighting for Markov random field estimation: application to medical image segmentation.

    PubMed

    Monaco, James P; Madabhushi, Anant

    2012-12-01

    Many estimation tasks require Bayesian classifiers capable of adjusting their performance (e.g. sensitivity/specificity). In situations where the optimal classification decision can be identified by an exhaustive search over all possible classes, means for adjusting classifier performance, such as probability thresholding or weighting the a posteriori probabilities, are well established. Unfortunately, analogous methods compatible with Markov random fields (i.e. large collections of dependent random variables) are noticeably absent from the literature. Consequently, most Markov random field (MRF) based classification systems typically restrict their performance to a single, static operating point (i.e. a paired sensitivity/specificity). To address this deficiency, we previously introduced an extension of maximum posterior marginals (MPM) estimation that allows certain classes to be weighted more heavily than others, thus providing a means for varying classifier performance. However, this extension is not appropriate for the more popular maximum a posteriori (MAP) estimation. Thus, a strategy for varying the performance of MAP estimators is still needed. Such a strategy is essential for several reasons: (1) the MAP cost function may be more appropriate in certain classification tasks than the MPM cost function, (2) the literature provides a surfeit of MAP estimation implementations, several of which are considerably faster than the typical Markov Chain Monte Carlo methods used for MPM, and (3) MAP estimation is used far more often than MPM. Consequently, in this paper we introduce multiplicative weighted MAP (MWMAP) estimation-achieved via the incorporation of multiplicative weights into the MAP cost function-which allows certain classes to be preferred over others. This creates a natural bias for specific classes, and consequently a means for adjusting classifier performance. Similarly, we show how this multiplicative weighting strategy can be applied to the MPM

  13. Class-Specific Weighting for Markov Random Field Estimation: Application to Medical Image Segmentation

    PubMed Central

    Monaco, James P.; Madabhushi, Anant

    2012-01-01

    Many estimation tasks require Bayesian classifiers capable of adjusting their performance (e.g. sensitivity/Specificity). In situations where the optimal classification decision can be identified by an exhaustive search over all possible classes, means for adjusting classifier performance, such as probability thresholding or weighting the a posteriori probabilities, are well established. Unfortunately, analogous methods compatible with Markov random fields (i.e. large collections of dependent random variables) are noticeably absent from the literature. Consequently, most Markov random field (MRF) based classification systems typically restrict their performance to a single, static operating point (i.e. a paired sensitivity/Specificity). To address this deficiency, we previously introduced an extension of maximum posterior marginals (MPM) estimation that allows certain classes to be weighted more heavily than others, thus providing a means for varying classifier performance. However, this extension is not appropriate for the more popular maximum a posteriori (MAP) estimation. Thus, a strategy for varying the performance of MAP estimators is still needed. Such a strategy is essential for several reasons: 1) the MAP cost function may be more appropriate in certain classification tasks than the MPM cost function, 2) the literature provides a surfeit of MAP estimation implementations, several of which are considerably faster than the typical Markov Chain Monte Carlo methods used for MPM, and 3) MAP estimation is used far more often than MPM. Consequently, in this paper we introduce multiplicative weighted MAP (MWMAP) estimation — achieved via the incorporation of multiplicative weights into the MAP cost function — which allows certain classes to be preferred over others. This creates a natural bias for Specific classes, and consequently a means for adjusting classifier performance. Similarly, we show how this multiplicative weighting strategy can be applied to the

  14. Stochastic generation of explicit pore structures by thresholding Gaussian random fields

    SciTech Connect

    Hyman, Jeffrey D.; Winter, C. Larrabee

    2014-11-15

    We provide a description and computational investigation of an efficient method to stochastically generate realistic pore structures. Smolarkiewicz and Winter introduced this specific method in pores resolving simulation of Darcy flows (Smolarkiewicz and Winter, 2010 [1]) without giving a complete formal description or analysis of the method, or indicating how to control the parameterization of the ensemble. We address both issues in this paper. The method consists of two steps. First, a realization of a correlated Gaussian field, or topography, is produced by convolving a prescribed kernel with an initial field of independent, identically distributed random variables. The intrinsic length scales of the kernel determine the correlation structure of the topography. Next, a sample pore space is generated by applying a level threshold to the Gaussian field realization: points are assigned to the void phase or the solid phase depending on whether the topography over them is above or below the threshold. Hence, the topology and geometry of the pore space depend on the form of the kernel and the level threshold. Manipulating these two user prescribed quantities allows good control of pore space observables, in particular the Minkowski functionals. Extensions of the method to generate media with multiple pore structures and preferential flow directions are also discussed. To demonstrate its usefulness, the method is used to generate a pore space with physical and hydrological properties similar to a sample of Berea sandstone. -- Graphical abstract: -- Highlights: •An efficient method to stochastically generate realistic pore structures is provided. •Samples are generated by applying a level threshold to a Gaussian field realization. •Two user prescribed quantities determine the topology and geometry of the pore space. •Multiple pore structures and preferential flow directions can be produced. •A pore space based on Berea sandstone is generated.

  15. A Markov random field approach to group-wise registration/mosaicing with application to ultrasound.

    PubMed

    Kutarnia, Jason; Pedersen, Peder

    2015-08-01

    In this paper we present a group-wise non-rigid registration/mosaicing algorithm based on block-matching, which is developed within a probabilistic framework. The discrete form of its energy functional is linked to a Markov Random Field (MRF) containing double and triple cliques, which can be effectively optimized using modern MRF optimization algorithms popular in computer vision. Also, the registration problem is simplified by introducing a mosaicing function which partitions the composite volume into regions filled with data from unique, partially overlapping source volumes. Ultrasound confidence maps are incorporated into the registration framework in order to give accurate results in the presence of image artifacts. The algorithm is initially tested on simulated images where shadows have been generated. Also, validation results for the group-wise registration algorithm using real ultrasound data from an abdominal phantom are presented. Finally, composite obstetrics image volumes are constructed using clinical scans of pregnant subjects, where fetal movement makes registration/mosaicing especially difficult. In addition, results are presented suggesting that a fusion approach to MRF registration can produce accurate displacement fields much faster than standard approaches.

  16. A Novel Microaneurysms Detection Method Based on Local Applying of Markov Random Field.

    PubMed

    Ganjee, Razieh; Azmi, Reza; Moghadam, Mohsen Ebrahimi

    2016-03-01

    Diabetic Retinopathy (DR) is one of the most common complications of long-term diabetes. It is a progressive disease and by damaging retina, it finally results in blindness of patients. Since Microaneurysms (MAs) appear as a first sign of DR in retina, early detection of this lesion is an essential step in automatic detection of DR. In this paper, a new MAs detection method is presented. The proposed approach consists of two main steps. In the first step, the MA candidates are detected based on local applying of Markov random field model (MRF). In the second step, these candidate regions are categorized to identify the correct MAs using 23 features based on shape, intensity and Gaussian distribution of MAs intensity. The proposed method is evaluated on DIARETDB1 which is a standard and publicly available database in this field. Evaluation of the proposed method on this database resulted in the average sensitivity of 0.82 for a confidence level of 75 as a ground truth. The results show that our method is able to detect the low contrast MAs with the background while its performance is still comparable to other state of the art approaches.

  17. Unsupervised 4D myocardium segmentation with a Markov Random Field based deformable model.

    PubMed

    Cordero-Grande, L; Vegas-Sánchez-Ferrero, G; Casaseca-de-la-Higuera, P; San-Román-Calvar, J Alberto; Revilla-Orodea, Ana; Martín-Fernández, M; Alberola-López, C

    2011-06-01

    A stochastic deformable model is proposed for the segmentation of the myocardium in Magnetic Resonance Imaging. The segmentation is posed as a probabilistic optimization problem in which the optimal time-dependent surface is obtained for the myocardium of the heart in a discrete space of locations built upon simple geometric assumptions. For this purpose, first, the left ventricle is detected by a set of image analysis tools gathered from the literature. Then, the segmentation solution is obtained by the Maximization of the Posterior Marginals for the myocardium location in a Markov Random Field framework which optimally integrates temporal-spatial smoothness with intensity and gradient related features in an unsupervised way by the Maximum Likelihood estimation of the parameters of the field. This scheme provides a flexible and robust segmentation method which has been able to generate results comparable to manually segmented images for some derived cardiac function parameters in a set of 43 patients affected in different degrees by an Acute Myocardial Infarction.

  18. Multilayer Markov Random Field models for change detection in optical remote sensing images

    NASA Astrophysics Data System (ADS)

    Benedek, Csaba; Shadaydeh, Maha; Kato, Zoltan; Szirányi, Tamás; Zerubia, Josiane

    2015-09-01

    In this paper, we give a comparative study on three Multilayer Markov Random Field (MRF) based solutions proposed for change detection in optical remote sensing images, called Multicue MRF, Conditional Mixed Markov model, and Fusion MRF. Our purposes are twofold. On one hand, we highlight the significance of the focused model family and we set them against various state-of-the-art approaches through a thematic analysis and quantitative tests. We discuss the advantages and drawbacks of class comparison vs. direct approaches, usage of training data, various targeted application fields and different ways of Ground Truth generation, meantime informing the Reader in which roles the Multilayer MRFs can be efficiently applied. On the other hand we also emphasize the differences between the three focused models at various levels, considering the model structures, feature extraction, layer interpretation, change concept definition, parameter tuning and performance. We provide qualitative and quantitative comparison results using principally a publicly available change detection database which contains aerial image pairs and Ground Truth change masks. We conclude that the discussed models are competitive against alternative state-of-the-art solutions, if one uses them as pre-processing filters in multitemporal optical image analysis. In addition, they cover together a large range of applications, considering the different usage options of the three approaches.

  19. Diffuse scattered field of elastic waves from randomly rough surfaces using an analytical Kirchhoff theory

    NASA Astrophysics Data System (ADS)

    Shi, F.; Lowe, M. J. S.; Xi, X.; Craster, R. V.

    2016-07-01

    We develop an elastodynamic theory to predict the diffuse scattered field of elastic waves by randomly rough surfaces, for the first time, with the aid of the Kirchhoff approximation (KA). Analytical expressions are derived incorporating surface statistics, to represent the expectation of the angular distribution of the diffuse intensity for different modes. The analytical solutions are successfully verified with numerical Monte Carlo simulations, and also validated by comparison with experiments. We then apply the theory to quantitatively investigate the effects of the roughness and the shear-to-compressional wave speed ratio on the mode conversion and the scattering intensity, from low to high roughness within the valid region of KA. Both the direct and the mode converted intensities are significantly affected by the roughness, which leads to distinct scattering patterns for different wave modes. The mode conversion effect is very strong around the specular angle and it is found to increase as the surface appears to be more rough. In addition, the 3D roughness induced coupling between the out-of-plane shear horizontal (SH) mode and the in-plane modes is studied. The intensity of the SH mode is shown to be very sensitive to the out-of-plane correlation length, being influenced more by this than by the RMS value of the roughness. However, it is found that the depolarization pattern for the diffuse field is independent of the actual value of the roughness.

  20. Temporal coherence of the acoustic field forward propagated through a continental shelf with random internal waves.

    PubMed

    Gong, Zheng; Chen, Tianrun; Ratilal, Purnima; Makris, Nicholas C

    2013-11-01

    An analytical model derived from normal mode theory for the accumulated effects of range-dependent multiple forward scattering is applied to estimate the temporal coherence of the acoustic field forward propagated through a continental-shelf waveguide containing random three-dimensional internal waves. The modeled coherence time scale of narrow band low-frequency acoustic field fluctuations after propagating through a continental-shelf waveguide is shown to decay with a power-law of range to the -1/2 beyond roughly 1 km, decrease with increasing internal wave energy, to be consistent with measured acoustic coherence time scales. The model should provide a useful prediction of the acoustic coherence time scale as a function of internal wave energy in continental-shelf environments. The acoustic coherence time scale is an important parameter in remote sensing applications because it determines (i) the time window within which standard coherent processing such as matched filtering may be conducted, and (ii) the number of statistically independent fluctuations in a given measurement period that determines the variance reduction possible by stationary averaging.

  1. The rotation of photospheric magnetic fields: A random walk transport model

    NASA Technical Reports Server (NTRS)

    Wang, Y. -M.; Sheeley, N. R., Jr.

    1994-01-01

    In an earlier study of solar differential rotation, we showed that the transport of magnetic flux across latitudes acts to establish quasi-stationary patterns, therby accounting for the observed rigid rotation of the large-scale photospheric field. In that paper, the effect of supergranular convection was represented by a continuum diffusion, limiting the applicability of the calculations to large spatial scales. Here we extend the model to scales comparable to that of the supergranulation itself by replacing the diffusive transport with a discrete random walk process. Rotation curves are derived by cross-correlating the simulated photospheric field maps for a variety of time lags and spatial resolutions. When the lag between maps is relatively short less than or approximately = 15 days), the midlatitude correlation functions show two distinct components: a broad feature associated with the large-scale unipolar patterns and a narrow feature originating from small magnetic structures encompossing from one to several supergranular cells. By fitting the broad component we obtain the rigid rotation profile of the patterns, whereas by fitting the narrow component, we recover the differential rate of the photospheric plasma itself. For time lags of 1 month or greater, only the broad feature associated with the long-lived patterns remains clearly identifiable in the simulations.

  2. A Poisson random field model of pathogen transport in surface water

    NASA Astrophysics Data System (ADS)

    Yeghiazarian, L.; Samorodnitsky, G.; Montemagno, C. D.

    2009-11-01

    To address the uncertainty associated with microbial transport and surface water contamination events, we developed a new comprehensive stochastic framework that combines processes on the microscopic (single microorganism) and macroscopic (ensembles of microorganisms) scales. The spatial and temporal population behavior is modeled as a nonhomogeneous Poisson random field with Markovian field dynamics. The model parameters are based on the actual physical and biological characteristics of the Cryptosporidium parvum transport process and can be extended to cover a variety of other pathogens. Since soil particles have been shown to be a major vehicle in microbial transport, a U.S. Department of Agriculture approved erosion model (Water Erosion Prediction Project) is incorporated into the model. Risk assessment is an integral part of the stochastic model and is conducted using a set of simple calculations. Poisson intensity functions and correlations are computed. The results consistently indicate that surface water contamination events are transient, with traveling high peaks of microorganism concentrations. Correlations between microorganism populations at different points in time and space reach relatively significant levels even at large distances from one another. This information is aimed to assist water resources management teams in the decision-making process to identify the likely timing and locations of high-risk areas and thus to avoid collection of contaminated water.

  3. Analysis and Validation of Grid dem Generation Based on Gaussian Markov Random Field

    NASA Astrophysics Data System (ADS)

    Aguilar, F. J.; Aguilar, M. A.; Blanco, J. L.; Nemmaoui, A.; García Lorca, A. M.

    2016-06-01

    Digital Elevation Models (DEMs) are considered as one of the most relevant geospatial data to carry out land-cover and land-use classification. This work deals with the application of a mathematical framework based on a Gaussian Markov Random Field (GMRF) to interpolate grid DEMs from scattered elevation data. The performance of the GMRF interpolation model was tested on a set of LiDAR data (0.87 points/m2) provided by the Spanish Government (PNOA Programme) over a complex working area mainly covered by greenhouses in Almería, Spain. The original LiDAR data was decimated by randomly removing different fractions of the original points (from 10% to up to 99% of points removed). In every case, the remaining points (scattered observed points) were used to obtain a 1 m grid spacing GMRF-interpolated Digital Surface Model (DSM) whose accuracy was assessed by means of the set of previously extracted checkpoints. The GMRF accuracy results were compared with those provided by the widely known Triangulation with Linear Interpolation (TLI). Finally, the GMRF method was applied to a real-world case consisting of filling the LiDAR-derived DSM gaps after manually filtering out non-ground points to obtain a Digital Terrain Model (DTM). Regarding accuracy, both GMRF and TLI produced visually pleasing and similar results in terms of vertical accuracy. As an added bonus, the GMRF mathematical framework makes possible to both retrieve the estimated uncertainty for every interpolated elevation point (the DEM uncertainty) and include break lines or terrain discontinuities between adjacent cells to produce higher quality DTMs.

  4. Segmenting pectoralis muscle on digital mammograms by a Markov random field-maximum a posteriori model.

    PubMed

    Ge, Mei; Mainprize, James G; Mawdsley, Gordon E; Yaffe, Martin J

    2014-10-01

    Accurate and automatic segmentation of the pectoralis muscle is essential in many breast image processing procedures, for example, in the computation of volumetric breast density from digital mammograms. Its segmentation is a difficult task due to the heterogeneity of the region, neighborhood complexities, and shape variability. The segmentation is achieved by pixel classification through a Markov random field (MRF) image model. Using the image intensity feature as observable data and local spatial information as a priori, the posterior distribution is estimated in a stochastic process. With a variable potential component in the energy function, by the maximum a posteriori (MAP) estimate of the labeling image, given the image intensity feature which is assumed to follow a Gaussian distribution, we achieved convergence properties in an appropriate sense by Metropolis sampling the posterior distribution of the selected energy function. By proposing an adjustable spatial constraint, the MRF-MAP model is able to embody the shape requirement and provide the required flexibility for the model parameter fitting process. We demonstrate that accurate and robust segmentation can be achieved for the curving-triangle-shaped pectoralis muscle in the medio-lateral-oblique (MLO) view, and the semielliptic-shaped muscle in cranio-caudal (CC) view digital mammograms. The applicable mammograms can be either "For Processing" or "For Presentation" image formats. The algorithm was developed using 56 MLO-view and 79 CC-view FFDM "For Processing" images, and quantitatively evaluated against a random selection of 122 MLO-view and 173 CC-view FFDM images of both presentation intent types.

  5. Fetal MEG evoked response latency from beamformer with random field theory

    PubMed Central

    McCubbin, J.; Vrba, J.; Murphy, P.; Temple, J.; Eswaran, H.; Lowery, C.L.; Preissl, H.

    2009-01-01

    Analysis of fetal magnetoencephalographic brain recordings is restricted by low signal to noise ratio (SNR) and non-stationarity of the sources. Beamformer techniques have been applied to improve SNR of fetal evoked responses. However, until now the effect of non-stationarity was not taken into account in detail, because the detection of evoked responses is in most cases determined by averaging a large number of trials. We applied a windowing technique to improve the stationarity of the data by using short time segments recorded during a flash evoked study. In addition, we implemented a random field theory approach for more stringent control of false positives in the statistical parametric map of the search volume for the beamformer. The search volume was based on detailed individual fetal/maternal biometrics from ultrasound scans and fetal heart localization. Average power over a sliding window within the averaged evoked response against a randomized average background power was used as the test z – statistic. The significance threshold was set at 10% over all members of a contiguous cluster of voxels. There was at least one significant response for 62% of fetal and 95% of newborn recordings with gestational age (GA) between 28 and 45 weeks from 29 subjects. We found that the latency was either substantially unchanged or decreased with increasing GA for most subjects, with a nominal rate of about −11 ms/week. These findings support the anticipated neurophysiological development, provide validation for the beamformer model search as a methodology, and may lead to a clinical test for fetal cognitive development. PMID:19686855

  6. The non-equilibrium allele frequency spectrum in a Poisson random field framework.

    PubMed

    Kaj, Ingemar; Mugal, Carina F

    2016-10-01

    In population genetic studies, the allele frequency spectrum (AFS) efficiently summarizes genome-wide polymorphism data and shapes a variety of allele frequency-based summary statistics. While existing theory typically features equilibrium conditions, emerging methodology requires an analytical understanding of the build-up of the allele frequencies over time. In this work, we use the framework of Poisson random fields to derive new representations of the non-equilibrium AFS for the case of a Wright-Fisher population model with selection. In our approach, the AFS is a scaling-limit of the expectation of a Poisson stochastic integral and the representation of the non-equilibrium AFS arises in terms of a fixation time probability distribution. The known duality between the Wright-Fisher diffusion process and a birth and death process generalizing Kingman's coalescent yields an additional representation. The results carry over to the setting of a random sample drawn from the population and provide the non-equilibrium behavior of sample statistics. Our findings are consistent with and extend a previous approach where the non-equilibrium AFS solves a partial differential forward equation with a non-traditional boundary condition. Moreover, we provide a bridge to previous coalescent-based work, and hence tie several frameworks together. Since frequency-based summary statistics are widely used in population genetics, for example, to identify candidate loci of adaptive evolution, to infer the demographic history of a population, or to improve our understanding of the underlying mechanics of speciation events, the presented results are potentially useful for a broad range of topics.

  7. Pulsed electromagnetic fields in knee osteoarthritis: a double blind, placebo-controlled, randomized clinical trial

    PubMed Central

    Miceli, Giovanni; Marino, Natale; Sciortino, Davide; Bagnato, Gian Filippo

    2016-01-01

    Objectives. This trial aimed to test the effectiveness of a wearable pulsed electromagnetic fields (PEMF) device in the management of pain in knee OA patients. Methods. In this randomized [with equal randomization (1:1)], double-blind, placebo-controlled clinical trial, patients with radiographic evidence of knee OA and persistent pain higher than 40 mm on the visual analog scale (VAS) were recruited. The trial consisted of 12 h daily treatment for 1 month in 60 knee OA patients. The primary outcome measure was the reduction in pain intensity, assessed through VAS and WOMAC scores. Secondary outcomes included quality of life assessment through the 36-item Medical Outcomes Study Short-Form version 2 (SF-36 v2), pressure pain threshold (PPT) and changes in intake of NSAIDs/analgesics. Results. Sixty-six patients were included, and 60 completed the study. After 1 month, PEMF induced a significant reduction in VAS pain and WOMAC scores compared with placebo. Additionally, pain tolerance, as expressed by PPT changes, and physical health improved in PEMF-treated patients. A mean treatment effect of −0.73 (95% CI − 1.24 to − 0.19) was seen in VAS score, while the effect size was −0.34 (95% CI − 0.85 to 0.17) for WOMAC score. Twenty-six per cent of patients in the PEMF group stopped NSAID/analgesic therapy. No adverse events were detected. Conclusion. These results suggest that PEMF therapy is effective for pain management in knee OA patients and also affects pain threshold and physical functioning. Future larger studies, including head-to-head studies comparing PEMF therapy with standard pharmacological approaches in OA, are warranted. Trial registration: ClinicalTrials.gov, http://www.clinicaltrials.gov, NCT01877278 PMID:26705327

  8. Segmenting pectoralis muscle on digital mammograms by a Markov random field-maximum a posteriori model

    PubMed Central

    Ge, Mei; Mainprize, James G.; Mawdsley, Gordon E.; Yaffe, Martin J.

    2014-01-01

    Abstract. Accurate and automatic segmentation of the pectoralis muscle is essential in many breast image processing procedures, for example, in the computation of volumetric breast density from digital mammograms. Its segmentation is a difficult task due to the heterogeneity of the region, neighborhood complexities, and shape variability. The segmentation is achieved by pixel classification through a Markov random field (MRF) image model. Using the image intensity feature as observable data and local spatial information as a priori, the posterior distribution is estimated in a stochastic process. With a variable potential component in the energy function, by the maximum a posteriori (MAP) estimate of the labeling image, given the image intensity feature which is assumed to follow a Gaussian distribution, we achieved convergence properties in an appropriate sense by Metropolis sampling the posterior distribution of the selected energy function. By proposing an adjustable spatial constraint, the MRF-MAP model is able to embody the shape requirement and provide the required flexibility for the model parameter fitting process. We demonstrate that accurate and robust segmentation can be achieved for the curving-triangle-shaped pectoralis muscle in the medio-lateral-oblique (MLO) view, and the semielliptic-shaped muscle in cranio-caudal (CC) view digital mammograms. The applicable mammograms can be either “For Processing” or “For Presentation” image formats. The algorithm was developed using 56 MLO-view and 79 CC-view FFDM “For Processing” images, and quantitatively evaluated against a random selection of 122 MLO-view and 173 CC-view FFDM images of both presentation intent types. PMID:26158068

  9. The non-equilibrium allele frequency spectrum in a Poisson random field framework.

    PubMed

    Kaj, Ingemar; Mugal, Carina F

    2016-10-01

    In population genetic studies, the allele frequency spectrum (AFS) efficiently summarizes genome-wide polymorphism data and shapes a variety of allele frequency-based summary statistics. While existing theory typically features equilibrium conditions, emerging methodology requires an analytical understanding of the build-up of the allele frequencies over time. In this work, we use the framework of Poisson random fields to derive new representations of the non-equilibrium AFS for the case of a Wright-Fisher population model with selection. In our approach, the AFS is a scaling-limit of the expectation of a Poisson stochastic integral and the representation of the non-equilibrium AFS arises in terms of a fixation time probability distribution. The known duality between the Wright-Fisher diffusion process and a birth and death process generalizing Kingman's coalescent yields an additional representation. The results carry over to the setting of a random sample drawn from the population and provide the non-equilibrium behavior of sample statistics. Our findings are consistent with and extend a previous approach where the non-equilibrium AFS solves a partial differential forward equation with a non-traditional boundary condition. Moreover, we provide a bridge to previous coalescent-based work, and hence tie several frameworks together. Since frequency-based summary statistics are widely used in population genetics, for example, to identify candidate loci of adaptive evolution, to infer the demographic history of a population, or to improve our understanding of the underlying mechanics of speciation events, the presented results are potentially useful for a broad range of topics. PMID:27378747

  10. Fetal MEG evoked response latency from beamformer with random field theory.

    PubMed

    McCubbin, J; Vrba, J; Murphy, P; Temple, J; Eswaran, H; Lowery, C L; Preissl, H

    2010-01-01

    Analysis of fetal magnetoencephalographic brain recordings is restricted by low signal to noise ratio (SNR) and non-stationarity of the sources. Beamformer techniques have been applied to improve SNR of fetal evoked responses. However, until now the effect of non-stationarity was not taken into account in detail, because the detection of evoked responses is in most cases determined by averaging a large number of trials. We applied a windowing technique to improve the stationarity of the data by using short time segments recorded during a flash-evoked study. In addition, we implemented a random field theory approach for more stringent control of false-positives in the statistical parametric map of the search volume for the beamformer. The search volume was based on detailed individual fetal/maternal biometrics from ultrasound scans and fetal heart localization. Average power over a sliding window within the averaged evoked response against a randomized average background power was used as the test z-statistic. The significance threshold was set at 10% over all members of a contiguous cluster of voxels. There was at least one significant response for 62% of fetal and 95% of newborn recordings with gestational age (GA) between 28 and 45 weeks from 29 subjects. We found that the latency was either substantially unchanged or decreased with increasing GA for most subjects, with a nominal rate of about -11 ms/week. These findings support the anticipated neurophysiological development, provide validation for the beamformer model search as a methodology, and may lead to a clinical test for fetal cognitive development.

  11. Discourse-based intervention for modifying supervisory communication as leverage for safety climate and performance improvement: a randomized field study.

    PubMed

    Zohar, Dov; Polachek, Tal

    2014-01-01

    The article presents a randomized field study designed to improve safety climate and resultant safety performance by modifying daily messages in supervisor-member communications. Supervisors in the experimental group received 2 individualized feedback sessions regarding the extent to which they integrated safety and productivity-related issues in daily verbal exchanges with their members; those in the control group received no feedback. Feedback data originated from 7-9 workers for each supervisor, reporting about received supervisory messages during the most recent verbal exchange. Questionnaire data collected 8 weeks before and after the 12-week intervention phase revealed significant changes for safety climate, safety behavior, subjective workload, teamwork, and (independently measured) safety audit scores for the experimental group. Data for the control group (except for safety behavior) remained unchanged. These results are explained by corresponding changes (or lack thereof in the control group) in perceived discourse messages during the 6-week period between the 1st and 2nd feedback sessions. Theoretical and practical implications for climate improvement and organizational discourse research are discussed.

  12. Nonpoint source solute transport normal to aquifer bedding in heterogeneous, Markov chain random fields

    NASA Astrophysics Data System (ADS)

    Zhang, Hua; Harter, Thomas; Sivakumar, Bellie

    2006-06-01

    examined, the third moment of the traveltime pdf varies from negatively skewed to strongly positively skewed. We also show that the Markov chain approach may give significantly different traveltime distributions when compared to the more commonly used Gaussian random field approach, even when the first- and second-order moments in the geostatistical distribution of the lnK field are identical. The choice of the appropriate geostatistical model is therefore critical in the assessment of nonpoint source transport, and uncertainty about that choice must be considered in evaluating the results.

  13. Metabolic properties in stroked rats revealed by relaxation-enhanced magnetic resonance spectroscopy at ultrahigh fields.

    PubMed

    Shemesh, Noam; Rosenberg, Jens T; Dumez, Jean-Nicolas; Muniz, Jose A; Grant, Samuel C; Frydman, Lucio

    2014-01-01

    (1)H magnetic resonance spectroscopy (MRS) yields site-specific signatures that directly report metabolic concentrations, biochemistry and kinetics-provided spectral sensitivity and quality are sufficient. Here, an enabling relaxation-enhanced (RE) MRS approach is demonstrated that by combining highly selective spectral excitations with operation at very high magnetic fields, delivers spectra exhibiting signal-to-noise ratios >50:1 in under 6 s for ~5 × 5 × 5 (mm)(3) voxels, with flat baselines and no interference from water. With this spectral quality, MRS was used to interrogate a number of metabolic properties in stroked rat models. Metabolic confinements imposed by randomly oriented micro-architectures were detected and found to change upon ischaemia; intensities of downfield resonances were found to be selectively altered in stroked hemispheres; and longitudinal relaxation time of lactic acid was found to increase by over 50% its control value as early as 3-h post ischaemia, paralleling the onset of cytotoxic oedema. These results demonstrate potential of (1)H MRS at ultrahigh fields. PMID:25229942

  14. A Hypergraph-Based Reduction for Higher-Order Binary Markov Random Fields.

    PubMed

    Fix, Alexander; Gruber, Aritanan; Boros, Endre; Zabih, Ramin

    2015-07-01

    Higher-order Markov Random Fields, which can capture important properties of natural images, have become increasingly important in computer vision. While graph cuts work well for first-order MRF's, until recently they have rarely been effective for higher-order MRF's. Ishikawa's graph cut technique [1], [2] shows great promise for many higher-order MRF's. His method transforms an arbitrary higher-order MRF with binary labels into a first-order one with the same minima. If all the terms are submodular the exact solution can be easily found; otherwise, pseudoboolean optimization techniques can produce an optimal labeling for a subset of the variables. We present a new transformation with better performance than [1], [2], both theoretically and experimentally. While [1], [2] transforms each higher-order term independently, we use the underlying hypergraph structure of the MRF to transform a group of terms at once. For n binary variables, each of which appears in terms with k other variables, at worst we produce n non-submodular terms, while [1], [2] produces O(nk). We identify a local completeness property under which our method perform even better, and show that under certain assumptions several important vision problems (including common variants of fusion moves) have this property. We show experimentally that our method produces smaller weight of non-submodular edges, and that this metric is directly related to the effectiveness of QPBO [3]. Running on the same field of experts dataset used in [1], [2] we optimally label significantly more variables (96 versus 80 percent) and converge more rapidly to a lower energy. Preliminary experiments suggest that some other higher-order MRF's used in stereo [4] and segmentation [5] are also locally complete and would thus benefit from our work.

  15. Context-aware patch-based image inpainting using Markov random field modeling.

    PubMed

    Ružić, Tijana; Pižurica, Aleksandra

    2015-01-01

    In this paper, we first introduce a general approach for context-aware patch-based image inpainting, where textural descriptors are used to guide and accelerate the search for well-matching (candidate) patches. A novel top-down splitting procedure divides the image into variable size blocks according to their context, constraining thereby the search for candidate patches to nonlocal image regions with matching context. This approach can be employed to improve the speed and performance of virtually any (patch-based) inpainting method. We apply this approach to the so-called global image inpainting with the Markov random field (MRF) prior, where MRF encodes a priori knowledge about consistency of neighboring image patches. We solve the resulting optimization problem with an efficient low-complexity inference method. Experimental results demonstrate the potential of the proposed approach in inpainting applications like scratch, text, and object removal. Improvement and significant acceleration of a related global MRF-based inpainting method is also evident.

  16. Incorporating biological pathways via a Markov random field model in genome-wide association studies.

    PubMed

    Chen, Min; Cho, Judy; Zhao, Hongyu

    2011-04-01

    Genome-wide association studies (GWAS) examine a large number of markers across the genome to identify associations between genetic variants and disease. Most published studies examine only single markers, which may be less informative than considering multiple markers and multiple genes jointly because genes may interact with each other to affect disease risk. Much knowledge has been accumulated in the literature on biological pathways and interactions. It is conceivable that appropriate incorporation of such prior knowledge may improve the likelihood of making genuine discoveries. Although a number of methods have been developed recently to prioritize genes using prior biological knowledge, such as pathways, most methods treat genes in a specific pathway as an exchangeable set without considering the topological structure of a pathway. However, how genes are related with each other in a pathway may be very informative to identify association signals. To make use of the connectivity information among genes in a pathway in GWAS analysis, we propose a Markov Random Field (MRF) model to incorporate pathway topology for association analysis. We show that the conditional distribution of our MRF model takes on a simple logistic regression form, and we propose an iterated conditional modes algorithm as well as a decision theoretic approach for statistical inference of each gene's association with disease. Simulation studies show that our proposed framework is more effective to identify genes associated with disease than a single gene-based method. We also illustrate the usefulness of our approach through its applications to a real data example.

  17. Service-oriented node scheduling scheme for wireless sensor networks using Markov random field model.

    PubMed

    Cheng, Hongju; Su, Zhihuang; Lloret, Jaime; Chen, Guolong

    2014-11-06

    Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime.

  18. Impact of Markov Random Field optimizer on MRI-based tissue segmentation in the aging brain.

    PubMed

    Schwarz, Christopher G; Tsui, Alex; Fletcher, Evan; Singh, Baljeet; DeCarli, Charles; Carmichael, Owen

    2011-01-01

    Automatically segmenting brain magnetic resonance images into grey matter, white matter, and cerebrospinal fluid compartments is a fundamentally important neuroimaging problem whose difficulty is heightened in the presence of aging and neurodegenerative disease. Current methods overlap greatly in terms of identifiable algorithmic components, and the impact of specific components on performance is generally unclear in important real-world scenarios involving serial scanning, multiple scanners, and neurodegenerative disease. Therefore we evaluated the impact that one such component, the Markov Random Field (MRF) optimizer that encourages spatially-smooth tissue labelings, has on brain tissue segmentation performance. Two challenging elderly data sets were used to test segmentation consistency across scanners and biological plausibility of tissue change estimates; and a simulated young brain data set was used to test accuracy against ground truth. Belief propagation (BP) and graph cuts (GC), used as the MRF optimizer component of a standardized segmentation system, provide high segmentation performance on aggregate that is competitive with end-to-end systems provided by SPM and FSL (FAST) as well as the more traditional MRF optimizer iterated conditional modes (ICM). However, the relative performance of each method varied strongly by performance criterion and differed between young and old brains. The findings emphasize the unique difficulties involved in segmenting the aging brain, and suggest that optimal algorithm components may depend in part on performance criteria.

  19. Markov random field based automatic alignment for low SNR imagesfor cryo electron tomography

    SciTech Connect

    Amat, Fernando; Moussavi, Farshid; Comolli, Luis R.; Elidan, Gal; Horowitz, Mark

    2007-07-21

    We present a method for automatic full precision alignmentof the images in a tomographic tilt series. Full-precision automaticalignment of cryo electron microscopy images has remained a difficultchallenge to date, due to the limited electron dose and low imagecontrast. These facts lead to poor signal to noise ratio (SNR) in theimages, which causes automatic feature trackers to generate errors, evenwith high contrast gold particles as fiducial features. To enable fullyautomatic alignment for full-precision reconstructions, we frame theproblem probabilistically as finding the most likely particle tracksgiven a set of noisy images, using contextual information to make thesolution more robust to the noise in each image. To solve this maximumlikelihood problem, we use Markov Random Fields (MRF) to establish thecorrespondence of features in alignment and robust optimization forprojection model estimation. The resultingalgorithm, called RobustAlignment and Projection Estimation for Tomographic Reconstruction, orRAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as goodas the manual approach by an expert user. We are able to automaticallymap complete and partial marker trajectories and thus obtain highlyaccurate image alignment. Our method has been applied to challenging cryoelectron tomographic datasets with low SNR from intact bacterial cells,as well as several plastic section and x-ray datasets.

  20. A wavelet-based Markov random field segmentation model in segmenting microarray experiments.

    PubMed

    Athanasiadis, Emmanouil; Cavouras, Dionisis; Kostopoulos, Spyros; Glotsos, Dimitris; Kalatzis, Ioannis; Nikiforidis, George

    2011-12-01

    In the present study, an adaptation of the Markov Random Field (MRF) segmentation model, by means of the stationary wavelet transform (SWT), applied to complementary DNA (cDNA) microarray images is proposed (WMRF). A 3-level decomposition scheme of the initial microarray image was performed, followed by a soft thresholding filtering technique. With the inverse process, a Denoised image was created. In addition, by using the Amplitudes of the filtered wavelet Horizontal and Vertical images at each level, three different Magnitudes were formed. These images were combined with the Denoised one to create the proposed SMRF segmentation model. For numerical evaluation of the segmentation accuracy, the segmentation matching factor (SMF), the Coefficient of Determination (r(2)), and the concordance correlation (p(c)) were calculated on the simulated images. In addition, the SMRF performance was contrasted to the Fuzzy C Means (FCM), Gaussian Mixture Models (GMM), Fuzzy GMM (FGMM), and the conventional MRF techniques. Indirect accuracy performances were also tested on the experimental images by means of the Mean Absolute Error (MAE) and the Coefficient of Variation (CV). In the latter case, SPOT and SCANALYZE software results were also tested. In the former case, SMRF attained the best SMF, r(2), and p(c) (92.66%, 0.923, and 0.88, respectively) scores, whereas, in the latter case scored MAE and CV, 497 and 0.88, respectively. The results and support the performance superiority of the SMRF algorithm in segmenting cDNA images.

