Simpson, P. J.; Stanton, C.; Fitzgerald, G. F.; Ross, R. P.
2002-01-01
The genomic diversity of 33 previously assigned strains from six species within the genus Pediococcus was assessed by randomly amplified polymorphic DNA (RAPD) PCR and pulsed-field-gel electrophoresis (PFGE). The RAPD PCR patterns produced by two separate random primers, termed P1 (ACGCGCCCT) and P2 (ATGTAACGCC), were compared by the Pearson correlation coefficient and the unweighted pair group method with arithmetic averages clustering algorithm. Pattern variations between repeat samples set a strain discrimination threshold of less than 70% similarity. P1 and P2 primers alone and in combination produced 14, 21, and 28 distinct patterns, respectively. When each strain was assigned with a type strain with which it shared the highest level of similarity, both primers grouped 17 of the 27 strains to their proposed species. PFGE following genomic digestion with the restriction enzymes ApaI, NotI, and AscI produced 30, 32, and 28 distinct macrorestriction patterns, respectively. Specific DNA fragments within the NotI and AscI macrorestriction patterns for each strain were observed that allowed 27 of the 33 strains to be assigned to their proposed species. For example, following digestion with AscI, all Pediococcus parvulus strains were characterized by two DNA fragments, one of approximately 220 kb and another between 700 and 800 kb. The exceptions correlated with those observed with both RAPD PCR primers and included three P. damnosus and two P. pentosaceus strains that grew at temperatures regarded as nonpermissive for their proposed species but not for those with which they grouped. PMID:11823217
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.
Associative Hierarchical Random Fields.
Ladický, L'ubor; Russell, Chris; Kohli, Pushmeet; Torr, Philip H S
2014-06-01
This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic segmentation are formulated as a labeling problem for variables that might correspond to either pixels or segments such as super-pixels. It is well known that the generation of super pixel segmentations is not unique. This has motivated many researchers to use multiple super pixel segmentations for problems such as semantic segmentation or single view reconstruction. These super-pixels have not yet been combined in a principled manner, this is a difficult problem, as they may overlap, or be nested in such a way that the segmentations form a segmentation tree. Our new hierarchical random field model allows information from all of the multiple segmentations to contribute to a global energy. MAP inference in this model can be performed efficiently using powerful graph cut based move making algorithms. Our framework generalizes much of the previous work based on pixels or segments, and the resulting labelings can be viewed both as a detailed segmentation at the pixel level, or at the other extreme, as a segment selector that pieces together a solution like a jigsaw, selecting the best segments from different segmentations as pieces. We evaluate its performance on some of the most challenging data sets for object class segmentation, and show that this ability to perform inference using multiple overlapping segmentations leads to state-of-the-art results.
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.
Random scalar fields and hyperuniformity
NASA Astrophysics Data System (ADS)
Ma, Zheng; Torquato, Salvatore
2017-06-01
Disordered many-particle hyperuniform systems are exotic amorphous states of matter that lie between crystals and liquids. Hyperuniform systems have attracted recent attention because they are endowed with novel transport and optical properties. Recently, the hyperuniformity concept has been generalized to characterize two-phase media, scalar fields, and random vector fields. In this paper, we devise methods to explicitly construct hyperuniform scalar fields. Specifically, we analyze spatial patterns generated from Gaussian random fields, which have been used to model the microwave background radiation and heterogeneous materials, the Cahn-Hilliard equation for spinodal decomposition, and Swift-Hohenberg equations that have been used to model emergent pattern formation, including Rayleigh-Bénard convection. We show that the Gaussian random scalar fields can be constructed to be hyperuniform. We also numerically study the time evolution of spinodal decomposition patterns and demonstrate that they are hyperuniform in the scaling regime. Moreover, we find that labyrinth-like patterns generated by the Swift-Hohenberg equation are effectively hyperuniform. We show that thresholding (level-cutting) a hyperuniform Gaussian random field to produce a two-phase random medium tends to destroy the hyperuniformity of the progenitor scalar field. We then propose guidelines to achieve effectively hyperuniform two-phase media derived from thresholded non-Gaussian fields. Our investigation paves the way for new research directions to characterize the large-structure spatial patterns that arise in physics, chemistry, biology, and ecology. Moreover, our theoretical results are expected to guide experimentalists to synthesize new classes of hyperuniform materials with novel physical properties via coarsening processes and using state-of-the-art techniques, such as stereolithography and 3D printing.
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
Randomized Field Experiments in Education.
ERIC Educational Resources Information Center
Tallmadge, G. Kasten
Problems with conducting randomized field experiments in education are explored. Focus is on problems encountered while evaluating a group of dropout prevention projects. Project planners were asked to manipulate the subject eligibility criteria until they identified as eligible three to four times as many students as they could serve. They were…
Maps of random walks on complex networks reveal community structure.
Rosvall, Martin; Bergstrom, Carl T
2008-01-29
To comprehend the multipartite organization of large-scale biological and social systems, we introduce an information theoretic approach that reveals community structure in weighted and directed networks. We use the probability flow of random walks on a network as a proxy for information flows in the real system and decompose the network into modules by compressing a description of the probability flow. The result is a map that both simplifies and highlights the regularities in the structure and their relationships. We illustrate the method by making a map of scientific communication as captured in the citation patterns of >6,000 journals. We discover a multicentric organization with fields that vary dramatically in size and degree of integration into the network of science. Along the backbone of the network-including physics, chemistry, molecular biology, and medicine-information flows bidirectionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences.
Efficient robust conditional random fields.
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.
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…
Random Assignment: Practical Considerations from Field Experiments.
