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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 fields reveal an N-terminal double beta-propeller motif as part of a bacterial hybrid two-component sensor system

    PubMed Central

    Menke, Matt; Berger, Bonnie; Cowen, Lenore

    2010-01-01

    The recent explosion in newly sequenced bacterial genomes is outpacing the capacity of researchers to try to assign functional annotation to all the new proteins. Hence, computational methods that can help predict structural motifs provide increasingly important clues in helping to determine how these proteins might function. We introduce a Markov Random Field approach tailored for recognizing proteins that fold into mainly β-structural motifs, and apply it to build recognizers for the β-propeller shapes. As an application, we identify a potential class of hybrid two-component sensor proteins, that we predict contain a double-propeller domain. PMID:20147619

  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. PMID:26080050

  5. Summer School Effects in a Randomized Field Trial

    ERIC Educational Resources Information Center

    Zvoch, Keith; Stevens, Joseph J.

    2013-01-01

    This field-based randomized trial examined the effect of assignment to and participation in summer school for two moderately at-risk samples of struggling readers. Application of multiple regression models to difference scores capturing the change in summer reading fluency revealed that kindergarten students randomly assigned to summer school…

  6. Defect Detection Using Hidden Markov Random Fields

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

    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.

  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. Digital servo control of random sound fields

    NASA Technical Reports Server (NTRS)

    Nakich, R. B.

    1973-01-01

    It is necessary to place number of sensors at different positions in sound field to determine actual sound intensities to which test object is subjected. It is possible to determine whether specification is being met adequately or exceeded. Since excitation is of random nature, signals are essentially coherent and it is impossible to obtain true average.

  9. Interfaces in Random Field Ising Systems

    NASA Astrophysics Data System (ADS)

    Seppälä, Eira

    2001-03-01

    Domain walls are studied in random field Ising magnets at T=0 in two and three dimensions using exact ground state calculations. In 2D below the random field strength dependent length scale Lb the walls exhibit a super-rough behavior with a roughness exponent greater than unity ζ ~= 1.20 ± 0.05. The nearest-neighbor height difference probability distribution depends on the system size below L_b. Above Lb domains become fractal, ζ ~= 1.(E. T. Seppälä, V. Petäjä, and M. J. Alava, Phys. Rev. E 58), R5217 (1998). The energy fluctuation exponent has a value θ=1, contradicting the exponent relation θ = 2ζ -1 due to the broken scale-invariance, below Lb and vanishes for system sizes above L_b. The broken scale-invariance should be manifest also in Kardar-Parisi-Zhang problem with random-field noise.(E. Frey, U. C. Täuber, and H. K. Janssen, Europhys. Lett. 47), 14 (1999). In 3D there exists a transition between ferromagnetic and paramagnetic phases at the critical random field strength (Δ/J)_c. Below (Δ/J)c the roughness exponent is also greater ζ ~= 0.73 ± 0.03 than the functional-renormalization-group calculation result ζ = (5-d)/3.(D. Fisher, Phys. Rev. Lett. 56), 1964 (1986).(P. Chauve, P. Le Doussal, and K. Wiese, cond-mat/0006056.) The height differences are system size dependent in 3D, as well. The behavior of the domain walls in 2D below Lb with a constant external field, i.e., the random-bulk wetting, is demonstrated.(E. T. Seppälä, I. Sillanpää, and M. J. Alava, unpublished.)

  10. Random fields at a nonequilibrium phase transition.

    PubMed

    Barghathi, Hatem; Vojta, Thomas

    2012-10-26

    We study nonequilibrium phase transitions in the presence of disorder that locally breaks the symmetry between two equivalent macroscopic states. In low-dimensional equilibrium systems, such random-field disorder is known to have dramatic effects: it prevents spontaneous symmetry breaking and completely destroys the phase transition. In contrast, we show that the phase transition of the one-dimensional generalized contact process persists in the presence of random-field disorder. The ultraslow dynamics in the symmetry-broken phase is described by a Sinai walk of the domain walls between two different absorbing states. We discuss the generality and limitations of our theory, and we illustrate our results by large-scale Monte Carlo simulations. PMID:23215170

  11. 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

  12. 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

  13. Efficient prediction designs for random fields

    PubMed Central

    Müller, Werner G; Pronzato, Luc; Rendas, Joao; Waldl, Helmut

    2015-01-01

    For estimation and predictions of random fields, it is increasingly acknowledged that the kriging variance may be a poor representative of true uncertainty. Experimental designs based on more elaborate criteria that are appropriate for empirical kriging (EK) are then often non-space-filling and very costly to determine. In this paper, we investigate the possibility of using a compound criterion inspired by an equivalence theorem type relation to build designs quasi-optimal for the EK variance when space-filling designs become unsuitable. Two algorithms are proposed, one relying on stochastic optimization to explicitly identify the Pareto front, whereas the second uses the surrogate criteria as local heuristic to choose the points at which the (costly) true EK variance is effectively computed. We illustrate the performance of the algorithms presented on both a simple simulated example and a real oceanographic dataset. © 2014 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons, Ltd. PMID:26300698

  14. Neutrino conversions in solar random magnetic fields

    NASA Astrophysics Data System (ADS)

    Semikoz, V. B.; Torrente-Lujan, E.

    1999-09-01

    We consider the effect of a random magnetic field in the convective zone of the Sun superimposed to a regular magnetic field on resonant neutrino spin-flavor oscillations. We argue for the existence of a field of strongly chaotic nature at the bottom of the convective zone. In contrast to previous attempts we employ a model motivated regular magnetic field profile: it is a static field solution to the solar equilibrium hydro-magnetic equations. These solutions have been known for a long time in the literature. We show for the first time that in addition they are twisting solutions. In this scenario electron antineutrinos are produced through cascades like νeL-->νμL-- >ν~eR, The detection of ν~eR at Earth would be a long-awaited signature of the Majorana nature of the neutrino. The expected signals in the different experiments (SK, GALLEX-SAGE, Homestake) are obtained as a function of the level of noise, regular magnetic field and neutrino mixing parameters. Previous results obtained for small mixing and ad-hoc regular magnetic profiles are reobtained. We confirm the strong suppression for a large part of the parameter space of the ν~eR-flux for high energy boron neutrinos in agreement with present data of the SK experiment. We find that MSW (Mikheyev-Smirnov-Wolfenstein) regions (Δm2~=10-5 eV2, both small and large mixing solutions) are stable up to very large levels of noise (P=0.7-0.8) but they are acceptable from the point of view of antineutrino production only for moderate levels of noise (P~=0.95). For strong noise and a reasonable regular magnetic field, any parameter region (Δm2, sin 2 2θ) is excluded. As a consequence, we are allowed to reverse the problem and to put limits on the r.m.s. field strength and transition magnetic moments by demanding a particle physics solution to the SNP in this scenario.

  15. 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.

  16. Conrad: gene prediction using conditional random fields.

    PubMed

    DeCaprio, David; Vinson, Jade P; Pearson, Matthew D; Montgomery, Philip; Doherty, Matthew; Galagan, James E

    2007-09-01

    We present Conrad, the first comparative gene predictor based on semi-Markov conditional random fields (SMCRFs). Unlike the best standalone gene predictors, which are based on generalized hidden Markov models (GHMMs) and trained by maximum likelihood, Conrad is discriminatively trained to maximize annotation accuracy. In addition, unlike the best annotation pipelines, which rely on heuristic and ad hoc decision rules to combine standalone gene predictors with additional information such as ESTs and protein homology, Conrad encodes all sources of information as features and treats all features equally in the training and inference algorithms. Conrad outperforms the best standalone gene predictors in cross-validation and whole chromosome testing on two fungi with vastly different gene structures. The performance improvement arises from the SMCRF's discriminative training methods and their ability to easily incorporate diverse types of information by encoding them as feature functions. On Cryptococcus neoformans, configuring Conrad to reproduce the predictions of a two-species phylo-GHMM closely matches the performance of Twinscan. Enabling discriminative training increases performance, and adding new feature functions further increases performance, achieving a level of accuracy that is unprecedented for this organism. Similar results are obtained on Aspergillus nidulans comparing Conrad versus Fgenesh. SMCRFs are a promising framework for gene prediction because of their highly modular nature, simplifying the process of designing and testing potential indicators of gene structure. Conrad's implementation of SMCRFs advances the state of the art in gene prediction in fungi and provides a robust platform for both current application and future research. PMID:17690204

  17. Cluster Mass Inference via Random Field Theory

    PubMed Central

    Zhang, Hui; Nichols, Thomas E.; Johnson, Timothy D.

    2009-01-01

    Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference method available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single-subject and a group fMRI dataset demonstrate better power than traditional cluster extent inference, and good accuracy relative to a gold-standard permutation test. PMID:18805493

  18. Random Field effects in perpendicular-anisotropy multilayer films

    NASA Astrophysics Data System (ADS)

    Xu, Jian; Silevitch, Daniel; Rosenbaum, Thomas

    With the application of a magnetic field transverse to the magnetic easy axis, randomly-distributed 3D collections of dipole-coupled Ising spins form a realization of the Random-Field Ising Model. Tuning the strength of the site-specific random field, and hence the disorder, via the applied transverse field regulates the domain reversal energetics and hence the macroscopic hysteresis loop. We extend this approach to two dimensions, using sputtered Perpendicular Magnetic Anisotropy (PMA) Co/Pt multilayer thin films. We characterize the coercive fields and hysteresis loops at a series of temperatures and transverse fields.

  19. Simulation of 3D infrared scenes using random fields model

    NASA Astrophysics Data System (ADS)

    Shao, Xiaopeng; Zhang, Jianqi

    2001-09-01

    Analysis and simulation of smart munitions requires imagery for the munition's sensor to view. The traditional infrared background simulations are always limited in the plane scene studies. A new method is described to synthesize the images in 3D view and with various terrains texture. We develop the random fields model and temperature fields to simulate 3D infrared scenes. Generalized long-correlation (GLC) model, one of random field models, will generate both the 3D terrains skeleton data and the terrains texture in this work. To build the terrain mesh with the random fields, digital elevation models (DEM) are introduced in the paper. And texture mapping technology will perform the task of pasting the texture in the concavo-convex surfaces of the 3D scene. The simulation using random fields model is a very available method to produce 3D infrared scene with great randomicity and reality.

  20. Ordering and phase transitions in random-field Ising systems

    NASA Technical Reports Server (NTRS)

    Maritan, Amos; Swift, Michael R.; Cieplak, Marek; Chan, Moses H. W.; Cole, Milton W.; Banavar, Jayanth R.

    1991-01-01

    An exact analysis of the Ising model with infinite-range interactions in a random field and a local mean-field theory in three dimensions is carried out leading to a phase diagram with several coexistence surfaces and lines of critical points. The results show that the phase diagram depends crucially on whether the distribution of random fields is symmetric or not. Thus, Ising-like phase transitions in a porous medium (the asymmetric case) are in a different universality class from the conventional random-field model (symmetric case).

  1. 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.

  2. 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.

  3. Creating order with the help of randomness: generating transversely random, longitudinally invariant vector optical fields.

    PubMed

    Khonina, Svetlana N; Golub, Ilya

    2015-09-01

    We show that it is possible to generate transversely random, diffraction-free/longitudinally invariant vector optical fields. The randomness in transverse polarization distribution complements a previously studied one in intensity of scalar Bessel-type beams, adding another degree of freedom to control these beams. Moreover, we show that the relative transversely random phase distribution is also conserved along the optical axis. Thus, intensity, phase, and polarization of Bessel-type beams can be transversely random/arbitrary while invariant upon propagation. Such fields may find applications in encryption/secure communications, optical trapping, etc. PMID:26368714

  4. 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.

  5. Diffusion of charged particles in a random magnetic field

    NASA Technical Reports Server (NTRS)

    Earl, J. A.

    1972-01-01

    When charged particles move in a random magnetic field superimposed upon a relatively large constant field, their pitch angle distribution can be calculated to any desired precision by an iterative approximation procedure. Improved knowledge of the pitch angle distribution and of the characteristic time for relaxation of anisotropy leads to an accurate expression for the coefficient of diffusion parallel to the mean field.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. A universal form of slow dynamics in zero-temperature random-field Ising model

    NASA Astrophysics Data System (ADS)

    Ohta, H.; Sasa, S.

    2010-04-01

    The zero-temperature Glauber dynamics of the random-field Ising model describes various ubiquitous phenomena such as avalanches, hysteresis, and related critical phenomena. Here, for a model on a random graph with a special initial condition, we derive exactly an evolution equation for an order parameter. Through a bifurcation analysis of the obtained equation, we reveal a new class of cooperative slow dynamics with the determination of critical exponents.

  11. 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.

  12. 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.

  13. 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.

  14. MC Estimator Variance Reduction with Antithetic and Common Random Fields

    NASA Astrophysics Data System (ADS)

    Guthke, P.; Bardossy, A.

    2011-12-01

    Monte Carlo methods are widely used to estimate the outcome of complex physical models. For physical models with spatial parameter uncertainty, it is common to apply spatial random functions to the uncertain variables, which can then be used to interpolate between known values or to simulate a number of equally likely realizations .The price, that has to be paid for such a stochastic approach, are many simulations of the physical model instead of just running one model with one 'best' input parameter set. The number of simulations is often limited because of computational constraints, so that a modeller has to make a compromise between the benefit in terms of an increased accuracy of the results and the effort in terms of a massively increased computational time. Our objective is, to reduce the estimator variance of dependent variables in Monte Carlo frameworks. Therefore, we adapt two variance reduction techniques (antithetic variates and common random numbers) to a sequential random field simulation scheme that uses copulas as spatial dependence functions. The proposed methodology leads to pairs of spatial random fields with special structural properties, that are advantageous in MC frameworks. Antithetic Random fields (ARF) exhibit a reversed structure on the large scale, while the dependence on the local scale is preserved. Common random fields (CRF) show the same large scale structures, but different spatial dependence on the local scale. The performances of the proposed methods are examined with two typical applications of stochastic hydrogeology. It is shown, that ARF have the property to massively reduce the number of simulation runs required for convergence in Monte Carlo frameworks while keeping the same accuracy in terms of estimator variance. Furthermore, in multi-model frameworks like in sensitivity analysis of the spatial structure, where more than one spatial dependence model is used, the influence of different dependence structures becomes obvious

  15. 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

  16. 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…

  17. Can fluctuations of classical random field produce quantum averages?

    NASA Astrophysics Data System (ADS)

    Khrennikov, Andrei

    2009-08-01

    Albert Einstein did not believe in completeness of QM. He dreamed of creation of prequantum classical statistical mechanics such that QM will be reproduced as its approximation. He also dreamed of total exclusion of corpuscules from the future model. Reality of Einstein's dream was pure fields' reality. Recently I made his dream come true in the form of so called prequantum classical statistical field theory (PCSFT). In this approach quantum systems are described by classical random fields, e.g., electromagnetic field (instead of photon), electron field or neutron field. In this paper we generalize PCSFT to composite quantum system. It is well known that in QM, unlike classical mechanics, the state of a composite system is described by the tensor product of state spaces for its subsystems. In PCSFT one can still use Cartesian product, but state spaces are spaces of classical fields (not particles). In particular, entanglement is nothing else than correlation of classical random fields, cf. again Einstein. Thus entanglement was finally demystified.