  1. Prostate cancer segmentation with simultaneous estimation of Markov random field parameters and class.

    PubMed

    Liu, Xin; Langer, Deanna L; Haider, Masoom A; Yang, Yongyi; Wernick, Miles N; Yetik, Imam Samil

    2009-06-01

    Prostate cancer is one of the leading causes of death from cancer among men in the United States. Currently, high-resolution magnetic resonance imaging (MRI) has been shown to have higher accuracy than trans-rectal ultrasound (TRUS) when used to ascertain the presence of prostate cancer. As MRI can provide both morphological and functional images for a tissue of interest, some researchers are exploring the uses of multispectral MRI to guide prostate biopsies and radiation therapy. However, success with prostate cancer localization based on current imaging methods has been limited due to overlap in feature space of benign and malignant tissues using any one MRI method and the interobserver variability. In this paper, we present a new unsupervised segmentation method for prostate cancer detection, using fuzzy Markov random fields (fuzzy MRFs) for the segmentation of multispectral MR prostate images. Typically, both hard and fuzzy MRF models have two groups of parameters to be estimated: the MRF parameters and class parameters for each pixel in the image. To date, these two parameters have been treated separately, and estimated in an alternating fashion. In this paper, we develop a new method to estimate the parameters defining the Markovian distribution of the measured data, while performing the data clustering simultaneously. We perform computer simulations on synthetic test images and multispectral MR prostate datasets to demonstrate the efficacy and efficiency of the proposed method and also provide a comparison with some of the commonly used methods.

  2. Segmentation of complementary DNA microarray images by wavelet-based Markov random field model.

    PubMed

    Athanasiadis, Emmanouil I; Cavouras, Dionisis A; Glotsos, Dimitris Th; Georgiadis, Pantelis V; Kalatzis, Ioannis K; Nikiforidis, George C

    2009-11-01

    A wavelet-based modification of the Markov random field (WMRF) model is proposed for segmenting complementary DNA (cDNA) microarray images. For evaluation purposes, five simulated and a set of five real microarray images were used. The one-level stationary wavelet transform (SWT) of each microarray image was used to form two images, a denoised image, using hard thresholding filter, and a magnitude image, from the amplitudes of the horizontal and vertical components of SWT. Elements from these two images were suitably combined to form the WMRF model for segmenting spots from their background. The WMRF was compared against the conventional MRF and the Fuzzy C means (FCM) algorithms on simulated and real microarray images and their performances were evaluated by means of the segmentation matching factor (SMF) and the coefficient of determination (r2). Additionally, the WMRF was compared against the SPOT and SCANALYZE, and performances were evaluated by the mean absolute error (MAE) and the coefficient of variation (CV). The WMRF performed more accurately than the MRF and FCM (SMF: 92.66, 92.15, and 89.22, r2 : 0.92, 0.90, and 0.84, respectively) and achieved higher reproducibility than the MRF, SPOT, and SCANALYZE (MAE: 497, 1215, 1180, and 503, CV: 0.88, 1.15, 0.93, and 0.90, respectively).

  3. A Markov Random Field orientation prior for electronic cleansing in CT Colonography.

    PubMed

    Krishnan, Karthik; Desai, Nasir

    2015-01-01

    Tagging of the bowel content with an oral contrast facilitates CT Colonography with limited bowel preparation. Electronic colon cleansing (ECC) reconstructs the colon lumen, devoid of feces from a CT scan acquired with fecal fluid tagging. A popular method to estimate the stool composition in an image (with the purpose of removing it) is the well-established Expectation Maximization (EM) method. The tagged fluid residue appears as a contrast enhanced region with a largely horizontal interface with air above it. One of the issues is the partial volume (PV) effect that creates voxels with attenuations similar to that of the colon wall at the boundary of air and tagged fluid. We present here, a novel orientation prior formulated as a Markov Random Field that is included as part of the EM tissue segmentation framework to mitigate this PV effect at the air and tagged fluid layer. We show quantitative results on a simple synthetic dataset and qualitative results on patient data that highlight improvements due to the inclusion of the orientation prior.

  4. Oriented Markov random field based dendritic spine segmentation for fluorescence microscopy images.

    PubMed

    Cheng, Jie; Zhou, Xiaobo; Miller, Eric L; Alvarez, Veronica A; Sabatini, Bernardo L; Wong, Stephen T C

    2010-10-01

    Dendritic spines have been shown to be closely related to various functional properties of the neuron. Usually dendritic spines are manually labeled to analyze their morphological changes, which is very time-consuming and susceptible to operator bias, even with the assistance of computers. To deal with these issues, several methods have been recently proposed to automatically detect and measure the dendritic spines with little human interaction. However, problems such as degraded detection performance for images with larger pixel size (e.g. 0.125 μm/pixel instead of 0.08 μm/pixel) still exist in these methods. Moreover, the shapes of detected spines are also distorted. For example, the "necks" of some spines are missed. Here we present an oriented Markov random field (OMRF) based algorithm which improves spine detection as well as their geometric characterization. We begin with the identification of a region of interest (ROI) containing all the dendrites and spines to be analyzed. For this purpose, we introduce an adaptive procedure for identifying the image background. Next, the OMRF model is discussed within a statistical framework and the segmentation is solved as a maximum a posteriori estimation (MAP) problem, whose optimal solution is found by a knowledge-guided iterative conditional mode (KICM) algorithm. Compared with the existing algorithms, the proposed algorithm not only provides a more accurate representation of the spine shape, but also improves the detection performance by more than 50% with regard to reducing both the misses and false detection.

  5. Joint modeling of ChIP-seq data via a Markov random field model.

    PubMed

    Bao, Yanchun; Vinciotti, Veronica; Wit, Ernst; 't Hoen, Peter A C

    2014-04-01

    Chromatin ImmunoPrecipitation-sequencing (ChIP-seq) experiments have now become routine in biology for the detection of protein-binding sites. In this paper, we present a Markov random field model for the joint analysis of multiple ChIP-seq experiments. The proposed model naturally accounts for spatial dependencies in the data, by assuming first-order Markov dependence and, for the large proportion of zero counts, by using zero-inflated mixture distributions. In contrast to all other available implementations, the model allows for the joint modeling of multiple experiments, by incorporating key aspects of the experimental design. In particular, the model uses the information about replicates and about the different antibodies used in the experiments. An extensive simulation study shows a lower false non-discovery rate for the proposed method, compared with existing methods, at the same false discovery rate. Finally, we present an analysis on real data for the detection of histone modifications of two chromatin modifiers from eight ChIP-seq experiments, including technical replicates with different IP efficiencies.

  6. Posterior-mean super-resolution with a causal Gaussian Markov random field prior.

    PubMed

    Katsuki, Takayuki; Torii, Akira; Inoue, Masato

    2012-07-01

    We propose a Bayesian image super-resolution (SR) method with a causal Gaussian Markov random field (MRF) prior. SR is a technique to estimate a spatially high-resolution image from given multiple low-resolution images. An MRF model with the line process supplies a preferable prior for natural images with edges. We improve the existing image transformation model, the compound MRF model, and its hyperparameter prior model. We also derive the optimal estimator--not the joint maximum a posteriori (MAP) or the marginalized maximum likelihood (ML) but the posterior mean (PM)--from the objective function of the L2-norm-based (mean square error) peak signal-to-noise ratio. Point estimates such as MAP and ML are generally not stable in ill-posed high-dimensional problems because of overfitting, whereas PM is a stable estimator because all the parameters in the model are evaluated as distributions. The estimator is numerically determined by using the variational Bayesian method. The variational Bayesian method is a widely used method that approximately determines a complicated posterior distribution, but it is generally hard to use because it needs the conjugate prior. We solve this problem with simple Taylor approximations. Experimental results have shown that the proposed method is more accurate or comparable to existing methods.

  7. Disease gene identification by using graph kernels and Markov random fields.

    PubMed

    Chen, BoLin; Li, Min; Wang, JianXin; Wu, Fang-Xiang

    2014-11-01

    Genes associated with similar diseases are often functionally related. This principle is largely supported by many biological data sources, such as disease phenotype similarities, protein complexes, protein-protein interactions, pathways and gene expression profiles. Integrating multiple types of biological data is an effective method to identify disease genes for many genetic diseases. To capture the gene-disease associations based on biological networks, a kernel-based MRF method is proposed by combining graph kernels and the Markov random field (MRF) method. In the proposed method, three kinds of kernels are employed to describe the overall relationships of vertices in five biological networks, respectively, and a novel weighted MRF method is developed to integrate those data. In addition, an improved Gibbs sampling procedure and a novel parameter estimation method are proposed to generate predictions from the kernel-based MRF method. Numerical experiments are carried out by integrating known gene-disease associations, protein complexes, protein-protein interactions, pathways and gene expression profiles. The proposed kernel-based MRF method is evaluated by the leave-one-out cross validation paradigm, achieving an AUC score of 0.771 when integrating all those biological data in our experiments, which indicates that our proposed method is very promising compared with many existing methods.

  8. Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

    PubMed

    Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

    2014-01-01

    The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

  9. Unsupervised polarimetric synthetic aperture radar image classification based on sketch map and adaptive Markov random field

    NASA Astrophysics Data System (ADS)

    Shi, Junfei; Li, Lingling; Liu, Fang; Jiao, Licheng; Liu, Hongying; Yang, Shuyuan; Liu, Lu; Hao, Hongxia

    2016-04-01

    Markov random field (MRF) model is an effective tool for polarimetric synthetic aperture radar (PolSAR) image classification. However, due to the lack of suitable contextual information in conventional MRF methods, there is usually a contradiction between edge preservation and region homogeneity in the classification result. To preserve edge details and obtain homogeneous regions simultaneously, an adaptive MRF framework is proposed based on a polarimetric sketch map. The polarimetric sketch map can provide the edge positions and edge directions in detail, which can guide the selection of neighborhood structures. Specifically, the polarimetric sketch map is extracted to partition a PolSAR image into structural and nonstructural parts, and then adaptive neighborhoods are learned for two parts. For structural areas, geometric weighted neighborhood structures are constructed to preserve image details. For nonstructural areas, the maximum homogeneous regions are obtained to improve the region homogeneity. Experiments are taken on both the simulated and real PolSAR data, and the experimental results illustrate that the proposed method can obtain better performance on both region homogeneity and edge preservation than the state-of-the-art methods.

  10. Medical image retrieval and analysis by Markov random fields and multi-scale fractal dimension.

    PubMed

    Backes, André Ricardo; Gerhardinger, Leandro Cavaleri; Batista Neto, João do Espírito Santo; Bruno, Odemir Martinez

    2015-02-01

    Many Content-based Image Retrieval (CBIR) systems and image analysis tools employ color, shape and texture (in a combined fashion or not) as attributes, or signatures, to retrieve images from databases or to perform image analysis in general. Among these attributes, texture has turned out to be the most relevant, as it allows the identification of a larger number of images of a different nature. This paper introduces a novel signature which can be used for image analysis and retrieval. It combines texture with complexity extracted from objects within the images. The approach consists of a texture segmentation step, modeled as a Markov Random Field process, followed by the estimation of the complexity of each computed region. The complexity is given by a Multi-scale Fractal Dimension. Experiments have been conducted using an MRI database in both pattern recognition and image retrieval contexts. The results show the accuracy of the proposed method in comparison with other traditional texture descriptors and also indicate how the performance changes as the level of complexity is altered.

  11. Network-based genomic discovery: application and comparison of Markov random field models.

    PubMed

    Wei, Peng; Pan, Wei

    2010-01-01

    As biological knowledge accumulates rapidly, gene networks encoding genome-wide gene-gene interactions have been constructed. As an improvement over the standard mixture model that tests all the genes iid a priori, Wei and Li (2007) and Wei and Pan (2008) proposed modeling a gene network as a Discrete- or Gaussian-Markov random field (DMRF or GMRF) respectively in a mixture model to analyze genomic data. However, how these methods compare in practical applications in not well understood and this is the aim here. We also propose two novel constraints in prior specifications for the GMRF model and a fully Bayesian approach to the DMRF model. We assess the accuracy of estimating the False Discovery Rate (FDR) by posterior probabilities in the context of MRF models. Applications to a ChIP-chip data set and simulated data show that the modified GMRF models has superior performance as compared with other models, while both MRF-based mixture models, with reasonable robustness to misspecified gene networks, outperform the standard mixture model.

  12. A comparative study of Gaussian geostatistical models and Gaussian Markov random field models1

    PubMed Central

    Song, Hae-Ryoung; Fuentes, Montserrat; Ghosh, Sujit

    2008-01-01

    Gaussian geostatistical models (GGMs) and Gaussian Markov random fields (GM-RFs) are two distinct approaches commonly used in spatial models for modeling point referenced and areal data, respectively. In this paper, the relations between GGMs and GMRFs are explored based on approximations of GMRFs by GGMs, and approximations of GGMs by GMRFs. Two new metrics of approximation are proposed: (i) the Kullback-Leibler discrepancy of spectral densities and (ii) the chi-squared distance between spectral densities. The distances between the spectral density functions of GGMs and GMRFs measured by these metrics are minimized to obtain the approximations of GGMs and GMRFs. The proposed methodologies are validated through several empirical studies. We compare the performance of our approach to other methods based on covariance functions, in terms of the average mean squared prediction error and also the computational time. A spatial analysis of a dataset on PM2.5 collected in California is presented to illustrate the proposed method. PMID:19337581

  13. Transport of Dirac electrons in a random magnetic field in topological heterostructures

    NASA Astrophysics Data System (ADS)

    Hurst, Hilary M.; Efimkin, Dmitry K.; Galitski, Victor

    2016-06-01

    We consider the proximity effect between Dirac states at the surface of a topological insulator and a ferromagnet with easy plane anisotropy, which is described by the XY model and undergoes a Berezinskii-Kosterlitz-Thouless (BKT) phase transition. The surface states of the topological insulator interacting with classical magnetic fluctuations of the ferromagnet can be mapped onto the problem of Dirac fermions in a random magnetic field. However, this analogy is only partial in the presence of electron-hole asymmetry or warping of the Dirac dispersion, which results in screening of magnetic fluctuations. Scattering at magnetic fluctuations influences the behavior of the surface resistivity as a function of temperature. Near the BKT phase transition temperature we find that the resistivity of surface states scales linearly with temperature and has a clear maximum which becomes more pronounced as the Fermi energy decreases. Additionally, at low temperatures we find linear resistivity, usually associated with non-Fermi-liquid behavior; however, here it appears entirely within the Fermi-liquid picture.

  14. a Method to Estimate Temporal Interaction in a Conditional Random Field Based Approach for Crop Recognition

    NASA Astrophysics Data System (ADS)

    Diaz, P. M. A.; Feitosa, R. Q.; Sanches, I. D.; Costa, G. A. O. P.

    2016-06-01

    This paper presents a method to estimate the temporal interaction in a Conditional Random Field (CRF) based approach for crop recognition from multitemporal remote sensing image sequences. This approach models the phenology of different crop types as a CRF. Interaction potentials are assumed to depend only on the class labels of an image site at two consecutive epochs. In the proposed method, the estimation of temporal interaction parameters is considered as an optimization problem, whose goal is to find the transition matrix that maximizes the CRF performance, upon a set of labelled data. The objective functions underlying the optimization procedure can be formulated in terms of different accuracy metrics, such as overall and average class accuracy per crop or phenological stages. To validate the proposed approach, experiments were carried out upon a dataset consisting of 12 co-registered LANDSAT images of a region in southeast of Brazil. Pattern Search was used as the optimization algorithm. The experimental results demonstrated that the proposed method was able to substantially outperform estimates related to joint or conditional class transition probabilities, which rely on training samples.

  15. Nonparametric Feature Matching Based Conditional Random Fields for Gesture Recognition from Multi-Modal Video.

    PubMed

    Chang, Ju Yong

    2016-08-01

    We present a new gesture recognition method that is based on the conditional random field (CRF) model using multiple feature matching. Our approach solves the labeling problem, determining gesture categories and their temporal ranges at the same time. A generative probabilistic model is formalized and probability densities are nonparametrically estimated by matching input features with a training dataset. In addition to the conventional skeletal joint-based features, the appearance information near the active hand in an RGB image is exploited to capture the detailed motion of fingers. The estimated likelihood function is then used as the unary term for our CRF model. The smoothness term is also incorporated to enforce the temporal coherence of our solution. Frame-wise recognition results can then be obtained by applying an efficient dynamic programming technique. To estimate the parameters of the proposed CRF model, we incorporate the structured support vector machine (SSVM) framework that can perform efficient structured learning by using large-scale datasets. Experimental results demonstrate that our method provides effective gesture recognition results for challenging real gesture datasets. By scoring 0.8563 in the mean Jaccard index, our method has obtained the state-of-the-art results for the gesture recognition track of the 2014 ChaLearn Looking at People (LAP) Challenge.

  16. A segmentation model using compound Markov random fields based on a boundary model.

    PubMed

    Wu, Jue; Chung, Albert C S

    2007-01-01

    Markov random field (MRF) theory has been widely applied to the challenging problem of image segmentation. In this paper, we propose a new nontexture segmentation model using compound MRFs, in which the original label MRF is coupled with a new boundary MRF to help improve the segmentation performance. The boundary model is relatively general and does not need prior training on boundary patterns. Unlike some existing related work, the proposed method offers a more compact interaction between label and boundary MRFs. Furthermore, our boundary model systematically takes into account all the possible scenarios of a single edge existing in a 3 x 3 neighborhood and, thus, incorporates sophisticated prior information about the relation between label and boundary. It is experimentally shown that the proposed model can segment objects with complex boundaries and at the same time is able to work under noise corruption. The new method has been applied to medical image segmentation. Experiments on synthetic images and real clinical datasets show that the proposed model is able to produce more accurate segmentation results and satisfactorily keep the delicate boundary. It is also less sensitive to noise in both high and low signal-to-noise ratio regions than some of the existing models in common use.

  17. A new method for direction finding based on Markov random field model

    NASA Astrophysics Data System (ADS)

    Ota, Mamoru; Kasahara, Yoshiya; Goto, Yoshitaka

    2015-07-01

    Investigating the characteristics of plasma waves observed by scientific satellites in the Earth's plasmasphere/magnetosphere is effective for understanding the mechanisms for generating waves and the plasma environment that influences wave generation and propagation. In particular, finding the propagation directions of waves is important for understanding mechanisms of VLF/ELF waves. To find these directions, the wave distribution function (WDF) method has been proposed. This method is based on the idea that observed signals consist of a number of elementary plane waves that define wave energy density distribution. However, the resulting equations constitute an ill-posed problem in which a solution is not determined uniquely; hence, an adequate model must be assumed for a solution. Although many models have been proposed, we have to select the most optimum model for the given situation because each model has its own advantages and disadvantages. In the present study, we propose a new method for direction finding of the plasma waves measured by plasma wave receivers. Our method is based on the assumption that the WDF can be represented by a Markov random field model with inference of model parameters performed using a variational Bayesian learning algorithm. Using computer-generated spectral matrices, we evaluated the performance of the model and compared the results with those obtained from two conventional methods.

  18. Reconstruction for distributed video coding: a Markov random field approach with context-adaptive smoothness prior

    NASA Astrophysics Data System (ADS)

    Zhang, Yongsheng; Xiong, Hongkai; He, Zhihai; Yu, Songyu

    2010-07-01

    An important issue in Wyner-Ziv video coding is the reconstruction of Wyner-Ziv frames with decoded bit-planes. So far, there are two major approaches: the Maximum a Posteriori (MAP) reconstruction and the Minimum Mean Square Error (MMSE) reconstruction algorithms. However, these approaches do not exploit smoothness constraints in natural images. In this paper, we model a Wyner-Ziv frame by Markov random fields (MRFs), and produce reconstruction results by finding an MAP estimation of the MRF model. In the MRF model, the energy function consists of two terms: a data term, MSE distortion metric in this paper, measuring the statistical correlation between side-information and the source, and a smoothness term enforcing spatial coherence. In order to better describe the spatial constraints of images, we propose a context-adaptive smoothness term by analyzing the correspondence between the output of Slepian-Wolf decoding and successive frames available at decoders. The significance of the smoothness term varies in accordance with the spatial variation within different regions. To some extent, the proposed approach is an extension to the MAP and MMSE approaches by exploiting the intrinsic smoothness characteristic of natural images. Experimental results demonstrate a considerable performance gain compared with the MAP and MMSE approaches.

  19. High energy X-ray phase and dark-field imaging using a random absorption mask.

    PubMed

    Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal

    2016-01-01

    High energy X-ray imaging has unique advantage over conventional X-ray imaging, since it enables higher penetration into materials with significantly reduced radiation damage. However, the absorption contrast in high energy region is considerably low due to the reduced X-ray absorption cross section for most materials. Even though the X-ray phase and dark-field imaging techniques can provide substantially increased contrast and complementary information, fabricating dedicated optics for high energies still remain a challenge. To address this issue, we present an alternative X-ray imaging approach to produce transmission, phase and scattering signals at high X-ray energies by using a random absorption mask. Importantly, in addition to the synchrotron radiation source, this approach has been demonstrated for practical imaging application with a laboratory-based microfocus X-ray source. This new imaging method could be potentially useful for studying thick samples or heavy materials for advanced research in materials science. PMID:27466217

  20. Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

    NASA Astrophysics Data System (ADS)

    Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

    2009-02-01

    Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

  1. Singular-potential random-matrix model arising in mean-field glassy systems

    NASA Astrophysics Data System (ADS)

    Akemann, Gernot; Villamaina, Dario; Vivo, Pierpaolo

    2014-06-01

    We consider an invariant random matrix ensemble where the standard Gaussian potential is distorted by an additional single pole of arbitrary fixed order. Potentials with first- and second-order poles have been considered previously and found applications in quantum chaos and number theory. Here we present an application to mean-field glassy systems. We derive and solve the loop equation in the planar limit for the corresponding class of potentials. We find that the resulting mean or macroscopic spectral density is generally supported on two disconnected intervals lying on the two sides of the repulsive pole, whose edge points can be completely determined imposing the additional constraint of traceless matrices on average. For an unbounded potential with an attractive pole, we also find a possible one-cut solution for certain values of the couplings, which is ruled out when the traceless condition is imposed. Motivated by the calculation of the distribution of the spin-glass susceptibility in the Sherrington-Kirkpatrick spin-glass model, we consider in detail a second-order pole for a zero-trace model and provide the most explicit solution in this case. In the limit of a vanishing pole, we recover the standard semicircle. Working in the planar limit, our results apply to matrices with orthogonal, unitary, and symplectic invariance. Numerical simulations and an independent analytical Coulomb fluid calculation for symmetric potentials provide an excellent confirmation of our results.

  2. Nonparametric Feature Matching Based Conditional Random Fields for Gesture Recognition from Multi-Modal Video.

    PubMed

    Chang, Ju Yong

    2016-08-01

    We present a new gesture recognition method that is based on the conditional random field (CRF) model using multiple feature matching. Our approach solves the labeling problem, determining gesture categories and their temporal ranges at the same time. A generative probabilistic model is formalized and probability densities are nonparametrically estimated by matching input features with a training dataset. In addition to the conventional skeletal joint-based features, the appearance information near the active hand in an RGB image is exploited to capture the detailed motion of fingers. The estimated likelihood function is then used as the unary term for our CRF model. The smoothness term is also incorporated to enforce the temporal coherence of our solution. Frame-wise recognition results can then be obtained by applying an efficient dynamic programming technique. To estimate the parameters of the proposed CRF model, we incorporate the structured support vector machine (SSVM) framework that can perform efficient structured learning by using large-scale datasets. Experimental results demonstrate that our method provides effective gesture recognition results for challenging real gesture datasets. By scoring 0.8563 in the mean Jaccard index, our method has obtained the state-of-the-art results for the gesture recognition track of the 2014 ChaLearn Looking at People (LAP) Challenge. PMID:26800528

  3. Increasing the maximally random jammed density with electric field to reduce the fat level in chocolate

    NASA Astrophysics Data System (ADS)

    Tao, R.; Tang, H.

    Chocolate is one of the most popular food types and flavors in the world. Unfortunately, at present, chocolate products contain too much fat, leading to obesity. For example, a typical molding chocolate has various fat up to 40% in total and chocolate for covering ice cream has fat 50 -60%. Especially, as children are the leading chocolate consumers, reducing the fat level in chocolate products to make them healthier is important and urgent. While this issue was called into attention and elaborated in articles and books decades ago and led to some patent applications, no actual solution was found unfortunately. Why is reducing fat in chocolate so difficult? What is the underlying physical mechanism? We have found that this issue is deeply related to the basic science of soft matters, especially to their viscosity and maximally random jammed (MRJ) density φx. All chocolate productions are handling liquid chocolate, a suspension with cocoa solid particles in melted fat, mainly cocoa butter. The fat level cannot be lower than 1-φxin order to have liquid chocolate to flow. Here we show that that with application of an electric field to liquid chocolate, we can aggregate the suspended particles into prolate spheroids. This microstructure change reduces liquid chocolate's viscosity along the flow direction and increases its MRJ density significantly. Hence the fat level in chocolate can be effectively reduced. We are looking forward to a new class of healthier and tasteful chocolate coming to the market soon. Dept. of Physics, Temple Univ, Philadelphia, PA 19122.

  4. Semiautomatic tumor segmentation with multimodal images in a conditional random field framework.

    PubMed

    Hu, Yu-Chi; Grossberg, Michael; Mageras, Gikas

    2016-04-01

    Volumetric medical images of a single subject can be acquired using different imaging modalities, such as computed tomography, magnetic resonance imaging (MRI), and positron emission tomography. In this work, we present a semiautomatic segmentation algorithm that can leverage the synergies between different image modalities while integrating interactive human guidance. The algorithm provides a statistical segmentation framework partly automating the segmentation task while still maintaining critical human oversight. The statistical models presented are trained interactively using simple brush strokes to indicate tumor and nontumor tissues and using intermediate results within a patient's image study. To accomplish the segmentation, we construct the energy function in the conditional random field (CRF) framework. For each slice, the energy function is set using the estimated probabilities from both user brush stroke data and prior approved segmented slices within a patient study. The progressive segmentation is obtained using a graph-cut-based minimization. Although no similar semiautomated algorithm is currently available, we evaluated our method with an MRI data set from Medical Image Computing and Computer Assisted Intervention Society multimodal brain segmentation challenge (BRATS 2012 and 2013) against a similar fully automatic method based on CRF and a semiautomatic method based on grow-cut, and our method shows superior performance. PMID:27413768

  5. High energy X-ray phase and dark-field imaging using a random absorption mask

    PubMed Central

    Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal

    2016-01-01

    High energy X-ray imaging has unique advantage over conventional X-ray imaging, since it enables higher penetration into materials with significantly reduced radiation damage. However, the absorption contrast in high energy region is considerably low due to the reduced X-ray absorption cross section for most materials. Even though the X-ray phase and dark-field imaging techniques can provide substantially increased contrast and complementary information, fabricating dedicated optics for high energies still remain a challenge. To address this issue, we present an alternative X-ray imaging approach to produce transmission, phase and scattering signals at high X-ray energies by using a random absorption mask. Importantly, in addition to the synchrotron radiation source, this approach has been demonstrated for practical imaging application with a laboratory-based microfocus X-ray source. This new imaging method could be potentially useful for studying thick samples or heavy materials for advanced research in materials science. PMID:27466217

  6. Reconstruction of compressive multispectral sensing data using a multilayered conditional random field approach

    NASA Astrophysics Data System (ADS)

    Kazemzadeh, Farnoud; Shafiee, Mohammad J.; Wong, Alexander; Clausi, David A.

    2014-09-01

    The prevalence of compressive sensing is continually growing in all facets of imaging science. Com- pressive sensing allows for the capture and reconstruction of an entire signal from a sparse (under- sampled), yet sufficient, set of measurements that is representative of the target being observed. This compressive sensing strategy reduces the duration of the data capture, the size of the acquired data, and the cost of the imaging hardware as well as complexity while preserving the necessary underlying information. Compressive sensing systems require the accompaniment of advanced re- construction algorithms to reconstruct complete signals from the sparse measurements made. Here, a new reconstruction algorithm is introduced specifically for the reconstruction of compressive multispectral (MS) sensing data that allows for high-quality reconstruction from acquisitions at sub-Nyquist rates. We propose a multilayered conditional random field (MCRF) model, which extends upon the CRF model by incorporating two joint layers of certainty and estimated states. The proposed algorithm treats the reconstruction of each spectral channel as a MCRF given the sparse MS measurements. Since the observations are incomplete, the MCRF incorporates an extra layer determining the certainty of the measurements. The proposed MCRF approach was evaluated using simulated compressive MS data acquisitions, and is shown to enable fast acquisition of MS sensing data with reduced imaging hardware cost and complexity.

  7. False discovery rate control in magnetic resonance imaging studies via Markov random fields.

    PubMed

    Nguyen, Hien D; McLachlan, Geoffrey J; Cherbuin, Nicolas; Janke, Andrew L

    2014-08-01

    Magnetic resonance imaging (MRI) is widely used to study population effects of factors on brain morphometry. Inference from such studies often require the simultaneous testing of millions of statistical hypotheses. Such scale of inference is known to lead to large numbers of false positive results. Control of the false discovery rate (FDR) is commonly employed to mitigate against such outcomes. However, current methodologies in FDR control only account for the marginal significance of hypotheses, and are not able to explicitly account for spatial relationships, such as those between MRI voxels. In this article, we present novel methods that incorporate spatial dependencies into the process of controlling FDR through the use of Markov random fields. Our method is able to automatically estimate the relationships between spatially dependent hypotheses by means of maximum pseudo-likelihood estimation and the pseudo-likelihood information criterion. We show that our methods have desirable statistical properties with regards to FDR control and are able to outperform noncontexual methods in simulations of dependent hypothesis scenarios. Our method is applied to investigate the effects of aging on brain morphometry using data from the PATH study. Evidence of whole brain and component level effects that correspond to similar findings in the literature is found in our investigation.

  8. Segmentation of cone-beam CT using a hidden Markov random field with informative priors

    NASA Astrophysics Data System (ADS)

    Moores, M.; Hargrave, C.; Harden, F.; Mengersen, K.

    2014-03-01

    Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

  9. An efficient conditional random field approach for automatic and interactive neuron segmentation.

    PubMed

    Uzunbas, Mustafa Gokhan; Chen, Chao; Metaxas, Dimitris

    2016-01-01

    We present a new graphical-model-based method for automatic and interactive segmentation of neuron structures from electron microscopy (EM) images. For automated reconstruction, our learning based model selects a collection of nodes from a hierarchical merging tree as the proposed segmentation. More specifically, this is achieved by training a conditional random field (CRF) whose underlying graph is the watershed merging tree. The maximum a posteriori (MAP) prediction of the CRF is the output segmentation. Our results are comparable to the results of state-of-the-art methods. Furthermore, both the inference and the training are very efficient as the graph is tree-structured. The problem of neuron segmentation requires extremely high segmentation quality. Therefore, proofreading, namely, interactively correcting mistakes of the automatic method, is a necessary module in the pipeline. Based on our efficient tree-structured inference algorithm, we develop an interactive segmentation framework which only selects locations where the model is uncertain for a user to proofread. The uncertainty is measured by the marginals of the graphical model. Only giving a limited number of choices makes the user interaction very efficient. Based on user corrections, our framework modifies the merging tree and thus improves the segmentation globally. PMID:26210001

  10. Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks

    PubMed Central

    Wei, Qikang; Chen, Tao; Xu, Ruifeng; He, Yulan; Gui, Lin

    2016-01-01

    The recognition of disease and chemical named entities in scientific articles is a very important subtask in information extraction in the biomedical domain. Due to the diversity and complexity of disease names, the recognition of named entities of diseases is rather tougher than those of chemical names. Although there are some remarkable chemical named entity recognition systems available online such as ChemSpot and tmChem, the publicly available recognition systems of disease named entities are rare. This article presents a system for disease named entity recognition (DNER) and normalization. First, two separate DNER models are developed. One is based on conditional random fields model with a rule-based post-processing module. The other one is based on the bidirectional recurrent neural networks. Then the named entities recognized by each of the DNER model are fed into a support vector machine classifier for combining results. Finally, each recognized disease named entity is normalized to a medical subject heading disease name by using a vector space model based method. Experimental results show that using 1000 PubMed abstracts for training, our proposed system achieves an F1-measure of 0.8428 at the mention level and 0.7804 at the concept level, respectively, on the testing data of the chemical-disease relation task in BioCreative V. Database URL: http://219.223.252.210:8080/SS/cdr.html PMID:27777244

  11. Segmentation of anatomical branching structures based on texture features and conditional random field

    NASA Astrophysics Data System (ADS)

    Nuzhnaya, Tatyana; Bakic, Predrag; Kontos, Despina; Megalooikonomou, Vasileios; Ling, Haibin

    2012-02-01

    This work is a part of our ongoing study aimed at understanding a relation between the topology of anatomical branching structures with the underlying image texture. Morphological variability of the breast ductal network is associated with subsequent development of abnormalities in patients with nipple discharge such as papilloma, breast cancer and atypia. In this work, we investigate complex dependence among ductal components to perform segmentation, the first step for analyzing topology of ductal lobes. Our automated framework is based on incorporating a conditional random field with texture descriptors of skewness, coarseness, contrast, energy and fractal dimension. These features are selected to capture the architectural variability of the enhanced ducts by encoding spatial variations between pixel patches in galactographic image. The segmentation algorithm was applied to a dataset of 20 x-ray galactograms obtained at the Hospital of the University of Pennsylvania. We compared the performance of the proposed approach with fully and semi automated segmentation algorithms based on neural network classification, fuzzy-connectedness, vesselness filter and graph cuts. Global consistency error and confusion matrix analysis were used as accuracy measurements. For the proposed approach, the true positive rate was higher and the false negative rate was significantly lower compared to other fully automated methods. This indicates that segmentation based on CRF incorporated with texture descriptors has potential to efficiently support the analysis of complex topology of the ducts and aid in development of realistic breast anatomy phantoms.

  12. Variable selection for discriminant analysis with Markov random field priors for the analysis of microarray data

    PubMed Central

    Stingo, Francesco C.; Vannucci, Marina

    2011-01-01

    Motivation: Discriminant analysis is an effective tool for the classification of experimental units into groups. Here, we consider the typical problem of classifying subjects according to phenotypes via gene expression data and propose a method that incorporates variable selection into the inferential procedure, for the identification of the important biomarkers. To achieve this goal, we build upon a conjugate normal discriminant model, both linear and quadratic, and include a stochastic search variable selection procedure via an MCMC algorithm. Furthermore, we incorporate into the model prior information on the relationships among the genes as described by a gene–gene network. We use a Markov random field (MRF) prior to map the network connections among genes. Our prior model assumes that neighboring genes in the network are more likely to have a joint effect on the relevant biological processes. Results: We use simulated data to assess performances of our method. In particular, we compare the MRF prior to a situation where independent Bernoulli priors are chosen for the individual predictors. We also illustrate the method on benchmark datasets for gene expression. Our simulation studies show that employing the MRF prior improves on selection accuracy. In real data applications, in addition to identifying markers and improving prediction accuracy, we show how the integration of existing biological knowledge into the prior model results in an increased ability to identify genes with strong discriminatory power and also aids the interpretation of the results. Contact: marina@rice.edu PMID:21159623

  13. Subject-Adaptive Real-Time Sleep Stage Classification Based on Conditional Random Field

    PubMed Central

    Luo, Gang; Min, Wanli

    2007-01-01

    Sleep staging is the pattern recognition task of classifying sleep recordings into sleep stages. This task is one of the most important steps in sleep analysis. It is crucial for the diagnosis and treatment of various sleep disorders, and also relates closely to brain-machine interfaces. We report an automatic, online sleep stager using electroencephalogram (EEG) signal based on a recently-developed statistical pattern recognition method, conditional random field, and novel potential functions that have explicit physical meanings. Using sleep recordings from human subjects, we show that the average classification accuracy of our sleep stager almost approaches the theoretical limit and is about 8% higher than that of existing systems. Moreover, for a new subject snew with limited training data Dnew, we perform subject adaptation to improve classification accuracy. Our idea is to use the knowledge learned from old subjects to obtain from Dnew a regulated estimate of CRF’s parameters. Using sleep recordings from human subjects, we show that even without any Dnew, our sleep stager can achieve an average classification accuracy of 70% on snew. This accuracy increases with the size of Dnew and eventually becomes close to the theoretical limit. PMID:18693884

  14. Singular-potential random-matrix model arising in mean-field glassy systems.

    PubMed

    Akemann, Gernot; Villamaina, Dario; Vivo, Pierpaolo

    2014-06-01

    We consider an invariant random matrix ensemble where the standard Gaussian potential is distorted by an additional single pole of arbitrary fixed order. Potentials with first- and second-order poles have been considered previously and found applications in quantum chaos and number theory. Here we present an application to mean-field glassy systems. We derive and solve the loop equation in the planar limit for the corresponding class of potentials. We find that the resulting mean or macroscopic spectral density is generally supported on two disconnected intervals lying on the two sides of the repulsive pole, whose edge points can be completely determined imposing the additional constraint of traceless matrices on average. For an unbounded potential with an attractive pole, we also find a possible one-cut solution for certain values of the couplings, which is ruled out when the traceless condition is imposed. Motivated by the calculation of the distribution of the spin-glass susceptibility in the Sherrington-Kirkpatrick spin-glass model, we consider in detail a second-order pole for a zero-trace model and provide the most explicit solution in this case. In the limit of a vanishing pole, we recover the standard semicircle. Working in the planar limit, our results apply to matrices with orthogonal, unitary, and symplectic invariance. Numerical simulations and an independent analytical Coulomb fluid calculation for symmetric potentials provide an excellent confirmation of our results.