ERIC Educational Resources Information Center
Dunford, Franklyn W.
1990-01-01
Seven qualitative issues associated with randomization that have the potential to weaken or destroy otherwise sound experimental designs are reviewed and illustrated via actual field experiments. Issue areas include ethics and legality, liability risks, manipulation of randomized outcomes, hidden bias, design intrusiveness, case flow, and…
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.)
Random processes, turbulence and disordering fields
NASA Astrophysics Data System (ADS)
Domokos, G.; Kovesi-Domokos, S.; Zoltani, C. K.
1987-10-01
There are many classical, nonlinear systems exhibiting some kind of chaotic behavior. Examples include the turbulent flow of a fluid, usually described by means of the Navier-Stokes equations, and the behavior of liquids, gases or antiferromagnets above the critical point, etc. In this paper, we reexamine and further develop an approach to the description of such systems. The statistical theory of random process is cast into a Lagrangian form. The formalism requires the existence of an arbitrarily weak random stirring force, playing the role of a disordering field. In scale invariant systems the coupling strength of the weak stirring force can be scaled out and it disappears from the theory.
Random electric field instabilities of relaxor ferroelectrics
Arce-Gamboa, Jose R.; Guzman-Verri, Gian G.
2017-06-13
Relaxor ferroelectrics are complex oxide materials which are rather unique to study the effects of compositional disorder on phase transitions. Here, we study the effects of quenched cubic random electric fields on the lattice instabilities that lead to a ferroelectric transition and show that, within a microscopic model and a statistical mechanical solution, even weak compositional disorder can prohibit the development of long-range order and that a random field state with anisotropic and power-law correlations of polarization emerges from the combined effect of their characteristic dipole forces and their inherent charge disorder. As a result, we compare and reproduce severalmore » key experimental observations in the well-studied relaxor PbMg1/3Nb2/3O3–PbTiO3.« less
Random fields at a nonequilibrium phase transition.
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.
Gradient Boosting for Conditional Random Fields
2014-09-23
Information Processing Systems 26 ( NIPS ’13), pages 647–655. 2013. [4] J. Friedman. Greedy function approximation: a gradient boosting machine. Annals of...and phrases and their compositionality. In Advances in Neural Information Processing Systems 26 ( NIPS ’13), pages 3111–3119. 2013. [15] A. Quattoni, M...Collins, and T. Darrell. Conditional random fields for object recognition. In Advances in Neural Information Processing Systems 17 ( NIPS ’04), pages
Variational Infinite Hidden Conditional Random Fields.
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.
Spectral Design in Markov Random Fields
NASA Astrophysics Data System (ADS)
Wang, Jiao; Thibault, Jean-Baptiste; Yu, Zhou; Sauer, Ken; Bouman, Charles
2011-03-01
Markov random fields (MRFs) have been shown to be a powerful and relatively compact stochastic model for imagery in the context of Bayesian estimation. The simplicity of their conventional embodiment implies local computation in iterative processes and relatively noncommittal statistical descriptions of image ensembles, resulting in stable estimators, particularly under models with strictly convex potential functions. This simplicity may be a liability, however, when the inherent bias of minimum mean-squared error or maximum a posteriori probability (MAP) estimators attenuate all but the lowest spatial frequencies. In this paper we explore generalization of MRFs by considering frequency-domain design of weighting coefficients which describe strengths of interconnections between clique members.
Neutrino propagation in a random magnetic field
Sahu, S.
1997-10-01
The active-sterile neutrino conversion probability is calculated for a neutrino propagating in a medium in the presence of random magnetic field fluctuations. A necessary condition for the probability to be positive definite is obtained for active-sterile electron neutrino conversion in the early universe hot plasma and in a supernova. The neutrino magnetic moment obtained from the positive definiteness of the conversion probability defines the range of validity of our approximation, rather than putting any physical bound on it. {copyright} {ital 1997} {ital The American Physical Society}
Neutrino Conversions in Solar Random Magnetic Fields
NASA Astrophysics Data System (ADS)
Torrente-Lujan, E.
We consider the effect of a random magnetic field in the convective zone of the Sun on resonant neutrino spin-flavour oscillations. We argue for the existence of a field of strongly chaotic nature at the bottom of the convective zone. 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 find that MSW regions are stable up to very large levels of noise (P=0.7-0.8) and they are acceptable from the point of view of antineutrino production. For strong noise any parameter region (Δm2,sin22θ) is excluded: this model of noisy magnetic field is not compatible with particle physics solutions to the SNP. One is allowed then to reverse the problem and to put limits on r.m.s field strength, correlation length and transition magnetic moments by demanding a solution to the SNP under this scenario.
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.
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.
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).
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.
Effects of random fields in an antiferromagnetic Ising bilayer film
NASA Astrophysics Data System (ADS)
Kaneyoshi, T.
2017-10-01
The magnetic properties (phase diagrams and magnetizations) of an antiferromagnetic Ising bilayer film with random fields are investigated by the use of the effective field theory with correlations. It is examined how an uncompensated magnetization can be realized in the system, due to the effects of random fields in the two layers. They show the tricritical, compensation point and reentrant phenomena, depending on these parameters.