  18. Three-dimensional extinction mapping using Gaussian random fields

    NASA Astrophysics Data System (ADS)

    Sale, S. E.; Magorrian, J.

    2014-11-01

    We present a scheme for using stellar catalogues to map the three-dimensional distributions of extinction and dust within our Galaxy. Extinction is modelled as a Gaussian random field, whose covariance function is set by a simple physical model of the interstellar medium that assumes a Kolmogorov-like power spectrum of turbulent fluctuations. As extinction is modelled as a random field, the spatial resolution of the resulting maps is set naturally by the data available; there is no need to impose any spatial binning. We verify the validity of our scheme by testing it on simulated extinction fields and show that its precision is significantly improved over previous dust-mapping efforts. The approach we describe here can make use of any photometric, spectroscopic or astrometric data; it is not limited to any particular survey. Consequently, it can be applied to a wide range of data from both existing and future surveys.

  19. 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.

  20. Transformation of phase transitions driven by an anisotropic random field

    NASA Astrophysics Data System (ADS)

    Popa-Nita, V.; Kralj, Samo

    2005-04-01

    We carry out a comparative study of the influence of a random anisotropy field on continuous and discontinuous phase transitions. The ordered phase, which is reached via a continuous symmetry breaking phase transition, is characterized by an order parameter and by a corresponding hydrodynamic continuum field. We assume that the response of the hydrodynamic field to the imposed disorder results in a domainlike pattern of the system. For a strong enough disorder both transitions become gradual. For weaker disorder strengths the disorder converts a second order transition into a discontinuous one.

  1. Disorder Identification in Hysteresis Data: Recognition Analysis of the Random-Bond-Random-Field Ising Model

    SciTech Connect

    Ovchinnikov, O. S.; Jesse, S.; Kalinin, S. V.; Bintacchit, P.; Trolier-McKinstry, S.

    2009-10-09

    An approach for the direct identification of disorder type and strength in physical systems based on recognition analysis of hysteresis loop shape is developed. A large number of theoretical examples uniformly distributed in the parameter space of the system is generated and is decorrelated using principal component analysis (PCA). The PCA components are used to train a feed-forward neural network using the model parameters as targets. The trained network is used to analyze hysteresis loops for the investigated system. The approach is demonstrated using a 2D random-bond-random-field Ising model, and polarization switching in polycrystalline ferroelectric capacitors.

  2. 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.

  3. 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.

  4. Phase conjugation with random fields and with deterministic and random scatterers

    SciTech Connect

    Gbur, G.; Wolf, E.

    1999-01-01

    The theory of distortion correction by phase conjugation, developed since the discovery of this phenomenon many years ago, applies to situations when the field that is conjugated is monochromatic and the medium with which it interacts is deterministic. In this Letter a generalization of the theory is presented that applies to phase conjugation of partially coherent waves interacting with either deterministic or random weakly scattering nonabsorbing media. {copyright} {ital 1999} {ital Optical Society of America}

  5. Synthetic aperture radar system design for random field classification

    NASA Technical Reports Server (NTRS)

    Harger, R. O.

    1973-01-01

    An optimum design study is carried out for synthetic aperture radar systems intended for classifying randomly reflecting areas (such as agricultural fields) characterized by a reflectivity density spectral density. The problem solution is obtained, neglecting interfield interference and assuming areas of known configuration and location, as well as a certain Gaussian signal field property. The optimum processor is nonlinear, but includes conventional matched filter processing. A set of summary design curves is plotted, and is applied to the design of a satellite synthetic aperture radar system.

  6. 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. PMID:25375468

  7. The excursion set approach in non-Gaussian random fields

    NASA Astrophysics Data System (ADS)

    Musso, Marcello; Sheth, Ravi K.

    2014-04-01

    Insight into a number of interesting questions in cosmology can be obtained by studying the first crossing distributions of physically motivated barriers by random walks with correlated steps: higher mass objects are associated with walks that cross the barrier in fewer steps. We write the first crossing distribution as a formal series, ordered by the number of times a walk upcrosses the barrier. Since the fraction of walks with many upcrossings is negligible if the walk has not taken many steps, the leading order term in this series is the most relevant for understanding the massive objects of most interest in cosmology. For walks associated with Gaussian random fields, this first term only requires knowledge of the bivariate distribution of the walk height and slope, and provides an excellent approximation to the first crossing distribution for all barriers and smoothing filters of current interest. We show that this simplicity survives when extending the approach to the case of non-Gaussian random fields. For non-Gaussian fields which are obtained by deterministic transformations of a Gaussian, the first crossing distribution is simply related to that for Gaussian walks crossing a suitably rescaled barrier. Our analysis shows that this is a useful way to think of the generic case as well. Although our study is motivated by the possibility that the primordial fluctuation field was non-Gaussian, our results are general. In particular, they do not assume the non-Gaussianity is small, so they may be viewed as the solution to an excursion set analysis of the late-time, non-linear fluctuation field rather than the initial one. They are also useful for models in which the barrier height is determined by quantities other than the initial density, since most other physically motivated variables (such as the shear) are usually stochastic and non-Gaussian. We use the Lognormal transformation to illustrate some of our arguments.

  8. 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.

  9. 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.

  10. Propagation of acoustic pulses in random gravity wave fields

    NASA Astrophysics Data System (ADS)

    Millet, Christophe; de La Camara, Alvaro; Lott, François

    2015-11-01

    A linear solution modeling the interaction between an incoming acoustic wave and a randomly perturbed atmosphere is developed, using the normal mode method. The wave mode structure is determined by a sound speed profile that is confining. The environmental uncertainty is described by a stochastic field obtained with a multiwave stochastic parameterization of gravity waves (GW). Using the propagating modes of the unperturbed atmosphere, the wave propagation problem is reduced to solving a system of ordinary differential equations. We focus on the asymptotic behavior of the transmitted waves in the weakly heterogeneous regime. In this regime, the coupling between the acoustic pulse and the randomly perturbed waveguides is weak and the propagation distance must be large enough for the wave to experience significant scattering. A general expression for the pressure far-field is derived in terms of saddle-point contributions. The saddle-points are obtained from a WKB approximation of the vertical eigenvalue problem. We present preliminary results that show how statistics of the transmitted signal are related to some eigenvalues and how an ``optimal'' GW field can trigger large deviations in the acoustic signals. The present model is used to explain the variability of infrasound signals.

  11. PREDICTION INTERVALS FOR INTEGRALS OF GAUSSIAN RANDOM FIELDS.

    PubMed

    De Oliveira, Victor; Kone, Bazoumana

    2015-03-01

    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

  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. Monte Carlo Integration Using Spatial Structure of Markov Random Field

    NASA Astrophysics Data System (ADS)

    Yasuda, Muneki

    2015-03-01

    Monte Carlo integration (MCI) techniques are important in various fields. In this study, a new MCI technique for Markov random fields (MRFs) is proposed. MCI consists of two successive parts: the first involves sampling using a technique such as the Markov chain Monte Carlo method, and the second involves an averaging operation using the obtained sample points. In the averaging operation, a simple sample averaging technique is often employed. The method proposed in this paper improves the averaging operation by addressing the spatial structure of the MRF and is mathematically guaranteed to statistically outperform standard MCI using the simple sample averaging operation. Moreover, the proposed method can be improved in a systematic manner and is numerically verified by numerical simulations using planar Ising models. In the latter part of this paper, the proposed method is applied to the inverse Ising problem and we observe that it outperforms the maximum pseudo-likelihood estimation.

  14. Mean field theory for scale-free random networks

    NASA Astrophysics Data System (ADS)

    Barabási, Albert-László; Albert, Réka; Jeong, Hawoong

    1999-10-01

    Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information is available display scale-free features. Here we study the scaling properties of the recently introduced scale-free model, that can account for the observed power-law distribution of the connectivities. We develop a mean-field method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the scaling exponents. The mean-field method can be used to address the properties of two variants of the scale-free model, that do not display power-law scaling.

  15. Critical Casimir forces in the presence of random surface fields

    NASA Astrophysics Data System (ADS)

    Maciołek, A.; Vasilyev, O.; Dotsenko, V.; Dietrich, S.

    2015-03-01

    We study critical Casimir forces (CCFs) fC for films of thickness L which in the three-dimensional bulk belong to the Ising universality class and which are exposed to random surface fields (RSFs) on both surfaces. We consider the case in which, in the absence of RSFs, the surfaces of the film belong to the surface universality class of the so-called ordinary transition. We carry out a finite-size scaling analysis and show that for weak disorder, CCFs still exhibit scaling, acquiring a random field scaling variable w that is zero for pure systems. We confirm these analytic predictions by Monte Carlo (MC) simulations. Moreover, our MC data show that fC varies as fC(w →0 ) -fC(w =0 ) ˜w2 . Asymptotically, for large L , w scales as w ˜L-0.26→0 , indicating that this type of disorder is an irrelevant perturbation of the ordinary surface universality class. However, for thin films such that w ≃1 , we find that the presence of RSFs with vanishing mean value increases significantly the strength of CCFs, as compared to systems without them, and it shifts the extremum of the scaling function of fC toward lower temperatures. But fC remains attractive.

  16. 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.

  17. Collapse transition of randomly branched polymers: renormalized field theory.

    PubMed

    Janssen, Hans-Karl; Stenull, Olaf

    2011-05-01

    We present a minimal dynamical model for randomly branched isotropic polymers, and we study this model in the framework of renormalized field theory. For the swollen phase, we show that our model provides a route to understand the well-established dimensional-reduction results from a different angle. For the collapse θ transition, we uncover a hidden Becchi-Rouet-Stora supersymmetry, signaling the sole relevance of tree configurations. We correct the long-standing one-loop results for the critical exponents, and we push these results on to two-loop order. For the collapse θ' transition, we find a runaway of the renormalization group flow, which lends credence to the possibility that this transition is a fluctuation-induced first-order transition. Our dynamical model allows us to calculate for the first time the fractal dimension of the shortest path on randomly branched polymers in the swollen phase as well as at the collapse transition and related fractal dimensions. PMID:21728509

  18. New description of charged particle propagation in random magnetic fields

    NASA Technical Reports Server (NTRS)

    Earl, James A.

    1994-01-01

    When charged particles spiral along a large constant magnetic field, their trajectories are scattered by random components that are superposed on the guiding field. In the simplest analysis of this situation, scattering causes the particles to diffuse parallel to the guiding field. At the next level of approximation, moving pulses that correspond to a coherent mode of propagation are present, but they are represented by delta-functions whose infinitely narrow width makes no sense physically and is inconsistent with the finite duration of coherent pulses observed in solar energetic particle events. To derive a more realistic description, the transport problem is formulated in terms of 4 x 4 matrices, which derive from a representation of the particle distribution function in terms of eigenfunctions of the scattering operator, and which lead to useful approximations that give explicit predictions of the detailed evolution not only of the coherent pulses, but also of the diffusive wake. More specifically, the new description embodies a simple convolution of a narrow Gaussian with the solutions above that involve delta-functions, but with a slightly reduced coherent velocity. The validity of these approximations, which can easily be calculated on a desktop computer, has been exhaustively confirmed by comparison with results of Monte Carlo simulations which kept track of 50 million particles and which were carried out on the Maspar computer at Goddard Space Flight Center.

  19. 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

  20. Multi-illuminant estimation with conditional random fields.

    PubMed

    Beigpour, Shida; Riess, Christian; van de Weijer, Joost; Angelopoulou, Elli

    2014-01-01

    Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimating the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an energy minimization task within a conditional random field over a set of local illuminant estimates. In order to quantitatively evaluate the proposed method, we created a novel data set of two-dominant-illuminant images comprised of laboratory, indoor, and outdoor scenes. Unlike prior work, our database includes accurate pixel-wise ground truth illuminant information. The performance of our method is evaluated on multiple data sets. Experimental results show that our framework clearly outperforms single illuminant estimators as well as a recently proposed multi-illuminant estimation approach. PMID:24144663

  1. 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

  2. Renormalized field theory of collapsing directed randomly branched polymers.

    PubMed

    Janssen, Hans-Karl; Wevelsiep, Frank; Stenull, Olaf

    2009-10-01

    We present a dynamical field theory for directed randomly branched polymers and in particular their collapse transition. We develop a phenomenological model in the form of a stochastic response functional that allows us to address several interesting problems such as the scaling behavior of the swollen phase and the collapse transition. For the swollen phase, we find that by choosing model parameters appropriately, our stochastic functional reduces to the one describing the relaxation dynamics near the Yang-Lee singularity edge. This corroborates that the scaling behavior of swollen branched polymers is governed by the Yang-Lee universality class as has been known for a long time. The main focus of our paper lies on the collapse transition of directed branched polymers. We show to arbitrary order in renormalized perturbation theory with epsilon expansion that this transition belongs to the same universality class as directed percolation. PMID:19905335

  3. 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

  4. 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.

  5. Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

    PubMed Central

    Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

    2015-01-01

    Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321

  6. Mean-Field Theory is Exact for the Random-Field Model with Long-Range Interactions

    NASA Astrophysics Data System (ADS)

    Tsuda, Junichi; Nishimori, Hidetoshi

    2014-07-01

    We study the classical spin model in random fields with long-range interactions and show the exactness of the mean-field theory under certain mild conditions. This is a generalization of the result of Mori for the non-random and spin-glass cases. To treat random fields, we evoke the self-averaging property of a function of random fields, without recourse to the replica method. The result is that the mean-field theory gives the exact expression of the canonical free energy for systems with power-decaying interactions if the power is smaller than or equal to the spatial dimension.