  15. Handwritten Chinese/Japanese text recognition using semi-Markov conditional random fields.

    PubMed

    Zhou, Xiang-Dong; Wang, Da-Han; Tian, Feng; Liu, Cheng-Lin; Nakagawa, Masaki

    2013-10-01

    This paper proposes a method for handwritten Chinese/Japanese text (character string) recognition based on semi-Markov conditional random fields (semi-CRFs). The high-order semi-CRF model is defined on a lattice containing all possible segmentation-recognition hypotheses of a string to elegantly fuse the scores of candidate character recognition and the compatibilities of geometric and linguistic contexts by representing them in the feature functions. Based on given models of character recognition and compatibilities, the fusion parameters are optimized by minimizing the negative log-likelihood loss with a margin term on a training string sample set. A forward-backward lattice pruning algorithm is proposed to reduce the computation in training when trigram language models are used, and beam search techniques are investigated to accelerate the decoding speed. We evaluate the performance of the proposed method on unconstrained online handwritten text lines of three databases. On the test sets of databases CASIA-OLHWDB (Chinese) and TUAT Kondate (Japanese), the character level correct rates are 95.20 and 95.44 percent, and the accurate rates are 94.54 and 94.55 percent, respectively. On the test set (online handwritten texts) of ICDAR 2011 Chinese handwriting recognition competition, the proposed method outperforms the best system in competition.

  16. Segmentation of 2D gel electrophoresis spots using a Markov random field

    NASA Astrophysics Data System (ADS)

    Hoeflich, Christopher S.; Corso, Jason J.

    2009-02-01

    We propose a statistical model-based approach for the segmentation of fragments of DNA as a first step in the automation of the primarily manual process of comparing two or more images resulting from the Restriction Landmark Genomic Scanning (RLGS) method. These 2D gel electrophoresis images are the product of the separation of DNA into fragments that appear as spots on X-ray films. The goal is to find instances where a spot appears in one image and not in another since a missing spot can be correlated with a region of DNA that has been affected by a disease such as cancer. The entire comparison process is typically done manually, which is tedious and very error prone. We pose the problem as the labeling of each image pixel as either a spot or non-spot and use a Markov Random Field (MRF) model and simulated annealing for inference. Neighboring spot labels are then connected to form spot regions. The MRF based model was tested on actual 2D gel electrophoresis images.

  17. Financial versus Health Motivation to Quit Smoking: A Randomized Field Study

    PubMed Central

    Sindelar, Jody L.; O’Malley, Stephanie S.

    2016-01-01

    Objective Smoking is the most preventable cause of death, thus justifying efforts to effectively motivate quitting. We compared the effectiveness of financial versus health messages to motivate smoking cessation. Low-income individuals disproportionately smoke and, given their greater income constraints, we hypothesized that making financial costs of smoking more salient would encourage more smokers to try quitting. Further, we predicted financial messages would be stronger in financial settings where pecuniary constraints are most salient. Methods We conducted a field study in low-income areas of New Haven, Connecticut using brochures with separate health vs. financial messages to motivate smoking cessation. Displays were rotated among community settings—check-cashing, health clinics, and grocery stores. We randomized brochure displays with gain-framed cessation messages across locations. Results Our predictions were confirmed. Financial messages attracted significantly more attention than health messages, especially in financial settings. Conclusions These findings suggest greater emphasis on the financial gains to quitting and use of financial settings to provide cessation messages may be more effective in motivating quitting. Importantly, use of financial settings could open new, non-medical venues for encouraging cessation. Encouraging quitting could improve health, enhance spending power of low-income smokers, and reduce health disparities in both health and purchasing power. PMID:24139975

  18. Beyond-mean-field corrections within the second random-phase approximation

    NASA Astrophysics Data System (ADS)

    Grasso, M.; Gambacurta, D.; Engel, J.

    2016-06-01

    A subtraction procedure, introduced to overcome double-counting problems in beyond-mean-field theories, is used in the second random-phase approximation (SRPA). Doublecounting problems arise in the energy-density functional framework in all cases where effective interactions tailored at leading order are used for higher-order calculations, such as those done in the SRPA model. It was recently shown that this subtraction procedure also guarantees that the stability condition related to the Thouless theorem is verified in extended RPA models. We discuss applications of the subtraction procedure, introduced within the SRPA model, to the nucleus 16O. The application of the subtraction procedure leads to: (i) stable results that are weakly cutoff dependent; (ii) a considerable upwards correction of the SRPA spectra (which were systematically shifted downwards by several MeV with respect to RPA spectra, in all previous calculations). With this important implementation of the model, many applications may be foreseen to analyze the genuine impact of 2 particle-2 hole configurations (without any cutoff dependences and anomalous shifts) on the excitation spectra of medium-mass and heavy nuclei.

  19. Unsupervised change detection based on improved Markov random field technique using multichannel synthetic aperture radar images

    NASA Astrophysics Data System (ADS)

    Salehi, Sara; Valadan Zoej, Mohammad Javad

    2014-01-01

    Change detection represents an important remote sensing tool in environmental monitoring and disaster management. In this respect, multichannel synthetic aperture radar (SAR) data offer great potential because of their insensitivity to atmospheric and sun-illumination conditions (over optical multispectral data) and the improved discrimination capability they may provide compared to single-channel SAR. The problem of detecting the changes caused by flooding is addressed by a contextual unsupervised technique based on a Markovian data fusion approach. However, the isotropic formulation of Markov random field (MRF) models causes oversmoothing of spatial boundaries in the final change maps. In order to reduce this drawback, an edge-preserving MRF model is proposed and formulated by using energy functions that combine the edge information extracted from the produced edge maps using competitive fuzzy rules and Canny technique, the information conveyed by each SAR channel, and the spatial contextual information. The proposed technique is experimentally validated with semisimulated data and real ASAR-ENVISAT images. Change detection results obtained by the improved MRF model exhibited a higher accuracy than its predecessors for both semisimulated (average 12%) and real (average 6%) data.

  20. Influence of memory in deterministic walks in random media: analytical calculation within a mean-field approximation.

    PubMed

    Terçariol, César Augusto Sangaletti; Martinez, Alexandre Souto

    2008-09-01

    Consider a random medium consisting of N points randomly distributed so that there is no correlation among the distances separating them. This is the random link model, which is the high dimensionality limit (mean-field approximation) for the Euclidean random point structure. In the random link model, at discrete time steps, a walker moves to the nearest point, which has not been visited in the last mu steps (memory), producing a deterministic partially self-avoiding walk (the tourist walk). We have analytically obtained the distribution of the number n of points explored by the walker with memory mu=2 , as well as the transient and period joint distribution. This result enables us to explain the abrupt change in the exploratory behavior between the cases mu=1 (memoryless walker, driven by extreme value statistics) and mu=2 (walker with memory, driven by combinatorial statistics). In the mu=1 case, the mean newly visited points in the thermodynamic limit (N1) is just n=e=2.72... while in the mu=2 case, the mean number n of visited points grows proportionally to N;{12} . Also, this result allows us to establish an equivalence between the random link model with mu=2 and random map (uncorrelated back and forth distances) with mu=0 and the abrupt change between the probabilities for null transient time and subsequent ones. PMID:18850997

  1. Reverse random amplified microsatellite polymorphism reveals enhanced polymorphisms in the 3' end of simple sequence repeats in the pepper genome.

    PubMed

    Min, Woong-Ki; Han, Jung-Heon; Kang, Won-Hee; Lee, Heung-Ryul; Kim, Byung-Dong

    2008-09-30

    Microsatellites or simple sequence repeats (SSR) are widely distributed in eukaryotic genomes and are informative genetic markers. Despite many advantages of SSR markers such as a high degree of allelic polymorphisms, co-dominant inheritance, multi-allelism, and genome-wide coverage in various plant species, they also have shortcomings such as low polymorphic rates between genetically close lines, especially in Capsicum annuum. We developed an alternative technique to SSR by normalizing and alternating anchored primers in random amplified microsatellite polymorphisms (RAMP). This technique, designated reverse random amplified microsatellite polymorphism (rRAMP), allows the detection of nucleotide variation in the 3' region flanking an SSR using normalized anchored and random primer combinations. The reproducibility and frequency of polymorphic loci in rRAMP was vigorously enhanced by translocation of the 5' anchor of repeat sequences to the 3' end position and selective use of moderate arbitrary primers. In our study, the PCR banding pattern of rRAMP was highly dependent on the frequency of repeat motifs and primer combinations with random primers. Linkage analysis showed that rRAMP markers were well scattered on an intra-specific pepper map. Based on these results, we suggest that this technique is useful for studying genetic diversity, molecular fingerprinting, and rapidly constructing molecular maps for diverse plant species. PMID:18483466

  2. Mindfulness Training and Reductions in Teacher Stress and Burnout: Results from Two Randomized, Waitlist-Control Field Trials

    ERIC Educational Resources Information Center

    Roeser, Robert W.; Schonert-Reichl, Kimberly A.; Jha, Amishi; Cullen, Margaret; Wallace, Linda; Wilensky, Rona; Oberle, Eva; Thomson, Kimberly; Taylor, Cynthia; Harrison, Jessica

    2013-01-01

    The effects of randomization to mindfulness training (MT) or to a waitlist-control condition on psychological and physiological indicators of teachers' occupational stress and burnout were examined in 2 field trials. The sample included 113 elementary and secondary school teachers (89% female) from Canada and the United States. Measures were…

  3. Apparent Ultra-High b-Value Diffusion-Weighted Image Reconstruction via Hidden Conditional Random Fields.

    PubMed

    Shafiee, Mohammad Javad; Haider, Shahid A; Wong, Alexander; Lui, Dorothy; Cameron, Andrew; Modhafar, Ameen; Fieguth, Paul; Haider, Masoom A

    2015-05-01

    A promising, recently explored, alternative to ultra-high b-value diffusion weighted imaging (UHB-DWI) is apparent ultra-high b-value diffusion-weighted image reconstruction (AUHB-DWR), where a computational model is used to assist in the reconstruction of apparent DW images at ultra-high b -values. Firstly, we present a novel approach to AUHB-DWR that aims to improve image quality. We formulate the reconstruction of an apparent DW image as a hidden conditional random field (HCRF) in which tissue model diffusion parameters act as hidden states in this random field. The second contribution of this paper is a new generation of fully connected conditional random fields, called the hidden stochastically fully connected conditional random fields (HSFCRF) that allows for efficient inference with significantly reduced computational complexity via stochastic clique structures. The proposed AUHB-DWR algorithms, HCRF and HSFCRF, are evaluated quantitatively in nine different patient cases using Fisher's criteria, probability of error, and coefficient of variation metrics to validate its effectiveness for the purpose of improving intensity delineation between expert identified suspected cancerous and healthy tissue within the prostate gland. The proposed methods are also examined using a prostate phantom, where the apparent ultra-high b-value DW images reconstructed using the tested AUHB-DWR methods are compared with real captured UHB-DWI. The results illustrate that the proposed AUHB-DWR methods has improved reconstruction quality and improved intensity delineation compared with existing AUHB-DWR approaches.

  4. Implementing Randomized Controlled Trial Studies in Afterschool Settings: The State of the Field. Afterschool Research Brief. Issue No. 1

    ERIC Educational Resources Information Center

    Vaden-Kiernan, Michael; Jones, Debra Hughes; Rudo, Zena

    2008-01-01

    SEDL is providing analytic and technical support to three large-scale randomized controlled trials assessing the efficacy of promising literacy curriculum in afterschool settings on student academic achievement. In the field of educational research, competition among research organizations and researchers can often impede collaborative efforts in…

  5. Assessment Data-Informed Guidance to Individualize Kindergarten Reading Instruction: Findings from a Cluster-Randomized Control Field Trial

    ERIC Educational Resources Information Center

    Al Otaiba, Stephanie; Connor, Carol M.; Folsom, Jessica S.; Greulich, Luana; Meadows, Jane; Li, Zhi

    2011-01-01

    The purpose of this cluster-randomized control field trial was to examine whether kindergarten teachers could learn to differentiate classroom reading instruction using Individualized Student Instruction for Kindergarten (ISI-K) and to test the efficacy of differentiation on reading outcomes. The study involved 14 schools, 23 ISI-K (n = 305…

  6. Quantum control of molecular handedness in a randomly oriented racemic mixture using three polarization components of electric fields

    NASA Astrophysics Data System (ADS)

    Hoki, Kunihito; González, Leticia; Fujimura, Yuichi

    2002-05-01

    A new laser control scenario is presented for obtaining substantial amounts of enantiomeric enrichment from a randomly oriented racemic mixture. This is carried out by using three polarization components of electric fields; one is used for orientation, the other two for controlling the chirality. The effectiveness is demonstrated by numerical simulations on the enantiomeric enrichment of the axial chiral H2POSH molecule.

  7. Effect of a quenched random field on a continuous symmetry breaking transition: Nematic to smectic-A transition in octyloxycyanobiphenyl-aerosil dispersions

    NASA Astrophysics Data System (ADS)

    Clegg, P. S.; Stock, C.; Birgeneau, R. J.; Garland, C. W.; Roshi, A.; Iannacchione, G. S.

    2003-02-01

    High-resolution x-ray diffraction and ac-calorimetric experiments have been carried out on the liquid-crystal octyloxycyanobiphenyl in which aerosil particles are dispersed. The measurements were made over a temperature range around the bulk nematic to smectic-A transition temperature. At this transition the liquid crystal breaks translational symmetry in a single direction. The silica particles, which hydrogen bond together to form a very low density gel, provide the quenched disorder. The random gel leads to observable broadening of the x-ray reflection from the smectic layers. The structure factor is well described by modeling the effect of the aerosils as a quenched random field. Dispersed aerosils are thought to pin both the direction of the translational ordering and the position of the layers. The latter appears to have the greatest effect on the x-ray line shape. We show that the aerosil surface area, as verified by small-angle scattering, equates to the variance of the random field. Calorimetric results reveal substantial change in the specific heat peak associated with the nematic to smectic-A transition. As the concentration of aerosil increases, the specific heat peak remains sharp yet decreases in magnitude and shifts in temperature in a nonmonotonic fashion. In this regime, the critical exponent α becomes progressively smaller. For the samples with the largest concentrations of aerosil particles the Cp(N-A) peak becomes highly smeared and shifts smoothly to lower temperatures.

  8. Random field theory to interpret the spatial variability of lacustrine soils

    NASA Astrophysics Data System (ADS)

    Russo, Savino; Vessia, Giovanna

    2015-04-01

    The lacustrine soils are quaternary soils, dated from Pleistocene to Holocene periods, generated in low-energy depositional environments and characterized by soil mixture of clays, sands and silts with alternations of finer and coarser grain size layers. They are often met at shallow depth filling several tens of meters of tectonic or erosive basins typically placed in internal Appenine areas. The lacustrine deposits are often locally interbedded by detritic soils resulting from the failure of surrounding reliefs. Their heterogeneous lithology is associated with high spatial variability of physical and mechanical properties both along horizontal and vertical directions. The deterministic approach is still commonly adopted to accomplish the mechanical characterization of these heterogeneous soils where undisturbed sampling is practically not feasible (if the incoherent fraction is prevalent) or not spatially representative (if the cohesive fraction prevails). The deterministic approach consists on performing in situ tests, like Standard Penetration Tests (SPT) or Cone Penetration Tests (CPT) and deriving design parameters through "expert judgment" interpretation of the measure profiles. These readings of tip and lateral resistances (Rp and RL respectively) are almost continuous but highly variable in soil classification according to Schmertmann (1978). Thus, neglecting the spatial variability cannot be the best strategy to estimated spatial representative values of physical and mechanical parameters of lacustrine soils to be used for engineering applications. Hereafter, a method to draw the spatial variability structure of the aforementioned measure profiles is presented. It is based on the theory of the Random Fields (Vanmarcke 1984) applied to vertical readings of Rp measures from mechanical CPTs. The proposed method relies on the application of the regression analysis, by which the spatial mean trend and fluctuations about this trend are derived. Moreover, the

  9. A hidden Markov random field model for genome-wide association studies.

    PubMed

    Li, Hongzhe; Wei, Zhi; Maris, John

    2010-01-01

    Genome-wide association studies (GWAS) are increasingly utilized for identifying novel susceptible genetic variants for complex traits, but there is little consensus on analysis methods for such data. Most commonly used methods include single single nucleotide polymorphism (SNP) analysis or haplotype analysis with Bonferroni correction for multiple comparisons. Since the SNPs in typical GWAS are often in linkage disequilibrium (LD), at least locally, Bonferroni correction of multiple comparisons often leads to conservative error control and therefore lower statistical power. In this paper, we propose a hidden Markov random field model (HMRF) for GWAS analysis based on a weighted LD graph built from the prior LD information among the SNPs and an efficient iterative conditional mode algorithm for estimating the model parameters. This model effectively utilizes the LD information in calculating the posterior probability that an SNP is associated with the disease. These posterior probabilities can then be used to define a false discovery controlling procedure in order to select the disease-associated SNPs. Simulation studies demonstrated the potential gain in power over single SNP analysis. The proposed method is especially effective in identifying SNPs with borderline significance at the single-marker level that nonetheless are in high LD with significant SNPs. In addition, by simultaneously considering the SNPs in LD, the proposed method can also help to reduce the number of false identifications of disease-associated SNPs. We demonstrate the application of the proposed HMRF model using data from a case-control GWAS of neuroblastoma and identify 1 new SNP that is potentially associated with neuroblastoma.

  10. Markov random field-based clustering applied to the segmentation of masses in digital mammograms.

    PubMed

    Suliga, M; Deklerck, R; Nyssen, E

    2008-09-01

    In this paper we propose a new pixel clustering model applied to the analysis of digital mammograms. The clustering represents here the first step in a more general method and aims at the creation of a concise data-set (clusters) for automatic detection and classification of masses, which are typically among the first symptoms analysed in early diagnosis of breast cancer. For the purpose of this work, a set of mammographic images has been employed, that are 12-bit gray level digital scans and as such, are inherently inhomogeneous and affected by the noise resulting from the film scanning. The image pixels are described only by their intensity (gray level), therefore, the available information is limited to one dimension. We propose a Markov random field (MRF)-based technique that is suitable for performing clustering in an environment which is described by poor or limited data. The proposed method is a statistical classification model, that labels the image pixels based on the description of their statistical and contextual information. Apart from evaluating the pixel statistics, that originate from the definition of the K-means clustering scheme, the model expands the analysis by the description of the spatial dependence between pixels and their labels (context), hence leading to the reduction of the inhomogeneity of the output. Moreover, we define a probabilistic description of the model, that is characterised by a remarkable simplicity, such that its realisation can be easily and efficiently implemented in any high- or low-level programming language, thus allowing it to be run on virtually any kind of platform. Finally, we evaluate the algorithm against the classical K-means clustering routine. We point out similarities between the two methods and, moreover, show the advantages and superiority of the MRF scheme.

  11. Enhancing Foster Parent Training with Parent-Child Interaction Therapy: Evidence from a Randomized Field Experiment

    PubMed Central

    Mersky, Joshua P.; Topitzes, James; Janczewski, Colleen E.; McNeil, Cheryl B.

    2015-01-01

    Objective Research indicates that foster parents often do not receive sufficient training and support to help them meet the demands of caring for foster children with emotional and behavioral disturbances. Parent-Child Interaction Therapy (PCIT) is a clinically efficacious intervention for child externalizing problems, and it also has been shown to mitigate parenting stress and enhance parenting attitudes and behaviors. However, PCIT is seldom available to foster families, and it rarely has been tested under intervention conditions that are generalizable to community-based child welfare service contexts. To address this gap, PCIT was adapted and implemented in a field experiment using 2 novel approaches—group-based training and telephone consultation—both of which have the potential to be integrated into usual care. Method This study analyzes 129 foster-parent-child dyads who were randomly assigned to 1 of 3 conditions: (a) waitlist control, (b) brief PCIT, and (c) extended PCIT. Self-report and observational data were gathered at multiple time points up to 14 weeks post baseline. Results Findings from mixed-model, repeated measures analyses indicated that the brief and extended PCIT interventions were associated with a significant decrease in self-reported parenting stress. Results from mixed-effects generalized linear models showed that the interventions also led to significant improvements in observed indicators of positive and negative parenting. The brief course of PCIT was as efficacious as the extended PCIT intervention. Conclusions The findings suggest that usual training and support services can be improved upon by introducing foster parents to experiential, interactive PCIT training. PMID:26977251

  12. SAR-based change detection using hypothesis testing and Markov random field modelling

    NASA Astrophysics Data System (ADS)

    Cao, W.; Martinis, S.

    2015-04-01

    The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step.

  13. A BAYESIAN HIERARCHICAL SPATIAL MODEL FOR DENTAL CARIES ASSESSMENT USING NON-GAUSSIAN MARKOV RANDOM FIELDS

    PubMed Central

    Jin, Ick Hoon; Yuan, Ying; Bandyopadhyay, Dipankar

    2016-01-01

    Research in dental caries generates data with two levels of hierarchy: that of a tooth overall and that of the different surfaces of the tooth. The outcomes often exhibit spatial referencing among neighboring teeth and surfaces, i.e., the disease status of a tooth or surface might be influenced by the status of a set of proximal teeth/surfaces. Assessments of dental caries (tooth decay) at the tooth level yield binary outcomes indicating the presence/absence of teeth, and trinary outcomes at the surface level indicating healthy, decayed, or filled surfaces. The presence of these mixed discrete responses complicates the data analysis under a unified framework. To mitigate complications, we develop a Bayesian two-level hierarchical model under suitable (spatial) Markov random field assumptions that accommodates the natural hierarchy within the mixed responses. At the first level, we utilize an autologistic model to accommodate the spatial dependence for the tooth-level binary outcomes. For the second level and conditioned on a tooth being non-missing, we utilize a Potts model to accommodate the spatial referencing for the surface-level trinary outcomes. The regression models at both levels were controlled for plausible covariates (risk factors) of caries, and remain connected through shared parameters. To tackle the computational challenges in our Bayesian estimation scheme caused due to the doubly-intractable normalizing constant, we employ a double Metropolis-Hastings sampler. We compare and contrast our model performances to the standard non-spatial (naive) model using a small simulation study, and illustrate via an application to a clinical dataset on dental caries. PMID:27807470

  14. Adaptive multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

    NASA Astrophysics Data System (ADS)

    Navarro, Cristóbal A.; Huang, Wei; Deng, Youjin

    2016-08-01

    This work presents an adaptive multi-GPU Exchange Monte Carlo approach for the simulation of the 3D Random Field Ising Model (RFIM). The design is based on a two-level parallelization. The first level, spin-level parallelism, maps the parallel computation as optimal 3D thread-blocks that simulate blocks of spins in shared memory with minimal halo surface, assuming a constant block volume. The second level, replica-level parallelism, uses multi-GPU computation to handle the simulation of an ensemble of replicas. CUDA's concurrent kernel execution feature is used in order to fill the occupancy of each GPU with many replicas, providing a performance boost that is more notorious at the smallest values of L. In addition to the two-level parallel design, the work proposes an adaptive multi-GPU approach that dynamically builds a proper temperature set free of exchange bottlenecks. The strategy is based on mid-point insertions at the temperature gaps where the exchange rate is most compromised. The extra work generated by the insertions is balanced across the GPUs independently of where the mid-point insertions were performed. Performance results show that spin-level performance is approximately two orders of magnitude faster than a single-core CPU version and one order of magnitude faster than a parallel multi-core CPU version running on 16-cores. Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99 % efficiency as long as the number of GPUs and L increase together. The combination of the adaptive approach with the parallel multi-GPU design has extended our possibilities of simulation to sizes of L = 32 , 64 for a workstation with two GPUs. Sizes beyond L = 64 can eventually be studied using larger multi-GPU systems.

  15. Improving Markov Random Field Based Super Resolution Mapping Through Fuzzy Parameter Integration

    NASA Astrophysics Data System (ADS)

    . Welikanna, D. R.; Tamura, M.; Tolpekin, V. A.; Susaki, J.; Maki, M.

    2012-07-01

    The objective of this study was to improve the Markov Random Field (MRF) based Super Resolution Mapping (SRM) technique to account for the vague land-cover interpretations (class mixture and the intermediate conditions) in an urban area. The algorithm has been improved to integrate the fuzzy mean and fuzzy covariance measurements, to a MRF based SRM scheme to optimize the classification results. The technique was tested on a WORLDVIEW-2 data set, acquired over a highway construction area, in Colombo, Sri Lanka. Based on the visual interpretation of the image, three major land-cover types of this area were identified for the study; those were vegetation, soil and exposed grass and impervious surface with low medium and high albedo. The membership values for each pixel were determined from training samples through Spectral Angle Mapper (SAM) technique. The compulsory fuzzy mean and the covariance measurements were derived using these membership grades, and subsequently was applied in MRF based SRM technique. The primary reference data was generated using Maximum Likelihood Classification (MLC) performed on the same data which was resampled to 1m resolution. The scale factor was set to be (S) = 2, to generate SRM of 1m resolution. The smoothening parameter (λ) which balances the prior and likelihood energy terms were tested in the range from 0.3 to 0.9. SRM were generated using fuzzy MRF and the conventional MRF models respectively. Results suggest that the fuzzy integrated model has improved the results with an overall accuracy of 85.60% and kappa value of 0.78 between the optimal results and the reference data, while in the conventional case it was 77.81% of overall accuracy with kappa being 0.65. Among the two MRF models, fuzzy parameter integrated model shows the highest agreement with class fractions from the reference image with a smallest average _MAE (MAE, Mean Absolute Error) of 0.03.

  16. An automatic water body area monitoring algorithm for satellite images based on Markov Random Fields

    NASA Astrophysics Data System (ADS)

    Elmi, Omid; Tourian, Mohammad J.; Sneeuw, Nico

    2016-04-01

    Our knowledge about spatial and temporal variation of hydrological parameters are surprisingly poor, because most of it is based on in situ stations and the number of stations have reduced dramatically during the past decades. On the other hand, remote sensing techniques have proven their ability to measure different parameters of Earth phenomena. Optical and SAR satellite imagery provide the opportunity to monitor the spatial change in coastline, which can serve as a way to determine the water extent repeatedly in an appropriate time interval. An appropriate classification technique to separate water and land is the backbone of each automatic water body monitoring. Due to changes in the water level, river and lake extent, atmosphere, sunlight radiation and onboard calibration of the satellite over time, most of the pixel-based classification techniques fail to determine accurate water masks. Beyond pixel intensity, spatial correlation between neighboring pixels is another source of information that should be used to decide the label of pixels. Water bodies have strong spatial correlation in satellite images. Therefore including contextual information as additional constraint into the procedure of water body monitoring improves the accuracy of the derived water masks significantly. In this study, we present an automatic algorithm for water body area monitoring based on maximum a posteriori (MAP) estimation of Markov Random Fields (MRF). First we collect all available images from selected case studies during the monitoring period. Then for each image separately we apply a k-means clustering to derive a primary water mask. After that we develop a MRF using pixel values and the primary water mask for each image. Then among the different realizations of the field we select the one that maximizes the posterior estimation. We solve this optimization problem using graph cut techniques. A graph with two terminals is constructed, after which the best labelling structure for

  17. Irrational use of antimalarial drugs in rural areas of eastern Pakistan: a random field study

    PubMed Central

    2012-01-01

    Background Prescription of antimalarial drugs in the absence of malarial disease is a common practice in countries where malaria is endemic. However, unwarranted use of such drugs can cause side effects in some people and is a financial drain on local economies. In this study, we surveyed the prevalence of malaria parasites in humans, and the prevalence of the malaria transmitting mosquito vectors in the study area. We also investigated the use of antimalarial drugs in the local people. We focused on randomly selected rural areas of eastern Pakistan where no malaria cases had been reported since May 2004. Methods Mass blood surveys, active case detection, passive case detection, and vector density surveys were carried out in selected areas of Sargodha district from September 2008 to August 2009. Data pertaining to the quantities and types of antimalarial drugs used in these areas were collected from health centers, pharmacies, and the district CDC program of the Health Department of the Government of the Punjab. Results Seven hundred and forty four blood samples were examined, resulting in a Blood Examination Rate (BER) of 3.18; microscopic analysis of blood smears showed that none of the samples were positive for malaria parasites. Investigation of the mosquito vector density in 43 living rooms (bedrooms or rooms used for sleeping), 23 stores, and 32 animal sheds, revealed no vectors capable of transmitting malaria in these locations. In contrast, the density of Culex mosquitoes was high. Substantial consumption of a variety of antimalarial tablets, syrups, capsules and injections costing around 1000 US$, was documented for the region. Conclusion Use of antimalarial drugs in the absence of malarial infection or the vectors that transmit the disease was common in the study area. Continuous use of such drugs, not only in Pakistan, but in other parts of the world, may lead to drug-induced side effects amongst users. Better training of health care professionals is

  18. A multiresolution random field model for estimating fossil-fuel CO2 emissions

    NASA Astrophysics Data System (ADS)

    Ray, J.; Yadav, V.; Michalak, A. M.; Lee, J.; Lefantzi, S.; VanBloemenWaanders, B.

    2013-12-01

    We present a multiscale random field model (MsRF) that can be used for representing fossil-fuel CO2 (ffCO2) emissions. It is low-dimensional and is meant to be used in atmospheric inversions. The MsRF is constructed using wavelets. In this work, we will demonstrate a synthetic-data inversion aimed at estimating ffCO2 emissions, with 1o x 1o resolution, in the lower 48 states of the US. Measurements from 35 towers will be used. The measurements are constructed using the Vulcan inventory. The MsRF consists of a subset of Haar wavelets that can be defined in a rectangle bounding the US. By subjecting the Vulcan database to wavelet-transforms with a wide choice, the Haar wavelet was found to offer the most compressible representation. The MsRF was constructed by subjecting an image of lights at night to Haar transforms and retaining those with large weights. The lights-at-night image is correlated with ffCO2 inversions and have been used to downscale national ffCO2 aggregates when constructing spatially resolved ffCO2 emission inventories. The MsRF is then used to solve the linear inverse problem that underlies ffCO2 emission estimation. The number of parameters in the MsRF is far too large to be constrained by the measurements and thus we enforce sparsity to regularize the inverse problem. Further, we show that the transport model is only somewhat incoherent with respect to the chosen Haar bases, indicating that sparsification will be insufficient and further regularization using a prior emission model is required. This model is obtained by scaling up the nightlights to match EDGAR emissions. Finally, we present the results of the inversion and show that the resulting inversion mechanism can extract information from the observation to update and improve upon the predictive accuracy of prior model. The density of measurements dominates the accuracy of the inversion. We find that sparsification plays an important role since it removes about 50% of the wavelets in the Ms

  19. A modified hybrid uncertain analysis method for dynamic response field of the LSOAAC with random and interval parameters

    NASA Astrophysics Data System (ADS)

    Zi, Bin; Zhou, Bin

    2016-07-01

    For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .

  20. Dynamic full field optical coherence tomography: subcellular metabolic contrast revealed in tissues by interferometric signals temporal analysis

    PubMed Central

    Apelian, Clement; Harms, Fabrice; Thouvenin, Olivier; Boccara, A. Claude

    2016-01-01

    We developed a new endogenous approach to reveal subcellular metabolic contrast in fresh ex vivo tissues taking advantage of the time dependence of the full field optical coherence tomography interferometric signals. This method reveals signals linked with local activity of the endogenous scattering elements which can reveal cells where other OCT-based techniques fail or need exogenous contrast agents. We benefit from the micrometric transverse resolution of full field OCT to image intracellular features. We used this time dependence to identify different dynamics at the millisecond scale on a wide range of organs in normal or pathological conditions. PMID:27446672

  1. Differences between MyoD DNA binding and activation site requirements revealed by functional random sequence selection.

    PubMed Central

    Huang, J; Blackwell, T K; Kedes, L; Weintraub, H

    1996-01-01

    A method has been developed for selecting functional enhancer/promoter sites from random DNA sequences in higher eukaryotic cells. Of sequences that were thus selected for transcriptional activation by the muscle-specific basic helix-loop-helix protein MyoD, only a subset are similar to the preferred in vitro binding consensus, and in the same promoter context an optimal in vitro binding site was inactive. Other sequences with full transcriptional activity instead exhibit sequence preferences that, remarkably, are generally either identical or very similar to those found in naturally occurring muscle-specific promoters. This first systematic examination of the relation between DNA binding and transcriptional activation by basic helix-loop-helix proteins indicates that binding per se is necessary but not sufficient for transcriptional activation by MyoD and implies a requirement for other DNA sequence-dependent interactions or conformations at its binding site. PMID:8668207

  2. Sudden death and rebirth of entanglement for different dimensional systems driven by a classical random external field

    NASA Astrophysics Data System (ADS)

    Metwally, N.; Eleuch, H.; Obada, A.-S.

    2016-10-01

    The entangled behavior of different dimensional systems driven by classical external random field is investigated. The amount of the survival entanglement between the components of each system is quantified. There are different behaviors of entanglement that come into view decay, sudden death, sudden birth and long-lived entanglement. The maximum entangled states which can be generated from any of theses suggested systems are much fragile than the partially entangled ones. The systems of larger dimensions are more robust than those of smaller dimensions systems, where the entanglement decay smoothly, gradually and may vanish for a very short time. For the class of $2\\times 3$ dimensional system, the one parameter family is found to be more robust than the two parameters family. Although the entanglement of driven $ 2 \\times 3$ dimensional system is very sensitive to the classical external random field, one can use them to generate a long-lived entanglement.

  3. Thermal vacancies in random alloys in the single-site mean-field approximation

    NASA Astrophysics Data System (ADS)

    Ruban, A. V.

    2016-04-01

    A formalism for the vacancy formation energies in random alloys within the single-site mean-filed approximation, where vacancy-vacancy interaction is neglected, is outlined. It is shown that the alloy configurational entropy can substantially reduce the concentration of vacancies at high temperatures. The energetics of vacancies in random Cu0.5Ni0.5 alloy is considered as a numerical example illustrating the developed formalism. It is shown that the effective formation energy increases with temperature, however, in this particular system it is still below the mean value of the vacancy formation energy, which would correspond to the vacancy formation energy in a homogeneous model of a random alloy, such as given by the coherent potential approximation.

  4. Crustal Velocity Field from InSAR and GPS reveals Internal Deformation of Western Tibet

    NASA Astrophysics Data System (ADS)

    Wang, H.; Wright, T. J.

    2010-12-01

    a compromise between solution roughness and data misfit. The resultant velocity field satisfies the InSAR and GPS data with an rms misfit of ~1 mm/yr. It reveals a series of focused strain zones within the plateau and low slip rate on the Karakoram fault. Although focused strain zones are predicted by block models, those that we observe appear to occur away from the major faults, in the interior of the plateau. At least one is associated with a possible postseismic transient (1996 Mw6.8). This is incompatible with block models, but consistent with continuum models of continental deformation modified by the short-term influence of the earthquake cycle. Finally, we augmented the GPS velocity field using existing InSAR rate maps for the whole Tibetan plateau. It shows that a continental-scale velocity fields can be constructed without complete InSAR coverage using our method.

  5. Scaling and super-universality in the coarsening dynamics of the 3D random field Ising model

    NASA Astrophysics Data System (ADS)

    Aron, Camille; Chamon, Claudio; Cugliandolo, Leticia F.; Picco, Marco

    2008-05-01

    We study the coarsening dynamics of the three-dimensional random field Ising model using Monte Carlo numerical simulations. We test the dynamic scaling and super-scaling properties of global and local two-time observables. We treat in parallel the three-dimensional Edward-Anderson spin glass and we recall results on Lennard-Jones mixtures and colloidal suspensions to highlight the common and different out of equilibrium properties of these glassy systems.

  6. A Monte Carlo study of the Blume-Capel thin film in the presence of a random crystal field

    NASA Astrophysics Data System (ADS)

    Boughrara, M.; Kerouad, M.; Zaim, A.

    2016-07-01

    A Monte Carlo simulation with heat bath algorithm is used to study the effect of random crystal field and surface exchange interactions on the critical behavior and the magnetic properties of a spin-1 Ising ferromagnetic thin film having the simple cubic symmetry. The phase diagram exhibits a rich variety of behaviors such as the double reentrant phenomena and the existence of tricritical points. Thermal magnetization behavior and phase diagrams have been discussed in detail.

  7. A randomized double-blind prospective study of the efficacy of pulsed electromagnetic fields for interbody lumbar fusions

    SciTech Connect

    Mooney, V. )

    1990-07-01

    A randomized double-blind prospective study of pulsed electromagnetic fields for lumbar interbody fusions was performed on 195 subjects. There were 98 subjects in the active group and 97 subjects in the placebo group. A brace containing equipment to induce an electromagnetic field was applied to patients undergoing interbody fusion in the active group, and a sham brace was used in the control group. In the active group there was a 92% success rate, while the control group had a 65% success rate (P greater than 0.005). The effectiveness of bone graft stimulation with the device is thus established.

  8. Mean-field theory of strongly nonlinear random composites: Strong power-law nonlinearity and scaling behavior

    NASA Astrophysics Data System (ADS)

    Wan, W. M. V.; Lee, H. C.; Hui, P. M.; Yu, K. W.

    1996-08-01

    The effective response of random media consisting of two different kinds of strongly nonlinear materials with strong power-law nonlinearity is studied. Each component satisfies current density and electric-field relation of the form J=χ\\|E\\|βE. A simple self-consistent mean-field theory, which leads to a simple way in determining the average local electric field in each constituent, is introduced. Each component is assumed to have a conductivity depending on the averaged local electric field. The averaged local electric field is then determined self-consistently. Numerical simulations of the system are carried out on random nonlinear resistor networks. Theoretical results are compared with simulation data, and excellent agreements are found. Results are also compared with the Hashin-Shtrikman lower bound proposed by Ponte Castaneda et al. [Phys. Rev. B 46, 4387 (1992)]. It is found that the present theory, at small contrasts of χ between the two components, gives a result identical to that of Ponte Castaneda et al. up to second order of the contrast. The crossover and scaling behavior of the effective response near the percolation threshold as suggested by the present theory are discussed and demonstrated.

  9. Genetic diversity and phylogenetic relationship among Tunisian cactus species (Opuntia) as revealed by random amplified microsatellite polymorphism markers.