Khaneja, Mamta; Ghosh, Santanu; Gautam, Seema; Kumar, Prashant; Rawat, J S; Chaudhury, P K; Vankar, V D; Kumar, Vikram
2015-05-01
High field emission (FE) current density from carbon nanotube (CNT) arrays grown on lithographically patterned silicon substrates is reported. A typical patterned field emitter array consists of bundles of nanotubes separated by a fixed gap and spread over the entire emission area. Emission performance from such an array having randomly oriented nanotube growth within each bundle is reported for different bundle sizes and separations. One typical sample with aligned CNTs within the bundle is also examined for comparison. It is seen that the current density from an array having random nanotube growth within the bundles is appreciably higher as compared to its aligned counterpart. The influence of structure on FE current densities as revealed by Raman spectroscopy is also seen. It is also observed that current density depends on edge length and increases with the same for all samples under study. Highest current density of -100 mA cm(-2) at an applied field of 5 V/μm is achieved from the random growth patterned sample with a bundle size of 2 μm and spacing of 4 μm between the bundles.
Effects of random fields in an antiferromagnetic Ising spin glass
Vieira; Nobre; Yokoi
2000-05-01
The effects of random fields on the two-sublattice infinite-ranged Ising spin-glass model are investigated. This model is expected to be appropriate as a mean-field description of antiferromagnetic spin glasses such as FexMn1-xTiO3. Within replica-symmetric calculations, we study the influence of Gaussian and bimodal random fields on the phase transitions and phase diagrams. It is shown that, in the presence of random fields, the first-order transitions are weakened and may become continuous. Also, the antiferromagnetic phases are always destroyed by sufficiently strong random fields. A qualitative comparison with existing experimental results and the limitations of the present calculations are discussed.
Frequency of encounter of aircraft in a random horizontal field
NASA Technical Reports Server (NTRS)
Bird, J. D.; Smith, K. A.
1976-01-01
Calculations were made of the frequency of encounter as a function of azimuth of encounter of a passing aircraft with the aircraft in a random planar horizontal field. All the field aircraft moved at a constant speed but in random directions. These calculations included the total frequency of encounter with the aircraft of the field and the frequency of encounter with those aircraft of the field which were encountered in the fore quadrant, in the lateral quadrants, and in the rear quadrant; the calculations were made for various speed ratios of the field aircraft and the passing aircraft.
Listening to the noise: random fluctuations reveal gene network parameters.
Munsky, Brian; Trinh, Brooke; Khammash, Mustafa
2009-01-01
The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations show cell-to-cell variability that can manifest significant phenotypic differences. Noise-induced stochastic fluctuations in cellular constituents 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 show 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.
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.
The space transformation in the simulation of multidimensional random fields
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.
Subquantum nonlocal correlations induced by the background random field
NASA Astrophysics Data System (ADS)
Khrennikov, Andrei
2011-10-01
We developed a purely field model of microphenomena—prequantum classical statistical field theory (PCSFT). This model not only reproduces important probabilistic predictions of quantum mechanics (QM) including correlations for entangled systems, but also gives a possibility to go beyond QM, i.e. to make predictions of phenomena that could be observed at the subquantum level. In this paper, we discuss one such prediction—the existence of nonlocal correlations between prequantum random fields corresponding to all quantum systems. (And by PCSFT, quantum systems are represented by classical Gaussian random fields and quantum observables by quadratic forms of these fields.) The source of these correlations is the common background field. Thus all prequantum random fields are 'entangled', but in the sense of classical signal theory. On the one hand, PCSFT demystifies quantum nonlocality by reducing it to nonlocal classical correlations based on the common random background. On the other hand, it demonstrates total generality of such correlations. They exist even for distinguishable quantum systems in factorizable states (by PCSFT terminology—for Gaussian random fields with covariance operators corresponding to factorizable quantum states).
Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters
NASA Astrophysics Data System (ADS)
Munsky, Brian; Trinh, Brooke; Khammash, Mustafa
2010-03-01
The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations exhibit cell-to-cell variability that can manifest significant prototypical differences. Noise induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified using flow cytometry, single molecule fluorescence in situ hybridization, time lapse fluorescence microscopy and other single cell and single molecule measurement techniques. 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. We use theoretical investigations to establish experimental guidelines for the identification of gene regulatory networks, and we apply these guideline to experimentally identify predictive models for different regulatory mechanisms in bacteria and yeast.
Listening to the noise: random fluctuations reveal gene network parameters
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.
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.
On the Angle for Stationary Random Fields.
1985-04-01
Soltani [15], dealing with regularity and quarter-plane moving average representation; and Miamee [10], where an extension of Szego’s theorem for...lemma. Using Lemma 3.8 above and Theorem 3.4 of Soltani [15] we arrive at the following lemma. 3.9 Lemma. Let X be a stationary field with spectral...Mandrekar [7]. (One can also see Korezlioglu and Loubaton [8], and Miamee [10]). A set of such sufficient conditions is also given by Soltani [15
Random fields and phase transitions in model magnetic systems
NASA Astrophysics Data System (ADS)
Birgeneau, R. J.
1998-01-01
Random fields occur in a wide variety of physical systems varying from type II superconductors to two-component fluids in a random medium. However, only in model magnetic systems have systematic studies as a function of both temperature and random-field strength been possible. In this article we review recent neutron and magnetic X-ray scattering studies of the magnetic ordering processes in the antiferromagnets Mn 0.75Zn 0.25F 2, Fe 0.5Zn 0.5F 2 and Fe 0.75Co 0.25TiO 3 in an applied magnetic field. These systems should all represent realizations of the three-dimensional random-field Ising model which is the simplest version of the random-field problem in models with discrete symmetry. In all cases on field cooling (FC) the systems evolve continuously from a high-temperature paramagnetic state to a low-temperature antiferromagnetic domain state. However, on cooling to low temperatures in zero field and then applying a field (ZFC) long-range order (LRO) is obtained. On subsequent heating in the three systems the LRO vanishes continuously with a rounded power-law behavior which has been labelled trompe l'oeil critical behavior. The width of the transition region scales as H2. Reconsideration of indirect ZFC specific-heat measurements shows that the observed peaks, previously attributed to equilibrium critical fluctuations, instead arise entirely from a LRO contribution, scaling like dM s2/dT , to the measured quantity. Here Ms is the staggered magnetization. These results thus reconcile scattering and bulk property measurements of random-field Ising systems.