  7. Condensation of helium in aerogel and athermal dynamics of the random-field Ising model.

    PubMed

    Aubry, Geoffroy J; Bonnet, Fabien; Melich, Mathieu; Guyon, Laurent; Spathis, Panayotis; Despetis, Florence; Wolf, Pierre-Etienne

    2014-08-22

    High resolution measurements reveal that condensation isotherms of (4)He in high porosity silica aerogel become discontinuous below a critical temperature. We show that this behavior does not correspond to an equilibrium phase transition modified by the disorder induced by the aerogel structure, but to the disorder-driven critical point predicted for the athermal out-of-equilibrium dynamics of the random-field Ising model. Our results evidence the key role of nonequilibrium effects in the phase transitions of disordered systems. PMID:25192103

  8. Random fields and the weakly first-order phase transition in superconductors

    SciTech Connect

    Busiello, G.; De Cesare, L.; Uzunov, D.I.

    1986-10-01

    We study the influence of random fields with short-range and long-range correlations on the weakly first-order phase transition in superconductors. Renormalization-group (RG) analysis near the upper critical dimensionality d/sub u/ = 6 (short-range correlations) reveals a new critical behavior which holds if the number of the order-parameter components is n>10. In the long-range case, the RG transformation is self-consistent only if the parameter theta of the long-range correlations is assumed of order epsilon, epsilon = 6-d.

  9. Adaptive Thouless-Anderson-Palmer approach to inverse Ising problems with quenched random fields.

    PubMed

    Huang, Haiping; Kabashima, Yoshiyuki

    2013-06-01

    The adaptive Thouless-Anderson-Palmer equation is derived for inverse Ising problems in the presence of quenched random fields. We test the proposed scheme on Sherrington-Kirkpatrick, Hopfield, and random orthogonal models and find that the adaptive Thouless-Anderson-Palmer approach allows accurate inference of quenched random fields whose distribution can be either Gaussian or bimodal. In particular, another competitive method for inferring external fields, namely, the naive mean field method with diagonal weights, is compared and discussed. PMID:23848649

  10. Gaussian conditional random fields for regression in remote sensing

    NASA Astrophysics Data System (ADS)

    Radosavljevic, Vladan

    In recent years many remote sensing instruments of various properties have been employed in an attempt to better characterize important geophysical phenomena. Satellite instruments provide an exceptional opportunity for global long-term observations of the land, the biosphere, the atmosphere, and the oceans. The collected data are used for estimation and better understanding of geophysical parameters such as land cover type, atmospheric properties, or ocean temperature. Achieving accurate estimations of such parameters is an important requirement for development of models able to predict global climate changes. One of the most challenging climate research problems is estimation of global composition, load, and variability of aerosols, small airborne particles that reflect and absorb incoming solar radiation. The existing algorithm for aerosol prediction from satellite observations is deterministic and manually tuned by domain scientist. In contrast to domain-driven method, we show that aerosol prediction is achievable by completely data-driven approaches. These statistical methods consist of learning of nonlinear regression models to predict aerosol load using the satellite observations as inputs. Measurements from unevenly distributed ground-based sites over the world are used as proxy to ground-truth outputs. Although statistical methods achieve better accuracy than deterministic method this setup is appropriate when data are independently and identically distributed (IID). The IID assumption is often violated in remote sensing where data exhibit temporal, spatial, or spatio-temporal dependencies. In such cases, the traditional supervised learning approaches could result in a model with degraded accuracy. Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classification where the outputs are discrete. We propose a CRF model for continuous outputs

  11. Transverse Field and Random-Field Ising Ferromagnetism in Mn12-acetates

    NASA Astrophysics Data System (ADS)

    Subedi, Pradeep

    2013-03-01

    Single molecule magnets (SMMs) single crystals can exhibit long range ferromagnetic order associated with intermolecular interactions, principally magnetic dipole interactions. With their high spin (S ~ 10) and strong Ising-like magnetic anisotropy, they are model materials to the study of physics associated with Transverse-Field Ising Ferromagnet Model (TFIFM). We have measured magnetic susceptibility of single crystals of the prototype SMM, Mn12-acetate, and of a new high-symmetry variant, Mn12-ac-MeOH. At zero transverse field the inverse susceptibility of both SMMs is found to accurately follow a Curie-Weiss law with an intercept at a non-zero temperature Tcw ~ 0.9 K, indicating a transition to a ferromagnetic phase due to dipolar interactions. With increasing transverse field, the susceptibility and the Curie-Weiss temperature decreases due to increase in spin fluctuations but the nature of the decrease is very different in the two materials. We find that in Mn12-ac-MeOH, the suppression of ferromagnetism by the transverse field is consistent with TFIFM, while the suppression of ferromagnetism by the transverse field is considerably more rapid in Mn12-acetate. Previous studies show that due to solvent disorder Mn12-acetate has an intrinsic distribution of discrete tilts of the molecular magnetic easy axis from the global easy axis of the crystal. Thus with the application of transverse field, the molecules with tilted easy axis experience an additional field along their easy axis and give rise to a distribution of random-fields that further destroys the long-range order, suggesting that this prototypical molecular magnet is a realization of Random-Field Ising Ferromagnet (RFIFM). Work performed in collaboration with: A. D. Kent, Physics Dept., NYU, Bo Wen, M. P. Sarachik, Physics Dept., CCNY, CUNY, Y. Yeshurun, Physics Dept., Bar Ilan U, A. J. Millis, Physics Dept., Columbia U, and G. Christou, Chemistry Dept., U of Florida.

  12. 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.

  13. 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

  14. Biomedical image analysis using Markov random fields & efficient linear programing.

    PubMed

    Komodakis, Nikos; Besbes, Ahmed; Glocker, Ben; Paragios, Nikos

    2009-01-01

    Computer-aided diagnosis through biomedical image analysis is increasingly considered in health sciences. This is due to the progress made on the acquisition side, as well as on the processing one. In vivo visualization of human tissues where one can determine both anatomical and functional information is now possible. The use of these images with efficient intelligent mathematical and processing tools allows the interpretation of the tissues state and facilitates the task of the physicians. Segmentation and registration are the two most fundamental tools in bioimaging. The first aims to provide automatic tools for organ delineation from images, while the second focuses on establishing correspondences between observations inter and intra subject and modalities. In this paper, we present some recent results towards a common formulation addressing these problems, called the Markov Random Fields. Such an approach is modular with respect to the application context, can be easily extended to deal with various modalities, provides guarantees on the optimality properties of the obtained solution and is computationally efficient. PMID:19963682

  15. 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.

  16. 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

  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. Revealing giant internal magnetic fields due to spin fluctuations in magnetically doped colloidal nanocrystals.

    PubMed

    Rice, William D; Liu, Wenyong; Baker, Thomas A; Sinitsyn, Nikolai A; Klimov, Victor I; Crooker, Scott A

    2016-02-01

    Strong quantum confinement in semiconductors can compress the wavefunctions of band electrons and holes to nanometre-scale volumes, significantly enhancing interactions between themselves and individual dopants. In magnetically doped semiconductors, where paramagnetic dopants (such as Mn(2+), Co(2+) and so on) couple to band carriers via strong sp-d spin exchange, giant magneto-optical effects can therefore be realized in confined geometries using few or even single impurity spins. Importantly, however, thermodynamic spin fluctuations become increasingly relevant in this few-spin limit. In nanoscale volumes, the statistical fluctuations of N spins are expected to generate giant effective magnetic fields Beff, which should dramatically impact carrier spin dynamics, even in the absence of any applied field. Here we directly and unambiguously reveal the large Beff that exist in Mn(2+)-doped CdSe colloidal nanocrystals using ultrafast optical spectroscopy. At zero applied magnetic field, extremely rapid (300-600 GHz) spin precession of photoinjected electrons is observed, indicating Beff ∼ 15 -30 T for electrons. Precession frequencies exceed 2 THz in applied magnetic fields. These signals arise from electron precession about the random fields due to statistically incomplete cancellation of the embedded Mn(2+) moments, thereby revealing the initial coherent dynamics of magnetic polaron formation, and highlighting the importance of magnetization fluctuations on carrier spin dynamics in nanomaterials. PMID:26595331

  19. 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.

  20. 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

  1. Understanding earthquake source processes with spatial random field models

    NASA Astrophysics Data System (ADS)

    Song, S.

    2011-12-01

    Earthquake rupture is a complex mechanical process that can be formulated as a dynamically running shear crack on a frictional interface embedded in an elastic continuum. This type of dynamic description of earthquake rupture is often preferred among researchers because they believe the kinematic description is likely to miss physical constraints introduced by dynamic approaches and to lead to arbitrary and nonphysical kinematic fault motions. However, dynamic rupture modeling, although they produce physically consistent models, often uses arbitrary input parameters, e.g., stress and fracture energy, partially because they are more difficult to constrain with data compared to kinematic ones. I propose to describe earthquake rupture as a stochastic model with a set of random variables (e.g., random field) that represent the spatial distribution of kinematic source parameters such as slip, rupture velocity, slip duration and velocity. This is a kinematic description of earthquake rupture in the sense that a model is formulated with kinematic parameters, but since the model can be constrained by both rupture dynamics and data, it may have both physical and observational constraints inside. The stochastic model is formulated by quantifying the 1-point and 2-point statistics of the kinematic parameters. 1-point statistics define a marginal probability density function for a certain source parameter at a given point on a fault. For example, a probability distribution for earthquake slip at a given point can control a possible range of values taken by earthquake slip and their likelihood. In the same way, we can control the existence of supershear rupture with a 1-point variability of the rupture velocity. Two point statistics, i.e. auto- and cross-coherence between source parameters, control the heterogeneity of each source parameter and their coupling, respectively. Several interesting features of earthquake rupture have been found by investigating cross

  2. Magnetic Field Line Random Walk in Isotropic Turbulence with Zero Mean Field

    NASA Astrophysics Data System (ADS)

    Sonsrettee, W.; Subedi, P.; Ruffolo, D.; Matthaeus, W. H.; Snodin, A. P.; Wongpan, P.; Chuychai, P.

    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 0)(l∥/l) for rms magnetic fluctuation b, large-scale mean field B 0, and parallel and perpendicular coherence scales l∥ and l, respectively. Here we examine the FLRW when R → ∞ by taking B 0 → 0 for finite bz (fluctuation component along B 0), which differs from the well-studied route with bz = 0 or bz Lt B 0 as the turbulence becomes quasi-two-dimensional (quasi-2D). Fluctuations with B 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 -1 or k -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 0 → 0, they remain in reasonable agreement. We conclude that their applicability is limited not by large R, but rather by quasi-two-dimensionality.

  3. 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.

  4. Functional Redundancy Patterns Reveal Non-Random Assembly Rules in a Species-Rich Marine Assemblage

    PubMed Central

    Guillemot, Nicolas; Kulbicki, Michel; Chabanet, Pascale; Vigliola, Laurent

    2011-01-01

    The relationship between species and the functional diversity of assemblages is fundamental in ecology because it contains key information on functional redundancy, and functionally redundant ecosystems are thought to be more resilient, resistant and stable. However, this relationship is poorly understood and undocumented for species-rich coastal marine ecosystems. Here, we used underwater visual censuses to examine the patterns of functional redundancy for one of the most diverse vertebrate assemblages, the coral reef fishes of New Caledonia, South Pacific. First, we found that the relationship between functional and species diversity displayed a non-asymptotic power-shaped curve, implying that rare functions and species mainly occur in highly diverse assemblages. Second, we showed that the distribution of species amongst possible functions was significantly different from a random distribution up to a threshold of ∼90 species/transect. Redundancy patterns for each function further revealed that some functions displayed fast rates of increase in redundancy at low species diversity, whereas others were only becoming redundant past a certain threshold. This suggested non-random assembly rules and the existence of some primordial functions that would need to be fulfilled in priority so that coral reef fish assemblages can gain a basic ecological structure. Last, we found little effect of habitat on the shape of the functional-species diversity relationship and on the redundancy of functions, although habitat is known to largely determine assemblage characteristics such as species composition, biomass, and abundance. Our study shows that low functional redundancy is characteristic of this highly diverse fish assemblage, and, therefore, that even species-rich ecosystems such as coral reefs may be vulnerable to the removal of a few keystone species. PMID:22039543

  5. Magnetic nanoparticle imaging by random and maximum length sequences of inhomogeneous activation fields.

    PubMed

    Baumgarten, Daniel; Eichardt, Roland; Crevecoeur, Guillaume; Supriyanto, Eko; Haueisen, Jens

    2013-01-01

    Biomedical applications of magnetic nanoparticles require a precise knowledge of their biodistribution. From multi-channel magnetorelaxometry measurements, this distribution can be determined by means of inverse methods. It was recently shown that the combination of sequential inhomogeneous excitation fields in these measurements is favorable regarding the reconstruction accuracy when compared to homogeneous activation . In this paper, approaches for the determination of activation sequences for these measurements are investigated. Therefor, consecutive activation of single coils, random activation patterns and families of m-sequences are examined in computer simulations involving a sample measurement setup and compared with respect to the relative condition number of the system matrix. We obtain that the values of this condition number decrease with larger number of measurement samples for all approaches. Random sequences and m-sequences reveal similar results with a significant reduction of the required number of samples. We conclude that the application of pseudo-random sequences for sequential activation in the magnetorelaxometry imaging of magnetic nanoparticles considerably reduces the number of required sequences while preserving the relevant measurement information. PMID:24110423

  6. The mean field theory in EM procedures for blind Markov random field image restoration.

    PubMed

    Zhang, J

    1993-01-01

    A Markov random field (MRF) model-based EM (expectation-maximization) procedure for simultaneously estimating the degradation model and restoring the image is described. The MRF is a coupled one which provides continuity (inside regions of smooth gray tones) and discontinuity (at region boundaries) constraints for the restoration problem which is, in general, ill posed. The computational difficulty associated with the EM procedure for MRFs is resolved by using the mean field theory from statistical mechanics. An orthonormal blur decomposition is used to reduce the chances of undesirable locally optimal estimates. Experimental results on synthetic and real-world images show that this approach provides good blur estimates and restored images. The restored images are comparable to those obtained by a Wiener filter in mean-square error, but are most visually pleasing. PMID:18296192

  7. 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.

  8. Compliant random fields in gels formed from side-chain liquid crystalline polymers

    NASA Astrophysics Data System (ADS)

    Goldbart, Paul; Ye, Fangfu; Lu, Bing; Xing, Xiangjun

    2013-03-01

    Localized polymer-chain backbones in gels formed from side-chain liquid crystalline polymers serve to create random fields that induce local orientational order of the nematogenic pendants of the side chains. These random fields differ, however, from conventional ones, in that they are compliant, and thus themselves undergo thermal fluctuations. We develop a free energy that describes local nematic ordering in presence of such compliant random fields. In particular, we show that, as a result of this compliance, the free energy has a qualitatively new structure, unattainable via truly static random fields. We discuss the physical implications this free energy, focusing on the consequences of the compliant nature of the random fields.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Russo, Antonio; Chakravarty, Sudip

    In the pseudogap regime of the cuprates, charge order breaks a ℤ2 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 2 D and 3 D . The glassy dynamics are treated as a heat bath which couple 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. 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.