    PubMed

    Bendhifi Zarroug, M; Baraket, G; Zourgui, L; Souid, S; Salhi Hannachi, A

    2015-02-13

    Opuntia ficus indica is one of the most economically important species in the Cactaceae family. Increased interest in this crop stems from its potential contribution to agricultural diversification, application in the exploitation of marginal lands, and utility as additional income sources for farmers. In Tunisia, O. ficus indica has been affected by drastic genetic erosion resulting from biotic and abiotic stresses. Thus, it is imperative to identify and preserve this germplasm. In this study, we focused on the use of random amplified microsatellite polymorphisms to assess genetic diversity among 25 representatives of Tunisian Opuntia species maintained in the collection of the National Institute of Agronomic Research of Tunisia. Seventy-two DNA markers were screened to discriminate accessions using 16 successful primer combinations. The high percentage of polymorphic band (100%), the resolving power value (5.68), the polymorphic information content (0.94), and the marker index (7.2) demonstrated the efficiency of the primers tested. Therefore, appropriate cluster analysis used in this study illustrated a divergence among the cultivars studied and exhibited continuous variation that occurred independently of geographic origin. O. ficus indica accessions did not cluster separately from the other cactus pear species, indicating that their current taxonomical classifications are not well aligned with their genetic variability or locality of origin.

  10. Genetic diversity and phylogenetic relationship among Tunisian cactus species (Opuntia) as revealed by random amplified microsatellite polymorphism markers.

    PubMed

    Bendhifi Zarroug, M; Baraket, G; Zourgui, L; Souid, S; Salhi Hannachi, A

    2015-01-01

    Opuntia ficus indica is one of the most economically important species in the Cactaceae family. Increased interest in this crop stems from its potential contribution to agricultural diversification, application in the exploitation of marginal lands, and utility as additional income sources for farmers. In Tunisia, O. ficus indica has been affected by drastic genetic erosion resulting from biotic and abiotic stresses. Thus, it is imperative to identify and preserve this germplasm. In this study, we focused on the use of random amplified microsatellite polymorphisms to assess genetic diversity among 25 representatives of Tunisian Opuntia species maintained in the collection of the National Institute of Agronomic Research of Tunisia. Seventy-two DNA markers were screened to discriminate accessions using 16 successful primer combinations. The high percentage of polymorphic band (100%), the resolving power value (5.68), the polymorphic information content (0.94), and the marker index (7.2) demonstrated the efficiency of the primers tested. Therefore, appropriate cluster analysis used in this study illustrated a divergence among the cultivars studied and exhibited continuous variation that occurred independently of geographic origin. O. ficus indica accessions did not cluster separately from the other cactus pear species, indicating that their current taxonomical classifications are not well aligned with their genetic variability or locality of origin. PMID:25730081

  11. The National Randomized Field Trial of Success for All: Second-Year Outcomes

    ERIC Educational Resources Information Center

    Borman, Geoffrey D.; Slavin, Robert E.; Alan Cheung; Chamberlain, Anne; Madden, Nancy; Chambers, Bette

    2005-01-01

    This paper reports the second-year outcomes of the national randomized evaluation of Success for All, a comprehensive reading reform model. Analyses focus on literacy outcomes for a two-year longitudinal student sample and a combined longitudinal and in-mover student sample, both of which were nested within 38 schools. Using a cluster…

  12. Professional Development Effects on Teacher Efficacy: Results of Randomized Field Trial

    ERIC Educational Resources Information Center

    Ross, John; Bruce, Catherine

    2007-01-01

    We designed a professional development (PD) program to increase the teacher efficacy of mathematics teachers. We randomly assigned 106 Grade 6 teachers in 1 school district to treatment and control conditions in a delayed-treatment design. The PD explicitly addressed 4 sources of teacher-efficacy information identified in social-cognition theory…

  13. Explaining Feast or Famine in Randomized Field Trials: Medical Science and Criminology Compared.

    ERIC Educational Resources Information Center

    Shepherd, Jonathan P.

    2003-01-01

    Discusses the contrast between the frequency of randomized clinical trials in the health sciences and the relative famine of such studies in criminology. Attributes this difference to the contexts in which research is done and the difference in the status of situational research in the two disciplines. (SLD)

  14. Angular spectral plane-wave expansion of nonstationary random fields in stochastic mode-stirred reverberation processes.

    PubMed

    Arnaut, Luk R

    2010-04-01

    We derive an integral expression for the plane-wave expansion of the time-varying (nonstationary) random field inside a mode-stirred reverberation chamber. It is shown that this expansion is a so-called oscillatory process, whose kernel can be expressed explicitly in closed form. The effect of nonstationarity is a modulation of the spectral density of the field on a time scale that is a function of the cavity relaxation time. It is also shown how the contribution by a nonzero initial value of the field can be incorporated into the expansion. The results are extended to a special class of second-order processes, relevant to the reception of a mode-stirred reverberation field by a device under test with a first-order (relaxation-type) frequency response.

  15. Angular spectral plane-wave expansion of nonstationary random fields in stochastic mode-stirred reverberation processes

    NASA Astrophysics Data System (ADS)

    Arnaut, Luk R.

    2010-04-01

    We derive an integral expression for the plane-wave expansion of the time-varying (nonstationary) random field inside a mode-stirred reverberation chamber. It is shown that this expansion is a so-called oscillatory process, whose kernel can be expressed explicitly in closed form. The effect of nonstationarity is a modulation of the spectral density of the field on a time scale that is a function of the cavity relaxation time. It is also shown how the contribution by a nonzero initial value of the field can be incorporated into the expansion. The results are extended to a special class of second-order processes, relevant to the reception of a mode-stirred reverberation field by a device under test with a first-order (relaxation-type) frequency response.

  16. A Markov Random Field Framework for Protein Side-Chain Resonance Assignment

    NASA Astrophysics Data System (ADS)

    Zeng, Jianyang; Zhou, Pei; Donald, Bruce Randall

    Nuclear magnetic resonance (NMR) spectroscopy plays a critical role in structural genomics, and serves as a primary tool for determining protein structures, dynamics and interactions in physiologically-relevant solution conditions. The current speed of protein structure determination via NMR is limited by the lengthy time required in resonance assignment, which maps spectral peaks to specific atoms and residues in the primary sequence. Although numerous algorithms have been developed to address the backbone resonance assignment problem [68,2,10,37,14,64,1,31,60], little work has been done to automate side-chain resonance assignment [43, 48, 5]. Most previous attempts in assigning side-chain resonances depend on a set of NMR experiments that record through-bond interactions with side-chain protons for each residue. Unfortunately, these NMR experiments have low sensitivity and limited performance on large proteins, which makes it difficult to obtain enough side-chain resonance assignments. On the other hand, it is essential to obtain almost all of the side-chain resonance assignments as a prerequisite for high-resolution structure determination. To overcome this deficiency, we present a novel side-chain resonance assignment algorithm based on alternative NMR experiments measuring through-space interactions between protons in the protein, which also provide crucial distance restraints and are normally required in high-resolution structure determination. We cast the side-chain resonance assignment problem into a Markov Random Field (MRF) framework, and extend and apply combinatorial protein design algorithms to compute the optimal solution that best interprets the NMR data. Our MRF framework captures the contact map information of the protein derived from NMR spectra, and exploits the structural information available from the backbone conformations determined by orientational restraints and a set of discretized side-chain conformations (i.e., rotamers). A Hausdorff

  17. Diffusion and stochastic island generation in the magnetic field line random walk

    SciTech Connect

    Vlad, M.; Spineanu, F.

    2014-08-10

    The cross-field diffusion of field lines in stochastic magnetic fields described by the 2D+slab model is studied using a semi-analytic statistical approach, the decorrelation trajectory method. We show that field line trapping and the associated stochastic magnetic islands strongly influence the diffusion coefficients, leading to dependences on the parameters that are different from the quasilinear and Bohm regimes. A strong amplification of the diffusion is produced by a small slab field in the presence of trapping. The diffusion regimes are determined and the corresponding physical processes are identified.

  18. Revealing molecular structure and dynamics through high harmonic generation driven by mid-IR fields

    NASA Astrophysics Data System (ADS)

    Marangos, Jonathan

    2010-03-01

    High harmonic generation (HHG) from molecules has recently been shown to be a promising tool for measuring instantaneous molecular structure, sub-femtosecond domain structural rearrangements in molecules and even hole dynamics initiated by laser field ionisation. To fully exploit this promise it is essential that we can; (1) systematically decouple structural and dynamic effects so that both may simultaneously be determined in the measurement, (2) can extend the method of molecular HHG imaging to a wide range of molecules. Here we demonstrate important steps towards both these objectives. Up until now HHG imaging measurements have been restricted to drive laser wavelengths close to 800nm, due to the availability of CPA titanium sapphire lasers, which dictates the use of relatively high intensities (> 2.5 x 10^14 Wcm-2) if a harmonic spectrum spanning to ˜70 eV is to be observed which is required for extracting structural data from most small molecules. By using a mid-IR laser (at 1300 nm) we show that with an intensity ˜ 1 x 10^14 W cm-2 we can observe a wide molecular harmonic spectrum spanning to ˜ 70 eV even in molecules where ionization saturation would clamp the cut-off to much lower energies if an 800nm field were used. Thus we have been able to observe evidence for two-centre interference in two new molecules, N2O and C2H2 for the first time. Moreover we can use the ability to observe a broad harmonic spectrum over a large range of intensities to reveal the subtle interplay between structural and dynamic effects in CO2 and so provide a new window into hole dynamics. [4pt] In collaboration with R. Torres, Blackett Laboratory, Imperial College London; O. Smirnova, Max-Born-Institute, Berlin; T. Siegel and L. Brugnera, Blackett Laboratory, Imperial College London; I. Procino and Jonathan G. Underwood, Department of Physics and Astronomy, University College London; C. Altucci and R. Velotta, CNSIM and Dipartimento di Scienze Fisiche, Universita di Napoli

  19. Partial spatial coherence and partial polarization in random evanescent fields on lossless interfaces.

    PubMed

    Norrman, Andreas; Setälä, Tero; Friberg, Ari T

    2011-03-01

    We consider partial spatial coherence and partial polarization of purely evanescent optical fields generated in total internal reflection at an interface of two dielectric (lossless) media. Making use of the electromagnetic degree of coherence, we show that, in such fields, the coherence length can be notably shorter than the light's vacuum wavelength, especially at a high-index-contrast interface. Physical explanation for this behavior, analogous to the generation of incoherent light in a multimode laser, is provided. We also analyze the degree of polarization by using a recent three-dimensional formulation and show that the field may be partially polarized at a subwavelength distance from the surface even though it is fully polarized farther away. The degree of polarization can assume values unattainable by beamlike fields, indicating that electromagnetic evanescent waves generally are genuine three-dimensional fields. The results can find applications in near-field optics and nanophotonics.

  20. Theory of magnetic field line random walk in noisy reduced magnetohydrodynamic turbulence

    SciTech Connect

    Ruffolo, D.; Matthaeus, W. H.

    2013-01-15

    When a magnetic field consists of a mean part and fluctuations, the stochastic wandering of its field lines is often treated as a diffusive process. Under suitable conditions, a stable value is found for the mean square transverse displacement per unit parallel displacement relative to the mean field. Here, we compute the associated field line diffusion coefficient for a highly anisotropic 'noisy' reduced magnetohydrodynamic model of the magnetic field, which is useful in describing low frequency turbulence in the presence of a strong applied DC mean magnetic field, as may be found, for example, in the solar corona, or in certain laboratory devices. Our approach is nonperturbative, based on Corrsin's independence hypothesis, and makes use of recent advances in understanding factors that control decorrelation over a range of parameters described by the Kubo number. Both Bohm and quasilinear regimes are identified.

  1. The rate of separation of magnetic lines of force in a random magnetic field.

    NASA Technical Reports Server (NTRS)

    Jokipii, J. R.

    1973-01-01

    The mixing of magnetic lines of force, as represented by their rate of separation, as a function of distance along the magnetic field, is considered with emphasis on neighboring lines of force. This effect is particularly important in understanding the transport of charged particles perpendicular to the average magnetic field. The calculation is carried out in the approximation that the separation changes by an amount small compared with the correlation scale normal to the field, in a distance along the field of a few correlation scales. It is found that the rate of separation is very sensitive to the precise form of the power spectrum. Application to the interplanetary and interstellar magnetic fields is discussed, and it is shown that in some cases field lines, much closer together than the correlation scale, separate at a rate which is effectively as rapid as if they were many correlation lengths apart.

  2. Properties of Optical Near-Field Excitation Transfers in Randomly Distributed Spherical Quantum Dots

    NASA Astrophysics Data System (ADS)

    Nomura, Wataru; Yatsui, Takashi; Ohtsu, Motoichi

    In this chapter, optical near-field interactions and energy transfer between spherical quantum dots are reviewed. The energy transfer was confirmed by time-resolved spectroscopy in both CdSe and ZnO quantum dots. Furthermore, structural dependency of quantum dots was theoretically and experimentally analyzed with respect to the basic properties of optical signal transfer using optical near-field interactions. The destination selectivity in the optical near-field signal transfer system was also evaluated.

  3. Electron random walk and collisional crossover in a gas in presence of electromagnetic waves and magnetostatic fields

    SciTech Connect

    Bhattacharjee, Sudeep; Paul, Samit; Dey, Indranuj

    2013-04-15

    This paper deals with random walk of electrons and collisional crossover in a gas evolving toward a plasma, in presence of electromagnetic (EM) waves and magnetostatic (B) fields, a fundamental subject of importance in areas requiring generation and confinement of wave assisted plasmas. In presence of EM waves and B fields, the number of collisions N suffered by an electron with neutral gas atoms while diffusing out of the volume during the walk is significantly modified when compared to the conventional field free square law diffusion; N=1.5({Lambda}/{lambda}){sup 2}, where {Lambda} is the characteristic diffusion length and {lambda} is the mean free path. There is a distinct crossover and a time scale associated with the transition from the elastic to inelastic collisions dominated regime, which can accurately predict the breakdown time ({tau}{sub c}) and the threshold electric field (E{sub BD}) for plasma initiation. The essential features of cyclotron resonance manifested as a sharp drop in {tau}{sub c}, lowering of E{sub BD} and enhanced electron energy gain is well reproduced in the constrained random walk.

  4. Effects of Gentle Human Touch and Field Massage on Urine Cortisol Level in Premature Infants: A Randomized, Controlled Clinical Trial

    PubMed Central

    Asadollahi, Malihe; Jabraeili, Mahnaz; Mahallei, Majid; Asgari Jafarabadi, Mohammad; Ebrahimi, Sakine

    2016-01-01

    Introduction: Hospitalization in neonatal intensive care unit may leads to many stresses for premature infants. Since premature infants cannot properly process stressors, identifying interventions that reduce the stress level for them is seems necessary. The aim of present study was to compare the effects of Field massage and Gentle Human Touch (GHT) techniques on the urine level of cortisol, as an indicator of stress in preterm infants. Methods: This randomized, controlled clinical trial was carried out in Al-Zahra hospital, Tabriz. A total of 84 premature infants were randomly assigned into three groups. First groups were touched by their mothers three times a day (15 minutes in each session) for 5 days by GHT technique. The second group was received 15 minutes Field massage with sunflower oil three times a day by their mothers for 5 days. The third group received routine care. In all groups, 24-hours urine samples were collected in the first and sixth day after the intervention and analyzed for cortisol level. Data were analyzed by SPSS software. Results: There were significant differences between mean of changes in cortisol level between GHT and control groups and Field massage and control groups (0.026). Conclusion: Although the massage with Field technique resulted in a significant reduction in blood cortisol level, but the GHT technique have also a similar effect. So, both methods are recommended for decreasing of stress in preterm infants. PMID:27752484

  5. Magnetic-field-induced ferroelectric polarization reversal in magnetoelectric composites revealed by piezoresponse force microscopy

    NASA Astrophysics Data System (ADS)

    Miao, Hongchen; Zhou, Xilong; Dong, Shuxiang; Luo, Haosu; Li, Faxin

    2014-07-01

    Controlling electric polarization (or magnetization) in multiferroic materials with external magnetic fields (or electric fields) is very important for fundamental physics and spintronic devices. Although there has been some progress on magnetic-field-induced polarization reversal in single-phase multiferroics, such behavior has so far never been realized in composites. Here we show that it is possible to reverse ferroelectric polarization using magnetic fields in a bilayer Terfenol-D/PMN-33%PT composite. We realized this by ferroelectric domain imaging using piezoresponse force microscopy (PFM) under applied magnetic field loading. The internal electric field caused by the magnetoelectric (ME) effect in the PMN-PT crystal is considered as the driving force for the 180° polarization switching, and its existence is verified by switching spectroscopy PFM testing under a series of external magnetic fields. A quantitative method is further suggested to estimate the local ME coefficient based on the switching spectroscopy PFM testing results.

  6. Magnetic-field-induced ferroelectric polarization reversal in magnetoelectric composites revealed by piezoresponse force microscopy.

    PubMed

    Miao, Hongchen; Zhou, Xilong; Dong, Shuxiang; Luo, Haosu; Li, Faxin

    2014-08-01

    Controlling electric polarization (or magnetization) in multiferroic materials with external magnetic fields (or electric fields) is very important for fundamental physics and spintronic devices. Although there has been some progress on magnetic-field-induced polarization reversal in single-phase multiferroics, such behavior has so far never been realized in composites. Here we show that it is possible to reverse ferroelectric polarization using magnetic fields in a bilayer Terfenol-D/PMN-33%PT composite. We realized this by ferroelectric domain imaging using piezoresponse force microscopy (PFM) under applied magnetic field loading. The internal electric field caused by the magnetoelectric (ME) effect in the PMN-PT crystal is considered as the driving force for the 180° polarization switching, and its existence is verified by switching spectroscopy PFM testing under a series of external magnetic fields. A quantitative method is further suggested to estimate the local ME coefficient based on the switching spectroscopy PFM testing results. PMID:24953042

  7. Towards phonon photonics: scattering-type near-field optical microscopy reveals phonon-enhanced near-field interaction.

    PubMed

    Hillenbrand, Rainer

    2004-08-01

    Diffraction limits the spatial resolution in classical microscopy or the dimensions of optical circuits to about half the illumination wavelength. Scanning near-field microscopy can overcome this limitation by exploiting the evanescent near fields existing close to any illuminated object. We use a scattering-type near-field optical microscope (s-SNOM) that uses the illuminated metal tip of an atomic force microscope (AFM) to act as scattering near-field probe. The presented images are direct evidence that the s-SNOM enables optical imaging at a spatial resolution on a 10nm scale, independent of the wavelength used (lambda=633 nm and 10 microm). Operating the microscope at specific mid-infrared frequencies we found a tip-induced phonon-polariton resonance on flat polar crystals such as SiC and Si3N4. Being a spectral fingerprint of any polar material such phonon-enhanced near-field interaction has enormous applicability in nondestructive, material-specific infrared microscopy at nanoscale resolution. The potential of s-SNOM to study eigenfields of surface polaritons in nanostructures opens the door to the development of phonon photonics-a proposed infrared nanotechnology that uses localized or propagating surface phonon polaritons for probing, manipulating and guiding infrared light in nanoscale devices, analogous to plasmon photonics.

  8. Motion of a quantum particle in a random-flux field

    NASA Astrophysics Data System (ADS)

    Łusakowski, Andrzej; Turski, Łukasz A.

    1993-08-01

    We consider a charged spinless quantum particle moving on a two-dimensional square lattice. Each plaquette of the lattice is penetrated by a random magnetic flux with values homogeneously distributed in the interval (0,2π) (in units of the elementary quantum flux h/e). The fluxes in different plaquettes are statistically independent. Using the path-integral method, within the saddle-point approximation, we evaluated the averaged density of states. Our results are compared with the recent numerical-simulation predictions of Pryor and Zee.

  9. Subthreshold-swing-adjustable tunneling-field-effect-transistor-based random-access memory for nonvolatile operation

    NASA Astrophysics Data System (ADS)

    Huh, In; Cheon, Woo Young; Choi, Woo Young

    2016-04-01

    A subthreshold-swing-adjustable tunneling-field-effect-transistor-based random-access memory (SAT RAM) has been proposed and fabricated for low-power nonvolatile memory applications. The proposed SAT RAM cell demonstrates adjustable subthreshold swing (SS) depending on stored information: small SS in the erase state ("1" state) and large SS in the program state ("0" state). Thus, SAT RAM cells can achieve low read voltage (Vread) with a large memory window in addition to the effective suppression of ambipolar behavior. These unique features of the SAT RAM are originated from the locally stored charge, which modulates the tunneling barrier width (Wtun) of the source-to-channel tunneling junction.

  10. The role of magnetic fields in starburst galaxies as revealed by OH megamasers

    SciTech Connect

    McBride, James; Quataert, Eliot; Heiles, Carl; Bauermeister, Amber E-mail: eliot@astro.berkeley.edu

    2014-01-10

    We present estimates of magnetic field strengths in the interstellar media of starburst galaxies derived from measurements of Zeeman splitting associated with OH megamasers. The results for eight galaxies with Zeeman detections suggest that the magnetic energy density in the interstellar medium of starburst galaxies is comparable to their hydrostatic gas pressure, as in the Milky Way. We discuss the significant uncertainties in this conclusion, and possible measurements that could reduce these uncertainties. We also compare the Zeeman splitting derived magnetic field estimates to magnetic field strengths estimated using synchrotron fluxes and assuming that the magnetic field and cosmic rays have comparable energy densities, known as the 'minimum energy' argument. We find that the minimum energy argument systematically underestimates magnetic fields in starburst galaxies, and that the conditions that would be required to produce agreement between the minimum energy estimate and the Zeeman derived estimate of interstellar medium magnetic fields are implausible. The conclusion that magnetic fields in starburst galaxies exceed the minimum energy magnetic fields is consistent with starburst galaxies adhering to the linearity of the far-infrared-radio correlation.

  11. Asteroseismology can reveal strong internal magnetic fields in red giant stars.

    PubMed

    Fuller, Jim; Cantiello, Matteo; Stello, Dennis; Garcia, Rafael A; Bildsten, Lars

    2015-10-23

    Internal stellar magnetic fields are inaccessible to direct observations, and little is known about their amplitude, geometry, and evolution. We demonstrate that strong magnetic fields in the cores of red giant stars can be identified with asteroseismology. The fields can manifest themselves via depressed dipole stellar oscillation modes, arising from a magnetic greenhouse effect that scatters and traps oscillation-mode energy within the core of the star. The Kepler satellite has observed a few dozen red giants with depressed dipole modes, which we interpret as stars with strongly magnetized cores. We find that field strengths larger than ~10(5) gauss may produce the observed depression, and in one case we infer a minimum core field strength of ≈10(7) gauss. PMID:26494754

  12. Asteroseismology can reveal strong internal magnetic fields in red giant stars.

    PubMed

    Fuller, Jim; Cantiello, Matteo; Stello, Dennis; Garcia, Rafael A; Bildsten, Lars

    2015-10-23

    Internal stellar magnetic fields are inaccessible to direct observations, and little is known about their amplitude, geometry, and evolution. We demonstrate that strong magnetic fields in the cores of red giant stars can be identified with asteroseismology. The fields can manifest themselves via depressed dipole stellar oscillation modes, arising from a magnetic greenhouse effect that scatters and traps oscillation-mode energy within the core of the star. The Kepler satellite has observed a few dozen red giants with depressed dipole modes, which we interpret as stars with strongly magnetized cores. We find that field strengths larger than ~10(5) gauss may produce the observed depression, and in one case we infer a minimum core field strength of ≈10(7) gauss.

  13. Revisiting the Stark Broadening by fluctuating electric fields using the Continuous Time Random Walk Theory

    NASA Astrophysics Data System (ADS)

    Capes, H.; Christova, M.; Boland, D.; Catoire, F.; Godbert-Mouret, L.; Koubiti, M.; Mekkaoui, A.; Rosato, J.; Marandet, Y.; Stamm, R.

    2010-10-01

    Stark broadening of atomic lines in plasmas is calculated by modelling the plasma stochastic electric field using the CTRW approach [1,2]. This allows retaining non Markovian terms in the Schrödinger equation averaged over the electric field fluctuations. As an application we consider a special case of a non separable CTRW process, the so called Kangaroo process [3]. An analytic expression for the line profile is presented for arbitrary waiting time distribution functions. A preliminary application to the hydrogen Lyman α line is discussed.

  14. The random field model of the spatial distribution of heavy vehicle loads on long-span bridges

    NASA Astrophysics Data System (ADS)

    Chen, Zhicheng; Bao, Yuequan; Li, Hui

    2016-04-01

    A stochastic model based on Markov random field is proposed to model the spatial distribution of vehicle loads on longspan bridges. The bridge deck is divided into a finite set of discrete grid cells, each cell has two states according to whether the cell is occupied by the heavy vehicle load or not, then a four-neighbor lattice-structured undirected graphical model with each node corresponding to a cell state variable is proposed to model the location distribution of heavy vehicle loads on the bridge deck. The node potential is defined to quantitatively describe the randomness of node state, and the edge potential is defined to quantitatively describe the correlation of the connected node pair. The junction tree algorithm is employed to obtain the systematic solutions of inference problems of the graphical model. A marked random variable is assigned to each node to represent the amplitude of the total weight of vehicle applied on the corresponding cell of the bridge deck. The rationality of the model is validated by a Monte Carlo simulation of a learned model based on monitored data of a cable-stayed bridge.

  15. Theory and implementation of a very high throughput true random number generator in field programmable gate array

    NASA Astrophysics Data System (ADS)

    Wang, Yonggang; Hui, Cong; Liu, Chong; Xu, Chao

    2016-04-01

    The contribution of this paper is proposing a new entropy extraction mechanism based on sampling phase jitter in ring oscillators to make a high throughput true random number generator in a field programmable gate array (FPGA) practical. Starting from experimental observation and analysis of the entropy source in FPGA, a multi-phase sampling method is exploited to harvest the clock jitter with a maximum entropy and fast sampling speed. This parametrized design is implemented in a Xilinx Artix-7 FPGA, where the carry chains in the FPGA are explored to realize the precise phase shifting. The generator circuit is simple and resource-saving, so that multiple generation channels can run in parallel to scale the output throughput for specific applications. The prototype integrates 64 circuit units in the FPGA to provide a total output throughput of 7.68 Gbps, which meets the requirement of current high-speed quantum key distribution systems. The randomness evaluation, as well as its robustness to ambient temperature, confirms that the new method in a purely digital fashion can provide high-speed high-quality random bit sequences for a variety of embedded applications.

  16. Theory and implementation of a very high throughput true random number generator in field programmable gate array.

    PubMed

    Wang, Yonggang; Hui, Cong; Liu, Chong; Xu, Chao

    2016-04-01

    The contribution of this paper is proposing a new entropy extraction mechanism based on sampling phase jitter in ring oscillators to make a high throughput true random number generator in a field programmable gate array (FPGA) practical. Starting from experimental observation and analysis of the entropy source in FPGA, a multi-phase sampling method is exploited to harvest the clock jitter with a maximum entropy and fast sampling speed. This parametrized design is implemented in a Xilinx Artix-7 FPGA, where the carry chains in the FPGA are explored to realize the precise phase shifting. The generator circuit is simple and resource-saving, so that multiple generation channels can run in parallel to scale the output throughput for specific applications. The prototype integrates 64 circuit units in the FPGA to provide a total output throughput of 7.68 Gbps, which meets the requirement of current high-speed quantum key distribution systems. The randomness evaluation, as well as its robustness to ambient temperature, confirms that the new method in a purely digital fashion can provide high-speed high-quality random bit sequences for a variety of embedded applications.

  17. Theory and implementation of a very high throughput true random number generator in field programmable gate array.

    PubMed

    Wang, Yonggang; Hui, Cong; Liu, Chong; Xu, Chao

    2016-04-01

    The contribution of this paper is proposing a new entropy extraction mechanism based on sampling phase jitter in ring oscillators to make a high throughput true random number generator in a field programmable gate array (FPGA) practical. Starting from experimental observation and analysis of the entropy source in FPGA, a multi-phase sampling method is exploited to harvest the clock jitter with a maximum entropy and fast sampling speed. This parametrized design is implemented in a Xilinx Artix-7 FPGA, where the carry chains in the FPGA are explored to realize the precise phase shifting. The generator circuit is simple and resource-saving, so that multiple generation channels can run in parallel to scale the output throughput for specific applications. The prototype integrates 64 circuit units in the FPGA to provide a total output throughput of 7.68 Gbps, which meets the requirement of current high-speed quantum key distribution systems. The randomness evaluation, as well as its robustness to ambient temperature, confirms that the new method in a purely digital fashion can provide high-speed high-quality random bit sequences for a variety of embedded applications. PMID:27131692

  18. Magnetoelectric assisted 180° magnetization switching for electric field addressable writing in magnetoresistive random-access memory.

    PubMed

    Wang, Zhiguang; Zhang, Yue; Wang, Yaojin; Li, Yanxi; Luo, Haosu; Li, Jiefang; Viehland, Dwight

    2014-08-26

    Magnetization-based memories, e.g., hard drive and magnetoresistive random-access memory (MRAM), use bistable magnetic domains in patterned nanomagnets for information recording. Electric field (E) tunable magnetic anisotropy can lower the energy barrier between two distinct magnetic states, promising reduced power consumption and increased recording density. However, integration of magnetoelectric heterostructure into MRAM is a highly challenging task owing to the particular architecture requirements of each component. Here, we show an epitaxial growth of self-assembled CoFe2O4 nanostripes with bistable in-plane magnetizations on Pb(Mg,Nb)O3-PbTiO3 (PMN-PT) substrates, where the magnetic switching can be triggered by E-induced elastic strain effect. An unprecedented magnetic coercive field change of up to 600 Oe was observed with increasing E. A near 180° magnetization rotation can be activated by E in the vicinity of the magnetic coercive field. These findings might help to solve the 1/2-selection problem in traditional MRAM by providing reduced magnetic coercive field in E field selected memory cells. PMID:25093903

  19. THE RADIATIVE TRANSFER OF SYNCHROTRON RADIATION THROUGH A COMPRESSED RANDOM MAGNETIC FIELD

    SciTech Connect

    Cawthorne, T. V.; Hughes, P. A.

    2013-07-01

    This paper examines the radiative transfer of synchrotron radiation in the presence of a magnetic field configuration resulting from the compression of a highly disordered magnetic field. It is shown that, provided Faraday rotation and circular polarization can be neglected, the radiative transfer equations for synchrotron radiation separate for this configuration, and the intensities and polarization values for sources that are uniform on large scales can be found straightforwardly in the case where opacity is significant. Although the emission and absorption coefficients must, in general, be obtained numerically, the process is much simpler than a full numerical solution to the transfer equations. Some illustrative results are given and an interesting effect, whereby the polarization increases while the magnetic field distribution becomes less strongly confined to the plane of compression, is discussed. The results are of importance for the interpretation of polarization near the edges of lobes in radio galaxies and of bright features in the parsec-scale jets of active galactic nuclei, where such magnetic field configurations are believed to exist.

  20. Ultrasonic propagation: a technique to reveal field induced structures in magnetic nanofluids.

    PubMed

    Parekh, Kinnari; Patel, Jaykumar; Upadhyay, R V

    2015-07-01

    The paper reports the study of magnetic field induced structures in magnetic nanofluid investigated through ultrasonic wave propagation. Modified Tarapov's theory is used to study variation in velocity anisotropy with magnetic field. The types of field induced structures depend upon the chemical structure of the carrier in which magnetic nanoparticles are dispersed. Our study indicates formation of fractals and chain respectively, in transformer oil and kerosene based fluid. This difference is explained on the basis of particle-particle interaction and particle-medium interaction. PMID:25791205

  1. Description of and users manual for TUBA: A computer code for generating two-dimensional random fields via the turning bands method

    SciTech Connect

    Zimmerman, D.A.; Wilson, J.L.

    1992-01-01

    TUBA is a computer code for the generation of synthetic two-dimensional random fields via the Turning Bands Method. It is primarily used to generate synthetic permeability fields for hydrologic and petroleum engineering applications, but it has applications wherever synthetic random fields are employed. This is version 2.0 of TUBA, a completely redesigned and rewritten code. It generates stationary or non-stationary, isotropic and anisotropic, and point or areal average random fields. Five functional covariance models are available in the code. These are Gaussian, Bessel, Telis, and Generalized Covariance models. The user can supply other forms. The random fields can be generated onto a gridded system (e.g., at the nodes of a point centered finite difference model, or the blocks of a block centered model), or at arbitrary locations in space (e.g., at the Gauss points of a finite element grid). TUBA can be used to generate the field values in local areas at much greater resolution than the original simulated field. The fields can be generated with a normal or a lognormal distribution. The size of the simulation is limited only by the virtual memory capabilities of the computer on which it is run. Random fields with over a million nodes have been generated with TUBA on a 386PC running Xenix. The code has been run on 286 and 386 PC's running DOS, on Sun 3's and 4's using Unix, and on Dec VAX's running VMS.

  2. Description of and users manual for TUBA: A computer code for generating two-dimensional random fields via the turning bands method

    SciTech Connect

    Zimmerman, D.A.; Wilson, J.L.

    1992-01-01

    TUBA is a computer code for the generation of synthetic two-dimensional random fields via the Turning Bands Method. It is primarily used to generate synthetic permeability fields for hydrologic and petroleum engineering applications, but it has applications wherever synthetic random fields are employed. This is version 2.0 of TUBA, a completely redesigned and rewritten code. It generates stationary or non-stationary, isotropic and anisotropic, and point or areal average random fields. Five functional covariance models are available in the code. These are Gaussian, Bessel, Telis, and Generalized Covariance models. The user can supply other forms. The random fields can be generated onto a gridded system (e.g., at the nodes of a point centered finite difference model, or the blocks of a block centered model), or at arbitrary locations in space (e.g., at the Gauss points of a finite element grid). TUBA can be used to generate the field values in local areas at much greater resolution than the original simulated field. The fields can be generated with a normal or a lognormal distribution. The size of the simulation is limited only by the virtual memory capabilities of the computer on which it is run. Random fields with over a million nodes have been generated with TUBA on a 386PC running Xenix. The code has been run on 286 and 386 PC`s running DOS, on Sun 3`s and 4`s using Unix, and on Dec VAX`s running VMS.

  3. Spectro-Polarimetric Imaging Reveals Helical Magnetic Fields in Solar Prominence Feet

    NASA Astrophysics Data System (ADS)

    Martínez González, M. J.; Manso Sainz, R.; Asensio Ramos, A.; Beck, C.; de la Cruz Rodríguez, J.; Díaz, A. J.

    2015-03-01

    Solar prominences are clouds of cool plasma levitating above the solar surface and insulated from the million-degree corona by magnetic fields. They form in regions of complex magnetic topology, characterized by non-potential fields, which can evolve abruptly, disintegrating the prominence and ejecting magnetized material into the heliosphere. However, their physics is not yet fully understood because mapping such complex magnetic configurations and their evolution is extremely challenging, and must often be guessed by proxy from photometric observations. Using state-of-the-art spectro-polarimetric data, we reconstruct the structure of the magnetic field in a prominence. We find that prominence feet harbor helical magnetic fields connecting the prominence to the solar surface below.

  4. MAGNETIC FIELD LINE RANDOM WALK FOR DISTURBED FLUX SURFACES: TRAPPING EFFECTS AND MULTIPLE ROUTES TO BOHM DIFFUSION

    SciTech Connect

    Ghilea, M. C.; Ruffolo, D.; Sonsrettee, W.; Seripienlert, A.; Chuychai, P.; Matthaeus, W. H. E-mail: scdjr@mahidol.ac.th E-mail: achara.seri@gmail.com E-mail: yswhm@bartol.udel.edu

    2011-11-01

    The magnetic field line random walk (FLRW) is important for the transport of energetic particles in many astrophysical situations. While all authors agree on the quasilinear diffusion of field lines for fluctuations that mainly vary parallel to a large-scale field, for the opposite case of fluctuations that mainly vary in the perpendicular directions, there has been an apparent conflict between concepts of Bohm diffusion and percolation/trapping effects. Here computer simulation and non-perturbative analytic techniques are used to re-examine the FLRW in magnetic turbulence with slab and two-dimensional (2D) components, in which 2D flux surfaces are disturbed by the slab fluctuations. Previous non-perturbative theories for D{sub perpendicular}, based on Corrsin's hypothesis, have identified a slab contribution with quasilinear behavior and a 2D contribution due to Bohm diffusion with diffusive decorrelation (DD), combined in a quadratic formula. Here we present analytic theories for other routes to Bohm diffusion, with random ballistic decorrelation (RBD) either due to the 2D component itself (for a weak slab contribution) or the total fluctuation field (for a strong slab contribution), combined in a direct sum with the slab contribution. Computer simulations confirm the applicability of RBD routes for weak or strong slab contributions, while the DD route applies for a moderate slab contribution. For a very low slab contribution, interesting trapping effects are found, including a depressed diffusion coefficient and subdiffusive behavior. Thus quasilinear, Bohm, and trapping behaviors are all found in the same system, together with an overall viewpoint to explain these behaviors.

  5. Atomic electric fields revealed by a quantum mechanical approach to electron picodiffraction

    PubMed Central

    Müller, Knut; Krause, Florian F.; Béché, Armand; Schowalter, Marco; Galioit, Vincent; Löffler, Stefan; Verbeeck, Johan; Zweck, Josef; Schattschneider, Peter; Rosenauer, Andreas

    2014-01-01

    By focusing electrons on probes with a diameter of 50 pm, aberration-corrected scanning transmission electron microscopy (STEM) is currently crossing the border to probing subatomic details. A major challenge is the measurement of atomic electric fields using differential phase contrast (DPC) microscopy, traditionally exploiting the concept of a field-induced shift of diffraction patterns. Here we present a simplified quantum theoretical interpretation of DPC. This enables us to calculate the momentum transferred to the STEM probe from diffracted intensities recorded on a pixel array instead of conventional segmented bright-field detectors. The methodical development yielding atomic electric field, charge and electron density is performed using simulations for binary GaN as an ideal model system. We then present a detailed experimental study of SrTiO3 yielding atomic electric fields, validated by comprehensive simulations. With this interpretation and upgraded instrumentation, STEM is capable of quantifying atomic electric fields and high-contrast imaging of light atoms. PMID:25501385

  6. NEAR-INFRARED-IMAGING POLARIMETRY TOWARD SERPENS SOUTH: REVEALING THE IMPORTANCE OF THE MAGNETIC FIELD

    SciTech Connect

    Sugitani, K.; Nakamura, F.; Tamura, M.; Kandori, R.; Watanabe, M.; Nishiyama, S.; Nagata, T.; Nagayama, T.; Sato, S.; Gutermuth, R. A.; Wilson, G. W.; Kawabe, R.