Markov Random Fields, Stochastic Quantization and Image Analysis
1990-01-01
Markov random fields based on the lattice Z2 have been extensively used in image analysis in a Bayesian framework as a-priori models for the...of Image Analysis can be given some fundamental justification then there is a remarkable connection between Probabilistic Image Analysis , Statistical Mechanics and Lattice-based Euclidean Quantum Field Theory.
Aging in the two-dimensional random-field systems
NASA Astrophysics Data System (ADS)
Cheng, Xiang; Ma, Tianyu; Urazhdin, Sergei; Boettcher, Stefan
Random fields introduced into the classical Ising and Heisenberg spin models can roughen the energy landscape, leading to complex nonequilibrium dynamics. The effects of random fields on magnetism have been previously studied in the context of dilute antiferromagnets (AF), impure substrates, and magnetic alloys [ 1 ] . We utilized random-field spin models to simulate the observed magnetic aging in thin-film ferromagnet/antiferromagnet (F/AF) bilayers. Our experiments show extremely slow cooperative relaxation over a wide range of temperatures and magnetic fields [ 2 ] . In our simulations, the experimental system is coarse-grained into a random field Ising model on a 2D square lattice. Monte Carlo simulations indicate that aging processes may be associated with the glassy evolution of the magnetic domain walls, due to the pinning by the random fields. The scaling of the simulated aging agrees well with experiments. Both are consistent with either a small power-law or logarithmic dependence on time. We further discuss the topological effects on aging due to the dimensional crossover from the Ising to the Heisenberg regime. Supported through NSF grant DMR-1207431.
Effective diffusion equation in a random velocity field
NASA Technical Reports Server (NTRS)
Vinals, Jorge; Sekerka, Robert F.
1992-01-01
The effects are studied of assumed random velocity fields on diffusion in a binary fluid. Random velocity fields can result, for example, from the high-frequency components of residual accelerations onboard spacecraft (often called g-jitter). An effective diffusion equation is derived for an average concentration which includes spatial and temporal correlations induced by the fluctuating velocity fields assumed to be Gaussianly distributed. The resulting equation becomes nonlocal, and if correlations between different components of the velocity field exist, it is also anisotropic. The simple limiting case of short correlation times is discussed and an effective diffusivity is obtained which reflects the enhanced mixing caused by the velocity fields. The results obtained in the limit of short correlation times are valid even if the probability distribution of the velocity field is not Gaussian.
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.
Field-theoretic simulations of random copolymers with structural rigidity.
Mao, Shifan; MacPherson, Quinn; Qin, Jian; Spakowitz, Andrew J
2017-04-12
Copolymers play an important role in a range of soft-materials applications and biological phenomena. Prevalent works on block copolymer phase behavior use flexible chain models and incorporate interactions using a mean-field approximation. However, when phase separation takes place on length scales comparable to a few monomers, the structural rigidity of the monomers becomes important. In addition, concentration fluctuations become significant at short length scales, rendering the mean-field approximation invalid. In this work, we use simulation to address the role of finite monomer rigidity and concentration fluctuations in microphase segregation of random copolymers. Using a field-theoretic Monte-Carlo simulation of semiflexible polymers with random chemical sequences, we generate phase diagrams for random copolymers. We find that the melt morphology of random copolymers strongly depends on chain flexibility and chemical sequence correlation. Chemically anti-correlated copolymers undergo first-order phase transitions to local lamellar structures. With increasing degree of chemical correlation, this first-order phase transition is softened, and melts form microphases with irregular shaped domains. Our simulations in the homogeneous phase exhibit agreement with the density-density correlation from mean-field theory. However, conditions near a phase transition result in deviations between simulation and mean-field theory for the density-density correlation and the critical wavemode. Chain rigidity and sequence randomness lead to frustration in the segregated phase, introducing heterogeneity in the resulting morphologies.
Trimodal Random-Field Ising Systems in a Transverse Field
1991-04-01
3009 (1985). 14. R. J. Elliott and C . Wood, J. Phys. C : Solid State Phys. 4, 2359 (197). 15. J. Otiman and M. Pischke, Physica B 86-88, 577 (1977). 16...separation of a two-component fluid mixture in porous material or gelatine and the solution of hydrogen in metallic alloys . 5 Of more interest is the...mean-field approximation, with the corresponding coordination number z - 6, 12 and c , respectively. It is observed from Figs. 2(a) and 2(b) that the
Internetwork magnetic field as revealed by two-dimensional inversions
NASA Astrophysics Data System (ADS)
Danilovic, S.; van Noort, M.; Rempel, M.