  13. Field assisted spin switching in magnetic random access memory

    NASA Astrophysics Data System (ADS)

    Jeong, W. C.; Park, J. H.; Oh, J. H.; Koh, G. H.; Jeong, G. T.; Jeong, H. S.; Kim, Kinam

    2006-04-01

    A switching method called by field assisted spin switching has been investigated. A field assisted spin switching consists of a metal line induced magnetic field and a spin switching through a magnetic tunnel junction. It is a variation of a current induced switching and assisted by the magnetic field induced by the current-carrying metal line. Various current paths have been tested to investigate how and how much the spin switching contributes to the overall switching and the results will be explained. A computer simulation has been complemented to measure the degree of the thermal effect in the switching.

  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. 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.

  16. Modulation of electromagnetic fields by a depolarizer of random polarizer array.

    PubMed

    Ma, Ning; Hanson, Steen G; Wang, Wei

    2016-05-01

    The statistical properties of the electric fields with random changes of the polarization state in space generated by a depolarizer are investigated on the basis of the coherence matrix. The depolarizer is a polarizer array composed of a multitude of contiguous square cells of polarizers with randomly distributed polarization angles, where the incident fields experience a random polarization modulation after passing through the depolarizer. The propagation of the modulated electric fields through any quadratic optical system is examined within the framework of the complex ABCD matrix to show how the degree of coherence and the degree of polarization change on propagation. PMID:27128058

  17. Charged Particle Diffusion in Isotropic Random Static Magnetic Fields

    NASA Astrophysics Data System (ADS)

    Subedi, P.; Sonsrettee, W.; Matthaeus, W. H.; Ruffolo, D. J.; Wan, M.; Montgomery, D.

    2013-12-01

    Study of the transport and diffusion of charged particles in a turbulent magnetic field remains a subject of considerable interest. Research has most frequently concentrated on determining the diffusion coefficient in the presence of a mean magnetic field. Here we consider Diffusion of charged particles in fully three dimensional statistically isotropic magnetic field turbulence with no mean field which is pertinent to many astrophysical situations. We classify different regions of particle energy depending upon the ratio of Larmor radius of the charged particle to the characteristic outer length scale of turbulence. We propose three different theoretical models to calculate the diffusion coefficient each applicable to a distinct range of particle energies. The theoretical results are compared with those from computer simulations, showing very good agreement.

  18. 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. PMID:24968171

  19. 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

  20. Mean-field magnetohydrodynamics associated with random Alfven waves in a plasma with weak magnetic diffusion

    NASA Astrophysics Data System (ADS)

    Hamabata, Hiromitsu; Namikawa, Tomikazu

    1988-02-01

    Using first-order smoothing theory, Fourier analysis and perturbation methods, a new equation is derived governing the evolution of the spectrum tensor (including the energy and helicity spectrum functions) of the random velocity field as well as the ponderomotive and mean electromotive forces generated by random Alfven waves in a plasma with weak magnetic diffusion. The ponderomotive and mean electromotive forces are expressed as series involving spatial derivatives of mean magnetic and velocity fields whose coefficients are associated with the helicity spectrum function of the random velocity field. The effect of microscale random Alfven waves, through ponderomotive and mean electromotive forces generated by them, on the propagation of large-scale Alfven waves is also investigated by solving the mean-field equations, including the transport equation of the helicity spectrum function.

  1. 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.

  2. Binary 3-D Markov Chain Random Fields: Finite-size Scaling Analysis of Percolation Properties

    NASA Astrophysics Data System (ADS)

    Harter, T.

    2004-12-01

    Percolation phenomena in random media have been extensively studied in a wide variety of fields in physics, chemistry, engineering, bio-, earth-, and environmental sciences. Most work has focused on uncorrelated random fields. The critical behavior in media with short-range correlations is thought to be identical to that in uncorrelated systems. However, the percolation threshold, pc, which is 0.3116 in uncorrelated media, has been observed to vary with the correlation scale and also with the random field type. Here, we present percolation properties and finite-size scaling effects in three-dimensional binary cubic lattices represented by correlated Markov-chain random fields and compare them to those in sequential Gaussian and sequential indicator random fields. We find that the computed percolation threshold in correlated random fields is significantly lower than in the uncorrelated lattice and decreases with increasing correlation scale. The rate of decrease rapidly flattens out for correlation lengths larger than 2-3 grid-blocks. At correlation scales of 5-6 grid blocks, pc is found to be 0.126 for the Markov chain random fields and slightly higher for sequential Gaussian and indicator random fields. The universal scaling constants for mean cluster size, backbone fraction, and connectivity are found to be consistent with results on uncorrelated lattices. For numerical studies, it is critical to understand finite-size effects on the percolation and associated phase connectivity properties of lattices. We present detailed statistical results on the percolation properties in finite sized lattice and their dependence on correlation scale. We show that appropriate grid resolution and choice of simulation boundaries is critical to properly simulate correlated natural geologic systems, which may display significant finite-size effects.

  3. 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 ...

  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. Effect of random field disorder on the first order transition in p-spin interaction model

    NASA Astrophysics Data System (ADS)

    Sumedha; Singh, Sushant K.

    2016-01-01

    We study the random field p-spin model with Ising spins on a fully connected graph using the theory of large deviations in this paper. This is a good model to study the effect of quenched random field on systems which have a sharp first order transition in the pure state. For p = 2, the phase-diagram of the model, for bimodal distribution of the random field, has been well studied and is known to undergo a continuous transition for lower values of the random field (h) and a first order transition beyond a threshold, htp(≈ 0.439) . We find the phase diagram of the model, for all p ≥ 2, with bimodal random field distribution, using large deviation techniques. We also look at the fluctuations in the system by calculating the magnetic susceptibility. For p = 2, beyond the tricritical point in the regime of first order transition, we find that for htp < h < 0.447, magnetic susceptibility increases rapidly (even though it never diverges) as one approaches the transition from the high temperature side. On the other hand, for 0.447 < h ≤ 0.5, the high temperature behaviour is well described by the Curie-Weiss law. For all p ≥ 2, we find that for larger magnitudes of the random field (h >ho = 1 / p!), the system does not show ferromagnetic order even at zero temperature. We find that the magnetic susceptibility for p ≥ 3 is discontinuous at the transition point for h

  6. 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.

  7. 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

  8. [Randomized field study of the etiology of strabismus concomitans].

    PubMed

    Aichmair, H; Grossmann, W; Aichmair, M; Bomze, I; Fröschl, K; Futschik, A; Theyer, I; Hirmann, E; Kautzky, I; Hafner, J

    1992-01-01

    After an introduction to the problems of binocular vision and an overview of the literature, the authors report on the reasons for undertaking this study and on its practical implications. Up to now, no other randomized study has been undertaken to our knowledge on children of this age group in such a large city as Vienna. All children in primary 3 classes in 20 out of the 256 elementary schools were examined ophthalmologically and orthoptically. It was found that hereditary factors are of statistically significant importance. Especially important for the ophthalmologist is also the statistically significant relation between the diagnosis poor range of fusion, poor fixation, incorrect Worth test for distance and/or proximity, and poor or lacking stereoscopic vision with the occurrence of strabism. The authors were astonished to find a remarkably high percentage of exophoria (58%), in contrast to esophoria (16%). It is interesting for prophylaxis and therapy that children originating from families where spectacles are worn, acted more cooperatively and tended to take the orders of the physician more seriously than those coming from families without eye problems. The promotion of genetic research related to squint and more counselling for couples wishing to have children or confronted with risk factor problems would be desirable, as well as the inclusion of more obligatory ophthalmological examinations in the mother-child medical "passport". PMID:1441555

  9. Structural aspects of antibody-antigen interaction revealed through small random peptide libraries.

    PubMed

    Slootstra, J W; Puijk, W C; Ligtvoet, G J; Langeveld, J P; Meloen, R H

    1996-02-01

    Two small random peptide libraries, one composed of 4550 dodecapeptides and one of 8000 tripeptides, were synthesized in newly developed credit-card format miniPEPSCAN cards (miniPEPSCAN libraries). Each peptide was synthesized in a discrete well (455 peptides/card). The two miniPEPSCAN libraries were screened with three different monoclonal antibodies (Mabs). Two other random peptide libraries, expressed on the wall of bacteria (recombinant libraries) and composed of 10(7) hexa- and octapeptides, were screened with the same three Mabs. The aim of this study was to compare the amino acid sequence of peptides selected from small and large pools of random peptides and, in this way, investigate the potential of small random peptide libraries. The screening of the two miniPEPSCAN libraries resulted in the identification of a surprisingly large number of antibody-binding peptides, while the screening of the large recombinant libraries, using the same Mabs, resulted in the identification of only a small number of peptides. The large number of peptides derived from the small random peptide libraries allowed the determination of consensus sequences. These consensus sequences could be related to small linear and nonlinear parts of the respective epitopes. The small number of peptides derived from the large random peptide libraries could only be related to linear epitopes that were previously mapped using small libraries of overlapping peptides covering the antigenic protein. Thus, with respect to the cost and speed of identifying peptides that resemble linear and nonlinear parts of epitopes, small diversity libraries based on synthetic peptides appear to be superior to large diversity libraries based on expression systems. PMID:9237197

  10. 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.

  11. 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.

  12. Magnetite reveals ambient field strength at low temperatures

    NASA Astrophysics Data System (ADS)

    Smirnov, Alexei V.; Tarduno, John A.

    Magnetite (Fe3O4) is the most important and oldest known magnetic mineral on Earth (Figure l). We have come a long way from the magnetite loadstone compasses of ancient China; magnetite and titanomagnetite have been established as the principal carriers of geologically important remanent magnetizations in rocks, the study of which led to the plate tectonic paradigm. We now recognize that magnetite plays an important role in the biosphere. Some organisms contain intra-cellular particles of Fe3O4 that they use for spatial orientation and navigation. When preserved in rocks, these particles—called "magnetofossils"— can provide important insight into the origin and development of life here, and perhaps, on other planets [e.g., Thomas-Keprta et al., 2000]. Magnetite is now used in the medical field and in nanotechnology research. Nanoparticles of magnetite are used as a contrasting agent in magnetic resonance imaging and are being developed to deliver site-specific drugs for the treatment of cancer [Alexiou et al., 2000]. Such applications add to a long list of industrial uses of magnetite that range from magnetic ink to magnetic recording media.

  13. Solution NMR of MPS-1 Reveals a Random Coil Cytosolic Domain Structure

    PubMed Central

    Lai, Chaohua; Li, Juan; Zheng, Yuanyuan; Xiong, Ying; Zhang, Longhua; Tian, Changlin

    2014-01-01

    Caenorhabditis elegans MPS1 is a single transmembrane helical auxiliary subunit that co-localizes with the voltage-gated potassium channel KVS1 in the nematode nervous system. MPS-1 shares high homology with KCNE (potassium voltage-gated channel subfamily E member) auxiliary subunits, and its cytosolic domain was reported to have a serine/threonine kinase activity that modulates KVS1 channel function via phosphorylation. In this study, NMR spectroscopy indicated that the full length and truncated MPS-1 cytosolic domain (134–256) in the presence or absence of n-dodecylphosphocholine detergent micelles adopted a highly flexible random coil secondary structure. In contrast, protein kinases usually adopt a stable folded conformation in order to implement substrate recognition and phosphoryl transfer. The highly flexible random coil secondary structure suggests that MPS-1 in the free state is unstructured but may require a substrate or binding partner to adopt stable structure required for serine/threonine kinase activity. PMID:25347290

  14. Solution NMR of MPS-1 reveals a random coil cytosolic domain structure.

    PubMed

    Li, Pan; Shi, Pan; Lai, Chaohua; Li, Juan; Zheng, Yuanyuan; Xiong, Ying; Zhang, Longhua; Tian, Changlin

    2014-01-01

    Caenorhabditis elegans MPS1 is a single transmembrane helical auxiliary subunit that co-localizes with the voltage-gated potassium channel KVS1 in the nematode nervous system. MPS-1 shares high homology with KCNE (potassium voltage-gated channel subfamily E member) auxiliary subunits, and its cytosolic domain was reported to have a serine/threonine kinase activity that modulates KVS1 channel function via phosphorylation. In this study, NMR spectroscopy indicated that the full length and truncated MPS-1 cytosolic domain (134-256) in the presence or absence of n-dodecylphosphocholine detergent micelles adopted a highly flexible random coil secondary structure. In contrast, protein kinases usually adopt a stable folded conformation in order to implement substrate recognition and phosphoryl transfer. The highly flexible random coil secondary structure suggests that MPS-1 in the free state is unstructured but may require a substrate or binding partner to adopt stable structure required for serine/threonine kinase activity. PMID:25347290

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

    PubMed Central

    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. PMID:23161673

  16. Markov random field restoration of point correspondences for active shape modeling

    NASA Astrophysics Data System (ADS)

    Hilger, Klaus B.; Paulsen, Rasmus R.; Larsen, Rasmus

    2004-05-01

    In this paper it is described how to build a statistical shape model using a training set with a sparse of landmarks. A well defined model mesh is selected and fitted to all shapes in the training set using thin plate spline warping. This is followed by a projection of the points of the warped model mesh to the target shapes. When this is done by a nearest neighbour projection it can result in folds and inhomogeneities in the correspondence vector field. The novelty in this paper is the use and extension of a Markov random field regularisation of the correspondence field. The correspondence field is regarded as a collection of random variables, and using the Hammersley-Clifford theorem it is proved that it can be treated as a Markov Random Field. The problem of finding the optimal correspondence field is cast into a Bayesian framework for Markov Random Field restoration, where the prior distribution is a smoothness term and the observation model is the curvature of the shapes. The Markov Random Field is optimised using a combination of Gibbs sampling and the Metropolis-Hasting algorithm. The parameters of the model are found using a leave-one-out approach. The method leads to a generative model that produces highly homogeneous polygonised shapes with improved reconstruction capabilities of the training data. Furthermore, the method leads to an overall reduction in the total variance of the resulting point distribution model. The method is demonstrated on a set of human ear canals extracted from 3D-laser scans.