    2011-06-10

    The Serpens South embedded cluster, which is located in the constricted part of a long, filamentary, infrared dark cloud, is believed to be in a very early stage of cluster formation. We present results of near-infrared (JHKs) polarization observations of the filamentary cloud. Our polarization measurements of near-infrared point sources indicate a well-ordered global magnetic field that is perpendicular to the main filament, implying that the magnetic field is likely to have controlled the formation of the main filament. On the other hand, the sub-filaments, which converge on the central part of the cluster, tend to run along the magnetic field. The global magnetic field appears to be curved in the southern part of the main filament. Such morphology is consistent with the idea that the global magnetic field is distorted by gravitational contraction along the main filament toward the northern part, which contains larger mass. Applying the Chandrasekhar-Fermi method, the magnetic field strength is roughly estimated to be a few x100 {mu}G, suggesting that the filamentary cloud is close to magnetically critical.

  7. Circular polarimetry reveals helical magnetic fields in the young stellar object HH 135-136.

    PubMed

    Chrysostomou, Antonio; Lucas, Philip W; Hough, James H

    2007-11-01

    Magnetic fields are believed to have a vital role in regulating and shaping the flow of material onto and away from protostars during their initial mass accretion phase. It is becoming increasingly accepted that bipolar outflows are generated and collimated as material is driven along magnetic field lines and centrifugally accelerated off a rotating accretion disk. However, the precise role of the magnetic field is poorly understood and evidence for its shape and structure has not been forthcoming. Here we report imaging circular polarimetry in the near-infrared and Monte Carlo modelling showing that the magnetic field along the bipolar outflow of the HH 135-136 young stellar object is helical. The field retains this shape for large distances along the outflow, so the field structure can also provide the necessary magnetic pressure for collimation of the outflow. This result lends further weight to the hypothesis--central to any theory of star formation--that the outflow is an important instrument for the removal of high-angular-momentum material from the accretion disk, thereby allowing the central protostar to increase its mass.

  8. Bayesian prestack seismic inversion with a self-adaptive Huber-Markov random-field edge protection scheme

    NASA Astrophysics Data System (ADS)

    Tian, Yu-Kun; Zhou, Hui; Chen, Han-Ming; Zou, Ya-Ming; Guan, Shou-Jun

    2013-12-01

    Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., the Tikhonov regularization are usually applied. The Tikhonov method can maintain a global smooth solution, but cause a fuzzy structure edge. In this paper we use Huber-Markov random-field edge protection method in the procedure of inverting three parameters, P-velocity, S-velocity and density. The method can avoid blurring the structure edge and resist noise. For the parameter to be inverted, the Huber-Markov random-field constructs a neighborhood system, which further acts as the vertical and lateral constraints. We use a quadratic Huber edge penalty function within the layer to suppress noise and a linear one on the edges to avoid a fuzzy result. The effectiveness of our method is proved by inverting the synthetic data without and with noises. The relationship between the adopted constraints and the inversion results is analyzed as well.

  9. Space-time models based on random fields with local interactions

    NASA Astrophysics Data System (ADS)

    Hristopulos, Dionissios T.; Tsantili, Ivi C.

    2016-08-01

    The analysis of space-time data from complex, real-life phenomena requires the use of flexible and physically motivated covariance functions. In most cases, it is not possible to explicitly solve the equations of motion for the fields or the respective covariance functions. In the statistical literature, covariance functions are often based on mathematical constructions. In this paper, we propose deriving space-time covariance functions by solving “effective equations of motion”, which can be used as statistical representations of systems with diffusive behavior. In particular, we propose to formulate space-time covariance functions based on an equilibrium effective Hamiltonian using the linear response theory. The effective space-time dynamics is then generated by a stochastic perturbation around the equilibrium point of the classical field Hamiltonian leading to an associated Langevin equation. We employ a Hamiltonian which extends the classical Gaussian field theory by including a curvature term and leads to a diffusive Langevin equation. Finally, we derive new forms of space-time covariance functions.

  10. Explaining feast or famine in randomized field trials. Medical science and criminology compared.

    PubMed

    Shepherd, Jonathan P

    2003-06-01

    A feast of randomized controlled trials (RCTs) in medical science and comparative famine in criminology can be explained in terms of cultural and structural factors. Of central importance is the context in which the evaluation of interventions is done and the difference in status of situational research in the two disciplines. Evaluation of medical interventions has traditionally been led by practitioner (clinical) academics. This is not the case in criminal justice, where theory has had higher status than intervention research. Medical science has advanced in, or closely associated with, university teaching hospitals, but links between criminology and criminal justice services are far more tenuous. The late development of situational crime prevention seems extraordinary from a medical perspective, as does the absence of university police schools in the United Kingdom and elsewhere. These structural and cultural factors explain concentration of expectation, resource, and RCT productivity in medical science. The Campbell Collaboration and the Academy of Experimental Criminology are forces which are reducing this polarization of feast and famine in RCTs. But unless scientific criminology is embedded in university schools which are responsible for the education and training of law, probation, and police practitioners, convergence in terms of RCTs and implementation of findings in practice seems unlikely.

  11. Stochastic simulation for the propagation of high-frequency acoustic waves through a random velocity field

    NASA Astrophysics Data System (ADS)

    Lu, B.; Darmon, M.; Leymarie, N.; Chatillon, S.; Potel, C.

    2012-05-01

    In-service inspection of Sodium-Cooled Fast Reactors (SFR) requires the development of non-destructive techniques adapted to the harsh environment conditions and the examination complexity. From past experiences, ultrasonic techniques are considered as suitable candidates. The ultrasonic telemetry is a technique used to constantly insure the safe functioning of reactor inner components by determining their exact position: it consists in measuring the time of flight of the ultrasonic response obtained after propagation of a pulse emitted by a transducer and its interaction with the targets. While in-service the sodium flow creates turbulences that lead to temperature inhomogeneities, which translates into ultrasonic velocity inhomogeneities. These velocity variations could directly impact the accuracy of the target locating by introducing time of flight variations. A stochastic simulation model has been developed to calculate the propagation of ultrasonic waves in such an inhomogeneous medium. Using this approach, the travel time is randomly generated by a stochastic process whose inputs are the statistical moments of travel times known analytically. The stochastic model predicts beam deviations due to velocity inhomogeneities, which are similar to those provided by a determinist method, such as the ray method.

  12. Stochastic simulation for the propagation of high-frequency acoustic waves through a random velocity field

    SciTech Connect

    Lu, B.; Darmon, M.; Leymarie, N.; Chatillon, S.; Potel, C.

    2012-05-17

    In-service inspection of Sodium-Cooled Fast Reactors (SFR) requires the development of non-destructive techniques adapted to the harsh environment conditions and the examination complexity. From past experiences, ultrasonic techniques are considered as suitable candidates. The ultrasonic telemetry is a technique used to constantly insure the safe functioning of reactor inner components by determining their exact position: it consists in measuring the time of flight of the ultrasonic response obtained after propagation of a pulse emitted by a transducer and its interaction with the targets. While in-service the sodium flow creates turbulences that lead to temperature inhomogeneities, which translates into ultrasonic velocity inhomogeneities. These velocity variations could directly impact the accuracy of the target locating by introducing time of flight variations. A stochastic simulation model has been developed to calculate the propagation of ultrasonic waves in such an inhomogeneous medium. Using this approach, the travel time is randomly generated by a stochastic process whose inputs are the statistical moments of travel times known analytically. The stochastic model predicts beam deviations due to velocity inhomogeneities, which are similar to those provided by a determinist method, such as the ray method.

  13. UNNOTICED MAGNETIC FIELD OSCILLATIONS IN THE VERY QUIET SUN REVEALED BY SUNRISE/IMaX

    SciTech Connect

    Martinez Gonzalez, M. J.; Asensio Ramos, A.; Manso Sainz, R.; Khomenko, E.; MartInez Pillet, V.; Lopez Ariste, A.

    2011-04-01

    We present observational evidence for oscillations of magnetic flux density in the quiet areas of the Sun. The majority of magnetic fields on the solar surface have strengths of the order of or lower than the equipartition field (300-500 G). This results in a myriad of magnetic fields whose evolution is largely determined by the turbulent plasma motions. When granules evolve they squash the magnetic field lines together or pull them apart. Here, we report on the periodic deformation of the shapes of features in circular polarization observed at high resolution with SUNRISE. In particular, we note that the area of patches with a constant magnetic flux oscillates with time, which implies that the apparent magnetic field intensity oscillates in antiphase. The periods associated with this oscillatory pattern are compatible with the granular lifetime and change abruptly, which suggests that these oscillations might not correspond to characteristic oscillatory modes of magnetic structures, but to the forcing by granular motions. In one particular case, we find three patches around the same granule oscillating in phase, which means that the spatial coherence of these oscillations can reach 1600 km. Interestingly, the same kind of oscillatory phenomenon is also found in the upper photosphere.

  14. Unnoticed Magnetic Field Oscillations in the Very Quiet Sun Revealed by SUNRISE/IMaX

    NASA Astrophysics Data System (ADS)

    Martínez González, M. J.; Asensio Ramos, A.; Manso Sainz, R.; Khomenko, E.; Martínez Pillet, V.; Solanki, S. K.; López Ariste, A.; Schmidt, W.; Barthol, P.; Gandorfer, A.

    2011-04-01

    We present observational evidence for oscillations of magnetic flux density in the quiet areas of the Sun. The majority of magnetic fields on the solar surface have strengths of the order of or lower than the equipartition field (300-500 G). This results in a myriad of magnetic fields whose evolution is largely determined by the turbulent plasma motions. When granules evolve they squash the magnetic field lines together or pull them apart. Here, we report on the periodic deformation of the shapes of features in circular polarization observed at high resolution with SUNRISE. In particular, we note that the area of patches with a constant magnetic flux oscillates with time, which implies that the apparent magnetic field intensity oscillates in antiphase. The periods associated with this oscillatory pattern are compatible with the granular lifetime and change abruptly, which suggests that these oscillations might not correspond to characteristic oscillatory modes of magnetic structures, but to the forcing by granular motions. In one particular case, we find three patches around the same granule oscillating in phase, which means that the spatial coherence of these oscillations can reach 1600 km. Interestingly, the same kind of oscillatory phenomenon is also found in the upper photosphere.

  15. A Markov random field approach for topology-preserving registration: application to object-based tomographic image interpolation.

    PubMed

    Cordero-Grande, Lucilio; Vegas-Sánchez-Ferrero, Gonzalo; Casaseca-de-la-Higuera, Pablo; Alberola-López, Carlos

    2012-04-01

    This paper proposes a topology-preserving multiresolution elastic registration method based on a discrete Markov random field of deformations and a block-matching procedure. The method is applied to the object-based interpolation of tomographic slices. For that purpose, the fidelity of a given deformation to the data is established by a block-matching strategy based on intensity- and gradient-related features, the smoothness of the transformation is favored by an appropriate prior on the field, and the deformation is guaranteed to maintain the topology by imposing some hard constraints on the local configurations of the field. The resulting deformation is defined as the maximum a posteriori configuration. Additionally, the relative influence of the fidelity and smoothness terms is weighted by the unsupervised estimation of the field parameters. In order to obtain an unbiased interpolation result, the registration is performed both in the forward and backward directions, and the resulting transformations are combined by using the local information content of the deformation. The method is applied to magnetic resonance and computed tomography acquisitions of the brain and the torso. Quantitative comparisons offer an overall improvement in performance with respect to related works in the literature. Additionally, the application of the interpolation method to cardiac magnetic resonance images has shown that the removal of any of the main components of the algorithm results in a decrease in performance which has proven to be statistically significant.

  16. Random crystal field effect on the kinetic spin-3/2 Blume-Capel model under a time-dependent oscillating field

    NASA Astrophysics Data System (ADS)

    El Hachimi, A. G.; Dakir, O.; Sidi Ahmed, S.; Zaari, H.; El Yadari, M.; Benyoussef, A.; El Kenz, A.

    2016-09-01

    The effect of random crystal-field on the stationary states of the kinetic spin-3/2 Blume-Capel model is investigated within the framework of the mean-field approach. The Glauber-type stochastic dynamics is used to describe the time evolution of the system which is subject to a time-dependent oscillating external magnetic field. In addition to the well-known phase transitions and the appearance of the partly ferromagnetic phase characterized by the magnetization m = 1 in equilibrium case, a new dynamical regions between the ferromagnetic phases F1/2, F1 and F3/2 are found where F3/2 +F 1 / 2 ,F3/2 +F1, F1 +F1/2 phases coexist for a weak value of the reduced magnetic field (h). Whereas for higher value of h both solutions ordered F and disordered P phases coexist. Hence we present six types topologies of phase diagrams which exhibit dynamical first-order, second-order transition lines, dynamical tricritical and isolated critical end points. Furthermore, the dynamical thermal behavior magnetizations, susceptibilities and phase space trajectories are given and discussed.

  17. Spectral shifts and switches in random fields upon interaction with negative-phase materials

    SciTech Connect

    Tong Zhisong; Korotkova, Olga

    2010-07-15

    Spectral shifts in stochastic beam-like fields on interaction with layers of positive- and negative-phase materials are examined on the basis of the ABCD-matrix approach and generalized Huygens-Fresnel principle. It is found that boundaries between such materials may cause spectral switches. Effect of absorption of negative-phase materials on the beam spectrum is discussed. Our results may find applications in connection with spectrum-selection optical interconnects, spectrally encoded information transfer, image formation in systems involving negative-phase materials, and geometrically tunable metamaterials.

  18. Evaluating the impact of a school-based health intervention using a randomized field experiment.

    PubMed

    Greve, Jane; Heinesen, Eskil

    2015-07-01

    We conduct an econometric evaluation of a health-promoting programme in primary and lower secondary schools in Denmark. The programme includes health-related measurements of the students, communication of knowledge about health, and support of health-promoting projects for students. Half of the schools in the fourth largest municipality in Denmark were randomly selected into a treatment group implementing the programme, while the remainder served as a control group. We estimate both OLS models using only post-intervention observations and difference in differences (DID) models using also pre-intervention observations. We estimate effects of the initiative on BMI, waist/height ratio, overweight and obesity for the entire sample and by gender and grade. We find no consistent effect of the programme. When we use the entire sample, no estimates are statistically significant at conventional levels, although the point estimates for the effect on BMI, indicating an average reduction in the range of 0.10-0.15 kg/m(2), are consistent with the results in a recent Cochrane review evaluating 55 studies of diet and exercise interventions targeting children; and DID estimates which are marginally significant (at the 10% level) indicate that the intervention reduces the risk of obesity by 1% point. Running separate estimations by gender and grade we find a few statistically significant estimates: OLS estimates indicate that the intervention reduces BMI in females in grade 5 by 0.39 kg/m(2) and reduces the risk of obesity in females in grade 9 by 2.6% points; DID estimates indicate an increase in waist for females in preschool class by 1.2 cm and an increase in the risk of obesity in grade 9 males by 4% points. However, if we corrected for multiple hypotheses testing these estimates would be insignificant. There is no statistically significant correlation between participation in the programme and the number of other health-promoting projects at the schools. PMID:25898077

  19. Randomized Controlled Field Trial to Assess the Immunogenicity and Safety of Rift Valley Fever Clone 13 Vaccine in Livestock

    PubMed Central

    Njenga, M. Kariuki; Njagi, Leonard; Thumbi, S. Mwangi; Kahariri, Samuel; Githinji, Jane; Omondi, Eunice; Baden, Amy; Murithi, Mbabu; Paweska, Janusz; Ithondeka, Peter M.; Ngeiywa, Kisa J.; Dungu, Baptiste; Donadeu, Meritxell; Munyua, Peninah M.

    2015-01-01

    Background Although livestock vaccination is effective in preventing Rift Valley fever (RVF) epidemics, there are concerns about safety and effectiveness of the only commercially available RVF Smithburn vaccine. We conducted a randomized controlled field trial to evaluate the immunogenicity and safety of the new RVF Clone 13 vaccine, recently registered in South Africa. Methods In a blinded randomized controlled field trial, 404 animals (85 cattle, 168 sheep, and 151 goats) in three farms in Kenya were divided into three groups. Group A included males and non-pregnant females that were randomized and assigned to two groups; one vaccinated with RVF Clone 13 and the other given placebo. Groups B included animals in 1st half of pregnancy, and group C animals in 2nd half of pregnancy, which were also randomized and either vaccinated and given placebo. Animals were monitored for one year and virus antibodies titers assessed on days 14, 28, 56, 183 and 365. Results In vaccinated goats (N = 72), 72% developed anti-RVF virus IgM antibodies and 97% neutralizing IgG antibodies. In vaccinated sheep (N = 77), 84% developed IgM and 91% neutralizing IgG antibodies. Vaccinated cattle (N = 42) did not develop IgM antibodies but 67% developed neutralizing IgG antibodies. At day 14 post-vaccination, the odds of being seropositive for IgG in the vaccine group was 3.6 (95% CI, 1.5 – 9.2) in cattle, 90.0 (95% CI, 25.1 – 579.2) in goats, and 40.0 (95% CI, 16.5 – 110.5) in sheep. Abortion was observed in one vaccinated goat but histopathologic analysis did not indicate RVF virus infection. There was no evidence of teratogenicity in vaccinated or placebo animals. Conclusions The results suggest RVF Clone 13 vaccine is safe to use and has high (>90%) immunogenicity in sheep and goats but moderate (> 65%) immunogenicity in cattle. PMID:25756501

  20. Analysis of biostimulated microbial communities from two field experiments reveals temporal and spatial differences in proteome profiles

    SciTech Connect

    Callister, S.J.; Wilkins, M.J.; Nicora, C.D.; Williams, K.H.; Banfield, J.F.; VerBerkmoes, N.C.; Hettich, R.L.; NGuessan, A.L.; Mouser, P.J.; Elifantz, H.; Smith, R.D.; Lovley, D.R.; Lipton, M.S.; Long, P.E.

    2010-07-15

    Stimulated by an acetate-amendment field experiment conducted in 2007, anaerobic microbial populations in the aquifer at the Rifle Integrated Field Research Challenge site in Colorado reduced mobile U(VI) to insoluble U(IV). During this experiment, planktonic biomass was sampled at various time points to quantitatively evaluate proteomes. In 2008, an acetate-amended field experiment was again conducted in a similar manner to the 2007 experiment. As there was no comprehensive metagenome sequence available for use in proteomics analysis, we systematically evaluated 12 different organism genome sequences to generate sets of aggregate genomes, or “pseudo-metagenomes”, for supplying relative quantitative peptide and protein identifications. Proteomics results support previous observations of the dominance of Geobacteraceae during biostimulation using acetate as sole electron donor, and revealed a shift from an early stage of iron reduction to a late stage of iron reduction. Additionally, a shift from iron reduction to sulfate reduction was indicated by changes in the contribution of proteome information contributed by different organism genome sequences within the aggregate set. In addition, the comparison of proteome measurements made between the 2007 field experiment and 2008 field experiment revealed differences in proteome profiles. These differences may be the result of alterations in abundance and population structure within the planktonic biomass samples collected for analysis.

  1. Field and laboratory studies reveal interacting effects of stream oxygenation and warming on aquatic ectotherms.

    PubMed

    Verberk, Wilco C E P; Durance, Isabelle; Vaughan, Ian P; Ormerod, Steve J

    2016-05-01

    Aquatic ecological responses to climatic warming are complicated by interactions between thermal effects and other environmental stressors such as organic pollution and hypoxia. Laboratory experiments have demonstrated how oxygen limitation can set heat tolerance for some aquatic ectotherms, but only at unrealistic lethal temperatures and without field data to assess whether oxygen shortages might also underlie sublethal warming effects. Here, we test whether oxygen availability affects both lethal and nonlethal impacts of warming on two widespread Eurasian mayflies, Ephemera danica, Müller 1764 and Serratella ignita (Poda 1761). Mayfly nymphs are often a dominant component of the invertebrate assemblage in streams, and play a vital role in aquatic and riparian food webs. In the laboratory, lethal impacts of warming were assessed under three oxygen conditions. In the field, effects of oxygen availability on nonlethal impacts of warming were assessed from mayfly occurrence in 42 293 UK stream samples where water temperature and biochemical oxygen demand were measured. Oxygen limitation affected both lethal and sublethal impacts of warming in each species. Hypoxia lowered lethal limits by 5.5 °C (±2.13) and 8.2 °C (±0.62) for E. danica and S. ignita respectively. Field data confirmed the importance of oxygen limitation in warmer waters; poor oxygenation drastically reduced site occupancy, and reductions were especially pronounced under warm water conditions. Consequently, poor oxygenation lowered optimal stream temperatures for both species. The broad concordance shown here between laboratory results and extensive field data suggests that oxygen limitation not only impairs survival at thermal extremes but also restricts species abundance in the field at temperatures well below upper lethal limits. Stream oxygenation could thus control the vulnerability of aquatic ectotherms to global warming. Improving water oxygenation and reducing pollution can provide

  2. Field and laboratory studies reveal interacting effects of stream oxygenation and warming on aquatic ectotherms.

    PubMed

    Verberk, Wilco C E P; Durance, Isabelle; Vaughan, Ian P; Ormerod, Steve J

    2016-05-01

    Aquatic ecological responses to climatic warming are complicated by interactions between thermal effects and other environmental stressors such as organic pollution and hypoxia. Laboratory experiments have demonstrated how oxygen limitation can set heat tolerance for some aquatic ectotherms, but only at unrealistic lethal temperatures and without field data to assess whether oxygen shortages might also underlie sublethal warming effects. Here, we test whether oxygen availability affects both lethal and nonlethal impacts of warming on two widespread Eurasian mayflies, Ephemera danica, Müller 1764 and Serratella ignita (Poda 1761). Mayfly nymphs are often a dominant component of the invertebrate assemblage in streams, and play a vital role in aquatic and riparian food webs. In the laboratory, lethal impacts of warming were assessed under three oxygen conditions. In the field, effects of oxygen availability on nonlethal impacts of warming were assessed from mayfly occurrence in 42 293 UK stream samples where water temperature and biochemical oxygen demand were measured. Oxygen limitation affected both lethal and sublethal impacts of warming in each species. Hypoxia lowered lethal limits by 5.5 °C (±2.13) and 8.2 °C (±0.62) for E. danica and S. ignita respectively. Field data confirmed the importance of oxygen limitation in warmer waters; poor oxygenation drastically reduced site occupancy, and reductions were especially pronounced under warm water conditions. Consequently, poor oxygenation lowered optimal stream temperatures for both species. The broad concordance shown here between laboratory results and extensive field data suggests that oxygen limitation not only impairs survival at thermal extremes but also restricts species abundance in the field at temperatures well below upper lethal limits. Stream oxygenation could thus control the vulnerability of aquatic ectotherms to global warming. Improving water oxygenation and reducing pollution can provide

  3. The many assembly histories of massive void galaxies as revealed by integral field spectroscopy

    NASA Astrophysics Data System (ADS)

    Fraser-McKelvie, Amelia; Pimbblet, Kevin A.; Penny, Samantha J.; Brown, Michael J. I.

    2016-06-01

    We present the first detailed integral field spectroscopy study of nine central void galaxies with M⋆ > 1010 M⊙ using the Wide Field Spectrograph to determine how a range of assembly histories manifest themselves in the current day Universe. While the majority of these galaxies are evolving secularly, we find a range of morphologies, merger histories and stellar population distributions, though similarly low Hα-derived star formation rates (<1 M⊙ yr-1). Two of our nine galaxies host active galactic nuclei, and two have kinematic disruptions to their gas that are not seen in their stellar component. Most massive void galaxies are red and discy, which we attribute to a lack of major mergers. Some have disturbed morphologies and may be in the process of evolving to early-type thanks to ongoing minor mergers at present times, likely fed by tendrils leading off filaments. The diversity in our small galaxy sample, despite being of similar mass and environment means that these galaxies are still assembling at present day, with minor mergers playing an important role in their evolution. We compare our sample to a mass and magnitude-matched sample of field galaxies, using data from the Sydney-AAO Multi-object Integral field spectrograph galaxy survey. We find that despite environmental differences, galaxies of mass M⋆ > 1010 M⊙ have similarly low star formation rates (<3 M⊙ yr-1). The lack of distinction between the star formation rates of the void and field environments points to quenching of massive galaxies being a largely mass-related effect.

  4. Approach for fast numerical propagation of uniformly polarized random electromagnetic fields in dispersive linearly birefringent systems.

    PubMed

    Makowski, Piotr L; Domanski, Andrzej W

    2013-09-01

    An efficient simulation technique is proposed for computing propagation of uniformly polarized statistically stationary fields in linear nonimage-forming systems that includes dispersion of linear birefringence to all orders. The method is based on the discrete-time Fourier transformation of modified frequency profiles of the spectral Stokes parameters. It works under the condition that all (linearly) birefringent sections present in the system are described by the same phase birefringence dispersion curve, being a monotonic function of the optical frequency within the bandwidth of the light. We demonstrate the technique as a supplement for the Mueller-Stokes matrix formalism extended to any uniformly polarized polychromatic illumination. Accuracy of its numerical implementation has been verified by using parameters of a Lyot depolarizer made of a highly birefringent and dispersive monomode photonic crystal fiber.

  5. Exact Mapping of the Stochastic Field Theory for Manna Sandpiles to Interfaces in Random Media

    NASA Astrophysics Data System (ADS)

    Le Doussal, Pierre; Wiese, Kay Jörg

    2015-03-01

    We show that the stochastic field theory for directed percolation in the presence of an additional conservation law [the conserved directed-percolation (C-DP) class] can be mapped exactly to the continuum theory for the depinning of an elastic interface in short-range correlated quenched disorder. Along one line of the parameters commonly studied, this mapping leads to the simplest overdamped dynamics. Away from this line, an additional memory term arises in the interface dynamics; we argue that this does not change the universality class. Since C-DP is believed to describe the Manna class of self-organized criticality, this shows that Manna stochastic sandpiles and disordered elastic interfaces (i.e., the quenched Edwards-Wilkinson model) share the same universal large-scale behavior.

  6. Can stochastic, dissipative wave fields be treated as random walk generators

    NASA Technical Reports Server (NTRS)

    Weinstock, J.

    1986-01-01

    A suggestion by Meek et al. (1985) that the gravity wave field be viewed as stochastic, with significant nonlinearities, is applied to calculate diffusivities. The purpose here is to calculate the diffusivity for stochastic wave model and compare it with previous diffusivity estimates. The researchers do this for an idealized case in which the wind velocity changes but slowly, and for which saturation is the principal mechanism by which wave energy is lost. A related calculation was given in a very brief way (Weinstock, 1976), but the approximations were not fully justified, nor were the physical pre-suppositions clearly explained. The observations of Meek et al. (1985) have clarified the pre-suppositions for the researchers and provided a rationalization and improvement of the approximations employed.

  7. Low-Energy Structures in Strong Field Ionization Revealed by Quantum Orbits

    SciTech Connect

    Yan, Tian-Min; Popruzhenko, S. V.; Vrakking, M. J. J.; Bauer, D.

    2010-12-17

    Experiments on atoms in intense laser pulses and the corresponding exact ab initio solutions of the time-dependent Schroedinger equation (TDSE) yield photoelectron spectra with low-energy features that are not reproduced by the otherwise successful work horse of strong field laser physics: the 'strong field approximation' (SFA). In the semiclassical limit, the SFA possesses an appealing interpretation in terms of interfering quantum trajectories. It is shown that a conceptually simple extension towards the inclusion of Coulomb effects yields very good agreement with exact TDSE results. Moreover, the Coulomb quantum orbits allow for a physically intuitive interpretation and detailed analysis of all low-energy features in the semiclassical regime, in particular, the recently discovered 'low-energy structure' [C. I. Blaga et al., Nature Phys. 5, 335 (2009) and W. Quan et al., Phys. Rev. Lett. 103, 093001 (2009)].

  8. Crustal Fracturing Field and Presence of Fluid as Revealed by Seismic Anisotropy

    NASA Astrophysics Data System (ADS)

    Pastori, M.; Piccinini, D.; de Gori, P.; Margheriti, L.; Barchi, M. R.; di Bucci, D.

    2010-12-01

    In the last three years, we developed, tested and improved an automatic analysis code (Anisomat+) to calculate the shear wave splitting parameters, fast polarization direction (φ) and delay time (∂t). The code is a set of MatLab scripts able to retrieve crustal anisotropy parameters from three-component seismic recording of local earthquakes using horizontal component cross-correlation method. The analysis procedure consists in choosing an appropriate frequency range, that better highlights the signal containing the shear waves, and a length of time window on the seismogram centered on the S arrival (the temporal window contains at least one cycle of S wave). The code was compared to other two automatic analysis code (SPY and SHEBA) and tested on three Italian areas (Val d’Agri, Tiber Valley and L’Aquila surrounding) along the Apennine mountains. For each region we used the anisotropic parameters resulting from the automatic computation as a tool to determine the fracture field geometries connected with the active stress field. We compare the temporal variations of anisotropic parameters to the evolution of vp/vs ratio for the same seismicity. The anisotropic fast directions are used to define the active stress field (EDA model), finding a general consistence between fast direction and main stress indicators (focal mechanism and borehole break-out). The magnitude of delay time is used to define the fracture field intensity finding higher value in the volume where micro-seismicity occurs. Furthermore we studied temporal variations of anisotropic parameters and vp/vs ratio in order to explain if fluids play an important role in the earthquake generation process. The close association of anisotropic and vp/vs parameters variations and seismicity rate changes supports the hypothesis that the background seismicity is influenced by the fluctuation of pore fluid pressure in the rocks.

  9. Genetic diversity in potato field populations of Thanatephorus cucumeris AG-3, revealed by ITS polymorphism and RAPD markers.

    PubMed

    Justesen, Annemarie Fejer; Yohalem, David; Bay, Anne; Nicolaisen, Mogens

    2003-11-01

    DNA sequence analysis of the internal transcribed spacer region 1 (ITS1) and random amplified polymorphic DNA (RAPD) markers were used to survey genetic variability in relation to agronomic and regional factors among 60 isolates of Thanatephorus cucumeris (anamorph Rhizoctonia solani) collected from lesions on potato stems or sclerotia of potato tubers. Based on comparative sequence analysis it was shown that all isolates belonged to anastomosis group 3 subgroup Potato Type (AG-3 PT). ITS1 sequence polymorphisms were found within 45 of the 60 isolates showing that different types of the ITS-region are present in individual isolates. Cloning and sequence analysis of the ITS1 region from three selected isolates with sequence polymorphism showed that two different ITS1-types were present in each isolate. RAPD analysis identified 51 RAPD-phenotypes among the 60 investigated isolates indicating a high level of diversity within the subgroup AG-3 PT. Putative clonal isolates with identical RAPD- and ITS1-types were identified within fields, and in one case the same phenotype was found in two different fields separated by several hundred kilometers. Population subdivision analysis based on phenotypic as well as genotypic diversities showed differentiation among populations from different fields when isolates were sampled from tubers, indicating restricted gene flow among soil populations. Low differentiation was seen among field populations sampled from stems, indicating that gene flow is taking place. The population structure was not influenced by the previous crop in the rotation nor by the two cultivars 'Sava' and 'Bintje'.

  10. Phase transitions in a three-dimensional kinetic spin-1/2 Ising model with random field: effective-field-theory study.

    PubMed

    Costabile, Emanuel; de Sousa, J Ricardo

    2012-01-01

    The dynamical phase transitions of the kinetic Ising model in the presence of a random magnetic field with a bimodal probability distribution is studied by using effective-field theory (EFT) with correlations. We have used a Glauber-type stochastic dynamic to describe the time evolution of the system, where the system strongly depends on the H≡√(c) root mean square deviation of the magnetic field. The EFT dynamic equation is given for the simple cubic lattice (z=6), and the dynamic order parameter is calculated. The system presents ferromagnetic and paramagnetic states for low and high temperatures, respectively. Our results predict first-order transitions at low temperatures and large disorder strengths, which corresponds to the existence of a nonequilibrium tricritical point (TCP) in a phase diagram in the T-H plane. We compare the results with the equilibrium phase diagram, where only the first-order line is different. Our qualitative results are compatible with recent Monte Carlo simulations.

  11. [Spine disc MR image analysis using improved independent component analysis based active appearance model and Markov random field].

    PubMed

    Hao, Shijie; Zhan, Shu; Jiang, Jianguo; Li, Hong; Ian, Rosse

    2010-02-01

    As there are not many research reports on segmentation and quantitative analysis of soft tissues in lumbar medical images, this paper presents an algorithm for segmenting and quantitatively analyzing discs in lumbar Magnetic Resonance Imaging (MRI). Vertebrae are first segmented using improved Independent component analysis based active appearance model (ICA-AAM), and lumbar curve is obtained with Minimum Description Length (MDL); based on these results, fast and unsupervised Markov Random Field (MRF) disc segmentation combining disc imaging features and intensity profile is further achieved; finally, disc herniation is quantitatively evaluated. The experiment proves that the proposed algorithm is fast and effective, thus providing doctors with aid in diagnosing and curing lumbar disc herniation.

  12. A functional network estimation method of resting-state fMRI using a hierarchical Markov random field.

    PubMed

    Liu, Wei; Awate, Suyash P; Anderson, Jeffrey S; Fletcher, P Thomas

    2014-10-15

    We propose a hierarchical Markov random field model for estimating both group and subject functional networks simultaneously. The model takes into account the within-subject spatial coherence as well as the between-subject consistency of the network label maps. The statistical dependency between group and subject networks acts as a regularization, which helps the network estimation on both layers. We use Gibbs sampling to approximate the posterior density of the network labels and Monte Carlo expectation maximization to estimate the model parameters. We compare our method with two alternative segmentation methods based on K-Means and normalized cuts, using synthetic and real fMRI data. The experimental results show that our proposed model is able to identify both group and subject functional networks with higher accuracy on synthetic data, more robustness, and inter-session consistency on the real data.

  13. A Functional Networks Estimation Method of Resting-State fMRI Using a Hierarchical Markov Random Field

    PubMed Central

    Liu, Wei; Awate, Suyash P.; Anderson, Jeffrey S.; Fletcher, P. Thomas

    2014-01-01

    We propose a hierarchical Markov random field model that estimates both group and subject functional networks simultaneously. The model takes into account the within-subject spatial coherence as well as the between-subject consistency of the network label maps. The statistical dependency between group and subject networks acts as a regularization, which helps the network estimation on both layers. We use Gibbs sampling to approximate the posterior density of the network labels and Monte Carlo expectation maximization to estimate the model parameters. We compare our method with two alternative segmentation methods based on K-Means and normalized cuts, using synthetic and real fMRI data. The experimental results show our proposed model is able to identify both group and subject functional networks with higher accuracy, more robustness, and inter-session consistency. PMID:24954282

  14. Robustness and sensitivity analysis of a virtual process chain using the S-rail specimen applying random fields

    NASA Astrophysics Data System (ADS)

    Konrad, T.; Wolff, S.; Wiegand, K.; Merklein, M.

    2016-08-01

    An important part in robustness evaluation of production processes is the identification of shape deviations. A systematic approach is typically based on the numerical evaluation of a DoE and the application of metamodels. They provide knowledge on solver noise and sensitivities of individual model parameters. This article presents the sensitivity analysis workflow of a linked deep drawing and joining process chain. LS-DYNA®, optiSLang and SoS is used. The challenge is to separate simulative from process and material parameters of AA 6014. Spatial quantities like variations in geometry, thinning and strain have to be considered in the next process steps. At the same time the number of required virtual CAE model evaluations must be limited. The solution is based on nonlinear metamodels and random fields.

  15. SubPatch: random kd-tree on a sub-sampled patch set for nearest neighbor field estimation

    NASA Astrophysics Data System (ADS)

    Pedersoli, Fabrizio; Benini, Sergio; Adami, Nicola; Okuda, Masahiro; Leonardi, Riccardo

    2015-02-01

    We propose a new method to compute the approximate nearest-neighbors field (ANNF) between image pairs using random kd-tree and patch set sub-sampling. By exploiting image coherence we demonstrate that it is possible to reduce the number of patches on which we compute the ANNF, while maintaining high overall accuracy on the final result. Information on missing patches is then recovered by interpolation and propagation of good matches. The introduction of the sub-sampling factor on patch sets also allows for setting the desired trade off between accuracy and speed, providing a flexibility that lacks in state-of-the-art methods. Tests conducted on a public database prove that our algorithm achieves superior performance with respect to PatchMatch (PM) and Coherence Sensitivity Hashing (CSH) algorithms in a comparable computational time.

  16. Equinoctial Activity Over Titan Dune Fields Revealed by Cassini/vims

    NASA Astrophysics Data System (ADS)

    Rodriguez, S.; Le Mouelic, S.; Barnes, J. W.; Hirtzig, M.; Rannou, P.; Sotin, C.; Brown, R. H.; Bow, J.; Vixie, G.; Cornet, T.; Bourgeois, O.; Narteau, C.; Courrech Du Pont, S.; Le Gall, A.; Reffet, E.; Griffith, C. A.; Jaumann, R.; Stephan, K.; Buratti, B. J.; Clark, R. N.; Baines, K. H.; Nicholson, P. D.; Coustenis, A.