2016-09-01
Context. Properties of magnetic field in the internetwork regions are still fairly unknown because of rather weak spectropolarimetric signals. Aims: We address the matter by using the two-dimensional (2D) inversion code, which is able to retrieve the information on smallest spatial scales up to the diffraction limit, while being less susceptible to noise than most of the previous methods used. Methods: Performance of the code and the impact of various effects on the retrieved field distribution is tested first on the realistic magneto-hydrodynamic (MHD) simulations. The best inversion scenario is then applied to the real data obtained by Spectropolarimeter (SP) on board Hinode. Results: Tests on simulations show that: (1) the best choice of node position ensures a decent retrieval of all parameters; (2) the code performs well for different configurations of magnetic field; (3) slightly different noise levels or slightly different defocus included in the spatial point spread function (PSF) produces no significant effect on the results; and (4) temporal integration shifts the field distribution to a stronger, more horizontally inclined field. Conclusions: Although the contribution of the weak field is slightly overestimated owing to noise, 2D inversions are able to recover well the overall distribution of the magnetic field strength. Application of the 2D inversion code on the Hinode SP internetwork observations reveals a monotonic field strength distribution. The mean field strength at optical depth unity is ~ 130 G. At higher layers, field strength drops as the field becomes more horizontal. Regarding the distribution of the field inclination, tests show that we cannot directly retrieve it with the observations and tools at hand, however, the obtained distributions are consistent with those expected from simulations with a quasi-isotropic field inclination after accounting for observational effects.
Dynamical properties of random-field Ising model.
Sinha, Suman; Mandal, Pradipta Kumar
2013-02-01
Extensive Monte Carlo simulations are performed on a two-dimensional random field Ising model. The purpose of the present work is to study the disorder-induced changes in the properties of disordered spin systems. The time evolution of the domain growth, the order parameter, and the spin-spin correlation functions are studied in the nonequilibrium regime. The dynamical evolution of the order parameter and the domain growth shows a power law scaling with disorder-dependent exponents. It is observed that for weak random fields, the two-dimensional random field Ising model possesses long-range order. Except for weak disorder, exchange interaction never wins over pinning interaction to establish long-range order in the system.
Rigorously testing multialternative decision field theory against random utility models.
Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg
2014-06-01
Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions.
Two Dimensional Honeycomb Materials: Random Fields, Dissipation and Fluctuations
NASA Astrophysics Data System (ADS)
Frederico, T.; Oliveira, O.; de Paula, W.; Hussein, M. S.; Cardoso, T. R.
2017-02-01
In this paper, we propose a method to describe the many-body problem of electrons in honeycomb materials via the introduction of random fields which are coupled to the electrons and have a Gaussian distribution. From a one-body approach to the problem, after integrating exactly the contribution of the random fields, one builds a non-hermitian and dissipative effective Hamiltonian with two-body interactions. Our approach introduces besides the usual average over the electron field a second average over the random fields. The interplay of two averages enables the definition of various types of Green's functions which allow the investigation of fluctuation-dissipation characteristics of the interactions that are a manifestation of the many-body problem. In the current work, we study only the dissipative term, through the perturbative analysis of the dynamics associated the effective Hamiltonian generated by two different kinds of couplings. For the cases analyzed, the eigenstates of the effective Hamiltonian are complex and, therefore, some of the states have a finite life time. Moreover, we also investigate, in the mean field approximation, the most general parity conserving coupling to the random fields and compute the width of charge carriers Γ as a function of the Fermi energy E F . The theoretical prediction for Γ( E F ) is compared to the available experimental data for graphene. The good agreement between Γ t h e o and Γ e x p suggests that description of the many-body problem associated to the electrons in honeycomb materials can indeed be done via the introduction of random fields.
Creep motion in a random-field Ising model.
Roters, L; Lübeck, S; Usadel, K D
2001-02-01
We analyze numerically a moving interface in the random-field Ising model which is driven by a magnetic field. Without thermal fluctuations the system displays a depinning phase transition, i.e., the interface is pinned below a certain critical value of the driving field. For finite temperatures the interface moves even for driving fields below the critical value. In this so-called creep regime the dependence of the interface velocity on the temperature is expected to obey an Arrhenius law. We investigate the details of this Arrhenius behavior in two and three dimensions and compare our results with predictions obtained from renormalization group approaches.
Stochastic Simulation of Microseisms Using Theory of Conditional Random Fields
NASA Astrophysics Data System (ADS)
Morikawa, H.; Akamatsu, J.; Nishimura, K.; Onoue, K.; Kameda, H.
-We examine the applicability of conditional stochastic simulation to interpretation of microseisms observed on soft soil sediments at Kushiro, Hokkaido, Japan. The theory of conditional random fields developed by Kameda and Morikawa (1994) is used, which allows one to perform interpolation of a Gaussian stochastic time-space field that is conditioned by realized values of time functions specified at some discrete locations. The applicability is examined by a blind test, that is, by comparing a set of simulated seismograms and recorded ones obtained from three-point array observa tions. A test of fitness was performed by means of the sign test. It is concluded that the method is applicable to interpretation of microseisms, and that the wave field of microseisms can be treated as Gaussian random fields both in time and space.
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…
Gaussian Markov Random Field Model without Boundary Conditions
NASA Astrophysics Data System (ADS)
Katakami, Shun; Sakamoto, Hirotaka; Murata, Shin; Okada, Masato
2017-06-01
In this study, we analyzed a Gaussian Markov random field model without periodic boundary conditions. On the basis of a Bayesian inference framework, we showed that image restoration, hyperparameter estimation, and an expectation value of free energy can be conducted analytically. Through numerical simulations, we showed the difference between methods with and without periodic boundary conditions and verified the effectiveness of the proposed method.
Probability Statements Extraction with Constrained Conditional Random Fields.
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.
Are Facilitated Mentoring Programs Beneficial? A Randomized Experimental Field Study
ERIC Educational Resources Information Center
Egan, Toby Marshall; Song, Zhaoli
2008-01-01
Results from a pretest-posttest randomized field experiment study with a control group comparing the impact of high- and low-level-facilitated mentoring programs on new employees' performance and perceptions about their jobs and organization were reported in this paper. Results indicated increases in job satisfaction, organizational commitment,…
Experimental studies of random-field effects in uniaxial random antiferromagnets
Wong, P.Z.; Cable, J.W.; von Molnar, S.; Dimon, P.