  17. 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

  18. Object-based Conditional Random Fields for Road Extraction from Remote Sensing Image

    NASA Astrophysics Data System (ADS)

    Huang, Zhijian; Xu, Fanjiang; Lu, Lei; Nie, Hongshan

    2014-03-01

    To make full use of spatially contextual information and topological information in the procedure of Object-based Image Analysis (OBIA), an object-based conditional random field is proposed and used for road extraction. Objects are produced with an initial segmentation, then their neighbours are constructed. Each object is represented by three kinds of features, including the colour, the gradient of histogram and the texture. Formulating the road extraction as a binary classification problem, a Conditional Random Fields model learns and is used for inference. The experimental results demonstrate that the proposed method is effective.

  19. 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.

  20. Field Studies Reveal Strong Postmating Isolation between Ecologically Divergent Butterfly Populations

    PubMed Central

    McBride, Carolyn S.; Singer, Michael C.

    2010-01-01

    Gene flow between populations that are adapting to distinct environments may be restricted if hybrids inherit maladaptive, intermediate phenotypes. This phenomenon, called extrinsic postzygotic isolation (EPI), is thought to play a critical role in the early stages of speciation. However, despite its intuitive appeal, we know surprisingly little about the strength and prevalence of EPI in nature, and even less about the specific phenotypes that tend to cause problems for hybrids. In this study, we searched for EPI among allopatric populations of the butterfly Euphydryas editha that have specialized on alternative host plants. These populations recall a situation thought typical of the very early stages of speciation. They lack consistent host-associated genetic differentiation at random nuclear loci and show no signs of reproductive incompatibility in the laboratory. However, they do differ consistently in diverse host-related traits. For each of these traits, we first asked whether hybrids between populations that use different hosts (different-host hybrids) were intermediate to parental populations and to hybrids between populations that use the same host (same-host hybrids). We then conducted field experiments to estimate the effects of intermediacy on fitness in nature. Our results revealed strong EPI under field conditions. Different-host hybrids exhibited an array of intermediate traits that were significantly maladaptive, including four behaviors. Intermediate foraging height slowed the growth of larvae, while intermediate oviposition preference, oviposition site height, and clutch size severely reduced the growth and survival of the offspring of adult females. We used our empirical data to construct a fitness surface on which different-host hybrids can be seen to fall in an adaptive valley between two peaks occupied by same-host hybrids. These findings demonstrate how ecological selection against hybrids can create a strong barrier to gene flow at the early

  1. 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.

  2. A first-order statistical smoothing approximation for the coherent wave field in random porous random media.

    PubMed

    Müller, Tobias M; Gurevich, Boris

    2005-04-01

    An important dissipation mechanism for waves in randomly inhomogeneous poroelastic media is the effect of wave-induced fluid flow. In the framework of Biot's theory of poroelasticity, this mechanism can be understood as scattering from fast into slow compressional waves. To describe this conversion scattering effect in poroelastic random media, the dynamic characteristics of the coherent wavefield using the theory of statistical wave propagation are analyzed. In particular, the method of statistical smoothing is applied to Biot's equations of poroelasticity. Within the accuracy of the first-order statistical smoothing an effective wave number of the coherent field, which accounts for the effect of wave-induced flow, is derived. This wave number is complex and involves an integral over the correlation function of the medium's fluctuations. It is shown that the known one-dimensional (1-D) result can be obtained as a special case of the present 3-D theory. The expression for the effective wave number allows to derive a model for elastic attenuation and dispersion due to wave-induced fluid flow. These wavefield attributes are analyzed in a companion paper. PMID:15898626

  3. Quantification of deterministic matched-field source localization error in the face of random model inputs

    NASA Astrophysics Data System (ADS)

    Daly, Peter M.; Hebenstreit, Gerald T.

    2003-04-01

    Deterministic source localization using matched-field processing (MFP) has yielded good results in propagation scenarios where the nonrandom model parameter input assumption is valid. In many shallow water environments, inputs to acoustic propagation models may be better represented using random distributions rather than fixed quantities. One can estimate the negative effect of random source inputs on deterministic MFP by (1) obtaining a realistic statistical representation of a signal model parameter, then (2) using the mean of the parameter as input to the MFP signal model (the so-called ``replica vector''), (3) synthesizing a source signal using multiple realizations of the random parameter, and (4) estimating the source localization error by correlating the synthesized signal vector with the replica vector over a three dimensional space. This approach allows one to quantify deterministic localization error introduced by random model parameters, including sound velocity profile, hydrophone locations, and sediment thickness and speed. [Work supported by DARPA Advanced Technology Office.

  4. Intraspecific differentiation of Hancornia speciosa revealed by simple sequence repeat and random amplified polymorphic DNA markers.

    PubMed

    Nogueira, C A; Stafuzza, N B; Ribeiro, T P; Prado, A D L; Menezes, I P P; Peixoto, N; Gonçalves, P J; Almeida, L M

    2015-01-01

    Hancornia speciosa, popularly known as mangabeira, is a fruit tree native to the Brazilian Cerrado that shows great economic potential, due to its multiple uses. Intraspecific classification of this species is difficult because it shows high morphological diversity. An early study of the species reported that there are six botanic varieties that differ morphologically mainly in the shapes of their leaves and flowers. Except to note the wide morphological variation and economic potential of this species, few studies have been published about the genetic diversity of mangabeira. Knowledge of the genetic variability of this species among populations would be useful for genetic conservation and breeding programs. Therefore, we tested the transferability of 12 simple sequence repeats from expressed sequence tags (EST-SSRs) from Catharanthus roseus to H. speciosa and used 10 random amplified polymorphic DNA markers to evaluate the genetic variability among botanical varieties of H. speciosa. We obtained a high transferability frequency of EST-SSR markers from C. roseus to H. speciosa (75%). However, EST-SSR markers showed low heterozygosity and locus variability (two or three alleles by locus), which suggest low genetic diversity in the mangabeira samples. The Jaccard dissimilarity index and an examination of geographic distances indicated a non-spatial structuring of the genetic variability. Our markers were unable to distinguish H. speciosa botanical varieties. PMID:26662392

  5. 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.

  6. Experimental measurements of topological singularity screening in random paraxial scalar and vector optical fields.

    PubMed

    Egorov, Roman I; Soskin, Marat S; Kessler, David A; Freund, Isaac

    2008-03-14

    There exists a substantial body of theory that predicts mutual screening of signed topological singularities (topological charges) in random optical fields (speckle patterns). Such screening appears to be rather mysterious because there are neither energetic nor entropic reasons for its existence. We present the first experimental confirmation of mutual screening by the stationary points of the intensity, the canonical optical scalar field, and of mutual screening by C points in elliptically polarized light, the generic optical vector field. We also elucidate specific aspects of the geometry and topology of these fields that we argue give rise to screening. PMID:18352186

  7. Phase-space representation and polarization domains of random electromagnetic fields.

    PubMed

    Castaneda, Roman; Betancur, Rafael; Herrera, Jorge; Carrasquilla, Juan

    2008-08-01

    The phase-space representation of stationary random electromagnetic fields is developed by using electromagnetic spatial coherence wavelets. The propagation of the field's power and states of spatial coherence and polarization results from correlations between the components of the field vectors at pairs of points in space. Polarization domains are theoretically predicted as the structure of the field polarization at the observation plane. In addition, the phase-space representation provides a generalization of the Poynting theorem. Theoretical predictions are examined by numerically simulating the Young experiment with electromagnetic waves. The experimental implementation of these results is a current subject of research. PMID:18670539

  8. Anisotropic four-state clock model in the presence of random fields

    NASA Astrophysics Data System (ADS)

    Salmon, Octavio D. Rodriguez; Nobre, Fernando D.

    2016-02-01

    A four-state clock ferromagnetic model is studied in the presence of different configurations of anisotropies and random fields. The model is considered in the limit of infinite-range interactions, for which the mean-field approach becomes exact. Both representations of Cartesian spin components and two Ising variables are used, in terms of which the physical properties and phase diagrams are discussed. The random fields follow bimodal probability distributions and the richest criticality is found when the fields, applied in the two Ising systems, are not correlated. The phase diagrams present new interesting topologies, with a wide variety of critical points, which are expected to be useful in describing different complex phenomena.

  9. 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.

  10. 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.

  11. On the unlikeliness of multi-field inflation: bounded random potentials and our vacuum

    SciTech Connect

    Battefeld, Diana; Battefeld, Thorsten; Schulz, Sebastian E-mail: tbattefe@astro.physik.uni-goettingen.de

    2012-06-01

    Based on random matrix theory, we compute the likelihood of saddles and minima in a class of random potentials that are softly bounded from above and below, as required for the validity of low energy effective theories. Imposing this bound leads to a random mass matrix with non-zero mean of its entries. If the dimensionality of field-space is large, inflation is rare, taking place near a saddle point (if at all), since saddles are more likely than minima or maxima for common values of the potential. Due to the boundedness of the potential, the latter become more ubiquitous for rare low/large values respectively. Based on the observation of a positive cosmological constant, we conclude that the dimensionality of field-space after (and most likely during) inflation has to be low if no anthropic arguments are invoked, since the alternative, encountering a metastable deSitter vacuum by chance, is extremely unlikely.

  12. 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.

  13. Application of operator-scaling anisotropic random fields to binary mixtures

    NASA Astrophysics Data System (ADS)

    Anders, Denis; Hoffmann, Alexander; Scheffler, Hans-Peter; Weinberg, Kerstin

    2011-10-01

    In modern technical applications various multiphase mixtures are used to meet demanding mechanical, chemical and electrical requirements. To understand their structural properties as continuous macroscopic materials, it is important to capture the microstructure of these mixtures. Due to their vast range of applications multicomponent systems are subjected to microstructural changes such as phase separation and coarsening. Therefore the ultimate microstructural arrangement depends on the system's configuration and on exterior driving forces. In addition to this, random physical imperfections within the material and random noise in the exterior thermodynamic fields influence in essence the microstructural evolution. Since all physical processes are subjected to a certain degree of random inhomogeneity under realistic conditions, the influence of random phenomena cannot be neglected in modern physical models. An advanced mathematical description and an implementation of these stochastic processes are required to adapt simulation results based on deterministic mathematical models to experimental observations. In our contribution we will present an operator-scaling anisotropic random field embedded in the Cahn-Hilliard phase-field model to describe the phase evolution in a binary mixture. The arising nonlinear diffusion equation will be solved numerically in the innovative framework of the isogeometric finite element method. To illustrate the flexibility and versatility of our approach, numerical and experimental results for a eutectic Sn-Pb alloy are contraposed. This is the first time that the microstructural evolution in a multicomponent system has been associated with operator-scaling anisotropic random fields. Due to its enormous potential as an essential ingredient in stochastic mathematical and physical modeling it is only a matter of time until these processes will become prevalent in engineering applications.

  14. 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…

  15. 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…

  16. 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. PMID:26518250

  17. 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.

  18. Multitemporal Crop Type Classification Using Conditional Random Fields and Rapideye Data

    NASA Astrophysics Data System (ADS)

    Hoberg, T.; Müller, S.

    2011-09-01

    The task of crop type classification with multitemporal imagery is nowadays often done applying classifiers that are originally developed for single images like support vector machines (SVM). These approaches do not model temporal dependencies in an explicit way. Existing approaches that make use of temporal dependencies are in most cases quite simple and based on rules. Approaches that integrate temporal dependencies to statistical models are very rare and at an early stage of development. Here our approach CRFmulti, based on conditional random fields (CRF), should make a contribution. Conditional random fields consider context knowledge among neighboring primitives in the same way as Markov random fields (MRF) do. Furthermore conditional random fields handle the feature vectors of the neighboring primitives and not only the class labels. Additional to taking spatial context into account, we present an approach for multitemporal data processing where a temporal association potential has been integrated to the common CRF approach to model temporal dependencies. The classification works on pixel -level using spectral image features, whereas all available single images are taken separately. For our experiments a high resolution RapidEye satellite data set of 2010 consisting of 4 images made during the whole vegetation period from April to October is taken. Six crop type categories are distinguished, namely grassland, corn, winter crop, rapeseed, root crops and other crops. To evaluate the potential of the new conditional random field approach the classification result is compared to a manual reference on pixel- and on object-level. Additional a SVM approach is applied under the same conditions and should serve as a benchmark.

  19. 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. PMID:27036626

  20. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

    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.

  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. 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.

  5. 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

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

    NASA Astrophysics Data System (ADS)

    Gebert, Martin; Lemm, Marius

    2016-06-01

    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.

  7. 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.

  8. 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

  9. 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.

  10. Typical kernel size and number of sparse random matrices over Galois fields: A statistical physics approach

    NASA Astrophysics Data System (ADS)

    Alamino, R. C.; Saad, D.

    2008-06-01

    Using methods of statistical physics, we study the average number and kernel size of general sparse random matrices over Galois fields GF(q) , with a given connectivity profile, in the thermodynamical limit of large matrices. We introduce a mapping of GF(q) matrices onto spin systems using the representation of the cyclic group of order q as the q th complex roots of unity. This representation facilitates the derivation of the average kernel size of random matrices using the replica approach, under the replica-symmetric ansatz, resulting in saddle point equations for general connectivity distributions. Numerical solutions are then obtained for particular cases by population dynamics. Similar techniques also allow us to obtain an expression for the exact and average numbers of random matrices for any general connectivity profile. We present numerical results for particular distributions.

  11. 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.

  12. 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).

  13. 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

  14. Fuzzy-based latent-dynamic conditional random fields for continuous gesture recognition

    NASA Astrophysics Data System (ADS)

    Zhang, Shengjun; He, Xiaohai; Teng, Qizhi

    2012-06-01

    We show an original method for automatic hand gesture recognition that makes use of fuzzified latent-dynamic conditional random fields (LDCRF). In this method, fuzzy linguistic variables are used to model the features of hand gestures and then to modify the potential function in LDCRFs. By combining LDCRFs and fuzzy sets, these fuzzy-based LDCRFs (FLDCRF) have the advantages of LDCRFs in sequence labeling along with the advantage of retaining the imprecise character of gestures. The efficiency of the proposed method was tested with unsegmented gesture sequences in three different hand gesture data sets. The experimental results demonstrate that FLDCRFs compare favorably with support vector machines, hidden conditional random fields, and LDCRFs on hand gesture recognition tasks.

  15. Ordered vs. disordered states of the random-field model in three dimensions

    NASA Astrophysics Data System (ADS)

    Garanin, Dmitry A.; Chudnovsky, Eugene M.

    2015-04-01

    We report numerical investigation of the glassy behavior of random-field exchange models in three dimensions. Correlation of energy with the magnetization for different numbers of spin components has been studied. There is a profound difference between the models with two and three spin components with respect to the stability of the magnetized state due to the different kinds of singularities: vortex loops and hedgehogs, respectively. Memory effects pertinent to such states have been investigated. Insight into the mechanism of the large-scale disordering is provided by numerically implementing the Imry-Ma argument in which the spins follow the random field averaged over correlated volumes. Thermal stability of the magnetized states is investigated by the Monte Carlo method.