    2012-12-01

    Titan, the largest satellite of Saturn, is the only satellite in the solar system with a dense atmosphere. The close and continuous observations of Titan by the Cassini spacecraft, in orbit around Saturn since July 2004, bring us evidences that Titan troposphere and low stratosphere experience an exotic, but complete meteorological cycle similar to the Earth hydrological cycle, with hydrocarbons evaporation, condensation in clouds, and rainfall. Cassini monitoring campaigns also demonstrate that Titan's cloud coverage and climate vary with latitude. Titan's tropics, with globally weak meteorological activity and widespread dune fields, seem to be slightly more arid than the poles, where extensive and numerous liquid reservoirs and sustained cloud activity have been discovered. Only a few tropo-spheric clouds have been observed at Titan's tropics during the southern summer. As equinox was approaching (in August 2009), they occurred more frequently and appeared to grow in strength and size. We present here the observation of intense brightening at Titan's tropics, very close to the equinox. These detections were conducted with the Visual and Infrared Mapping Spectrometer (VIMS) onboard Cassini. We will discuss the VIMS images of the three individual events detected so far, observed during the Titan's flybys T56 (22 May 2009), T65 (13 January 2010) and T70 (21 June 2010). T56, T65 and T70 observations show an intense and transient brighten-ing of large regions very close to the equator, right over the extensive dune fields of Senkyo, Belet and Shangri-La. They all appear spectrally and morphologically different from all transient surface features or atmospheric phenomena previously reported. Indeed, these events share in particular a strong brightening at wavelengths greater than 2 μm (especially at 5 μm), making them spectrally distinct from the small tropical clouds observed before the equinox and the large storms observed near the equator in September and October

  17. Near-field deformation from the El Mayor-Cucapah earthquake revealed by differential LIDAR.

    PubMed

    Oskin, Michael E; Arrowsmith, J Ramon; Hinojosa Corona, Alejandro; Elliott, Austin J; Fletcher, John M; Fielding, Eric J; Gold, Peter O; Gonzalez Garcia, J Javier; Hudnut, Ken W; Liu-Zeng, Jing; Teran, Orlando J

    2012-02-10

    Large [moment magnitude (M(w)) ≥ 7] continental earthquakes often generate complex, multifault ruptures linked by enigmatic zones of distributed deformation. Here, we report the collection and results of a high-resolution (≥nine returns per square meter) airborne light detection and ranging (LIDAR) topographic survey of the 2010 M(w) 7.2 El Mayor-Cucapah earthquake that produced a 120-kilometer-long multifault rupture through northernmost Baja California, Mexico. This differential LIDAR survey completely captures an earthquake surface rupture in a sparsely vegetated region with pre-earthquake lower-resolution (5-meter-pixel) LIDAR data. The postevent survey reveals numerous surface ruptures, including previously undocumented blind faults within thick sediments of the Colorado River delta. Differential elevation changes show distributed, kilometer-scale bending strains as large as ~10(3) microstrains in response to slip along discontinuous faults cutting crystalline bedrock of the Sierra Cucapah. PMID:22323817

  18. The Attentional Field Revealed by Single-Voxel Modeling of fMRI Time Courses

    PubMed Central

    DeYoe, Edgar A.

    2015-01-01

    The spatial topography of visual attention is a distinguishing and critical feature of many theoretical models of visuospatial attention. Previous fMRI-based measurements of the topography of attention have typically been too crude to adequately test the predictions of different competing models. This study demonstrates a new technique to make detailed measurements of the topography of visuospatial attention from single-voxel, fMRI time courses. Briefly, this technique involves first estimating a voxel's population receptive field (pRF) and then “drifting” attention through the pRF such that the modulation of the voxel's fMRI time course reflects the spatial topography of attention. The topography of the attentional field (AF) is then estimated using a time-course modeling procedure. Notably, we are able to make these measurements in many visual areas including smaller, higher order areas, thus enabling a more comprehensive comparison of attentional mechanisms throughout the full hierarchy of human visual cortex. Using this technique, we show that the AF scales with eccentricity and varies across visual areas. We also show that voxels in multiple visual areas exhibit suppressive attentional effects that are well modeled by an AF having an enhancing Gaussian center with a suppressive surround. These findings provide extensive, quantitative neurophysiological data for use in modeling the psychological effects of visuospatial attention. PMID:25810532

  19. A replicated climate change field experiment reveals rapid evolutionary response in an ecologically important soil invertebrate.

    PubMed

    Bataillon, Thomas; Galtier, Nicolas; Bernard, Aurelien; Cryer, Nicolai; Faivre, Nicolas; Santoni, Sylvain; Severac, Dany; Mikkelsen, Teis N; Larsen, Klaus S; Beier, Claus; Sørensen, Jesper G; Holmstrup, Martin; Ehlers, Bodil K

    2016-07-01

    Whether species can respond evolutionarily to current climate change is crucial for the persistence of many species. Yet, very few studies have examined genetic responses to climate change in manipulated experiments carried out in natural field conditions. We examined the evolutionary response to climate change in a common annelid worm using a controlled replicated experiment where climatic conditions were manipulated in a natural setting. Analyzing the transcribed genome of 15 local populations, we found that about 12% of the genetic polymorphisms exhibit differences in allele frequencies associated to changes in soil temperature and soil moisture. This shows an evolutionary response to realistic climate change happening over short-time scale, and calls for incorporating evolution into models predicting future response of species to climate change. It also shows that designed climate change experiments coupled with genome sequencing offer great potential to test for the occurrence (or lack) of an evolutionary response. PMID:27109012

  20. Trichoderma Biodiversity of Agricultural Fields in East China Reveals a Gradient Distribution of Species

    PubMed Central

    Chen, Jing; Mao, Li-Juan; Feng, Xiao-Xiao; Zhang, Chu-Long; Lin, Fu-Cheng

    2016-01-01

    We surveyed the Trichoderma (Hypocreales, Ascomycota) biodiversity in agricultural fields in four major agricultural provinces of East China. Trichoderma strains were identified based on molecular approaches and morphological characteristics. In three sampled seasons (spring, summer and autumn), 2078 strains were isolated and identified to 17 known species: T. harzianum (429 isolates), T. asperellum (425), T. hamatum (397), T. virens (340), T. koningiopsis (248), T. brevicompactum (73), T. atroviride (73), T. fertile (26), T. longibrachiatum (22), T. pleuroticola (16), T. erinaceum (16), T. oblongisporum (2), T. polysporum (2), T. spirale (2), T. capillare (2), T. velutinum (2), and T. saturnisporum (1). T. harzianum, T. asperellum, T. hamatum, and T. virens were identified as the dominant species with dominance (Y) values of 0.057, 0.052, 0.048, and 0.039, respectively. The species amount, isolate numbers and the dominant species of Trichoderma varied between provinces. Zhejiang Province has shown the highest diversity, which was reflected in the highest species amount (14) and the highest Shannon–Wiener diversity index of Trichoderma haplotypes (1.46). We observed that relative frequencies of T. hamatum and T. koningiopsis under rice soil were higher than those under wheat and maize soil, indicating the preference of Trichoderma to different crops. Remarkable seasonal variation was shown, with summer exhibiting the highest biodiversity of the studied seasons. These results show that Trichoderma biodiversity in agricultural fields varies by region, crop, and season. Zhejiang Province (the southernmost province in the investigated area) had more T. hamatum than Shandong Province (the northernmost province), not only in isolate amounts but also in haplotype amounts. Furthermore, at haplotype level, only T. hamatum showed a gradient distribution from south to north in correspondence analysis among the four dominant species. The above results would contribute to the

  1. Trichoderma Biodiversity of Agricultural Fields in East China Reveals a Gradient Distribution of Species.

    PubMed

    Jiang, Yuan; Wang, Jin-Liang; Chen, Jing; Mao, Li-Juan; Feng, Xiao-Xiao; Zhang, Chu-Long; Lin, Fu-Cheng

    2016-01-01

    We surveyed the Trichoderma (Hypocreales, Ascomycota) biodiversity in agricultural fields in four major agricultural provinces of East China. Trichoderma strains were identified based on molecular approaches and morphological characteristics. In three sampled seasons (spring, summer and autumn), 2078 strains were isolated and identified to 17 known species: T. harzianum (429 isolates), T. asperellum (425), T. hamatum (397), T. virens (340), T. koningiopsis (248), T. brevicompactum (73), T. atroviride (73), T. fertile (26), T. longibrachiatum (22), T. pleuroticola (16), T. erinaceum (16), T. oblongisporum (2), T. polysporum (2), T. spirale (2), T. capillare (2), T. velutinum (2), and T. saturnisporum (1). T. harzianum, T. asperellum, T. hamatum, and T. virens were identified as the dominant species with dominance (Y) values of 0.057, 0.052, 0.048, and 0.039, respectively. The species amount, isolate numbers and the dominant species of Trichoderma varied between provinces. Zhejiang Province has shown the highest diversity, which was reflected in the highest species amount (14) and the highest Shannon-Wiener diversity index of Trichoderma haplotypes (1.46). We observed that relative frequencies of T. hamatum and T. koningiopsis under rice soil were higher than those under wheat and maize soil, indicating the preference of Trichoderma to different crops. Remarkable seasonal variation was shown, with summer exhibiting the highest biodiversity of the studied seasons. These results show that Trichoderma biodiversity in agricultural fields varies by region, crop, and season. Zhejiang Province (the southernmost province in the investigated area) had more T. hamatum than Shandong Province (the northernmost province), not only in isolate amounts but also in haplotype amounts. Furthermore, at haplotype level, only T. hamatum showed a gradient distribution from south to north in correspondence analysis among the four dominant species. The above results would contribute to the

  2. Decades of field data reveal that turtles senesce in the wild.

    PubMed

    Warner, Daniel A; Miller, David A W; Bronikowski, Anne M; Janzen, Fredric J

    2016-06-01

    Lifespan and aging rates vary considerably across taxa; thus, understanding the factors that lead to this variation is a primary goal in biology and has ramifications for understanding constraints and flexibility in human aging. Theory predicts that senescence-declining reproduction and increasing mortality with advancing age-evolves when selection against harmful mutations is weaker at old ages relative to young ages or when selection favors pleiotropic alleles with beneficial effects early in life despite late-life costs. However, in many long-lived ectotherms, selection is expected to remain strong at old ages because reproductive output typically increases with age, which may lead to the evolution of slow or even negligible senescence. We show that, contrary to current thinking, both reproduction and survival decline with adult age in the painted turtle, Chrysemys picta, based on data spanning >20 y from a wild population. Older females, despite relatively high reproductive output, produced eggs with reduced hatching success. Additionally, age-specific mark-recapture analyses revealed increasing mortality with advancing adult age. These findings of reproductive and mortality senescence challenge the contention that chelonians do not age and more generally provide evidence of reduced fitness at old ages in nonmammalian species that exhibit long chronological lifespans. PMID:27140634

  3. Random Sampling of Squamate Reptiles in Spanish Natural Reserves Reveals the Presence of Novel Adenoviruses in Lacertids (Family Lacertidae) and Worm Lizards (Amphisbaenia).

    PubMed

    Szirovicza, Leonóra; López, Pilar; Kopena, Renáta; Benkő, Mária; Martín, José; Pénzes, Judit J

    2016-01-01

    Here, we report the results of a large-scale PCR survey on the prevalence and diversity of adenoviruses (AdVs) in samples collected randomly from free-living reptiles. On the territories of the Guadarrama Mountains National Park in Central Spain and of the Chafarinas Islands in North Africa, cloacal swabs were taken from 318 specimens of eight native species representing five squamate reptilian families. The healthy-looking animals had been captured temporarily for physiological and ethological examinations, after which they were released. We found 22 AdV-positive samples in representatives of three species, all from Central Spain. Sequence analysis of the PCR products revealed the existence of three hitherto unknown AdVs in 11 Carpetane rock lizards (Iberolacerta cyreni), nine Iberian worm lizards (Blanus cinereus), and two Iberian green lizards (Lacerta schreiberi), respectively. Phylogeny inference showed every novel putative virus to be a member of the genus Atadenovirus. This is the very first description of the occurrence of AdVs in amphisbaenian and lacertid hosts. Unlike all squamate atadenoviruses examined previously, two of the novel putative AdVs had A+T rich DNA, a feature generally deemed to mirror previous host switch events. Our results shed new light on the diversity and evolution of atadenoviruses. PMID:27399970

  4. High-Throughput Genotyping of Green Algal Mutants Reveals Random Distribution of Mutagenic Insertion Sites and Endonucleolytic Cleavage of Transforming DNA[W][OPEN

    PubMed Central

    Zhang, Ru; Patena, Weronika; Armbruster, Ute; Gang, Spencer S.; Blum, Sean R.; Jonikas, Martin C.

    2014-01-01

    A high-throughput genetic screening platform in a single-celled photosynthetic eukaryote would be a transformative addition to the plant biology toolbox. Here, we present ChlaMmeSeq (Chlamydomonas MmeI-based insertion site Sequencing), a tool for simultaneous mapping of tens of thousands of mutagenic insertion sites in the eukaryotic unicellular green alga Chlamydomonas reinhardtii. We first validated ChlaMmeSeq by in-depth characterization of individual insertion sites. We then applied ChlaMmeSeq to a mutant pool and mapped 11,478 insertions, covering 39% of annotated protein coding genes. We observe that insertions are distributed in a manner largely indistinguishable from random, indicating that mutants in nearly all genes can be obtained efficiently. The data reveal that sequence-specific endonucleolytic activities cleave the transforming DNA and allow us to propose a simple model to explain the origin of the poorly understood exogenous sequences that sometimes surround insertion sites. ChlaMmeSeq is quantitatively reproducible, enabling its use for pooled enrichment screens and for the generation of indexed mutant libraries. Additionally, ChlaMmeSeq allows genotyping of hits from Chlamydomonas screens on an unprecedented scale, opening the door to comprehensive identification of genes with roles in photosynthesis, algal lipid metabolism, the algal carbon-concentrating mechanism, phototaxis, the biogenesis and function of cilia, and other processes for which C. reinhardtii is a leading model system. PMID:24706510

  5. Random Sampling of Squamate Reptiles in Spanish Natural Reserves Reveals the Presence of Novel Adenoviruses in Lacertids (Family Lacertidae) and Worm Lizards (Amphisbaenia)

    PubMed Central

    Szirovicza, Leonóra; López, Pilar; Kopena, Renáta; Benkő, Mária; Martín, José; Pénzes, Judit J.

    2016-01-01

    Here, we report the results of a large-scale PCR survey on the prevalence and diversity of adenoviruses (AdVs) in samples collected randomly from free-living reptiles. On the territories of the Guadarrama Mountains National Park in Central Spain and of the Chafarinas Islands in North Africa, cloacal swabs were taken from 318 specimens of eight native species representing five squamate reptilian families. The healthy-looking animals had been captured temporarily for physiological and ethological examinations, after which they were released. We found 22 AdV-positive samples in representatives of three species, all from Central Spain. Sequence analysis of the PCR products revealed the existence of three hitherto unknown AdVs in 11 Carpetane rock lizards (Iberolacerta cyreni), nine Iberian worm lizards (Blanus cinereus), and two Iberian green lizards (Lacerta schreiberi), respectively. Phylogeny inference showed every novel putative virus to be a member of the genus Atadenovirus. This is the very first description of the occurrence of AdVs in amphisbaenian and lacertid hosts. Unlike all squamate atadenoviruses examined previously, two of the novel putative AdVs had A+T rich DNA, a feature generally deemed to mirror previous host switch events. Our results shed new light on the diversity and evolution of atadenoviruses. PMID:27399970

  6. Random Sampling of Squamate Reptiles in Spanish Natural Reserves Reveals the Presence of Novel Adenoviruses in Lacertids (Family Lacertidae) and Worm Lizards (Amphisbaenia).

    PubMed

    Szirovicza, Leonóra; López, Pilar; Kopena, Renáta; Benkő, Mária; Martín, José; Pénzes, Judit J

    2016-01-01

    Here, we report the results of a large-scale PCR survey on the prevalence and diversity of adenoviruses (AdVs) in samples collected randomly from free-living reptiles. On the territories of the Guadarrama Mountains National Park in Central Spain and of the Chafarinas Islands in North Africa, cloacal swabs were taken from 318 specimens of eight native species representing five squamate reptilian families. The healthy-looking animals had been captured temporarily for physiological and ethological examinations, after which they were released. We found 22 AdV-positive samples in representatives of three species, all from Central Spain. Sequence analysis of the PCR products revealed the existence of three hitherto unknown AdVs in 11 Carpetane rock lizards (Iberolacerta cyreni), nine Iberian worm lizards (Blanus cinereus), and two Iberian green lizards (Lacerta schreiberi), respectively. Phylogeny inference showed every novel putative virus to be a member of the genus Atadenovirus. This is the very first description of the occurrence of AdVs in amphisbaenian and lacertid hosts. Unlike all squamate atadenoviruses examined previously, two of the novel putative AdVs had A+T rich DNA, a feature generally deemed to mirror previous host switch events. Our results shed new light on the diversity and evolution of atadenoviruses.

  7. Geographic Variation in Skull Morphology of the Large Japanese Field Mice, Apodemus speciosus (Rodentia: Muridae) Revealed by Geometric Morphometric Analysis.

    PubMed

    Shintaku, Yuta; Motokawa, Masaharu

    2016-04-01

    We analyzed geographic variation in skull morphology of the large Japanese field mouse (Apodemus speciosus) and determined changes in skull morphology that occurred during the evolutionary history of A. speciosus in relation to the estimated distribution range in the last glacial maximum (LGM). We analyzed 1,416 specimens from 78 localities using geometric morphometric techniques applied to the dorsal side of the cranium and mandible. While large variations within and among the populations in Honshu, Shikoku, and Kyushu were observed, geographic patterns were not observed. Hokkaido and peripheral island populations showed shared differentiation from the Honshu, Shikoku, and Kyushu populations with a larger skull and distinct mandible shape. In addition, these two groups also differed from each other in accumulated random shape variation. Common characteristics found in Hokkaido and peripheral island populations were considered to be the ancestral states, which were retained by geographic isolation from the main islands. Random variations in Hokkaido and the peripheral island populations were formed through stochastic processes in relation to their isolation. Characteristic morphologies widely found in the populations of Honshu, Shikoku, and Kyushu were considered to be derived states that expanded after separation from the peripheral islands. Complex geomorphology and a shift in distribution range related to climate change and altitudinal distribution are suggested to have formed the complex geographic variation in this species. PMID:27032678

  8. Geographic Variation in Skull Morphology of the Large Japanese Field Mice, Apodemus speciosus (Rodentia: Muridae) Revealed by Geometric Morphometric Analysis.

    PubMed

    Shintaku, Yuta; Motokawa, Masaharu

    2016-04-01

    We analyzed geographic variation in skull morphology of the large Japanese field mouse (Apodemus speciosus) and determined changes in skull morphology that occurred during the evolutionary history of A. speciosus in relation to the estimated distribution range in the last glacial maximum (LGM). We analyzed 1,416 specimens from 78 localities using geometric morphometric techniques applied to the dorsal side of the cranium and mandible. While large variations within and among the populations in Honshu, Shikoku, and Kyushu were observed, geographic patterns were not observed. Hokkaido and peripheral island populations showed shared differentiation from the Honshu, Shikoku, and Kyushu populations with a larger skull and distinct mandible shape. In addition, these two groups also differed from each other in accumulated random shape variation. Common characteristics found in Hokkaido and peripheral island populations were considered to be the ancestral states, which were retained by geographic isolation from the main islands. Random variations in Hokkaido and the peripheral island populations were formed through stochastic processes in relation to their isolation. Characteristic morphologies widely found in the populations of Honshu, Shikoku, and Kyushu were considered to be derived states that expanded after separation from the peripheral islands. Complex geomorphology and a shift in distribution range related to climate change and altitudinal distribution are suggested to have formed the complex geographic variation in this species.

  9. Whole Genome Sequencing of Field Isolates Reveals Extensive Genetic Diversity in Plasmodium vivax from Colombia

    PubMed Central

    Winter, David J.; Pacheco, M. Andreína; Vallejo, Andres F.; Schwartz, Rachel S.; Arevalo-Herrera, Myriam; Herrera, Socrates

    2015-01-01

    Plasmodium vivax is the most prevalent malarial species in South America and exerts a substantial burden on the populations it affects. The control and eventual elimination of P. vivax are global health priorities. Genomic research contributes to this objective by improving our understanding of the biology of P. vivax and through the development of new genetic markers that can be used to monitor efforts to reduce malaria transmission. Here we analyze whole-genome data from eight field samples from a region in Cordóba, Colombia where malaria is endemic. We find considerable genetic diversity within this population, a result that contrasts with earlier studies suggesting that P. vivax had limited diversity in the Americas. We also identify a selective sweep around a substitution known to confer resistance to sulphadoxine-pyrimethamine (SP). This is the first observation of a selective sweep for SP resistance in this species. These results indicate that P. vivax has been exposed to SP pressure even when the drug is not in use as a first line treatment for patients afflicted by this parasite. We identify multiple non-synonymous substitutions in three other genes known to be involved with drug resistance in Plasmodium species. Finally, we found extensive microsatellite polymorphisms. Using this information we developed 18 polymorphic and easy to score microsatellite loci that can be used in epidemiological investigations in South America. PMID:26709695

  10. Field Flumes to Floodplains: Revealing the Influence of Flow Dynamics in Structuring Aquatic Ecosystems

    NASA Astrophysics Data System (ADS)

    Harvey, J. W.

    2011-12-01

    Decades of research has demonstrated the role of flood pulses in energy flow and nutrient cycling in large rivers. However, the study of hydroecology in small to medium size channels has often focused on static processes occurring during steady channel baseflow. Yet storm dynamics and their ecological effects are key issues for land managers responding to accelerating land use change in urban and agricultural areas, grazing lands, and in forested watersheds. As a means to understand the role of variable flows, researchers are increasingly moving towards study designs that explicitly address natural or experimentally altered flows in streams, or manipulation of flow in controlled "stair step" of experimental discharges in smaller field flumes. Studies often focus on both dissolved and fine particulate materials, their redistribution by stormflow, and physical effects of bedform migration and expansion and contraction of surface-water storage and hyporheic zones. In this framework investigators are seeking not only to identify the factors causing "hot spots" of biogeochemical transformation in streams, but also the "hot moments" related to flow variation and its interactions with geomorphic, sediment, and solute dynamics. Examples illustrating these advancements come from studies of flash floods from urban areas and their effects of solute and sediment dynamics in a 2nd order stream, nitrogen cycling and floodplain dynamics in a 5th order river, and longer term co-evolution of pulsed flow hydraulics, geomorphic form, and sediment and nutrient retention in two contrasting river and wetland corridors in the southwestern U.S. and southern Florida.

  11. Compartment Shape Anisotropy (CSA) Revealed by Double Pulsed Field Gradient MR

    PubMed Central

    Özarslan, Evren

    2009-01-01

    The multiple scattering extensions of the pulsed field gradient (PFG) experiments can be used to characterize restriction-induced anisotropy at different length scales. In double-PFG acquisitions that involve two pairs of diffusion gradient pulses, the dependence of the MR signal attenuation on the angle between the two gradients is a signature of restriction that can be observed even at low gradient strengths. In this article, a comprehensive theoretical treatment of the double-PFG observation of restricted diffusion is presented. In the first part of the article, the problem is treated for arbitrarily shaped pores under idealized experimental conditions, comprising infinitesimally narrow gradient pulses with long separation times and long or vanishing mixing times. New insights are obtained when the treatment is applied to simple pore shapes of spheres, ellipsoids, and capped cylinders. The capped cylinder geometry is considered in the second part of the article where the solution for a double-PFG experiment with arbitrary experimental parameters is introduced. Although compartment shape anisotropy (CSA) is emphasized here, the findings of this article can be used in gleaning the volume, eccentricity, and orientation distribution function associated with ensembles of anisotropic compartments using double-PFG acquisitions with arbitrary experimental parameters. PMID:19398210

  12. Dark field optical imaging reveals vascular changes in an inducible hamster cheek pouch model during carcinogenesis

    PubMed Central

    Hu, Fangyao; Morhard, Robert; Murphy, Helen A.; Zhu, Caigang; Ramanujam, Nimmi

    2016-01-01

    In this study, we propose a low-cost cross-polarized dark field microscopy system for in vivo vascular imaging to detect head and neck cancer. A simple-to-use Gabor-filter-based image processing technique was developed to objectively and automatically quantify several important vascular features, including tortuosity, length, diameter and area fraction, from vascular images. Simulations were performed to evaluate the accuracies of vessel segmentation and feature extraction for our algorithm. Sensitivity and specificity for vessel segmentation of the Gabor masks both remained above 80% at all contrast levels when compared to gold-standard masks. Errors for vascular feature extraction were under 5%. Moreover, vascular contrast and vessel diameter were identified to be the two primary factors which affected the segmentation accuracies. After our algorithm was validated, we monitored the blood vessels in an inducible hamster cheek pouch carcinogen model over 17 weeks and quantified vascular features during carcinogenesis. A significant increase in vascular tortuosity and a significant decrease in vessel length were observed during carcinogenesis. PMID:27699096

  13. Dark field optical imaging reveals vascular changes in an inducible hamster cheek pouch model during carcinogenesis

    PubMed Central

    Hu, Fangyao; Morhard, Robert; Murphy, Helen A.; Zhu, Caigang; Ramanujam, Nimmi

    2016-01-01

    In this study, we propose a low-cost cross-polarized dark field microscopy system for in vivo vascular imaging to detect head and neck cancer. A simple-to-use Gabor-filter-based image processing technique was developed to objectively and automatically quantify several important vascular features, including tortuosity, length, diameter and area fraction, from vascular images. Simulations were performed to evaluate the accuracies of vessel segmentation and feature extraction for our algorithm. Sensitivity and specificity for vessel segmentation of the Gabor masks both remained above 80% at all contrast levels when compared to gold-standard masks. Errors for vascular feature extraction were under 5%. Moreover, vascular contrast and vessel diameter were identified to be the two primary factors which affected the segmentation accuracies. After our algorithm was validated, we monitored the blood vessels in an inducible hamster cheek pouch carcinogen model over 17 weeks and quantified vascular features during carcinogenesis. A significant increase in vascular tortuosity and a significant decrease in vessel length were observed during carcinogenesis.

  14. Revealing backward rescattering photoelectron interference of molecules in strong infrared laser fields

    PubMed Central

    Li, Min; Sun, Xufei; Xie, Xiguo; Shao, Yun; Deng, Yongkai; Wu, Chengyin; Gong, Qihuang; Liu, Yunquan

    2015-01-01

    Photoelectrons ionized from atoms and molecules in a strong laser field are either emitted directly or rescattered by the nucleus, both of which can serve as efficiently useful tools for molecular orbital imaging. We measure the photoelectron angular distributions of molecules (N2, O2 and CO2) ionized by infrared laser pulses (1320 nm, 0.2 ~ 1 × 1014 W/cm2) from multiphoton to tunneling regime and observe an enhancement of interference stripes in the tunneling regime. Using a semiclassical rescattering model with implementing the interference effect, we show that the enhancement arises from the sub-laser-cycle holographic interference of the contributions of the back-rescattering and the non-rescattering electron trajectory. It is shown that the low-energy backscattering photoelectron interference patterns have encoded the structural information of the molecular initial orbitals and attosecond time-resolved dynamics of photoelectron, opening new paths in high-resolution imaging of sub-Ångström and sub-femtosecond structural dynamics in molecules. PMID:25687446

  15. Whole Genome Sequencing of Field Isolates Reveals Extensive Genetic Diversity in Plasmodium vivax from Colombia.

    PubMed

    Winter, David J; Pacheco, M Andreína; Vallejo, Andres F; Schwartz, Rachel S; Arevalo-Herrera, Myriam; Herrera, Socrates; Cartwright, Reed A; Escalante, Ananias A

    2015-12-01

    Plasmodium vivax is the most prevalent malarial species in South America and exerts a substantial burden on the populations it affects. The control and eventual elimination of P. vivax are global health priorities. Genomic research contributes to this objective by improving our understanding of the biology of P. vivax and through the development of new genetic markers that can be used to monitor efforts to reduce malaria transmission. Here we analyze whole-genome data from eight field samples from a region in Cordóba, Colombia where malaria is endemic. We find considerable genetic diversity within this population, a result that contrasts with earlier studies suggesting that P. vivax had limited diversity in the Americas. We also identify a selective sweep around a substitution known to confer resistance to sulphadoxine-pyrimethamine (SP). This is the first observation of a selective sweep for SP resistance in this species. These results indicate that P. vivax has been exposed to SP pressure even when the drug is not in use as a first line treatment for patients afflicted by this parasite. We identify multiple non-synonymous substitutions in three other genes known to be involved with drug resistance in Plasmodium species. Finally, we found extensive microsatellite polymorphisms. Using this information we developed 18 polymorphic and easy to score microsatellite loci that can be used in epidemiological investigations in South America.

  16. Passive error concealment for wavelet-coded I-frames with an inhomogeneous Gauss-Markov random field model.

    PubMed

    Rombaut, Joost; Pizurica, Aleksandra; Philips, Wilfried

    2009-04-01

    In video communication over lossy packet networks (e.g., the Internet), packet loss errors can severely damage the transmitted video. The damaged video can largely be repaired with passive error concealment, where neighboring information is used to estimate missing information. We address the problem of passive error concealment for wavelet coded data with dispersive packetization. The reported techniques of this kind have many problems and usually fail in the reconstruction of high-frequency content. This paper presents a novel locally adaptive error concealment method for subband coded I-frames based on an inhomogeneous Gaussian Markov random field model. We estimate the parameters of this model from a local context of each lost coefficient, and we interpolate the lost coefficients accordingly. The results demonstrate a significant improvement over the reported related methods both in terms of objective performance measures and visually. The biggest improvement of the proposed method compared to the state-of-the-art in the field is the correct reconstruction of high-frequency information such as textures and edges.

  17. Revisiting the scaling of the specific heat of the three-dimensional random-field Ising model

    NASA Astrophysics Data System (ADS)

    Fytas, Nikolaos G.; Theodorakis, Panagiotis E.; Hartmann, Alexander K.

    2016-09-01

    We revisit the scaling behavior of the specific heat of the three-dimensional random-field Ising model with a Gaussian distribution of the disorder. Exact ground states of the model are obtained using graph-theoretical algorithms for different strengths 𝒩 = 268 3 spins. By numerically differentiating the bond energy with respect to h, a specific-heat-like quantity is obtained whose maximum is found to converge to a constant in the thermodynamic limit. Compared to a previous study following the same approach, we have studied here much larger system sizes with an increased statistical accuracy. We discuss the relevance of our results under the prism of a modified Rushbrooke inequality for the case of a saturating specific heat. Finally, as a byproduct of our analysis, we provide high-accuracy estimates of the critical field h c = 2.279(7) and the critical exponent of the correlation exponent ν = 1.37(1), in excellent agreement to the most recent computations in the literature.

  18. Life table assay of field-caught Mediterranean fruit flies, Ceratitis capitata, reveals age bias

    PubMed Central

    Kouloussis, Nikos A.; Papadopoulos, Nikos T.; Müller, Hans-Georg; Wang, Jane-Ling; Mao, Meng; Katsoyannos, Byron I.; Duyck, Pierre-François; Carey, James R.

    2012-01-01

    Though traps are used widely to sample phytophagous insects for research or management purposes, and recently in aging research, possible bias stemming from differential response of individuals of various ages to traps has never been examined. In this paper, we tested the response of Ceratitis capitata (Wiedemann) (Diptera: Tephritidae) males and females of four ages (spanning from 1 to 40 days) to McPhail-type traps baited with a synthetic food attractant in field cages and found that the probability of trapping was significantly influenced by age. The type of food on which flies were maintained before testing (sugar or protein) also had a strong effect and interacted with age. In another experiment, we collected wild C. capitata adults of unknown age using 1–3 methods and then reared them in the laboratory until death. The survival schedules of these flies were subsequently used in a life table assay to infer their age at the time of capture. Results showed that on a single sampling date, males captured in traps baited with a food attractant were younger compared with males aspirated from fruiting host trees, or males captured in traps baited with a sex attractant. Likewise, females captured in food-baited traps were younger compared with aspirated females. In addition to providing the first evidence of age-dependent sampling bias for a phytophagous insect species, this paper also provides a novel approach to estimate the differences in the age composition of samples collected with different techniques. These findings are of utmost importance for several categories of insects, medically important groups notwithstanding. PMID:22844133

  19. Shipboard magnetic field "noise" reveals shallow heavy mineral sediment concentrations in Chesapeake Bay

    USGS Publications Warehouse

    Shah, Anjana K.; Vogt, Peter R.; Rosenbaum, Joseph G.; Newell, Wayne; Cronin, Thomas M.; Willard, Debra A.; Hagen, Rick A.; Brozena, John; Hofstra, Albert

    2012-01-01

    Shipboard magnetic field data collected over Chesapeake Bay exhibit low-amplitude, short-wavelength anomalies that most likely indicate shallow concentrations of heavy mineral sediments. Piston core layers and black sand beach samples exhibit enhanced magnetic susceptibilities and carry remanent magnetization, with mineralogical analyses indicating ilmenite and trace magnetite and/or maghemite and hematite. The anomalies are subtle and would be filtered as noise using traditional approaches, but can instead be highlighted using spectral methods, thus providing nearly continuous coverage along survey tracks. The distribution of the anomalies provides constraints on relevant sorting mechanisms. Comparisons to sonar data and previous grab samples show that two of three areas surveyed exhibit short-wavelength anomalies that are clustered over sand-covered areas, suggesting initial sorting through settling mechanisms. This is supported by a correlation between core magnetic susceptibility and grain size. Near the Choptank River, where sediment resuspension is wave-dominated, anomalies show a sharp decrease with seafloor depth that cannot be explained by signal attenuation alone. In Pocomoke Sound, where both tidal currents and wave-action impact sediment resuspension, anomalies show a more gradual decrease with depth. Near the mouth of the bay, where there is a higher influx of sediments from the continental shelf, short-wavelength anomalies are isolated and do not appear to represent heavy mineral sand concentrations. These combined observations suggest the importance of further sorting by erosional processes in certain parts of the bay. Additionally, comparisons of these data to cores sampling pre-Holocene sediments suggest that the sorting of heavy minerals in higher energy, shallow water environments provides a mechanism for correlations between core magnetic susceptibility and sea-level changes.