1983-11-01
We discuss how random fields (RFs) are generated in uniaxial random antiferromagnets (URAFs) by applied fields and review the experiments that have been performed on these systems. They include direct and indirect specific heat measurements, neutron scattering experiments and phase diagram studies. We compare the results of different experiments on different systems, discuss their implications on the theories, and suggest further experiments. A new explanation for the Lorentzian-squared (LSQ) structure factor observed in the neutron scattering experiments is also given. 47 references, 4 figures.
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.
Fuzzy Field Theory as a Random Matrix Model
NASA Astrophysics Data System (ADS)
Tekel, Juraj
This dissertation considers the theory of scalar fields on fuzzy spaces from the point of view of random matrices. First we define random matrix ensembles, which are natural description of such theory. These ensembles are new and the novel feature is a presence of kinetic term in the probability measure, which couples the random matrix to a set of external matrices and thus breaks the original symmetry. Considering the case of a free field ensemble, which is generalization of a Gaussian matrix ensemble, we develop a technique to compute expectation values of the observables of the theory based on explicit Wick contractions and we write down recursion rules for these. We show that the eigenvalue distribution of the random matrix follows the Wigner semicircle distribution with a rescaled radius. We also compute distributions of the matrix Laplacian of the random matrix given by the new term and demonstrate that the eigenvalues of these two matrices are correlated. We demonstrate the robustness of the method by computing expectation values and distributions for more complicated observables. We then consider the ensemble corresponding to an interacting field theory, with a quartic interaction. We use the same method to compute the distribution of the eigenvalues and show that the presence of the kinetic terms rescales the distribution given by the original theory, which is a polynomially deformed Wigner semicircle. We compute the eigenvalue distribution of the matrix Laplacian and the joint distribution up to second order in the correlation and we show that the correlation between the two changes from the free field case. Finally, as an application of these results, we compute the phase diagram of the fuzzy scalar field theory, we find multiscaling which stabilizes this diagram in the limit of large matrices and compare it with the results obtained numerically and by considering the kinetic part as a perturbation.
Using convex quadratic programming to model random media with Gaussian random fields
Quintanilla, John A.; Jones, W. Max
2007-04-15
Excursion sets of Gaussian random fields (GRFs) have been frequently used in the literature to model two-phase random media with measurable phase autocorrelation functions. The goal of successful modeling is finding the optimal field autocorrelation function that best approximates the prescribed phase autocorrelation function. In this paper, we present a technique which uses convex quadratic programming to find the best admissible field autocorrelation function under a prescribed discretization. Unlike previous methods, this technique efficiently optimizes over all admissible field autocorrelation functions, instead of optimizing only over a predetermined parametrized family. The results from using this technique indicate that the GRF model is significantly more versatile than observed in previous studies. An application to modeling a base-catalyzed tetraethoxysilane aerogel system given small-angle neutron scattering data is also presented.
Driving a Superconductor to Insulator Transition with Random Gauge Fields
Nguyen, H. Q.; Hollen, S. M.; Shainline, J.; Xu, J. M.; Valles, J. M.
2016-01-01
Typically the disorder that alters the interference of particle waves to produce Anderson localization is potential scattering from randomly placed impurities. Here we show that disorder in the form of random gauge fields that act directly on particle phases can also drive localization. We present evidence of a superfluid bose glass to insulator transition at a critical level of this gauge field disorder in a nano-patterned array of amorphous Bi islands. This transition shows signs of metallic transport near the critical point characterized by a resistance , indicative of a quantum phase transition. The critical disorder depends on interisland coupling in agreement with recent Quantum Monte Carlo simulations. We discuss how this disorder tuned SIT differs from the common frustration tuned SIT that also occurs in magnetic fields. Its discovery enables new high fidelity comparisons between theoretical and experimental studies of disorder effects on quantum critical systems. PMID:27901081
Compound random field models of multiple scale hydraulic conductivity
Haselow, J.S. ); Brannan, J.R. )
1992-09-01
Enormous amounts of hydrologic data are required to accurately simulate subsurface contaminant transport. Effectively supplementing measurements of hydrologic parameters such as permeability and porosity with soft'' information obtained from the interpretation of geologic cores and geophysical logs can improve the simulation of contaminant transport while reducing the measured data that are required. A method is presented herein for generating hydraulic conductivity fields comprised of several geological materials with hydraulic conductivities that can range over several orders of magnitude. This method utilizes indicator fields that are designed to allow random variation at the megascopic scale but are constrained by observations inferred from geophysical logs and geologic core data. The statistical description of random hydraulic conductivity values of distinct geological materials at the macroscopic scale may be obtained by conventional parameter estimation techniques. The combined approach can then be used to generate realizations of a hydraulic conductivity field for subsequent use in flow and transport simulations.
Compound random field models of multiple scale hydraulic conductivity
Haselow, J.S.; Brannan, J.R.
1992-09-01
Enormous amounts of hydrologic data are required to accurately simulate subsurface contaminant transport. Effectively supplementing measurements of hydrologic parameters such as permeability and porosity with ``soft`` information obtained from the interpretation of geologic cores and geophysical logs can improve the simulation of contaminant transport while reducing the measured data that are required. A method is presented herein for generating hydraulic conductivity fields comprised of several geological materials with hydraulic conductivities that can range over several orders of magnitude. This method utilizes indicator fields that are designed to allow random variation at the megascopic scale but are constrained by observations inferred from geophysical logs and geologic core data. The statistical description of random hydraulic conductivity values of distinct geological materials at the macroscopic scale may be obtained by conventional parameter estimation techniques. The combined approach can then be used to generate realizations of a hydraulic conductivity field for subsequent use in flow and transport simulations.