  16. 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.

  17. 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.

  18. 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.

  19. Planned Variations Study. Volume IV: Field Implementation Plan for a Field Randomized Experiment.

    ERIC Educational Resources Information Center

    Shiban, John R.

    System Development Corporation conducted an extensive project of conceptualization and planning of models for compensatory educational intervention for older disadvantaged youth, at the secondary and postsecondary levels. Two intervention strategies were developed, and this report details the development of a field implementation plan for a…

  20. 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

  1. 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

  2. Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

    NASA Astrophysics Data System (ADS)

    Hong, Liang

    2013-10-01

    The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

  3. 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.

  4. Random field disorder at an absorbing state transition in one and two dimensions

    NASA Astrophysics Data System (ADS)

    Barghathi, Hatem; Vojta, Thomas

    2016-02-01

    We investigate the behavior of nonequilibrium phase transitions under the influence of disorder that locally breaks the symmetry between two symmetrical macroscopic absorbing states. In equilibrium systems such "random-field" disorder destroys the phase transition in low dimensions by preventing spontaneous symmetry breaking. In contrast, we show here that random-field disorder fails to destroy the nonequilibrium phase transition of the one- and two-dimensional generalized contact process. Instead, it modifies the dynamics in the symmetry-broken phase. Specifically, the dynamics in the one-dimensional case is described by a Sinai walk of the domain walls between two different absorbing states. In the two-dimensional case, we map the dynamics onto that of the well studied low-temperature random-field Ising model. We also study the critical behavior of the nonequilibrium phase transition and characterize its universality class in one dimension. We support our results by large-scale Monte Carlo simulations, and we discuss the applicability of our theory to other systems.

  5. 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.

  6. The diffusive idealization of charged-particle transport in random magnetic fields. [cosmic ray propagation

    NASA Technical Reports Server (NTRS)

    Earl, J. A.

    1974-01-01

    The uniqueness and accuracy of the equations which describe the transport of charged particles diffusing in a random magnetic field parallel to a relatively large guiding field is examined. With regard to uniqueness, it is found that the same coefficient of diffusion is obtained by three methods that have apparently led to discrepancies in previous work. With regard to accuracy, it is found that two corrections must be added to Fick's law 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.

  7. Nonlinear amplification of Langmuir waves in a plasma with regular and random magnetic fields

    NASA Astrophysics Data System (ADS)

    Krivitskii, V. S.; Priadko, Iu. M.; Tsytovich, V. N.

    1990-07-01

    The nonlinear interaction of Langmuir waves in a turbulent plasma with random resonance magnetic fields in the presence of an external regular magnetic field is investigated analytically. In particular, attention is given to the possibility of Langmuir wave amplification using the plasma maser effect. The frequency and angle dependences of the amplification increment (attenuation decrement) of Langmuir waves are determined in the isotropic case and in the presence of anisotropy. For an anisotropic particle distribution function, the amplification increment of Langmuir waves may reach values of the order of the plasma frequency.

  8. Random Field Driven Spatial Complexity at the Mott Transition in VO(2).

    PubMed

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

    2016-01-22

    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. PMID:26849604

  9. 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

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

    PubMed

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

    2016-08-01

    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

  11. 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

  12. 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.

  13. Modeling of nonlinear microscopy of localized field enhancements in random metal nanostructures

    NASA Astrophysics Data System (ADS)

    Beermann, Jonas; Bozhevolnyi, Sergey I.; Coello, Victor

    2006-03-01

    Nonlinear microscopy of localized field enhancements in random metal nanostructures with a tightly focused laser beam scanning over a sample surface is modeled by making use of analytic representations of the Green dyadic in the near- and far-field regions, with the latter being approximated by the part describing the scattering via excitation of surface plasmon polaritons. The developed approach is applied to scanning second-harmonic (SH) microscopy of small gold spheres placed randomly on a gold surface. We calculate self-consistent fundamental harmonic (FH) and SH field distributions at the illuminated sample surface and, thereby, FH and SH images for different polarization configurations of the illuminating and detected fields. The simulated images bear close resemblance to the images obtained experimentally, exhibiting similar sensitivity to the wavelength and polarization, as well as sensitivity to the scattering configuration. We verify directly our conjecture that very bright spots in the SH images occur due to the spatial overlap of properly polarized FH and SH eigenmodes. Applications and further improvements of the developed model are discussed.

  14. Metastates in Mean-Field Models with Random External Fields Generated by Markov Chains

    NASA Astrophysics Data System (ADS)

    Formentin, M.; Külske, C.; Reichenbachs, A.

    2012-01-01

    We extend the construction by Külske and Iacobelli of metastates in finite-state mean-field models in independent disorder to situations where the local disorder terms are a sample of an external ergodic Markov chain in equilibrium. We show that for non-degenerate Markov chains, the structure of the theorems is analogous to the case of i.i.d. variables when the limiting weights in the metastate are expressed with the aid of a CLT for the occupation time measure of the chain. As a new phenomenon we also show in a Potts example that for a degenerate non-reversible chain this CLT approximation is not enough, and that the metastate can have less symmetry than the symmetry of the interaction and a Gaussian approximation of disorder fluctuations would suggest.

  15. 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).

  16. Mean-field behavior of the negative-weight percolation model on random regular graphs.

    PubMed

    Melchert, Oliver; Hartmann, Alexander K; Mézard, Marc

    2011-10-01

    We investigate both analytically and numerically the ensemble of minimum-weight loops in the negative-weight percolation model on random graphs with fixed connectivity and bimodal weight distribution. This allows us to study the mean-field behavior of this model. The analytical study is based on a conjectured equivalence with the problem of self-avoiding walks in a random medium. The numerical study is based on a mapping to a standard minimum-weight matching problem for which fast algorithms exist. Both approaches yield results that are in agreement on the location of the phase transition, on the value of critical exponents, and on the absence of any sizable indications of a glass phase. By these results, the previously conjectured upper critical dimension of d(u)=6 is confirmed. PMID:22181086

  17. 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.

  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. Genetic profiling of Klebsiella pneumoniae: comparison of pulsed field gel electrophoresis and random amplified polymorphic DNA

    PubMed Central

    Ashayeri-Panah, Mitra; Eftekhar, Fereshteh; Ghamsari, Maryam Mobarak; Parvin, Mahmood; Feizabadi, Mohammad Mehdi

    2013-01-01

    In this study, the discriminatory power of pulsed field gel electrophoresis (PFGE) and random amplified polymorphic DNA (RAPD) methods for subtyping of 54 clinical isolates of Klebsiella pneumoniae were compared. All isolates were typeable by RAPD, while 3.6% of them were not typeable by PFGE. The repeatability of both typing methods were 100% with satisfying reproducibility (≥ 95%). Although the discriminatory power of PFGE was greater than RAPD, both methods showed sufficient discriminatory power (DI > 0.95) which reflects the heterogeneity among the K. pneumoniae isolates. An optimized RAPD protocol is less technically demanding and time consuming that makes it a reliable typing method and competitive with PFGE. PMID:24516423

  20. Hierarchical Markov random-field modeling for texture classification in chest radiographs

    NASA Astrophysics Data System (ADS)

    Vargas-Voracek, Rene; Floyd, Carey E., Jr.; Nolte, Loren W.; McAdams, Page

    1996-04-01

    A hierarchical Markov random field (MRF) modeling approach is presented for the classification of textures in selected regions of interest (ROIs) of chest radiographs. The procedure integrates possible texture classes and their spatial definition with other components present in an image such as noise and background trend. Classification is performed as a maximum a-posteriori (MAP) estimation of texture class and involves an iterative Gibbs- sampling technique. Two cases are studied: classification of lung parenchyma versus bone and classification of normal lung parenchyma versus miliary tuberculosis (MTB). Accurate classification was obtained for all examined cases showing the potential of the proposed modeling approach for texture analysis of radiographic images.

  1. Fusion of Hidden Markov Random Field models and its Bayesian estimation.

    PubMed

    Destrempes, François; Angers, Jean-François; Mignotte, Max

    2006-10-01

    In this paper, we present a Hidden Markov Random Field (HMRF) data-fusion model. The proposed model is applied to the segmentation of natural images based on the fusion of colors and textons into Julesz ensembles. The corresponding Exploration/ Selection/Estimation (ESE) procedure for the estimation of the parameters is presented. This method achieves the estimation of the parameters of the Gaussian kernels, the mixture proportions, the region labels, the number of regions, and the Markov hyper-parameter. Meanwhile, we present a new proof of the asymptotic convergence of the ESE procedure, based on original finite time bounds for the rate of convergence. PMID:17022259

  2. Central Limit Theorems and Uniform Laws of Large Numbers for Arrays of Random Fields

    PubMed Central

    Jenish, Nazgul; Prucha, Ingmar R.

    2009-01-01

    Over the last decades, spatial-interaction models have been increasingly used in economics. However, the development of a sufficiently general asymptotic theory for nonlinear spatial models has been hampered by a lack of relevant central limit theorems (CLTs), uniform laws of large numbers (ULLNs) and pointwise laws of large numbers (LLNs). These limit theorems form the essential building blocks towards developing the asymptotic theory of M-estimators, including maximum likelihood and generalized method of moments estimators. The paper establishes a CLT, ULLN, and LLN for spatial processes or random fields that should be applicable to a broad range of data processes. PMID:20161289

  3. 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

  4. Ensemble solute transport in two-dimensional operator-scaling random fields

    NASA Astrophysics Data System (ADS)

    Monnig, Nathan D.; Benson, David A.; Meerschaert, Mark M.

    2008-02-01

    Motivated by field measurements of aquifer hydraulic conductivity (K), recent techniques were developed to construct anisotropic fractal random fields in which the scaling, or self-similarity parameter, varies with direction and is defined by a matrix. Ensemble numerical results are analyzed for solute transport through these two-dimensional "operator-scaling" fractional Brownian motion ln(K) fields. Both the longitudinal and transverse Hurst coefficients, as well as the "radius of isotropy" are important to both plume growth rates and the timing and duration of breakthrough. It is possible to create operator-scaling fractional Brownian motion fields that have more "continuity" or stratification in the direction of transport. The effects on a conservative solute plume are continually faster-than-Fickian growth rates, highly non-Gaussian shapes, and a heavier tail early in the breakthrough curve. Contrary to some analytic stochastic theories for monofractal K fields, the plume growth rates never exceed A. Mercado's (1967) purely stratified aquifer growth rate of plume apparent dispersivity proportional to mean distance. Apparent superstratified growth must be the result of other demonstrable factors, such as initial plume size.

  5. 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.

  6. 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.

  7. 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

  8. Randomized field experiments for program planning, development, and evaluation: an illustrative bibliography.

    PubMed

    Boruch, R F; Mcsweeny, A J; Soderstrom, E J

    1978-11-01

    This bibliography lists references to over 300 field experiments undertaken in schools, hospitals, prisons, and other social settings, mainly in the U.S. The list is divided into 10 major categories corresponding to the type of program under examination. They include: criminal and civil justice programs, mental health, training and education, mass media, information collection, utilization, commerce and industry, welfare, health, and family planning. The main purpose of the bibliography is to provide evidence on feasibility and scope of randomized field tests, since despite their advantages, it is not always clear from managerial, political, and other constraints on research that they can be mounted. Dates of publications range from 1944 to 1978. PMID:12335777

  9. 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.

  10. The effect of adiabatic focusing upon charged particle propagation in random magnetic fields

    NASA Technical Reports Server (NTRS)

    Earl, J. A.

    1975-01-01

    Charged particles propagating along the diverging lines of force of a spatially inhomogeneous guiding field were considered as they are scattered by random fields. Their longitudinal transport is described in terms of the eigenfunctions of a Sturm-Liouville operator incorporating the effect of adiabatic focussing along with that of scattering. The relaxation times and characteristic velocities are graphed and tabulated. The particle density is evaluated as a function of space and time for two different regimes. In the first regime (relatively weak focussing), a diffusive mode of propagation is dominant but coherent modes are also dominant. In the second regime (strong focussing), diffusion does not occur and the propagation is purely coherent. This supercoherent mode corresponds exactly to the so-called scatter-free propagation of kilovolt solar flare electrons. On a larger scale, focussed transport provides an interpretation of many observed characteristics of extragalactic radio sources.

  11. Effects of dehydroepiandrosterone supplementation during stressful military training: a randomized, controlled, double-blind field study.