  20. Pulsed electromagnetic fields after arthroscopic treatment for osteochondral defects of the talus: double-blind randomized controlled multicenter trial

    PubMed Central

    van Bergen, Christiaan JA; Blankevoort, Leendert; de Haan, Rob J; Sierevelt, Inger N; Meuffels, Duncan E; d'Hooghe, Pieter RN; Krips, Rover; van Damme, Geert; van Dijk, C Niek

    2009-01-01

    Background Osteochondral talar defects usually affect athletic patients. The primary surgical treatment consists of arthroscopic debridement and microfracturing. Although this is mostly successful, early sport resumption is difficult to achieve, and it can take up to one year to obtain clinical improvement. Pulsed electromagnetic fields (PEMFs) may be effective for talar defects after arthroscopic treatment by promoting tissue healing, suppressing inflammation, and relieving pain. We hypothesize that PEMF-treatment compared to sham-treatment after arthroscopy will lead to earlier resumption of sports, and aim at 25% increase in patients that resume sports. Methods/Design A prospective, double-blind, randomized, placebo-controlled trial (RCT) will be conducted in five centers throughout the Netherlands and Belgium. 68 patients will be randomized to either active PEMF-treatment or sham-treatment for 60 days, four hours daily. They will be followed-up for one year. The combined primary outcome measures are (a) the percentage of patients that resume and maintain sports, and (b) the time to resumption of sports, defined by the Ankle Activity Score. Secondary outcome measures include resumption of work, subjective and objective scoring systems (American Orthopaedic Foot and Ankle Society – Ankle-Hindfoot Scale, Foot Ankle Outcome Score, Numeric Rating Scales of pain and satisfaction, EuroQol-5D), and computed tomography. Time to resumption of sports will be analyzed using Kaplan-Meier curves and log-rank tests. Discussion This trial will provide level-1 evidence on the effectiveness of PEMFs in the management of osteochondral ankle lesions after arthroscopy. Trial registration Netherlands Trial Register (NTR1636) PMID:19591674

  1. Routine programs of health care systems as an opportunity toward communication skills training for family physicians: A randomized field trial

    PubMed Central

    Zamani, Ahmad Reza; Motamedi, Narges; Farajzadegan, Ziba

    2015-01-01

    Background: To have high-quality primary health care services, an adequate doctor–patient communication is necessary. Because of time restrictions and limited budget in health system, an effective, feasible, and continuous training approach is important. The aim of this study is to assess the appropriateness of a communication skills training program simultaneously with routine programs of health care system. Materials and Methods: It was a randomized field trial in two health network settings during 2013. Twenty-eight family physicians through simple random sampling and 140 patients through convenience sampling participated as intervention and control group. The physicians in the intervention group (n = 14) attended six educational sessions, simultaneous organization meeting, with case discussion and peer education method. In both the groups, physicians completed communication skills knowledge and attitude questionnaires, and patients completed patient satisfaction of medical interview questionnaire at baseline, immediately after intervention, and four months postintervention. Physicians and health network administrators (stakeholders), completed a set of program evaluation forms. Descriptive statistics and Chi-square test, t-test, and repeated measure analysis of variance were used to analyze the data. Results: Use of routine program as a strategy of training was rated by stakeholders highly on “feasibility” (80.5%), “acceptability” (93.5%), “educational content and method appropriateness” (80.75%), and “ability to integrating in the health system programs” (approximate 60%). Significant improvements were found in physicians’ knowledge (P < 0.001), attitude (P < 0.001), and patients’ satisfaction (P = 0.002) in intervention group. Conclusions: Communication skills training program, simultaneous organization meeting was successfully implemented and well received by stakeholders, without considering extra time and manpower. Therefore it can be

  2. Transcranial pulsed electromagnetic fields for multiple chemical sensitivity: study protocol for a randomized, double-blind, placebo-controlled trial

    PubMed Central

    2013-01-01

    Background Multiple chemical sensitivity (MCS) is a chronic condition of unknown etiology. MCS is characterized by recurrent nonspecific symptoms from multiple organ systems in response to chemical exposures in concentrations that are normally tolerated by the majority of the population. The symptoms may have severe impact on patients’ lives, but an evidence-based treatment for the condition is nonexisting. The pathophysiology is unclarified, but several indicators point towards abnormal processing of sensory signals in the central nervous system. Pulsed electromagnetic fields (PEMF) offer a promising new treatment for refractory depression and can be targeted at the brain, thereby activating biochemical cell processes. Methods/Design In a parallel, randomized, double-blind, placebo-controlled trial conducted at the Danish Research Centre for Chemical Sensitivities, the effects of PEMF in MCS patients will be assessed using the Re5 Independent System. Based on sample size estimation, 40 participants will be randomized to either PEMF therapy or placebo. The allocation sequence will be generated by computer. All involved parties (that is, participants, investigators, the research nurse, and the statistician) will be blinded to group allocation. The participants will receive PEMF therapy or placebo applied transcranially 30 minutes twice a day for 7 days a week over 6 consecutive weeks. Outcomes will be measured at baseline, once weekly during treatment, post treatment, and at 2.5-month and 4.5-month follow-up according to a predefined timetable. The primary outcome will be a measurement of the impact of MCS on everyday life. The secondary outcomes will be measurements of MCS symptoms, psychological distress (stress, anxiety or depressive symptoms), capsaicin-induced secondary punctate hyperalgesia, immunological markers in serum, and quality of life. Discussion This trial will assess the effects of PEMF therapy for MCS. Currently, there is no treatment with a

  3. Time resolved X-ray Dark-Field Tomography Revealing Water Transport in a Fresh Cement Sample

    PubMed Central

    Prade, Friedrich; Fischer, Kai; Heinz, Detlef; Meyer, Pascal; Mohr, Jürgen; Pfeiffer, Franz

    2016-01-01

    Grating-based X-ray dark-field tomography is a promising technique for biomedical and materials research. Even if the resolution of conventional X-ray tomography does not suffice to resolve relevant structures, the dark-field signal provides valuable information about the sub-pixel microstructural properties of the sample. Here, we report on the potential of X-ray dark-field imaging to be used for time-resolved three-dimensional studies. By repeating consecutive tomography scans on a fresh cement sample, we were able to study the hardening dynamics of the cement paste in three dimensions over time. The hardening of the cement was accompanied by a strong decrease in the dark-field signal pointing to microstructural changes within the cement paste. Furthermore our results hint at the transport of water from certain limestone grains, which were embedded in the sample, to the cement paste during the process of hardening. This is indicated by an increasing scattering signal which was observed for two of the six tested limestone grains. Electron microscopy images revealed a distinct porous structure only for those two grains which supports the following interpretation of our results. When the water filled pores of the limestone grains empty during the experiment the scattering signal of the grains increases. PMID:27357449

  4. Time resolved X-ray Dark-Field Tomography Revealing Water Transport in a Fresh Cement Sample.

    PubMed

    Prade, Friedrich; Fischer, Kai; Heinz, Detlef; Meyer, Pascal; Mohr, Jürgen; Pfeiffer, Franz

    2016-01-01

    Grating-based X-ray dark-field tomography is a promising technique for biomedical and materials research. Even if the resolution of conventional X-ray tomography does not suffice to resolve relevant structures, the dark-field signal provides valuable information about the sub-pixel microstructural properties of the sample. Here, we report on the potential of X-ray dark-field imaging to be used for time-resolved three-dimensional studies. By repeating consecutive tomography scans on a fresh cement sample, we were able to study the hardening dynamics of the cement paste in three dimensions over time. The hardening of the cement was accompanied by a strong decrease in the dark-field signal pointing to microstructural changes within the cement paste. Furthermore our results hint at the transport of water from certain limestone grains, which were embedded in the sample, to the cement paste during the process of hardening. This is indicated by an increasing scattering signal which was observed for two of the six tested limestone grains. Electron microscopy images revealed a distinct porous structure only for those two grains which supports the following interpretation of our results. When the water filled pores of the limestone grains empty during the experiment the scattering signal of the grains increases. PMID:27357449

  5. Time resolved X-ray Dark-Field Tomography Revealing Water Transport in a Fresh Cement Sample

    NASA Astrophysics Data System (ADS)

    Prade, Friedrich; Fischer, Kai; Heinz, Detlef; Meyer, Pascal; Mohr, Jürgen; Pfeiffer, Franz

    2016-06-01

    Grating-based X-ray dark-field tomography is a promising technique for biomedical and materials research. Even if the resolution of conventional X-ray tomography does not suffice to resolve relevant structures, the dark-field signal provides valuable information about the sub-pixel microstructural properties of the sample. Here, we report on the potential of X-ray dark-field imaging to be used for time-resolved three-dimensional studies. By repeating consecutive tomography scans on a fresh cement sample, we were able to study the hardening dynamics of the cement paste in three dimensions over time. The hardening of the cement was accompanied by a strong decrease in the dark-field signal pointing to microstructural changes within the cement paste. Furthermore our results hint at the transport of water from certain limestone grains, which were embedded in the sample, to the cement paste during the process of hardening. This is indicated by an increasing scattering signal which was observed for two of the six tested limestone grains. Electron microscopy images revealed a distinct porous structure only for those two grains which supports the following interpretation of our results. When the water filled pores of the limestone grains empty during the experiment the scattering signal of the grains increases.

  6. Reducing contralateral SI activity reveals hindlimb receptive fields in the SI forelimb-stump representation of neonatally amputated rats.

    PubMed

    Pluto, Charles P; Chiaia, Nicolas L; Rhoades, Robert W; Lane, Richard D

    2005-09-01

    In adult rats that sustained forelimb amputation on the day of birth, >30% of multiunit recording sites in the forelimb-stump representation of primary somatosensory cortex (SI) also respond to cutaneous hindlimb stimulation when cortical GABA(A+B) receptors are blocked (GRB). This study examined whether hindlimb receptive fields could also be revealed in forelimb-stump sites by reducing one known source of excitatory input to SI GABAergic neurons, the contralateral SI cortex. Corpus callosum projection neurons connect homotopic SI regions, making excitatory contacts onto pyramidal cells and interneurons. Thus in addition to providing monosynaptic excitation in SI, callosal fibers can produce disynaptic inhibition through excitatory synapses with inhibitory interneurons. Based on the latter of these connections, we hypothesized that inactivating the contralateral (intact) SI forelimb region would "unmask" normally suppressed hindlimb responses by reducing the activity of SI GABAergic neurons. The SI forelimb-stump representation was first mapped under normal conditions and then during GRB to identify stump/hindlimb responsive sites. After GRB had dissipated, the contralateral (intact) SI forelimb region was mapped and reversibly inactivated with injections of 4% lidocaine, and selected forelimb-stump sites were retested. Contralateral SI inactivation revealed hindlimb responses in approximately 60% of sites that were stump/hindlimb responsive during GRB. These findings indicate that activity in the contralateral SI contributes to the suppression of reorganized hindlimb receptive fields in neonatally amputated rats.

  7. Markov random field driven region-based active contour model (MaRACel): application to medical image segmentation.

    PubMed

    Xu, Jun; Monaco, James P; Madabhushi, Anant

    2010-01-01

    In this paper we present a Markov random field (MRF) driven region-based active contour model (MaRACel) for medical image segmentation. State-of-the-art region-based active contour (RAC) models assume that every spatial location in the image is statistically independent of the others, thereby ignoring valuable contextual information. To address this shortcoming we incorporate a MRF prior into the AC model, further generalizing Chan & Vese's (CV) and Rousson and Deriche's (RD) AC models. This incorporation requires a Markov prior that is consistent with the continuous variational framework characteristic of active contours; consequently, we introduce a continuous analogue to the discrete Potts model. To demonstrate the effectiveness of MaRACel, we compare its performance to those of the CV and RD AC models in the following scenarios: (1) the qualitative segmentation of a cancerous lesion in a breast DCE-MR image and (2) the qualitative and quantitative segmentations of prostatic acini (glands) in 200 histopathology images. Across the 200 prostate needle core biopsy histology images, MaRACel yielded an average sensitivity, specificity, and positive predictive value of 71%, 95%, 74% with respect to the segmented gland boundaries; the CV and RD models have corresponding values of 19%, 81%, 20% and 53%, 88%, 56%, respectively.

  8. Multimodal brain-tumor segmentation based on Dirichlet process mixture model with anisotropic diffusion and Markov random field prior.

    PubMed

    Lu, Yisu; Jiang, Jun; Yang, Wei; Feng, Qianjin; Chen, Wufan

    2014-01-01

    Brain-tumor segmentation is an important clinical requirement for brain-tumor diagnosis and radiotherapy planning. It is well-known that the number of clusters is one of the most important parameters for automatic segmentation. However, it is difficult to define owing to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this study, a nonparametric mixture of Dirichlet process (MDP) model is applied to segment the tumor images, and the MDP segmentation can be performed without the initialization of the number of clusters. Because the classical MDP segmentation cannot be applied for real-time diagnosis, a new nonparametric segmentation algorithm combined with anisotropic diffusion and a Markov random field (MRF) smooth constraint is proposed in this study. Besides the segmentation of single modal brain-tumor images, we developed the algorithm to segment multimodal brain-tumor images by the magnetic resonance (MR) multimodal features and obtain the active tumor and edema in the same time. The proposed algorithm is evaluated using 32 multimodal MR glioma image sequences, and the segmentation results are compared with other approaches. The accuracy and computation time of our algorithm demonstrates very impressive performance and has a great potential for practical real-time clinical use.

  9. A Bayesian 3D data fusion and unsupervised joint segmentation approach for stochastic geological modelling using Hidden Markov random fields

    NASA Astrophysics Data System (ADS)

    Wang, Hui; Wellmann, Florian

    2016-04-01

    It is generally accepted that 3D geological models inferred from observed data will contain a certain amount of uncertainties. The uncertainty quantification and stochastic sampling methods are essential for gaining the insight into the geological variability of subsurface structures. In the community of deterministic or traditional modelling techniques, classical geo-statistical methods using boreholes (hard data sets) are still most widely accepted although suffering certain drawbacks. Modern geophysical measurements provide us regional data sets in 2D or 3D spaces either directly from sensors or indirectly from inverse problem solving using observed signal (soft data sets). We propose a stochastic modelling framework to extract subsurface heterogeneity from multiple and complementary types of data. In the presented work, subsurface heterogeneity is considered as the "hidden link" among multiple spatial data sets as well as inversion results. Hidden Markov random field models are employed to perform 3D segmentation which is the representation of the "hidden link". Finite Gaussian mixture models are adopted to characterize the statistical parameters of the multiple data sets. The uncertainties are quantified via a Gibbs sampling process under the Bayesian inferential framework. The proposed modelling framework is validated using two numerical examples. The model behavior and convergence are also well examined. It is shown that the presented stochastic modelling framework is a promising tool for the 3D data fusion in the communities of geological modelling and geophysics.

  10. A model-based approach to gene clustering with missing observation reconstruction in a Markov random field framework.

    PubMed

    Blanchet, Juliette; Vignes, Matthieu

    2009-03-01

    The different measurement techniques that interrogate biological systems provide means for monitoring the behavior of virtually all cell components at different scales and from complementary angles. However, data generated in these experiments are difficult to interpret. A first difficulty arises from high-dimensionality and inherent noise of such data. Organizing them into meaningful groups is then highly desirable to improve our knowledge of biological mechanisms. A more accurate picture can be obtained when accounting for dependencies between components (e.g., genes) under study. A second difficulty arises from the fact that biological experiments often produce missing values. When it is not ignored, the latter issue has been solved by imputing the expression matrix prior to applying traditional analysis methods. Although helpful, this practice can lead to unsound results. We propose in this paper a statistical methodology that integrates individual dependencies in a missing data framework. More explicitly, we present a clustering algorithm dealing with incomplete data in a Hidden Markov Random Field context. This tackles the missing value issue in a probabilistic framework and still allows us to reconstruct missing observations a posteriori without imposing any pre-processing of the data. Experiments on synthetic data validate the gain in using our method, and analysis of real biological data shows its potential to extract biological knowledge.

  11. Sutureless Adult Voluntary Male Circumcision with Topical Anesthetic: A Randomized Field Trial of Unicirc, a Single-Use Surgical Instrument

    PubMed Central

    2016-01-01

    Introduction The World Health Organization has solicited rapid and minimally invasive techniques to facilitate scale-up of voluntary medical male circumcision (VMMC). Study design Non-blinded randomized controlled field trial with 2:1 allocation ratio. Participants 75 adult male volunteers. Setting Outpatient primary care clinic. Intervention Open surgical circumcision under local anesthetic with suturing vs. Unicirc disposable instrument under topical anesthetic and wound sealing with cyanoacrylate tissue adhesive. Primary Outcome Intraoperative duration. Secondary Outcomes Intraoperative and postoperative pain; adverse events; time to healing; patient satisfaction; cosmetic result. Results The intraoperative time was less with the Unicirc technique (median 12 vs. 25 min, p < 0.001). Wound healing and cosmetic results were superior in the Unicirc group. Adverse events were similar in both groups. Conclusions VMMC with Unicirc under topical anesthetic and wound sealing with cyanoacrylate tissue adhesive is rapid, heals by primary intention with superior cosmetic results, and is potentially safer and more cost-effective than open surgical VMMC. Trial Registration Clinicaltrials.gov NCT02443792 PMID:27299735

  12. Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

    NASA Astrophysics Data System (ADS)

    Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

    2011-11-01

    Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

  13. Effects of pulsed electromagnetic fields on peripheral blood circulation in people with diabetes: A randomized controlled trial.

    PubMed

    Sun, Jiahui; Kwan, Rachel Lai-Chu; Zheng, Yongping; Cheing, Gladys Lai-Ying

    2016-07-01

    Cutaneous blood flow provides nourishment that plays an essential role in maintaining skin health. We examined the effects of pulsed electromagnetic fields (PEMFs) on cutaneous circulation of dorsal feet. Twenty-two patients with diabetes mellitus (DM) and 21 healthy control subjects were randomly allocated to receive either PEMFs or sham PEMFs (0.5 mT, 12 Hz, 30 min). Blood flow velocity and diameter of the small vein were examined by using ultrasound biomicroscopy; also, microcirculation at skin over the base of the 1st metatarsal bone (Flux1) and distal 1st phalange (Flux2) was measured by laser Doppler flowmetry before and after intervention. Results indicated that PEMFs produced significantly greater changes in blood flow velocity of the smallest observable vein than did sham PEMFs (both P < 0.05) in both types of subjects. However, no significant difference was found in changes of vein diameter, nor in Flux1 and Flux2, between PEMFs and sham PEMFs groups in subjects with or without DM. We hypothesized that PEMFs would increase blood flow velocity of the smallest observable vein in people with or without DM. Bioelectromagnetics. 37:290-297, 2016. © 2016 Wiley Periodicals, Inc.

  14. Multimodal brain-tumor segmentation based on Dirichlet process mixture model with anisotropic diffusion and Markov random field prior.

    PubMed

    Lu, Yisu; Jiang, Jun; Yang, Wei; Feng, Qianjin; Chen, Wufan

    2014-01-01

    Brain-tumor segmentation is an important clinical requirement for brain-tumor diagnosis and radiotherapy planning. It is well-known that the number of clusters is one of the most important parameters for automatic segmentation. However, it is difficult to define owing to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this study, a nonparametric mixture of Dirichlet process (MDP) model is applied to segment the tumor images, and the MDP segmentation can be performed without the initialization of the number of clusters. Because the classical MDP segmentation cannot be applied for real-time diagnosis, a new nonparametric segmentation algorithm combined with anisotropic diffusion and a Markov random field (MRF) smooth constraint is proposed in this study. Besides the segmentation of single modal brain-tumor images, we developed the algorithm to segment multimodal brain-tumor images by the magnetic resonance (MR) multimodal features and obtain the active tumor and edema in the same time. The proposed algorithm is evaluated using 32 multimodal MR glioma image sequences, and the segmentation results are compared with other approaches. The accuracy and computation time of our algorithm demonstrates very impressive performance and has a great potential for practical real-time clinical use. PMID:25254064

  15. Experimental realization of the zero temperature Random Field Ising Model : the condensation of 4He in aerogels

    NASA Astrophysics Data System (ADS)

    Aubry, Geoffroy; Guyon, Laurent; Melich, Mathieu; Spathis, Panayotis; Despetis, Florence; Wolf, Pierre-Etienne

    2013-03-01

    Although widely studied, the effect of disorder on a first order phase transition is still highly debated. Numerical simulations of the T = 0 Random Field Ising Model show that magnetization evolves by avalanches, the average size of which diverges below a critical disorder (Sethna et al., PRL 70 3347 (1993)). Nevertheless, experimental evidence is scarce up to now (Berger et al., PRL 85, 4176 (2000)). In the case of the liquid gas transition in disordered porous media, the same theoretical concepts can be applied (Detcheverry et al., PRE 72 051506 (2005)). We have studied experimentally this phase transition using 4He in silica aerogels. Optical and thermodynamical measurements show that the condensation is an out of equilibrium process. We clearly observe two filling regimes separated by a critical temperature T* : below T*, filling is discontinuous (macro avalanche) whereas above T* it becomes continuous (micro avalanches). In addition, we have developed a speckle interferometry technique to detect single avalanches. We argue that our results support the disorder induced phase transition. This work was supported by ANR-06-BLAN-0098.

  16. Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

    NASA Astrophysics Data System (ADS)

    Abdulbaqi, Hayder Saad; Jafri, Mohd Zubir Mat; Omar, Ahmad Fairuz; Mustafa, Iskandar Shahrim Bin; Abood, Loay Kadom

    2015-04-01

    Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introduce a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.

  17. Microbiological Evaluation of the Efficacy of Soapy Water to Clean Hands: A Randomized, Non-Inferiority Field Trial

    PubMed Central

    Amin, Nuhu; Pickering, Amy J.; Ram, Pavani K.; Unicomb, Leanne; Najnin, Nusrat; Homaira, Nusrat; Ashraf, Sania; Abedin, Jaynal; Islam, M. Sirajul; Luby, Stephen P.

    2014-01-01

    We conducted a randomized, non-inferiority field trial in urban Dhaka, Bangladesh among mothers to compare microbial efficacy of soapy water (30 g powdered detergent in 1.5 L water) with bar soap and water alone. Fieldworkers collected hand rinse samples before and after the following washing regimens: scrubbing with soapy water for 15 and 30 seconds; scrubbing with bar soap for 15 and 30 seconds; and scrubbing with water alone for 15 seconds. Soapy water and bar soap removed thermotolerant coliforms similarly after washing for 15 seconds (mean log10 reduction = 0.7 colony-forming units [CFU], P < 0.001 for soapy water; mean log10 reduction = 0.6 CFU, P = 0.001 for bar soap). Increasing scrubbing time to 30 seconds did not improve removal (P > 0.05). Scrubbing hands with water alone also reduced thermotolerant coliforms (mean log10 reduction = 0.3 CFU, P = 0.046) but was less efficacious than scrubbing hands with soapy water. Soapy water is an inexpensive and microbiologically effective cleansing agent to improve handwashing among households with vulnerable children. PMID:24914003

  18. Asynchronous decoding of finger movements from ECoG signals using long-range dependencies conditional random fields

    NASA Astrophysics Data System (ADS)

    Delgado Saa, Jaime F.; de Pesters, Adriana; Cetin, Mujdat

    2016-06-01

    Objective. In this work we propose the use of conditional random fields with long-range dependencies for the classification of finger movements from electrocorticographic recordings. Approach. The proposed method uses long-range dependencies taking into consideration time-lags between the brain activity and the execution of the motor task. In addition, the proposed method models the dynamics of the task executed by the subject and uses information about these dynamics as prior information during the classification stage. Main results. The results show that incorporating temporal information about the executed task as well as incorporating long-range dependencies between the brain signals and the labels effectively increases the system’s classification performance compared to methods in the state of art. Significance. The method proposed in this work makes use of probabilistic graphical models to incorporate temporal information in the classification of finger movements from electrocorticographic recordings. The proposed method highlights the importance of including prior information about the task that the subjects execute. As the results show, the combination of these two features effectively produce a significant improvement of the system’s classification performance.

  19. Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields

    PubMed Central

    Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi

    2015-01-01

    Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy. PMID:26630674

  20. Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.

    PubMed

    Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi; Åkerfelt, Malin; Nees, Matthias

    2015-01-01

    Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.

  1. COMBAT: Initial experience with a randomized clinical trial of plasma-based resuscitation in the field for traumatic hemorrhagic shock

    PubMed Central

    Chapman, Michael P.; Moore, Ernest E.; Chin, Theresa L; Ghasabyan, Arsen; Chandler, James; Stringham, John; Gonzalez, Eduardo; Moore, Hunter B.; Banerjee, Anirban; Silliman, Christopher C; Sauaia, Angela

    2015-01-01

    The existing evidence shows great promise for plasma as the first resuscitation fluid in both civilian and military trauma. We embarked on the Control of Major Bleeding After Trauma (COMBAT) trial with the support of the Department of Defense, in order to determine if plasma-first resuscitation yields hemostatic and survival benefits. The methodology of the COMBAT study represents not only three years of development work, but the integration of nearly two-decades of technical experience with the design and implementation of other clinical trials and studies. Herein, we describe the key features of the study design, critical personnel and infrastructural elements, and key innovations. We will also briefly outline the systems engineering challenges entailed by this study. COMBAT is a randomized, placebo controlled, semi-blinded prospective Phase IIB clinical trial, conducted in a ground ambulance fleet based at a Level I trauma center, and part of a multicenter collaboration. The primary objective of COMBAT is to determine the efficacy of field resuscitation with plasma first, compared to standard of care (normal saline). To date we have enrolled 30 subjects in the COMBAT study. The ability to achieve intervention with a hemostatic resuscitation agent in the closest possible temporal proximity to injury is critical and represents an opportunity to forestall the evolution of the “bloody vicious cycle”. Thus, the COMBAT model for deploying plasma in first response units should serve as a model for RCTs of other hemostatic resuscitative agents. PMID:25784527

  2. Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

    SciTech Connect

    Abdulbaqi, Hayder Saad; Jafri, Mohd Zubir Mat; Omar, Ahmad Fairuz; Mustafa, Iskandar Shahrim Bin; Abood, Loay Kadom

    2015-04-24

    Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introduce a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.

  3. Multi-penalty conditional random field approach to super-resolved reconstruction of optical coherence tomography images

    PubMed Central

    Boroomand, Ameneh; Wong, Alexander; Li, Edward; Cho, Daniel S.; Ni, Betty; Bizheva, Kostandinka

    2013-01-01

    Improving the spatial resolution of Optical Coherence Tomography (OCT) images is important for the visualization and analysis of small morphological features in biological tissue such as blood vessels, membranes, cellular layers, etc. In this paper, we propose a novel reconstruction approach to obtaining super-resolved OCT tomograms from multiple lower resolution images. The proposed Multi-Penalty Conditional Random Field (MPCRF) method combines four different penalty factors (spatial proximity, first and second order intensity variations, as well as a spline-based smoothness of fit) into the prior model within a Maximum A Posteriori (MAP) estimation framework. Test carried out in retinal OCT images illustrate the effectiveness of the proposed MPCRF reconstruction approach in terms of spatial resolution enhancement, as compared to previously published super resolved image reconstruction methods. Visual assessment of the MPCRF results demonstrate the potential of this method in better preservation of fine details and structures of the imaged sample, as well as retaining the sharpness of biological tissue boundaries while reducing the effects of speckle noise inherent to OCT. Quantitative evaluation using imaging metrics such as Signal-to-Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Equivalent Number of Looks (ENL), and Edge Preservation Parameter show significant visual quality improvement with the MPCRF approach. Therefore, the proposed MPCRF reconstruction approach is an effective tool for enhancing the spatial resolution of OCT images without the necessity for significant imaging hardware modifications. PMID:24156062

  4. Multimodal Brain-Tumor Segmentation Based on Dirichlet Process Mixture Model with Anisotropic Diffusion and Markov Random Field Prior

    PubMed Central

    Lu, Yisu; Jiang, Jun; Chen, Wufan

    2014-01-01

    Brain-tumor segmentation is an important clinical requirement for brain-tumor diagnosis and radiotherapy planning. It is well-known that the number of clusters is one of the most important parameters for automatic segmentation. However, it is difficult to define owing to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this study, a nonparametric mixture of Dirichlet process (MDP) model is applied to segment the tumor images, and the MDP segmentation can be performed without the initialization of the number of clusters. Because the classical MDP segmentation cannot be applied for real-time diagnosis, a new nonparametric segmentation algorithm combined with anisotropic diffusion and a Markov random field (MRF) smooth constraint is proposed in this study. Besides the segmentation of single modal brain-tumor images, we developed the algorithm to segment multimodal brain-tumor images by the magnetic resonance (MR) multimodal features and obtain the active tumor and edema in the same time. The proposed algorithm is evaluated using 32 multimodal MR glioma image sequences, and the segmentation results are compared with other approaches. The accuracy and computation time of our algorithm demonstrates very impressive performance and has a great potential for practical real-time clinical use. PMID:25254064

  5. Microbiological evaluation of the efficacy of soapy water to clean hands: a randomized, non-inferiority field trial.

    PubMed

    Amin, Nuhu; Pickering, Amy J; Ram, Pavani K; Unicomb, Leanne; Najnin, Nusrat; Homaira, Nusrat; Ashraf, Sania; Abedin, Jaynal; Islam, M Sirajul; Luby, Stephen P

    2014-08-01

    We conducted a randomized, non-inferiority field trial in urban Dhaka, Bangladesh among mothers to compare microbial efficacy of soapy water (30 g powdered detergent in 1.5 L water) with bar soap and water alone. Fieldworkers collected hand rinse samples before and after the following washing regimens: scrubbing with soapy water for 15 and 30 seconds; scrubbing with bar soap for 15 and 30 seconds; and scrubbing with water alone for 15 seconds. Soapy water and bar soap removed thermotolerant coliforms similarly after washing for 15 seconds (mean log10 reduction = 0.7 colony-forming units [CFU], P < 0.001 for soapy water; mean log10 reduction = 0.6 CFU, P = 0.001 for bar soap). Increasing scrubbing time to 30 seconds did not improve removal (P > 0.05). Scrubbing hands with water alone also reduced thermotolerant coliforms (mean log10 reduction = 0.3 CFU, P = 0.046) but was less efficacious than scrubbing hands with soapy water. Soapy water is an inexpensive and microbiologically effective cleansing agent to improve handwashing among households with vulnerable children.

  6. Microbiological evaluation of the efficacy of soapy water to clean hands: a randomized, non-inferiority field trial.

    PubMed

    Amin, Nuhu; Pickering, Amy J; Ram, Pavani K; Unicomb, Leanne; Najnin, Nusrat; Homaira, Nusrat; Ashraf, Sania; Abedin, Jaynal; Islam, M Sirajul; Luby, Stephen P

    2014-08-01

    We conducted a randomized, non-inferiority field trial in urban Dhaka, Bangladesh among mothers to compare microbial efficacy of soapy water (30 g powdered detergent in 1.5 L water) with bar soap and water alone. Fieldworkers collected hand rinse samples before and after the following washing regimens: scrubbing with soapy water for 15 and 30 seconds; scrubbing with bar soap for 15 and 30 seconds; and scrubbing with water alone for 15 seconds. Soapy water and bar soap removed thermotolerant coliforms similarly after washing for 15 seconds (mean log10 reduction = 0.7 colony-forming units [CFU], P < 0.001 for soapy water; mean log10 reduction = 0.6 CFU, P = 0.001 for bar soap). Increasing scrubbing time to 30 seconds did not improve removal (P > 0.05). Scrubbing hands with water alone also reduced thermotolerant coliforms (mean log10 reduction = 0.3 CFU, P = 0.046) but was less efficacious than scrubbing hands with soapy water. Soapy water is an inexpensive and microbiologically effective cleansing agent to improve handwashing among households with vulnerable children. PMID:24914003

  7. Recognition and Evaluation of Clinical Section Headings in Clinical Documents Using Token-Based Formulation with Conditional Random Fields.

    PubMed

    Dai, Hong-Jie; Syed-Abdul, Shabbir; Chen, Chih-Wei; Wu, Chieh-Chen

    2015-01-01

    Electronic health record (EHR) is a digital data format that collects electronic health information about an individual patient or population. To enhance the meaningful use of EHRs, information extraction techniques have been developed to recognize clinical concepts mentioned in EHRs. Nevertheless, the clinical judgment of an EHR cannot be known solely based on the recognized concepts without considering its contextual information. In order to improve the readability and accessibility of EHRs, this work developed a section heading recognition system for clinical documents. In contrast to formulating the section heading recognition task as a sentence classification problem, this work proposed a token-based formulation with the conditional random field (CRF) model. A standard section heading recognition corpus was compiled by annotators with clinical experience to evaluate the performance and compare it with sentence classification and dictionary-based approaches. The results of the experiments showed that the proposed method achieved a satisfactory F-score of 0.942, which outperformed the sentence-based approach and the best dictionary-based system by 0.087 and 0.096, respectively. One important advantage of our formulation over the sentence-based approach is that it presented an integrated solution without the need to develop additional heuristics rules for isolating the headings from the surrounding section contents. PMID:26380302

  8. Möbius-strip-like columnar functional connections are revealed in somato-sensory receptive field centroids

    PubMed Central

    Wright, James Joseph; Bourke, Paul David; Favorov, Oleg Vyachesslavovich

    2014-01-01

    Receptive fields of neurons in the forelimb region of areas 3b and 1 of primary somatosensory cortex, in cats and monkeys, were mapped using extracellular recordings obtained sequentially from nearly radial penetrations. Locations of the field centroids indicated the presence of a functional system in which cortical homotypic representations of the limb surfaces are entwined in three-dimensional Möbius-strip-like patterns of synaptic connections. Boundaries of somatosensory receptive field in nested groups irregularly overlie the centroid order, and are interpreted as arising from the superposition of learned connections upon the embryonic order. Since the theory of embryonic synaptic self-organization used to model these results was devised and earlier used to explain findings in primary visual cortex, the present findings suggest the theory may be of general application throughout cortex and may reveal a modular functional synaptic system, which, only in some parts of the cortex, and in some species, is manifest as anatomical ordering into columns. PMID:25400552

  9. RELAXATION OF MAGNETIC FIELD RELATIVE TO PLASMA DENSITY REVEALED FROM MICROWAVE ZEBRA PATTERNS ASSOCIATED WITH SOLAR FLARES

    SciTech Connect

    Yu Sijie; Yan Yihua; Tan Baolin E-mail: yyh@nao.cas.cn

    2012-12-20

    It is generally considered that the emission of microwave zebra pattern (ZP) structures requires high density and high temperature, which is similar to the situation of the flaring region where primary energy is released. Therefore, a parameter analysis of ZPs may reveal the physical conditions of the flaring source region. This work investigates the variations of 74 microwave ZP structures observed by the Chinese Solar Broadband Radio Spectrometer (SBRS/Huairou) at 2.6-3.8 GHz in nine solar flares, and we find that the ratio between the plasma density scale height L{sub N} and the magnetic field scale height L{sub B} in emission sources displays a tendency to decrease during the flaring processes. The ratio L{sub N} /L{sub B} is about 3-5 before the maximum of flares. It decreases to about 2 after the maximum. The detailed analysis of three typical X-class flares implies that the variation of L{sub N} /L{sub B} during the flaring process is most likely due to topological changes of the magnetic field in the flaring source region, and the stepwise decrease of L{sub N} /L{sub B} possibly reflects the magnetic field relaxation relative to the plasma density when the flaring energy is released. This result may also constrain solar flare modeling to some extent.

  10. Adaptive multi-level conditional random fields for detection and segmentation of small enhanced pathology in medical images.

    PubMed

    Karimaghaloo, Zahra; Arnold, Douglas L; Arbel, Tal

    2016-01-01

    Detection and segmentation of large structures in an image or within a region of interest have received great attention in the medical image processing domains. However, the problem of small pathology detection and segmentation still remains an unresolved challenge due to the small size of these pathologies, their low contrast and variable position, shape and texture. In many contexts, early detection of these pathologies is critical in diagnosis and assessing the outcome of treatment. In this paper, we propose a probabilistic Adaptive Multi-level Conditional Random Fields (AMCRF) with the incorporation of higher order cliques for detecting and segmenting such pathologies. In the first level of our graphical model, a voxel-based CRF is used to identify candidate lesions. In the second level, in order to further remove falsely detected regions, a new CRF is developed that incorporates higher order textural features, which are invariant to rotation and local intensity distortions. At this level, higher order textures are considered together with the voxel-wise cliques to refine boundaries and is therefore adaptive. The proposed algorithm is tested in the context of detecting enhancing Multiple Sclerosis (MS) lesions in brain MRI, where the problem is further complicated as many of the enhancing voxels are associated with normal structures (i.e. blood vessels) or noise in the MRI. The algorithm is trained and tested on large multi-center clinical trials from Relapsing-Remitting MS patients. The effect of several different parameter learning and inference techniques is further investigated. When tested on 120 cases, the proposed method reaches a lesion detection rate of 90%, with very few false positive lesion counts on average, ranging from 0.17 for very small (3-5 voxels) to 0 for very large (50+ voxels) regions. The proposed model is further tested on a very large clinical trial containing 2770 scans where a high sensitivity of 91% with an average false positive

  11. In (Re)Search of Evidence-Based School Practices: Possibilities for Integrating Nationally Representative Surveys and Randomized Field Trials To Inform Educational Policy.

    ERIC Educational Resources Information Center

    Berends, Mark; Garet, Michael S.

    2002-01-01

    Asserts that integrating randomized field trials (RFTs) and nationally representative surveys can strengthen the evidence base for school reform, suggesting national surveys can help determine the focus of RFTs by identifying factors that place schools at risk of poor achievement or buffer schools from risk. Surveys can provide data on the…

  12. Invariant joint distribution of a stationary random field and its derivatives: Euler characteristic and critical point counts in 2 and 3D

    SciTech Connect

    Pogosyan, Dmitry; Gay, Christophe; Pichon, Christophe

    2009-10-15

    The full moments expansion of the joint probability distribution of an isotropic random field, its gradient, and invariants of the Hessian are presented in 2 and 3D. It allows for explicit expression for the Euler characteristic in ND and computation of extrema counts as functions of the excursion set threshold and the spectral parameter, as illustrated on model examples.

  13. Effects of Adult Education Vouchers on the Labor Market: Evidence from a Randomized Field Experiment. Program on Education Policy and Governance Working Papers Series. PEPG 11-01

    ERIC Educational Resources Information Center

    Schwerdt, Guido; Messer, Dolores; Woessmann, Ludger; Wolter, Stefan C.

    2011-01-01

    Lifelong learning is often promoted in ageing societies, but little is known about its returns or governments' ability to advance it. This paper evaluates the effects of a large-scale randomized field experiment issuing vouchers for adult education in Switzerland. We find no significant average effects of voucher-induced adult education on…

  14. Randomly detected genetically modified (GM) maize (Zea mays L.) near a transport route revealed a fragile 45S rDNA phenotype.

    PubMed

    Waminal, Nomar Espinosa; Ryu, Ki Hyun; Choi, Sun-Hee; Kim, Hyun Hee

    2013-01-01

    Monitoring of genetically modified (GM) crops has been emphasized to prevent their potential effects on the environment and human health. Monitoring of the inadvertent dispersal of transgenic maize in several fields and transport routes in Korea was carried out by qualitative multiplex PCR, and molecular analyses were conducted to identify the events of the collected GM maize. Cytogenetic investigations through fluorescence in situ hybridization (FISH) of the GM maize were performed to check for possible changes in the 45S rDNA cluster because this cluster was reported to be sensitive to replication and transcription stress. Three GM maize kernels were collected from a transport route near Incheon port, Korea, and each was found to contain NK603, stacked MON863 x NK603, and stacked NK603 x MON810 inserts, respectively. Cytogenetic analysis of the GM maize containing the stacked NK603 x MON810 insert revealed two normal compact 5S rDNA signals, but the 45S rDNA showed a fragile phenotype, demonstrating a "beads-on-a-string" fragmentation pattern, which seems to be a consequence of genetic modification. Implications of the 45S rDNA cluster fragility in GM maize are also discussed.

  15. Randomly Detected Genetically Modified (GM) Maize (Zea mays L.) near a Transport Route Revealed a Fragile 45S rDNA Phenotype

    PubMed Central

    Waminal, Nomar Espinosa; Ryu, Ki Hyun; Choi, Sun-Hee; Kim, Hyun Hee

    2013-01-01

    Monitoring of genetically modified (GM) crops has been emphasized to prevent their potential effects on the environment and human health. Monitoring of the inadvertent dispersal of transgenic maize in several fields and transport routes in Korea was carried out by qualitative multiplex PCR, and molecular analyses were conducted to identify the events of the collected GM maize. Cytogenetic investigations through fluorescence in situ hybridization (FISH) of the GM maize were performed to check for possible changes in the 45S rDNA cluster because this cluster was reported to be sensitive to replication and transcription stress. Three GM maize kernels were collected from a transport route near Incheon port, Korea, and each was found to contain NK603, stacked MON863 x NK603, and stacked NK603 x MON810 inserts, respectively. Cytogenetic analysis of the GM maize containing the stacked NK603 x MON810 insert revealed two normal compact 5S rDNA signals, but the 45S rDNA showed a fragile phenotype, demonstrating a “beads-on-a-string” fragmentation pattern, which seems to be a consequence of genetic modification. Implications of the 45S rDNA cluster fragility in GM maize are also discussed. PMID:24040165

  16. Perceptual suppression revealed by adaptive multi-scale entropy analysis of local field potential in monkey visual cortex.