Driving a Superconductor to Insulator Transition with Random Gauge Fields
NASA Astrophysics Data System (ADS)
Nguyen, H. Q.; Hollen, S. M.; Shainline, J.; Xu, J. M.; Valles, J. M.
2016-11-01
Typically the disorder that alters the interference of particle waves to produce Anderson localization is potential scattering from randomly placed impurities. Here we show that disorder in the form of random gauge fields that act directly on particle phases can also drive localization. We present evidence of a superfluid bose glass to insulator transition at a critical level of this gauge field disorder in a nano-patterned array of amorphous Bi islands. This transition shows signs of metallic transport near the critical point characterized by a resistance , indicative of a quantum phase transition. The critical disorder depends on interisland coupling in agreement with recent Quantum Monte Carlo simulations. We discuss how this disorder tuned SIT differs from the common frustration tuned SIT that also occurs in magnetic fields. Its discovery enables new high fidelity comparisons between theoretical and experimental studies of disorder effects on quantum critical systems.
Driving a Superconductor to Insulator Transition with Random Gauge Fields.
Nguyen, H Q; Hollen, S M; Shainline, J; Xu, J M; Valles, J M
2016-11-30
Typically the disorder that alters the interference of particle waves to produce Anderson localization is potential scattering from randomly placed impurities. Here we show that disorder in the form of random gauge fields that act directly on particle phases can also drive localization. We present evidence of a superfluid bose glass to insulator transition at a critical level of this gauge field disorder in a nano-patterned array of amorphous Bi islands. This transition shows signs of metallic transport near the critical point characterized by a resistance , indicative of a quantum phase transition. The critical disorder depends on interisland coupling in agreement with recent Quantum Monte Carlo simulations. We discuss how this disorder tuned SIT differs from the common frustration tuned SIT that also occurs in magnetic fields. Its discovery enables new high fidelity comparisons between theoretical and experimental studies of disorder effects on quantum critical systems.
Cosmological fluctuations of a random field and radiation fluid
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.
Electronic transport in graphene sheets in a random magnetic field
NASA Astrophysics Data System (ADS)
Lewenkopf, Caio; Burgos, Rhonald; Warnes, Jesus; Lima, Leandro
2014-03-01
We present a theoretical study of the effect of ripples and strain fields in the transport properties of diffusive deposited graphene flakes. Defects in the crystalline structure, adsorbed atomic impurities and charge inhomogeneities at the substrate are believed to be the dominant disorder sources for the electronic transport in graphene at low temperatures. We show that intrinsic ripples also effect the conductivity, in particular, its quantum corrections. To this end, we analyze recent experimental results on the conductivity of rippled monolayer graphene sheets subjected to a strong magnetic field parallel to the graphene-substrate interface, B∥ [M. B. Lundeberg and J. A. Folk, Phys. Rev. Lett. 105, 146804 (2010)]. In this setting, B∥ gives rise to a random magnetic field normal to graphene sheet, that depends on the local curvature of the smooth disordered ripples. The analysis of the weak localization corrections of the magnetoconductance allows to establish the dependence of electronic dephasing rate on the magnitude of the random magnetic field. We compare the results for B∥ with the conductivity and weak localization corrections due to the pseudo-magnetic fields originated by intrinsic ripples and strain fields.
Weak scattering of scalar and electromagnetic random fields
NASA Astrophysics Data System (ADS)
Tong, Zhisong
This dissertation encompasses several studies relating to the theory of weak potential scattering of scalar and electromagnetic random, wide-sense statistically stationary fields from various types of deterministic or random linear media. The proposed theory is largely based on the first Born approximation for potential scattering and on the angular spectrum representation of fields. The main focus of the scalar counterpart of the theory is made on calculation of the second-order statistics of scattered light fields in cases when the scattering medium consists of several types of discrete particles with deterministic or random potentials. It is shown that the knowledge of the correlation properties for the particles of the same and different types, described with the newly introduced pair-scattering matrix, is crucial for determining the spectral and coherence states of the scattered radiation. The approach based on the pair-scattering matrix is then used for solving an inverse problem of determining the location of an "alien" particle within the scattering collection of "normal" particles, from several measurements of the spectral density of scattered light. Weak scalar scattering of light from a particulate medium in the presence of optical turbulence existing between the scattering centers is then approached using the combination of the Born's theory for treating the light interaction with discrete particles and the Rytov's theory for light propagation in extended turbulent medium. It is demonstrated how the statistics of scattered radiation depend on scattering potentials of particles and the power spectra of the refractive index fluctuations of turbulence. This theory is of utmost importance for applications involving atmospheric and oceanic light transmission. The second part of the dissertation includes the theoretical procedure developed for predicting the second-order statistics of the electromagnetic random fields, such as polarization and linear momentum
Conditional random field-based gesture recognition with depth information
NASA Astrophysics Data System (ADS)
Chung, Hyunsook; Yang, Hee-Deok
2013-01-01
Gesture recognition is useful for human-computer interaction. The difficulty of gesture recognition is that instances of gestures vary both in motion and shape in three-dimensional (3-D) space. We use depth information generated using Microsoft's Kinect in order to detect 3-D human body components and apply a threshold model with a conditional random field in order to recognize meaningful gestures using continuous motion information. Body gesture recognition is achieved through a framework consisting of two steps. First, a human subject is described by a set of features, encoding the angular relationship between body components in 3-D space. Second, a feature vector is recognized using a threshold model with a conditional random field. In order to show the performance of the proposed method, we use a public data set, the Microsoft Research Cambridge-12 Kinect gesture database. The experimental results demonstrate that the proposed method can efficiently and effectively recognize body gestures automatically.