    PubMed

    Taylor, Marcus K; Padilla, Genieleah A; Stanfill, Katherine E; Markham, Amanda E; Khosravi, Jasmine Y; Ward, Michael D Dial; Koehler, Matthew M

    2012-01-01

    Dehydroepiandrosterone (DHEA) and DHEA sulfate (DHEAS) are anabolic prehormones involved in the synthesis of testosterone. Both have been shown to exert neuroprotective effects during stress. In this randomized, controlled, double-blind field study, we examined the effects of a 12-day DHEA regimen on stress indices in military men undergoing survival training. Forty-eight men were randomized to either a DHEA treatment group or placebo control group. The treatment group received 50 mg of oral DHEA supplementation daily for 5 days during classroom training followed by 7 days of 75 mg during stressful field operations. Control subjects received identical placebo pills. Salivary assays (DHEA[S], testosterone, and cortisol) were conducted at four time points: distal pre-stress (T1), proximal pre-stress (T2), mock-captivity stress (T3), and 24 h recovery (T4). Subjective distress was also assessed at T1, T3, and T4. As expected, DHEA treatment resulted in higher salivary concentrations of DHEA and DHEAS during daily living, mock-captivity stress, and recovery. Similar patterns were observed for salivary markers of anabolic balance: DHEA/cortisol, DHEAS/cortisol, and testosterone/cortisol concentration ratios. Despite notable time effects, no group differences emerged for subjective distress. A brief, low dose DHEA regimen yielded large increases in salivary DHEA(S) concentrations and enhanced anabolic balance throughout sustained military stress. These physiological changes did not extrapolate to subjective distress. PMID:21790446

  12. A recursive model-reduction method for approximate inference in Gaussian Markov random fields.

    PubMed

    Johnson, Jason K; Willsky, Alan S

    2008-01-01

    This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to subdivide the random field into smaller subfields, constructing cavity models which approximate these subfields. Each cavity model is a concise, yet faithful, model for the surface of one subfield sufficient for near-optimal inference in adjacent subfields. This basic idea leads to a tree-structured algorithm which recursively builds a hierarchy of cavity models during an "upward pass" and then builds a complementary set of blanket models during a reverse "downward pass." The marginal statistics of individual variables can then be approximated using their blanket models. Model thinning plays an important role, allowing us to develop thinned cavity and blanket models thereby providing tractable approximate inference. We develop a maximum-entropy approach that exploits certain tractable representations of Fisher information on thin chordal graphs. Given the resulting set of thinned cavity models, we also develop a fast preconditioner, which provides a simple iterative method to compute optimal estimates. Thus, our overall approach combines recursive inference, variational learning and iterative estimation. We demonstrate the accuracy and scalability of this approach in several challenging, large-scale remote sensing problems. PMID:18229805

  13. Risk Prediction Modeling of Sequencing Data Using a Forward Random Field Method

    PubMed Central

    Wen, Yalu; He, Zihuai; Li, Ming; Lu, Qing

    2016-01-01

    With the advance in high-throughput sequencing technology, it is feasible to investigate the role of common and rare variants in disease risk prediction. While the new technology holds great promise to improve disease prediction, the massive amount of data and low frequency of rare variants pose great analytical challenges on risk prediction modeling. In this paper, we develop a forward random field method (FRF) for risk prediction modeling using sequencing data. In FRF, subjects’ phenotypes are treated as stochastic realizations of a random field on a genetic space formed by subjects’ genotypes, and an individual’s phenotype can be predicted by adjacent subjects with similar genotypes. The FRF method allows for multiple similarity measures and candidate genes in the model, and adaptively chooses the optimal similarity measure and disease-associated genes to reflect the underlying disease model. It also avoids the specification of the threshold of rare variants and allows for different directions and magnitudes of genetic effects. Through simulations, we demonstrate the FRF method attains higher or comparable accuracy over commonly used support vector machine based methods under various disease models. We further illustrate the FRF method with an application to the sequencing data obtained from the Dallas Heart Study. PMID:26892725

  14. 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

  15. 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. PMID:27566771

  16. Prediction coefficient estimation in Markov random fields for iterative x-ray CT reconstruction

    NASA Astrophysics Data System (ADS)

    Wang, Jiao; Sauer, Ken; Thibault, Jean-Baptiste; Yu, Zhou; Bouman, Charles

    2012-02-01

    Bayesian estimation is a statistical approach for incorporating prior information through the choice of an a priori distribution for a random field. A priori image models in Bayesian image estimation are typically low-order Markov random fields (MRFs), effectively penalizing only differences among immediately neighboring voxels. This limits spectral description to a crude low-pass model. For applications where more flexibility in spectral response is desired, potential benefit exists in models which accord higher a priori probability to content in higher frequencies. Our research explores the potential of larger neighborhoods in MRFs to raise the number of degrees of freedom in spectral description. Similarly to classical filter design, the MRF coefficients may be chosen to yield a desired pass-band/stop-band characteristic shape in the a priori model of the images. In this paper, we present an alternative design method, where high-quality sample images are used to estimate the MRF coefficients by fitting them into the spatial correlation of the given ensemble. This method allows us to choose weights that increase the probability of occurrence of strong components at particular spatial frequencies. This allows direct adaptation of the MRFs for different tissue types based on sample images with different frequency content. In this paper, we consider particularly the preservation of detail in bone structure in X-ray CT. Our results show that MRF design can be used to obtain bone emphasis similar to that of conventional filtered back-projection (FBP) with a bone kernel.

  17. 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.

  18. Scene-Layout Compatible Conditional Random Field for Classifying Terrestrial Laser Point Clouds

    NASA Astrophysics Data System (ADS)

    Luo, C.; Sohn, G.

    2014-08-01

    Terrestrial Laser Scanning (TLS) rapidly becomes a primary surveying tool due to its fast acquisition of highly dense threedimensional point clouds. For fully utilizing its benefits, developing a robust method to classify many objects of interests from huge amounts of laser point clouds is urgently required. Conditional Random Field (CRF) is a well-known discriminative classifier, which integrates local appearance of the observation (laser point) with spatial interactions among its neighbouring points in classification process. Typical CRFs employ generic label consistency using short-range dependency only, which often causes locality problem. In this paper, we present a multi-range and asymmetric Conditional Random Field (CRF) (maCRF), which adopts a priori information of scene-layout compatibility addressing long-range dependency. The proposed CRF constructs two graphical models, one for enhancing a local labelling smoothness within short-range (srCRF) and the other for favouring a global and asymmetric regularity of spatial arrangement between different object classes within long-range (lrCRF). This maCRF classifier assumes two graphical models (srCRF and lrCRF) are independent of each other. Final labelling decision was accomplished by probabilistically combining prediction results obtained from two CRF models. We validated maCRF's performance with TLS point clouds acquired from RIEGL LMS-Z390i scanner using cross validation. Experiment results demonstrate that synergetic classification improvement can be achievable by incorporating two CRF models.

  19. 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

  20. 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

  1. 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

  2. Discharge simulation using downscaled spatial rainfall field by introducing correlation effect in random cascade method

    NASA Astrophysics Data System (ADS)

    Shrestha, R. K.; Tachikawa, Y.; Takara, K.

    2003-04-01

    The simulation of spatial rainfall field based on non-homogenous random cascade method disaggregates a regionally averaged rainfall such as the GCM output. The cascade-generators are used to disaggregate and produce spatial patterns across the region (Over and Gupta, 1996; Chatchai et al. 2000; Tachikawa et al. 2003). However, the disaggregated data is rarely used to produce discharge by using distributed hydrological model. The hesitation to use disaggregated GCM data in discharge simulation is mainly due to lower reliability to reproduce spatial pattern and higher chance of magnitude fluctuation in a few trials of disaggregation. Long term disaggregation results, which are expected to produce true spatial pattern, may not be convenient for practical discharge simulation. A modified method is tested by keeping the volume balanced and forcing the location of cascade generators on the basis of spatial correlation of rainfall field with respect to surround regions. In this method, a reference matrix is prepared, which is calculated for every target grid by summing the multiplication of rainfall magnitude and spatial correlation coefficient of the respective reference grids. The reference matrix is used to adjust the location of random generator in two ways -- hierarchically and statistically. So, this method is designated as Hierarchical and Statistical Adjustment (HSA) method. The HSA method preserves the magnitude of random cascade generators but modifies the location. Unlike the previous non-homogenous random cascade method, this method produced similar spatial patterns as that of ground truth in every realization, which is a clear indication of improved reliability of the disaggregation method from coarse GCM output to a finer resolution as demanded by the hydrological model. The forced volume balance may be justified from the engineering aspect to maintain the same input quantity of rainfall in a watershed for hydrologic simulation purpose. The downscaled data

  3. Ensemble Solute Transport in 2-D Operator-Stable Random Fields

    NASA Astrophysics Data System (ADS)

    Monnig, N. D.; Benson, D. A.

    2006-12-01

    The heterogeneous velocity field that exists at many scales in an aquifer will typically cause a dissolved solute plume to grow at a rate faster than Fick's Law predicts. Some statistical model must be adopted to account for the aquifer structure that engenders the velocity heterogeneity. A fractional Brownian motion (fBm) model has been shown to create the long-range correlation that can produce continually faster-than-Fickian plume growth. Previous fBm models have assumed isotropic scaling (defined here by a scalar Hurst coefficient). Motivated by field measurements of aquifer hydraulic conductivity, recent techniques were developed to construct random fields with anisotropic scaling with a self-similarity parameter that is defined by a matrix. The growth of ensemble plumes is analyzed for transport through 2-D "operator- stable" fBm hydraulic conductivity (K) fields. Both the longitudinal and transverse Hurst coefficients are important to both plume growth rates and the timing and duration of breakthrough. Smaller Hurst coefficients in the transverse direction lead to more "continuity" or stratification in the direction of transport. The result is continually faster-than-Fickian growth rates, highly non-Gaussian ensemble plumes, and a longer tail early in the breakthrough curve. Contrary to some analytic stochastic theories for monofractal K fields, the plume growth rate never exceeds Mercado's [1967] purely stratified aquifer growth rate of plume apparent dispersivity proportional to mean distance. Apparent super-Mercado growth must be the result of other factors, such as larger plumes corresponding to either a larger initial plume size or greater variance of the ln(K) field.

  4. 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. PMID:26926866

  5. 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

  6. 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

  7. 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.

  8. 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

  9. Distribution of the Height of Local Maxima of Gaussian Random Fields*

    PubMed Central

    Cheng, Dan; Schwartzman, Armin

    2015-01-01

    Let {f(t) : t ∈ T} be a smooth Gaussian random field over a parameter space T, where T may be a subset of Euclidean space or, more generally, a Riemannian manifold. We provide a general formula for the distribution of the height of a local maximum P{f(t0)>u∣t0 is a local maximum of f(t)} when f is non-stationary. Moreover, we establish asymptotic approximations for the overshoot distribution of a local maximum P{f(t0)>u+v∣t0 is a local maximum of f(t) and f(t0) > v} as v → ∞. Assuming further that f is isotropic, we apply techniques from random matrix theory related to the Gaussian orthogonal ensemble to compute such conditional probabilities explicitly when T is Euclidean or a sphere of arbitrary dimension. Such calculations are motivated by the statistical problem of detecting peaks in the presence of smooth Gaussian noise. PMID:26478714

  10. 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.

  11. 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.

  12. Polarization dynamics and polarization time of random three-dimensional electromagnetic fields

    SciTech Connect

    Voipio, Timo; Setaelae, Tero; Shevchenko, Andriy; Friberg, Ari T.

    2010-12-15

    We investigate the polarization dynamics of random, stationary three-dimensional (3D) electromagnetic fields. For analyzing the time evolution of the instantaneous polarization state, two intensity-normalized polarization autocorrelation functions are introduced, one based on a geometric approach with the Poincare vectors and the other on energy considerations with the Jones vectors. Both approaches lead to the same conclusions on the rate and strength of the polarization dynamics and enable the definition of a polarization time over which the state of polarization remains essentially unchanged. For fields obeying Gaussian statistics, the two correlation functions are shown to be expressible in terms of quantities characterizing partial 3D polarization and electromagnetic coherence. The 3D degree of polarization is found to have the same meaning in the 3D polarization dynamics as the usual two-dimensional (2D) degree of polarization does with planar fields. The formalism is demonstrated with several examples, and it is expected to be useful in applications dealing with polarization fluctuations of 3D light.

  13. 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.

  14. 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.

  15. Face Association for Videos Using Conditional Random Fields and Max-Margin Markov Networks.

    PubMed

    Du, Ming; Chellappa, Rama

    2016-09-01

    We address the video-based face association problem, in which one attempts to extract the face tracks of multiple subjects while maintaining label consistency. Traditional tracking algorithms have difficulty in handling this task, especially when challenging nuisance factors like motion blur, low resolution or significant camera motions are present. We demonstrate that contextual features, in addition to face appearance itself, play an important role in this case. We propose principled methods to combine multiple features using Conditional Random Fields and Max-Margin Markov networks to infer labels for the detected faces. Different from many existing approaches, our algorithms work in online mode and hence have a wider range of applications. We address issues such as parameter learning, inference and handling false positves/negatives that arise in the proposed approach. Finally, we evaluate our approach on several public databases. PMID:26552075

  16. 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

  17. 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.

  18. Adaptation of the projection-slice theorem for stock valuation estimation using random Markov fields

    NASA Astrophysics Data System (ADS)

    Riasati, Vahid R.

    2009-04-01

    The Projection-Slice Synthetic Discriminant function filter is utilized with Random Markov Fields, RMF to estimate trends that may be used as prediction for stock valuation through the representation of the market behavior as a hidden Markov Model, HMM. In this work, we utilize a set of progressive and contiguous time segments of a given stock, and treat the set as a two dimensional object that has been represented by its one-d projections. The abstract two-D object is thus an incarnation of N-temporal projections. The HMM is then utilized to generate N+1 projections that maximizes the two-dimensional correlation peak between the data and the HMM-generated stochastic processes. This application of the PSDF provides a method of stock valuation prediction via the market stochastic behavior utilized in the filter.

  19. RANDOM AND SYSTEMATIC FIELD ERRORS IN THE SNS RING: A STUDY OF THEIR EFFECTS AND COMPENSATION

    SciTech Connect

    GARDNER,C.J.; LEE,Y.Y.; WENG,W.T.

    1998-06-22

    The Accumulator Ring for the proposed Spallation Neutron Source (SNS) [l] is to accept a 1 ms beam pulse from a 1 GeV Proton Linac at a repetition rate of 60 Hz. For each beam pulse, 10{sup 14} protons (some 1,000 turns) are to be accumulated via charge-exchange injection and then promptly extracted to an external target for the production of neutrons by spallation. At this very high intensity, stringent limits (less than two parts in 10,000 per pulse) on beam loss during accumulation must be imposed in order to keep activation of ring components at an acceptable level. To stay within the desired limit, the effects of random and systematic field errors in the ring require careful attention. This paper describes the authors studies of these effects and the magnetic corrector schemes for their compensation.

  20. Specifications and Martin boundaries for P(Φ)2-random fields

    NASA Astrophysics Data System (ADS)

    Röckner, Michael

    1986-03-01

    It is shown that P(Φ)2-Gibbs states in the sense of Guerra, Rosen and Simon are given by a specification. The construction of the specification is based on finding a proper version of the interaction density given by the polynomial P. The existence of this version follows from the fact that all powers of the solution of a Dirichlet problem for an open bounded set U with boundary data given by a distribution are integrable on U. As a consequence the Martin boundary theory for specifications can be applied to P(Φ)2-random fields. It follows that any P(Φ)2-Gibbs state can be represented in terms of extreme Gibbs states. In certain cases the extreme Gibbs states are characterized in terms of harmonic functions. It follows, in particular, that for any given boundary condition introduced so far the associated cutoff P(Φ)2-measure has a representation as an integral over harmonic functions.

  1. 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

  2. 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.

  3. Kinetic equations for hopping transport and spin relaxation in a random magnetic field

    NASA Astrophysics Data System (ADS)

    Shumilin, A. V.; Kabanov, V. V.

    2015-07-01

    We derive the kinetic equations for a hopping transport that take into account an electron spin and the possibility of double occupation. In the Ohmic regime, the equations are reduced to the generalized Miller-Abrahams resistor network. We apply these equations to the problem of the magnetic moment relaxation due to the interaction with the random hyperfine fields. It is shown that in a wide range of parameters the relaxation rate is governed by the hops with the similar rates as spin precession frequency. It is demonstrated that at the large time scale spin relaxation is nonexponential. We argue that the nonexponential relaxation of the magnetic moment is related to the spin of electrons in the slow-relaxing traps. Interestingly, the traps can significantly influence the spin relaxation in the infinite conducting cluster at large times.