    PubMed

    Hu, Meng; Liang, Hualou

    2013-04-01

    Generalized flash suppression (GFS), in which a salient visual stimulus can be rendered invisible despite continuous retinal input, provides a rare opportunity to directly study the neural mechanism of visual perception. Previous work based on linear methods, such as spectral analysis, on local field potential (LFP) during GFS has shown that the LFP power at distinctive frequency bands are differentially modulated by perceptual suppression. Yet, the linear method alone may be insufficient for the full assessment of neural dynamic due to the fundamentally nonlinear nature of neural signals. In this study, we set forth to analyze the LFP data collected from multiple visual areas in V1, V2 and V4 of macaque monkeys while performing the GFS task using a nonlinear method - adaptive multi-scale entropy (AME) - to reveal the neural dynamic of perceptual suppression. In addition, we propose a new cross-entropy measure at multiple scales, namely adaptive multi-scale cross-entropy (AMCE), to assess the nonlinear functional connectivity between two cortical areas. We show that: (1) multi-scale entropy exhibits percept-related changes in all three areas, with higher entropy observed during perceptual suppression; (2) the magnitude of the perception-related entropy changes increases systematically over successive hierarchical stages (i.e. from lower areas V1 to V2, up to higher area V4); and (3) cross-entropy between any two cortical areas reveals higher degree of asynchrony or dissimilarity during perceptual suppression, indicating a decreased functional connectivity between cortical areas. These results, taken together, suggest that perceptual suppression is related to a reduced functional connectivity and increased uncertainty of neural responses, and the modulation of perceptual suppression is more effective at higher visual cortical areas. AME is demonstrated to be a useful technique in revealing the underlying dynamic of nonlinear/nonstationary neural signal.

  17. Automatic segmentation of ground-glass opacities in lung CT images by using Markov random field-based algorithms.

    PubMed

    Zhu, Yanjie; Tan, Yongqing; Hua, Yanqing; Zhang, Guozhen; Zhang, Jianguo

    2012-06-01

    Chest radiologists rely on the segmentation and quantificational analysis of ground-glass opacities (GGO) to perform imaging diagnoses that evaluate the disease severity or recovery stages of diffuse parenchymal lung diseases. However, it is computationally difficult to segment and analyze patterns of GGO while compared with other lung diseases, since GGO usually do not have clear boundaries. In this paper, we present a new approach which automatically segments GGO in lung computed tomography (CT) images using algorithms derived from Markov random field theory. Further, we systematically evaluate the performance of the algorithms in segmenting GGO in lung CT images under different situations. CT image studies from 41 patients with diffuse lung diseases were enrolled in this research. The local distributions were modeled with both simple and adaptive (AMAP) models of maximum a posteriori (MAP). For best segmentation, we used the simulated annealing algorithm with a Gibbs sampler to solve the combinatorial optimization problem of MAP estimators, and we applied a knowledge-guided strategy to reduce false positive regions. We achieved AMAP-based GGO segmentation results of 86.94%, 94.33%, and 94.06% in average sensitivity, specificity, and accuracy, respectively, and we evaluated the performance using radiologists' subjective evaluation and quantificational analysis and diagnosis. We also compared the results of AMAP-based GGO segmentation with those of support vector machine-based methods, and we discuss the reliability and other issues of AMAP-based GGO segmentation. Our research results demonstrate the acceptability and usefulness of AMAP-based GGO segmentation for assisting radiologists in detecting GGO in high-resolution CT diagnostic procedures.

  18. Improved longitudinal gray and white matter atrophy assessment via application of a 4-dimensional hidden Markov random field model.

    PubMed

    Dwyer, Michael G; Bergsland, Niels; Zivadinov, Robert

    2014-04-15

    SIENA and similar techniques have demonstrated the utility of performing "direct" measurements as opposed to post-hoc comparison of cross-sectional data for the measurement of whole brain (WB) atrophy over time. However, gray matter (GM) and white matter (WM) atrophy are now widely recognized as important components of neurological disease progression, and are being actively evaluated as secondary endpoints in clinical trials. Direct measures of GM/WM change with advantages similar to SIENA have been lacking. We created a robust and easily-implemented method for direct longitudinal analysis of GM/WM atrophy, SIENAX multi-time-point (SIENAX-MTP). We built on the basic halfway-registration and mask composition components of SIENA to improve the raw output of FMRIB's FAST tissue segmentation tool. In addition, we created LFAST, a modified version of FAST incorporating a 4th dimension in its hidden Markov random field model in order to directly represent time. The method was validated by scan-rescan, simulation, comparison with SIENA, and two clinical effect size comparisons. All validation approaches demonstrated improved longitudinal precision with the proposed SIENAX-MTP method compared to SIENAX. For GM, simulation showed better correlation with experimental volume changes (r=0.992 vs. 0.941), scan-rescan showed lower standard deviations (3.8% vs. 8.4%), correlation with SIENA was more robust (r=0.70 vs. 0.53), and effect sizes were improved by up to 68%. Statistical power estimates indicated a potential drop of 55% in the number of subjects required to detect the same treatment effect with SIENAX-MTP vs. SIENAX. The proposed direct GM/WM method significantly improves on the standard SIENAX technique by trading a small amount of bias for a large reduction in variance, and may provide more precise data and additional statistical power in longitudinal studies.

  19. Application of hidden Markov random field approach for quantification of perfusion/diffusion mismatch in acute ischemic stroke.

    PubMed

    Dwyer, Michael G; Bergsland, Niels; Saluste, Erik; Sharma, Jitendra; Jaisani, Zeenat; Durfee, Jacqueline; Abdelrahman, Nadir; Minagar, Alireza; Hoque, Romy; Munschauer, Frederick E; Zivadinov, Robert

    2008-10-01

    The perfusion/diffusion 'mismatch model' in acute ischemic stroke provides the potential to more accurately understand the consequences of thrombolytic therapy on an individual patient basis. Few methods exist to quantify mismatch extent (ischemic penumbra) and none have shown a robust ability to predict infarcted tissue outcome. Hidden Markov random field (HMRF) approaches have been used successfully in many other applications. The aim of the study was to develop a method for rapid and reliable identification and quantification of perfusion/diffusion mismatch using an HMRF approach. An HMRF model was used in combination with automated contralateral identification to segment normal tissue from non-infarcted tissue with perfusion abnormality. The infarct was used as a seed point to initialize segmentation, along with the contralateral mirror tissue. The two seeds were then allowed to compete for ownership of all unclassified tissue. In addition, a novel method was presented for quantifying tissue salvageability by weighting the volume with the degree of hypoperfusion, allowing the penumbra voxels to contribute unequal potential damage estimates. Simulated and in vivo datasets were processed and compared with results from a conventional thresholding approach. Both simulated and in vivo experiments demonstrated a dramatic improvement in accuracy with the proposed technique. For the simulated dataset, the mean absolute error decreased from 171.9% with conventional thresholding to 2.9% for the delay-weighted HMRF approach. For the in vivo dataset, the mean absolute error decreased from 564.6% for thresholding to 34.2% for the delay-weighted HMRF approach. The described method represents a significant improvement over thresholding techniques.

  20. Inference in alpha rhythm phase and amplitude modeled on Markov random field using belief propagation from electroencephalograms.

    PubMed

    Naruse, Yasushi; Takiyama, Ken; Okada, Masato; Murata, Tsutomu

    2010-07-01

    Alpha rhythm is a major component of spontaneous electroencephalographic (EEG) data. We develop a novel method that can be used to estimate the instantaneous phases and amplitudes of the alpha rhythm with high accuracy by modeling the alpha rhythm phase and amplitude as Markov random field (MRF) models. By using a belief propagation technique, we construct an exact-inference algorithm that can be used to estimate instantaneous phases and amplitudes and calculate the marginal likelihood. Maximizing the marginal likelihood enables us to estimate the hyperparameters on the basis of type-II maximum likelihood estimation. We prove that the instantaneous phase and amplitude estimation by our method is consistent with that by the Hilbert transform, which has been commonly used to estimate instantaneous phases and amplitudes, of a signal filtered from observed data in the limited case that the observed data consist of only one frequency signal whose amplitude is constant and a Gaussian noise. Comparison of the performances of observation noise reduction by our method and by a Gaussian MRF model of alpha rhythm signal indicates that our method reduces observation noise more efficiently. Moreover, the instantaneous phase and amplitude estimates obtained using our method are more accurate than those obtained by the Hilbert transform. Application of our method to experimental EEG data also demonstrates that the relationship between the alpha rhythm phase and the reaction time emerges more clearly by using our method than the Hilbert transform. This indicates our method's practical usefulness. Therefore, applying our method to experimental EEG data will enable us to estimate the instantaneous phases and amplitudes of the alpha rhythm more precisely.

  1. Weighted maximum posterior marginals for random fields using an ensemble of conditional densities from multiple Markov chain Monte Carlo simulations.

    PubMed

    Monaco, James Peter; Madabhushi, Anant

    2011-07-01

    The ability of classification systems to adjust their performance (sensitivity/specificity) is essential for tasks in which certain errors are more significant than others. For example, mislabeling cancerous lesions as benign is typically more detrimental than mislabeling benign lesions as cancerous. Unfortunately, methods for modifying the performance of Markov random field (MRF) based classifiers are noticeably absent from the literature, and thus most such systems restrict their performance to a single, static operating point (a paired sensitivity/specificity). To address this deficiency we present weighted maximum posterior marginals (WMPM) estimation, an extension of maximum posterior marginals (MPM) estimation. Whereas the MPM cost function penalizes each error equally, the WMPM cost function allows misclassifications associated with certain classes to be weighted more heavily than others. This creates a preference for specific classes, and consequently a means for adjusting classifier performance. Realizing WMPM estimation (like MPM estimation) requires estimates of the posterior marginal distributions. The most prevalent means for estimating these--proposed by Marroquin--utilizes a Markov chain Monte Carlo (MCMC) method. Though Marroquin's method (M-MCMC) yields estimates that are sufficiently accurate for MPM estimation, they are inadequate for WMPM. To more accurately estimate the posterior marginals we present an equally simple, but more effective extension of the MCMC method (E-MCMC). Assuming an identical number of iterations, E-MCMC as compared to M-MCMC yields estimates with higher fidelity, thereby 1) allowing a far greater number and diversity of operating points and 2) improving overall classifier performance. To illustrate the utility of WMPM and compare the efficacies of M-MCMC and E-MCMC, we integrate them into our MRF-based classification system for detecting cancerous glands in (whole-mount or quarter) histological sections of the prostate.

  2. An Iterative Inference Procedure Applying Conditional Random Fields for Simultaneous Classification of Land Cover and Land Use

    NASA Astrophysics Data System (ADS)

    Albert, L.; Rottensteiner, F.; Heipke, C.

    2015-08-01

    Land cover and land use exhibit strong contextual dependencies. We propose a novel approach for the simultaneous classification of land cover and land use, where semantic and spatial context is considered. The image sites for land cover and land use classification form a hierarchy consisting of two layers: a land cover layer and a land use layer. We apply Conditional Random Fields (CRF) at both layers. The layers differ with respect to the image entities corresponding to the nodes, the employed features and the classes to be distinguished. In the land cover layer, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Both CRFs model spatial dependencies between neighbouring image sites. The complex semantic relations between land cover and land use are integrated in the classification process by using contextual features. We propose a new iterative inference procedure for the simultaneous classification of land cover and land use, in which the two classification tasks mutually influence each other. This helps to improve the classification accuracy for certain classes. The main idea of this approach is that semantic context helps to refine the class predictions, which, in turn, leads to more expressive context information. Thus, potentially wrong decisions can be reversed at later stages. The approach is designed for input data based on aerial images. Experiments are carried out on a test site to evaluate the performance of the proposed method. We show the effectiveness of the iterative inference procedure and demonstrate that a smaller size of the super-pixels has a positive influence on the classification result.

  3. Assessment Data-Informed Guidance to Individualize Kindergarten Reading Instruction: Findings from a Cluster-Randomized Control Field Trial.

    PubMed

    Al Otaiba, Stephanie; Connor, Carol M; Folsom, Jessica Sidler; Greulich, Luana; Meadows, Jane; Li, Zhi

    2011-06-01

    The purpose of this cluster-randomized control field trial was to was to examine the extent to which kindergarten teachers could learn a promising instructional strategy, wherein kindergarten reading instruction was differentiated based upon students' ongoing assessments of language and literacy skills and documented child characteristic by instruction (CXI) interactions; and to test the efficacy of this differentiated reading instruction on the reading outcomes of students from culturally diverse backgrounds. The study involved 14 schools and included 23 treatment (n = 305 students) and 21 contrast teacher (n = 251 students). Teachers in the contrast condition received only a baseline professional development that included a researcher-delivered summer day-long workshop on individualized instruction. Data sources included parent surveys, individually administered child assessments of language, cognitive, and reading skills and videotapes of classroom instruction. Using Hierarchical Multivariate Linear Modeling (HMLM), we found students in treatment classrooms outperformed students in the contrast classrooms on a latent measure of reading skills, comprised of letter-word reading, decoding, alphabetic knowledge, and phonological awareness (ES = .52). Teachers in both conditions provided small group instruction, but teachers in the treatment condition provided significantly more individualized instruction. Our findings extend research on the efficacy of teachers using Individualized Student Instruction to individualize instruction based upon students' language and literacy skills in first through third grade. Findings are discussed regarding the value of professional development related to differentiating core reading instruction and the challenges of using Response to Intervention approaches to address students' needs in the areas of reading in general education contexts.

  4. Inference in alpha rhythm phase and amplitude modeled on Markov random field using belief propagation from electroencephalograms

    NASA Astrophysics Data System (ADS)

    Naruse, Yasushi; Takiyama, Ken; Okada, Masato; Murata, Tsutomu

    2010-07-01

    Alpha rhythm is a major component of spontaneous electroencephalographic (EEG) data. We develop a novel method that can be used to estimate the instantaneous phases and amplitudes of the alpha rhythm with high accuracy by modeling the alpha rhythm phase and amplitude as Markov random field (MRF) models. By using a belief propagation technique, we construct an exact-inference algorithm that can be used to estimate instantaneous phases and amplitudes and calculate the marginal likelihood. Maximizing the marginal likelihood enables us to estimate the hyperparameters on the basis of type-II maximum likelihood estimation. We prove that the instantaneous phase and amplitude estimation by our method is consistent with that by the Hilbert transform, which has been commonly used to estimate instantaneous phases and amplitudes, of a signal filtered from observed data in the limited case that the observed data consist of only one frequency signal whose amplitude is constant and a Gaussian noise. Comparison of the performances of observation noise reduction by our method and by a Gaussian MRF model of alpha rhythm signal indicates that our method reduces observation noise more efficiently. Moreover, the instantaneous phase and amplitude estimates obtained using our method are more accurate than those obtained by the Hilbert transform. Application of our method to experimental EEG data also demonstrates that the relationship between the alpha rhythm phase and the reaction time emerges more clearly by using our method than the Hilbert transform. This indicates our method’s practical usefulness. Therefore, applying our method to experimental EEG data will enable us to estimate the instantaneous phases and amplitudes of the alpha rhythm more precisely.

  5. Sequence polymorphism in an insect RNA virus field population: A snapshot from a single point in space and time reveals stochastic differences among and within individual hosts

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Population structure of Homalodisca coagulata Virus-1 (HoCV-1) among and within field-collected insects was examined. To minimize effects of different evolutionary histories and/or selection pressures, all glassy-winged sharpshooter (Homalodisca vitripennis; synonym H. coagulata) hosts were randomly...

  6. New automated Markov-Gibbs random field based framework for myocardial wall viability quantification on agent enhanced cardiac magnetic resonance images.

    PubMed

    Elnakib, Ahmed; Beache, Garth M; Gimel'farb, Georgy; El-Baz, Ayman

    2012-10-01

    A novel automated framework for detecting and quantifying viability from agent enhanced cardiac magnetic resonance images is proposed. The framework identifies the pathological tissues based on a joint Markov-Gibbs random field (MGRF) model that accounts for the 1st-order visual appearance of the myocardial wall (in terms of the pixel-wise intensities) and the 2nd-order spatial interactions between pixels. The pathological tissue is quantified based on two metrics: the percentage area in each segment with respect to the total area of the segment, and the trans-wall extent of the pathological tissue. This transmural extent is estimated using point-to-point correspondences based on a Laplace partial differential equation. Transmural extent was validated using a simulated phantom. We tested the proposed framework on 14 datasets (168 images) and validated against manual expert delineation of the pathological tissue by two observers. Mean Dice similarity coefficients (DSC) of 0.90 and 0.88 were obtained for the observers, approaching the ideal value, 1. The Bland-Altman statistic of infarct volumes estimated by manual versus the MGRF estimation revealed little bias difference, and most values fell within the 95% confidence interval, suggesting very good agreement. Using the DSC measure we documented statistically significant superior segmentation performance for our MGRF method versus established intensity-based methods (greater DSC, and smaller standard deviation). Our Laplace method showed good operating characteristics across the full range of extent of transmural infarct, outperforming conventional methods. Phantom validation and experiments on patient data confirmed the robustness and accuracy of the proposed framework.

  7. Evaluating coastal sea surface heights based on a novel sub-waveform approach using sparse representation and conditional random fields

    NASA Astrophysics Data System (ADS)

    Uebbing, Bernd; Roscher, Ribana; Kusche, Jürgen

    2016-04-01

    Satellite radar altimeters allow global monitoring of mean sea level changes over the last two decades. However, coastal regions are less well observed due to influences on the returned signal energy by land located inside the altimeter footprint. The altimeter emits a radar pulse, which is reflected at the nadir-surface and measures the two-way travel time, as well as the returned energy as a function of time, resulting in a return waveform. Over the open ocean the waveform shape corresponds to a theoretical model which can be used to infer information on range corrections, significant wave height or wind speed. However, in coastal areas the shape of the waveform is significantly influenced by return signals from land, located in the altimeter footprint, leading to peaks which tend to bias the estimated parameters. Recently, several approaches dealing with this problem have been published, including utilizing only parts of the waveform (sub-waveforms), estimating the parameters in two steps or estimating additional peak parameters. We present a new approach in estimating sub-waveforms using conditional random fields (CRF) based on spatio-temporal waveform information. The CRF piece-wise approximates the measured waveforms based on a pre-derived dictionary of theoretical waveforms for various combinations of the geophysical parameters; neighboring range gates are likely to be assigned to the same underlying sub-waveform model. Depending on the choice of hyperparameters in the CRF estimation, the classification into sub-waveforms can either be more fine or coarse resulting in multiple sub-waveform hypotheses. After the sub-waveforms have been detected, existing retracking algorithms can be applied to derive water heights or other desired geophysical parameters from particular sub-waveforms. To identify the optimal heights from the multiple hypotheses, instead of utilizing a known reference height, we apply a Dijkstra-algorithm to find the "shortest path" of all

  8. Xenopus mutant reveals necessity of rax for specifying the eye field which otherwise forms tissue with telencephalic and diencephalic character

    PubMed Central

    Fisher, Marilyn; Hirsch, Nicolas; Cox, Amanda; Reeder, Rollin; Carruthers, Samantha; Hall, Amanda; Stemple, Derek L.; Grainger, Robert M.

    2014-01-01

    SUMMARY The retinal anterior homeobox (rax) gene encodes a transcription factor necessary for vertebrate eye development. rax transcription is initiated at the end of gastrulation in Xenopus, and is a key part of the regulatory network specifying anterior neural plate and retina. We describe here a Xenopus tropicalis rax mutant, the first mutant analyzed in detail from a reverse genetic screen. As in other vertebrates, this nonsense mutation results in eyeless animals, and is lethal peri-metamorphosis. Tissue normally fated to form retina in these mutants instead forms tissue with characteristics of diencephalon and telencephalon. This implies that a key role of rax, in addition to defining the eye field, is in preventing alternative forebrain identities. Our data highlight that brain and retina regions are not determined by the mid-gastrula stage but are by the neural plate stage. An RNA-Seq analysis and in situ hybridization assays for early gene expression in the mutant revealed that several key eye field transcription factors (e.g. pax6, lhx2 and six6) are not dependent on rax activity through neurulation. However, these analyses identified other genes either up- or down-regulated in mutant presumptive retinal tissue. Two neural patterning genes of particular interest that appear up-regulated in the rax mutant RNA-seq analysis are hesx1 and fezf2. These genes were not previously known to be regulated by rax. The normal function of rax is to partially repress their expression by an indirect mechanism in the presumptive retina region in wildtype embryos, thus accounting for the apparent up-regulation in the rax mutant. Knock-down experiments using antisense morpholino oligonucleotides directed against hesx1 and fezf2 show that failure to repress these two genes contributes to transformation of presumptive retinal tissue into non-retinal forebrain identities in the rax mutant. PMID:25224223

  9. Xenopus mutant reveals necessity of rax for specifying the eye field which otherwise forms tissue with telencephalic and diencephalic character.

    PubMed

    Fish, Margaret B; Nakayama, Takuya; Fisher, Marilyn; Hirsch, Nicolas; Cox, Amanda; Reeder, Rollin; Carruthers, Samantha; Hall, Amanda; Stemple, Derek L; Grainger, Robert M

    2014-11-15

    The retinal anterior homeobox (rax) gene encodes a transcription factor necessary for vertebrate eye development. rax transcription is initiated at the end of gastrulation in Xenopus, and is a key part of the regulatory network specifying anterior neural plate and retina. We describe here a Xenopus tropicalis rax mutant, the first mutant analyzed in detail from a reverse genetic screen. As in other vertebrates, this nonsense mutation results in eyeless animals, and is lethal peri-metamorphosis. Tissue normally fated to form retina in these mutants instead forms tissue with characteristics of diencephalon and telencephalon. This implies that a key role of rax, in addition to defining the eye field, is in preventing alternative forebrain identities. Our data highlight that brain and retina regions are not determined by the mid-gastrula stage but are by the neural plate stage. An RNA-Seq analysis and in situ hybridization assays for early gene expression in the mutant revealed that several key eye field transcription factors (e.g. pax6, lhx2 and six6) are not dependent on rax activity through neurulation. However, these analyses identified other genes either up- or down-regulated in mutant presumptive retinal tissue. Two neural patterning genes of particular interest that appear up-regulated in the rax mutant RNA-seq analysis are hesx1 and fezf2. These genes were not previously known to be regulated by rax. The normal function of rax is to partially repress their expression by an indirect mechanism in the presumptive retina region in wildtype embryos, thus accounting for the apparent up-regulation in the rax mutant. Knock-down experiments using antisense morpholino oligonucleotides directed against hesx1 and fezf2 show that failure to repress these two genes contributes to transformation of presumptive retinal tissue into non-retinal forebrain identities in the rax mutant.

  10. Revealing the consequences and errors of substance arising from the inverse confusion between the crystal (ligand) field quantities and the zero-field splitting ones

    NASA Astrophysics Data System (ADS)

    Rudowicz, Czesław; Karbowiak, Mirosław

    2015-01-01

    Survey of recent literature has revealed a doubly-worrying tendency concerning the treatment of the two distinct types of Hamiltonians, namely, the physical crystal field (CF), or equivalently ligand field (LF), Hamiltonians and the zero-field splitting (ZFS) Hamiltonians, which appear in the effective spin Hamiltonians (SH). The nature and properties of the CF (LF) Hamiltonians have been mixed up in various ways with those of the ZFS Hamiltonians. Such cases have been identified in a rapidly growing number of studies of the transition-ion based systems using electron magnetic resonance (EMR), optical spectroscopy, and magnetic measurements. These findings have far ranging implications since these Hamiltonians are cornerstones for interpretation of magnetic and spectroscopic properties of the single transition ions in various crystals or molecules as well as the exchange coupled systems (ECS) of transition ions, e.g. single molecule magnets (SMM) or single ion magnets (SIM). The seriousness of the consequences of such conceptual problems and related terminological confusions has reached a level that goes far beyond simple semantic issues or misleading keyword classifications of papers in journals and scientific databases. The prevailing confusion, denoted as the CF=ZFS confusion, pertains to the cases of labeling the true ZFS quantities as purportedly the CF (LF) quantities. Here we consider the inverse confusion between the CF (LF) quantities and the SH (ZFS) ones, denoted the ZFS=CF confusion, which consists in referring to the parameters (or Hamiltonians), which are the true CF (LF) quantities, as purportedly the ZFS (or SH) quantities. Specific cases of the ZFS=CF confusion identified in recent textbooks, reviews and papers, especially SMM- and SIM-related ones, are surveyed and the pertinent misconceptions are clarified. The serious consequences of the terminological confusions include misinterpretation of data from a wide range of experimental techniques and

  11. Time Series Measurements of Diffuse Hydrothermal Flow at the ASHES Vent Field Reveal Tidally Modulated Heat and Volume Flux

    NASA Astrophysics Data System (ADS)

    Mittelstaedt, E. L.; Fornari, D. J.; Crone, T. J.

    2015-12-01

    Existing time-series measurements of temperature and velocity of diffuse hydrothermal fluids exhibit variability over a range of periods from seconds to days. Frequency analysis of these measurements reveals differences between studies and field locations including nearly white spectra, as well as spectra with peaks at tidal and inertial periods. Based upon these results, previous authors have suggested several processes that may control diffuse flow rates, including tidally induced currents and 'tidal pumping', and have also suggested that there are no systematic controls. To further investigate the processes that control variability in diffuse flow, we use data from a new, deep-sea camera and temperature measurement system, the Diffuse Effluent Measurement System (DEMS), deployed during the July, 2014 cruise of the R/V Atlantis. The DEMS was deployed with DSV Alvin above a fracture network at the Phoenix vent within the ASHES vent field (Axial Seamount, 1541 mbsl). The system collected 20 seconds of imagery at 20 Hz and 24 seconds of temperature measurements at 1 Hz each hour over the period between July 22 and August 2nd. Velocities of the upwelling fluids were calculated using Diffuse Fluid Velocimetry (DFV; Mittelstaedt et al., 2010). DFV is a cross correlation technique that tracks moving index of refraction anomalies (i.e., hot parcels of fluid) through time. Over the ~12 day deployment, median flow rates ranged from 0.5 cm/s to 6 cm/s and mean fluid temperature anomalies from 0°C up to ~6.5°C, yielding an average heat flux density of 0.23 MW/m2. Spectral analysis of both the measured temperatures and calculated velocities yield a peak in normalized power at the semi-diurnal lunar period (M2, 12.4hrs), but no other spectral peaks above the 95% confidence level. Here, we present these results and discuss their implications for the tidal current and tidal pressure models of diffuse flow variability at the ASHES vent field.

  12. Effect of the Reaction Field on Molecular Forces and Torques Revealed by an Image-Charge Solvation Model.

    PubMed

    Song, Wei; Lin, Yuchun; Baumketner, Andrij; Deng, Shaozhong; Cai, Wei; Jacobs, Donald J

    2013-01-01

    We recently developed the Image-Charge Solvation Model (ICSM), which is an explicit/implicit hybrid model to accurately account for long-range electrostatic forces in molecular dynamics simulations [Lin et al., J. Chem. Phys., 131, 154103, 2009]. The ICSM has a productive spherical volume within the simulation cell for which key physical properties of bulk water are reproduced, such as density, radial distribution function, diffusion constants and dielectric properties. Although the reaction field (RF) is essential, it typically accounts for less than 2% of the total electrostatic force on a water molecule. This observation motivates investigating further the role of the RF within the ICSM. In this report we focus on distributions of forces and torques on water molecules as a function of distance from the origin and make extensive tests over a range of model parameters where Coulomb forces are decomposed into direct interactions from waters modeled explicitly and the RF. Molecular torques due to the RF typically account for 20% of the total torque, revealing why the RF plays an important role in the dielectric properties of simulated water. Moreover, it becomes clear that the buffer layer in the ICSM is essential to mitigate artifacts caused by the discontinuous change in dielectric constants at the explicit/implicit interface.

  13. Effect of the Reaction Field on Molecular Forces and Torques Revealed by an Image-Charge Solvation Model.

    PubMed

    Song, Wei; Lin, Yuchun; Baumketner, Andrij; Deng, Shaozhong; Cai, Wei; Jacobs, Donald J

    2013-01-01

    We recently developed the Image-Charge Solvation Model (ICSM), which is an explicit/implicit hybrid model to accurately account for long-range electrostatic forces in molecular dynamics simulations [Lin et al., J. Chem. Phys., 131, 154103, 2009]. The ICSM has a productive spherical volume within the simulation cell for which key physical properties of bulk water are reproduced, such as density, radial distribution function, diffusion constants and dielectric properties. Although the reaction field (RF) is essential, it typically accounts for less than 2% of the total electrostatic force on a water molecule. This observation motivates investigating further the role of the RF within the ICSM. In this report we focus on distributions of forces and torques on water molecules as a function of distance from the origin and make extensive tests over a range of model parameters where Coulomb forces are decomposed into direct interactions from waters modeled explicitly and the RF. Molecular torques due to the RF typically account for 20% of the total torque, revealing why the RF plays an important role in the dielectric properties of simulated water. Moreover, it becomes clear that the buffer layer in the ICSM is essential to mitigate artifacts caused by the discontinuous change in dielectric constants at the explicit/implicit interface. PMID:23833681

  14. Parallelization of a spatial random field characterization process using the Method of Anchored Distributions and the HTCondor high throughput computing system

    NASA Astrophysics Data System (ADS)

    Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.

    2013-12-01

    A new software application called MAD# has been coupled with the HTCondor high throughput computing system to aid scientists and educators with the characterization of spatial random fields and enable understanding the spatial distribution of parameters used in hydrogeologic and related modeling. MAD# is an open source desktop software application used to characterize spatial random fields using direct and indirect information through Bayesian inverse modeling technique called the Method of Anchored Distributions (MAD). MAD relates indirect information with a target spatial random field via a forward simulation model. MAD# executes inverse process running the forward model multiple times to transfer information from indirect information to the target variable. MAD# uses two parallelization profiles according to computational resources available: one computer with multiple cores and multiple computers - multiple cores through HTCondor. HTCondor is a system that manages a cluster of desktop computers for submits serial or parallel jobs using scheduling policies, resources monitoring, job queuing mechanism. This poster will show how MAD# reduces the time execution of the characterization of random fields using these two parallel approaches in different case studies. A test of the approach was conducted using 1D problem with 400 cells to characterize saturated conductivity, residual water content, and shape parameters of the Mualem-van Genuchten model in four materials via the HYDRUS model. The number of simulations evaluated in the inversion was 10 million. Using the one computer approach (eight cores) were evaluated 100,000 simulations in 12 hours (10 million - 1200 hours approximately). In the evaluation on HTCondor, 32 desktop computers (132 cores) were used, with a processing time of 60 hours non-continuous in five days. HTCondor reduced the processing time for uncertainty characterization by a factor of 20 (1200 hours reduced to 60 hours.)

  15. Analysis of Two Randomized Field Trials Testing the Effects of Online Vocabulary Instruction on Vocabulary Test Scores

    ERIC Educational Resources Information Center

    Fehr, Charles Norman

    2011-01-01

    Learning to read requires knowledge of word meanings for those words most commonly encountered in basic reading materials. Many young students lack the basic vocabulary knowledge needed to facilitate learning to read. Two randomized studies were conducted to test the effects of an online, computer-adaptive vocabulary instruction program designed…

  16. The conditional independences between variables derived from two independent identically distributed Markov random fields when pairwise order is ignored.

    PubMed

    Thomas, Alun

    2010-09-01

    A result for the equivalence of conditional independence graphs of ordered and unordered vector random variables from first-order Markov models is extended to arbitrary forests. The result is relevant to estimating graphical models for linkage disequilibrium between genetic loci. It explains why, in terms of the conditional independence structure, it sometimes does not matter whether you consider haplotypes or genotypes.

  17. Micro-digitate Silica Structures on Earth and Mars: Potential Biosignatures Revealed in the Geyser Field of El Tatio, Chile

    NASA Astrophysics Data System (ADS)

    Ruff, S. W.; Farmer, J. D.

    2015-12-01

    Opaline silica outcrops and soil identified by the Spirit rover adjacent to "Home Plate" in Gusev crater are associated with a suite of geologic features that demonstrates that they are the products of a volcanic hydrothermal system, the first such example verified on Mars [1]. Fumarolic acid-sulfate leaching of basaltic precursor materials was suggested as the origin of the opaline silica, based largely on geochemical arguments. A more complete analysis by Ruff et al. [2] included stratigraphic and textural observations of the outcrops to advance the hypothesis of a hot spring and/or geyser-related origin under alkaline-neutral conditions; acid-sulfate leaching appears much less tenable. But the nodular expression of many of the outcrops and sub-cm-scale "digitate protrusions" they contain remained enigmatic, precluding a complete explanation for the silica. Now, new observations of silica deposits produced in small discharge channels from hot springs and geysers in a high elevation geothermal field known as El Tatio in the Atacama Desert of northern Chile reveal remarkably similar features, including infrared spectral characteristics and what we describe here as micro-digitate silica structures. We hypothesize that these structures at El Tatio arise through microbial mediation of silica precipitation, i.e., that they are microstromatolites and that they provide favorable environments for the capture and preservation of microbial biosignatures. Similar features have been identified among hot spring silica deposits in Yellowstone National Park, the Taupo Volcanic Zone of New Zealand, and Iceland [e.g., 3; 4; 5]. Our ongoing field and lab studies are intended provide a robust assessment of the biogenicity of the micro-digitate silica structures and other aspects of El Tatio silica sinter deposits and test their viability as direct analogs to similar features found among the Home Plate silica deposits on Mars. [1] Squyres, S. W., et al. (2008), Science, 320, 1063

  18. FRET imaging and statistical signal processing reveal positive and negative feedback loops regulating the morphology of randomly migrating HT-1080 cells.

    PubMed

    Kunida, Katsuyuki; Matsuda, Michiyuki; Aoki, Kazuhiro

    2012-05-15

    Cell migration plays an important role in many physiological processes. Rho GTPases (Rac1, Cdc42, RhoA) and phosphatidylinositols have been extensively studied in directional cell migration. However, it remains unclear how Rho GTPases and phosphatidylinositols regulate random cell migration in space and time. We have attempted to address this issue using fluorescence resonance energy transfer (FRET) imaging and statistical signal processing. First, we acquired time-lapse images of random migration of HT-1080 fibrosarcoma cells expressing FRET biosensors of Rho GTPases and phosphatidyl inositols. We developed an image-processing algorithm to extract FRET values and velocities at the leading edge of migrating cells. Auto- and cross-correlation analysis suggested the involvement of feedback regulations among Rac1, phosphatidyl inositols and membrane protrusions. To verify the feedback regulations, we employed an acute inhibition of the signaling pathway with pharmaceutical inhibitors. The inhibition of actin polymerization decreased Rac1 activity, indicating the presence of positive feedback from actin polymerization to Rac1. Furthermore, treatment with PI3-kinase inhibitor induced an adaptation of Rac1 activity, i.e. a transient reduction of Rac1 activity followed by recovery to the basal level. In silico modeling that reproduced the adaptation predicted the existence of a negative feedback loop from Rac1 to actin polymerization. Finally, we identified MLCK as the probable controlling factor in the negative feedback. These findings quantitatively demonstrate positive and negative feedback loops that involve actin, Rac1 and MLCK, and account for the ordered patterns of membrane dynamics observed in randomly migrating cells.

  19. Hidden local symmetry of Eu{sup 3+} in xenotime-like crystals revealed by high magnetic fields

    SciTech Connect

    Han, Yibo; Ma, Zongwei; Zhang, Junpei; Wang, Junfeng; Du, Guihuan; Xia, Zhengcai; Han, Junbo Li, Liang; Yu, Xuefeng

    2015-02-07

    The excellent optical properties of europium-doped crystals in visible and near infrared wavelength regions enable them to have broad applications in optoelectronics, laser crystals and sensing devices. The local site crystal fields can affect the intensities and peak positions of the photo-emission lines strongly, but they are usually difficult to be clarified due to magnetically degenerate 4f electronic levels coupling with the crystal fields. Here, we provide an effective way to explore the hidden local symmetry of the Eu{sup 3+} sites in different hosts by taking photoluminescence measurements under pulsed high magnetic fields up to 46 T. The zero-field photoluminescence peaks split further at high magnetic fields when the Zeeman splitting energy is comparable to or larger than that of the crystal field induced zero-field splitting. In particular, a magnetic field induced crossover of the local crystal fields has been observed in the GdVO{sub 4}:Eu{sup 3+} crystal, which resulted from the alignment of Gd{sup 3+} magnetic moment in high magnetic fields; and a hexagonally symmetric local crystal fields was observed in the YPO{sub 4} nanocrystals at the Eu{sup 3+} sites characterized by the special axial and rhombic crystal field terms. These distinct Zeeman splitting behaviors uncover the crystal fields-related local symmetry of luminescent Eu{sup 3+} centers in different hosts or magnetic environments, which are significant for their applications in optics and optoelectronics.

  20. Radio polarization maps of shell-type supernova remnants - I. Effects of a random magnetic field component and thin-shell models

    NASA Astrophysics Data System (ADS)

    Bandiera, R.; Petruk, O.

    2016-06-01

    The maps of intensity and polarization of the radio synchrotron emission from shell-type supernova remnants (SNRs) contain a considerable amount of information, although of not easy interpretation. With the aim of deriving constraints on the 3D spatial distribution of the emissivity, as well as on the structure of both ordered and random magnetic fields (MFs), we present here a scheme to model maps of the emission and polarization in SNRs. We first generalize the classical treatment of the synchrotron emission to the case in which the MF is composed of an ordered MF plus an isotropic random component, with arbitrary relative strengths. For a power-law particle energy distribution, we derive analytic formulae that formally resemble those for the classical case. We also treat the shock compression of a fully random upstream field and we predict that the polarization fraction in this case should be higher than typically measured in SNRs. We implement the above treatment into a code, which simulates the observed polarized emission of an emitting shell, taking into account also the effect of the internal Faraday rotation. Finally, we show simulated maps for different orientations with respect to the observer, levels of the turbulent MF component, Faraday rotation levels, distributions of the emissivity (either barrel-shaped or limited to polar caps) and geometries for the ordered MF component (either tangential to the shell or radial). Their analysis allows us to outline properties useful for the interpretation of radio intensity and polarization maps.