  4. 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.

  5. Mean-field dynamics of a random neural network with noise

    NASA Astrophysics Data System (ADS)

    Klinshov, Vladimir; Franović, Igor

    2015-12-01

    We consider a network of randomly coupled rate-based neurons influenced by external and internal noise. We derive a second-order stochastic mean-field model for the network dynamics and use it to analyze the stability and bifurcations in the thermodynamic limit, as well as to study the fluctuations due to the finite-size effect. It is demonstrated that the two types of noise have substantially different impact on the network dynamics. While both sources of noise give rise to stochastic fluctuations in the case of the finite-size network, only the external noise affects the stationary activity levels of the network in the thermodynamic limit. We compare the theoretical predictions with the direct simulation results and show that they agree for large enough network sizes and for parameter domains sufficiently away from bifurcations.

  6. Object-oriented image coding scheme based on DWT and Markov random field

    NASA Astrophysics Data System (ADS)

    Zheng, Lei; Wu, Hsien-Hsun S.; Liu, Jyh-Charn S.; Chan, Andrew K.

    1998-12-01

    In this paper, we introduce an object-oriented image coding algorithm to differentiate regions of interest (ROI) in visual communications. Our scheme is motivated by the fact that in visual communications, image contents (objects) are not equally important. For a given network bandwidth budget, one should give the highest transmission priority to the most interesting object, and serve the remaining ones at lower priorities. We propose a DWT based Multiresolution Markov Random Field technique to segment image objects according to their textures. We show that this technique can effectively distinguish visual objects and assign them different priorities. This scheme can be integrated with our ROI compression coder, the Generalized Self-Similarity Tress codex, for networking applications.

  7. Extended power-law scaling of heavy-tailed random fields or processes

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

    We analyze the scaling behaviors of two log permeability data sets showing heavy-tailed frequency distributions in three and two spatial dimensions, respectively. One set consists of 1-m scale pneumatic packer test data from six vertical and inclined boreholes spanning a decameters scale block of unsaturated fractured tuffs near Superior, Arizona, the other of pneumatic minipermeameter data measured at a spacing of 15 cm along two horizontal transects on a 21 m long outcrop of lower-shoreface bioturbated sandstone near Escalante, Utah. Order q sample structure functions of each data set scale as a power ξ (q) of separation scale or lag, s, over limited ranges of s. A procedure known as Extended Self-Similarity (ESS) extends this range to all lags and yields a nonlinear (concave) functional relationship between ξ (q) and q. Whereas the literature tends to associate extended and nonlinear power-law scaling with multifractals or fractional Laplace motions, we have shown elsewhere that (a) ESS of data having a normal frequency distribution is theoretically consistent with (Gaussian) truncated (additive, self-affine, monofractal) fractional Brownian motion (tfBm), the latter being unique in predicting a breakdown in power-law scaling at small and large lags, and (b) nonlinear power-law scaling of data having either normal or heavy-tailed frequency distributions is consistent with samples from sub-Gaussian random fields or processes subordinated to tfBm, stemming from lack of ergodicity which causes sample moments to scale differently than do their ensemble counterparts. Here we (i) demonstrate that the above two data sets are consistent with sub-Gaussian random fields subordinated to tfBm and (ii) provide maximum likelihood estimates of parameters characterizing the corresponding Lévy stable subordinators and tfBm functions.

  8. Classifying Urban Land cover using Spatial Weights: A Comparison of Discriminant Analysis and Markov Random Fields

    NASA Astrophysics Data System (ADS)

    Wentz, E.; Song, Y.

    2011-12-01

    Classifying urban area images is challenging because of the heterogeneous nature of the urban landscape. This means that each pixel represents a mixture of classes with potentially highly variable various spectral values. Land cover classification approaches using ancillary data, such as knowledge based or expert systems, have shown to improve the classification accuracy in urban areas, particularly with medium or low-resolution imagery. This is because information other than the spectral signatures is used to assign pixels to classes. Defining rules is challenging and acquiring appropriate ancillary data may not always be possible. The goal of this study is to compare the results of three approaches to classify urban land cover with medium resolution data with and without ancillary information. We compare discriminant analysis, Markov random fields, and an expert system. Furthermore, we explore whether including spatial weights improves classification accuracy of the discriminant model. Discriminant analysis is a statistical technique used to predict group membership for a pixel based on the linear combination of independent variables. Adding spatial weights to this includes a weighted value for neighboring pixels. Markov random fields represent spatial dependencies through conditional relationships defined using Markov principles. In comparison to using spatial dependencies in neighbouring pixels, strict per pixel statistical analysis, however, does not consider the spatial dependencies among neighbouring pixels. Our study showed that approaches using ancillary data continued to outperform strict spectral classifiers but that using a spatial weight improved the results. Furthermore, results demonstrate that when the discriminant analysis technique works well then the spatially weighted approach works better. However, when the discriminant analysis performs ineffectively, those poor results are magnified. This study suggests that spatial weights improve the

  9. 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

  10. 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

  11. The effect of random field errors on the radiation spectra of selected APS (Advanced Photon Source) undulators

    SciTech Connect

    Alp, E.E.; Viccaro, P.J.

    1987-08-01

    The effect of random magnetic field errors are introduced into the calculations of spectral characteristics of tunable undulators for the proposed 7 GeV Advanced Photon Source (APS). Single electron calculations are made for an undulator with a first harmonic radiation tunable between 3.5 and 13 keV. Using the universal curves developed by Kincaid, the effect of randomly distributed field errors on the first and third harmonics of two proposed typical undulators are calculated. It is found that the lower limit of 0.5% in field errors is more than sufficient for the successful operation of the undulators planned for the APS.

  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. 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.

  14. Sub-pixel porosity revealed by x-ray scatter dark field imaging

    NASA Astrophysics Data System (ADS)

    Revol, V.; Jerjen, I.; Kottler, C.; Schütz, P.; Kaufmann, R.; Lüthi, T.; Sennhauser, U.; Straumann, U.; Urban, C.

    2011-08-01

    X-ray scatter dark field imaging based on the Talbot-Lau interferometer allows for the measurement of ultra-small angle x-ray scattering. The latter is related to the variations in the electron density in the sample at the sub- and micron-scale. Therefore, information on features of the object below the detector resolution can be revealed. In this article, it is demonstrated that scatter dark field imaging is particularly adapted to the study of a material's porosity. An interferometer, optimized for x-ray energies around 50 keV, enables the investigation of aluminum welding with conventional laboratory x-ray tubes. The results show an unprecedented contrast between the pool and the aluminum workpiece. Our conclusions are confirmed due to micro-tomographic three-dimensional reconstructions of the same object with a microscopic resolution.

  15. Compensated Row-Column Ultrasound Imaging System Using Fisher Tippett Multilayered Conditional Random Field Model

    PubMed Central

    Ben Daya, Ibrahim; Chen, Albert I. H.; Shafiee, Mohammad Javad; Wong, Alexander; Yeow, John T. W.

    2015-01-01

    3-D ultrasound imaging offers unique opportunities in the field of non destructive testing that cannot be easily found in A-mode and B-mode images. To acquire a 3-D ultrasound image without a mechanically moving transducer, a 2-D array can be used. The row column technique is preferred over a fully addressed 2-D array as it requires a significantly lower number of interconnections. Recent advances in 3-D row-column ultrasound imaging systems were largely focused on sensor design. However, these imaging systems face three intrinsic challenges that cannot be addressed by improving sensor design alone: speckle noise, sparsity of data in the imaged volume, and the spatially dependent point spread function of the imaging system. In this paper, we propose a compensated row-column ultrasound image reconstruction system using Fisher-Tippett multilayered conditional random field model. Tests carried out on both simulated and real row-column ultrasound images show the effectiveness of our proposed system as opposed to other published systems. Visual assessment of the results show our proposed system’s potential at preserving detail and reducing speckle. Quantitative analysis shows that our proposed system outperforms previously published systems when evaluated with metrics such as Peak Signal to Noise Ratio, Coefficient of Correlation, and Effective Number of Looks. These results show the potential of our proposed system as an effective tool for enhancing 3-D row-column imaging. PMID:26658577

  16. 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.

  17. 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. PMID:24180758

  18. 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. PMID:26779642

  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. A random field approach to the Lagrangian modeling of turbulent transport in vegetated canopies

    NASA Astrophysics Data System (ADS)

    Cesari, Rita; Paradisi, Paolo

    2015-09-01

    We present an application of a Lagrangian Stochastic Model (LSM) to turbulent dispersion over complex terrain, where turbulent coherent structures are known to play a crucial role. We investigate the case of a vegetated canopy by using semi-empirical parameterizations of turbulence profiles in the region inside and above a canopy layer. The LSM is based on a 4-dimensional Fokker-Planck (4DFP) equation, which extends the standard Thomson87 Lagrangian approach. The 4DFP model is derived by means of a Random Field description of the turbulent velocity field. The main advantage of this approach is that not only the experimental Eulerian one-point statistics, but also the Eulerian two-point two-time covariance structure can be included explicitly in the LSM. At variance with the standard Thomson87 approach, the 4DFP model allows to consider explicit parameterizations of the turbulent coherent structures as it explicitly includes both spatial and temporal correlation functions. In order to investigate the effect of the turbulent geometrical structure on a scalar concentration profile, we performed numerical simulations with two different covariance parameterizations, the first one isotropic and the second anisotropic. We show that the accumulation of scalars near the ground is due to the anisotropic geometrical properties of the turbulent boundary layer.

  1. 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

  2. Image Enhancement and Speckle Reduction of Full Polarimetric SAR Data by Gaussian Markov Random Field

    NASA Astrophysics Data System (ADS)

    Mahdian, M.; Motagh, M.; Akbari, V.

    2013-09-01

    In recent years, the use of Polarimetric Synthetic Aperture Radar (PolSAR) data in different applications dramatically has been increased. In SAR imagery an interference phenomenon with random behavior exists which is called speckle noise. The interpretation of data encounters some troubles due to the presence of speckle which can be considered as a multiplicative noise affecting all coherent imaging systems. Indeed, speckle degrade radiometric resolution of PolSAR images, therefore it is needful to perform speckle filtering on the SAR data type. Markov Random Field (MRF) has proven to be a powerful method for drawing out eliciting contextual information from remotely sensed images. In the present paper, a probability density function (PDF), which is fitted well with the PolSAR data based on the goodness-of-fit test, is first obtained for the pixel-wise analysis. Then the contextual smoothing is achieved with the MRF method. This novel speckle reduction method combines an advanced statistical distribution with spatial contextual information for PolSAR data. These two parts of information are combined based on weighted summation of pixel-wise and contextual models. This approach not only preserves edge information in the images, but also improves signal-to-noise ratio of the results. The method maintains the mean value of original signal in the homogenous areas and preserves the edges of features in the heterogeneous regions. Experiments on real medium resolution ALOS data from Tehran, and also high resolution full polarimetric SAR data over the Oberpfaffenhofen test-site in Germany, demonstrate the effectiveness of the algorithm compared with well-known despeckling methods.

  3. 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

  4. 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.

  5. A biorthogonal decomposition for the identification and simulation of non-stationary and non-Gaussian random fields

    NASA Astrophysics Data System (ADS)

    Zentner, I.; Ferré, G.; Poirion, F.; Benoit, M.

    2016-06-01

    In this paper, a new method for the identification and simulation of non-Gaussian and non-stationary stochastic fields given a database is proposed. It is based on two successive biorthogonal decompositions aiming at representing spatio-temporal stochastic fields. The proposed double expansion allows to build the model even in the case of large-size problems by separating the time, space and random parts of the field. A Gaussian kernel estimator is used to simulate the high dimensional set of random variables appearing in the decomposition. The capability of the method to reproduce the non-stationary and non-Gaussian features of random phenomena is illustrated by applications to earthquakes (seismic ground motion) and sea states (wave heights).

  6. A multiarm randomized field trial evaluating strategies for udder health improvement in Swiss dairy herds.

    PubMed

    Tschopp, A; Reist, M; Kaufmann, T; Bodmer, M; Kretzschmar, L; Heiniger, D; Berchtold, B; Wohlfender, F; Harisberger, M; Boss, R; Strabel, D; Cousin, M-E; Graber, H U; Steiner, A; van den Borne, B H P

    2015-02-01

    The aims of this study were to quantify the effectiveness of specialist advice about udder health in Swiss dairy herds and to compare 3 different udder health improvement strategies against a negative control group. In 2010, 100 Swiss dairy herds with a high (between 200,000 and 300,000 cells/mL) yield-corrected bulk milk somatic cell count (YCBMSCC) were recruited for a 1-yr multiarm randomized field trial. The herds were visited between September and December 2011 to evaluate udder health-management practices and then randomly allocated into 1 of 4 study arms containing 25 herds each. The negative control study arm received neither recommendations for improving udder health nor any active support. The remaining 75 farmers received a herd-specific report with recommendations to improve udder health management. The positive control study arm received no further active support during 2012. The veterinarian study arm received additional support in the form of monthly visits by their herd veterinarian. Finally, the study group study arm received support in the form of bimonthly study group meetings where different topics concerning udder health were discussed. One year later, implementation of recommendations and changes in udder health were assessed. Of the recommendations given, 44.3% were completely implemented, 23.1% partially, and 32.6% were not implemented. No differences in implementation of recommendations were noted between the 3 study arms. At study enrollment, farmers were asked for the study arm of their preference but were subsequently randomly assigned to 1 of the 4 study arms. Farmers that were assigned to the study arm of their preference implemented more recommendations than farmers assigned to a study arm not of their preference. No decrease in the within-herd prevalence of cows that had a high (≥200,000 cells/mL) composite somatic cell count was observed in herds that had a YCBMSCC ≥200,000 cells/mL at the start of intervention. However, the 3

  7. 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

  8. Phase Transitions in Disordered Systems: The Example of the Random-Field Ising Model in Four Dimensions

    NASA Astrophysics Data System (ADS)

    Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

    2016-06-01

    By performing a high-statistics simulation of the D =4 random-field Ising model at zero temperature for different shapes of the random-field distribution, we show that the model is ruled by a single universality class. We compute to a high accuracy the complete set of critical exponents for this class, including the correction-to-scaling exponent. Our results indicate that in four dimensions (i) dimensional reduction as predicted by the perturbative renormalization group does not hold and (ii) three independent critical exponents are needed to describe the transition.

  9. 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.

  10. 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. PMID:26352447