Ground state nonuniversality in the random-field Ising model
Duxbury, P. M.; Meinke, J. H.
2001-09-01
Two attractive and often used ideas, namely, universality and the concept of a zero-temperature fixed point, are violated in the infinite-range random-field Ising model. In the ground state we show that the exponents can depend continuously on the disorder and so are nonuniversal. However, we also show that at finite temperature the thermal order-parameter exponent 1/2 is restored so that temperature is a relevant variable. Broader implications of these results are discussed.
Spectral expansions of tensor-valued random fields
NASA Astrophysics Data System (ADS)
Malyarenko, Anatoliy
2017-01-01
In this paper, we review the theory of random fields that are defined on the space domain ℝ3, take values in a real finite-dimensional linear space V that consists of tensors of a fixed rank, and are homogeneous and isotropic with respect to an orthogonal representation of a closed subgroup G of the group O(3). A historical introduction, the statement of the problem, some current results, and a sketch of proofs are included.
Liouville Field Theory and Log-Correlated Random Energy Models
NASA Astrophysics Data System (ADS)
Cao, Xiangyu; Rosso, Alberto; Santachiara, Raoul; Le Doussal, Pierre
2017-03-01
An exact mapping is established between the c ≥25 Liouville field theory (LFT) and the Gibbs measure statistics of a thermal particle in a 2D Gaussian free field plus a logarithmic confining potential. The probability distribution of the position of the minimum of the energy landscape is obtained exactly by combining the conformal bootstrap and one-step replica symmetry-breaking methods. Operator product expansions in the LFT allow us to unveil novel universal behaviors of the log-correlated random energy class. High-precision numerical tests are given.
Liouville Field Theory and Log-Correlated Random Energy Models.
Cao, Xiangyu; Rosso, Alberto; Santachiara, Raoul; Le Doussal, Pierre
2017-03-03
An exact mapping is established between the c≥25 Liouville field theory (LFT) and the Gibbs measure statistics of a thermal particle in a 2D Gaussian free field plus a logarithmic confining potential. The probability distribution of the position of the minimum of the energy landscape is obtained exactly by combining the conformal bootstrap and one-step replica symmetry-breaking methods. Operator product expansions in the LFT allow us to unveil novel universal behaviors of the log-correlated random energy class. High-precision numerical tests are given.
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.
Statistical mechanics of the spherical hierarchical model with random fields
NASA Astrophysics Data System (ADS)
Metz, Fernando L.; Rocchi, Jacopo; Urbani, Pierfrancesco
2014-09-01
We study analytically the equilibrium properties of the spherical hierarchical model in the presence of random fields. The expression for the critical line separating a paramagnetic from a ferromagnetic phase is derived. The critical exponents characterising this phase transition are computed analytically and compared with those of the corresponding D-dimensional short-range model, leading to conclude that the usual mapping between one dimensional long-range models and D-dimensional short-range models holds exactly for this system, in contrast to models with Ising spins. Moreover, the critical exponents of the pure model and those of the random field model satisfy a relationship that mimics the dimensional reduction rule. The absence of a spin-glass phase is strongly supported by the local stability analysis of the replica symmetric saddle-point as well as by an independent computation of the free-energy using a renormalization-like approach. This latter result enlarges the class of random field models for which the spin-glass phase has been recently ruled out.
Localization of disordered bosons and magnets in random fields
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.
Universality in four-dimensional random-field magnets
NASA Astrophysics Data System (ADS)
Fytas, Nikolaos G.; Theodorakis, Panagiotis E.
2015-08-01
We investigate the universality aspects of the four-dimensional random-field Ising model (RFIM) using numerical simulations at zero temperature. We consider two different, in terms of the field distribution, versions of the model, namely a Gaussian RFIM and an equal-weight trimodal RFIM. By implementing a computational approach that maps the ground-state of the system to the maximum-flow optimization problem of a network, we employ the most up-to-date version of the push-relabel algorithm and simulate large ensembles of disorder realizations of both models for a broad range of random-field values and system sizes. Using as finite-size measures the sample-to-sample fluctuations of the order parameter of the system, we propose, for both types of distributions, estimates of the critical field hc and the critical exponent ν of the correlation length, the latter suggesting that the two models in four dimensions share the same universality class.
Visibility graphs of random scalar fields and spatial data
NASA Astrophysics Data System (ADS)
Lacasa, Lucas; Iacovacci, Jacopo
2017-07-01
We extend the family of visibility algorithms to map scalar fields of arbitrary dimension into graphs, enabling the analysis of spatially extended data structures as networks. We introduce several possible extensions and provide analytical results on the topological properties of the graphs associated to different types of real-valued matrices, which can be understood as the high and low disorder limits of real-valued scalar fields. In particular, we find a closed expression for the degree distribution of these graphs associated to uncorrelated random fields of generic dimension. This result holds independently of the field's marginal distribution and it directly yields a statistical randomness test, applicable in any dimension. We showcase its usefulness by discriminating spatial snapshots of two-dimensional white noise from snapshots of a two-dimensional lattice of diffusively coupled chaotic maps, a system that generates high dimensional spatiotemporal chaos. The range of potential applications of this combinatorial framework includes image processing in engineering, the description of surface growth in material science, soft matter or medicine, and the characterization of potential energy surfaces in chemistry, disordered systems, and high energy physics. An illustration on the applicability of this method for the classification of the different stages involved in carcinogenesis is briefly discussed.
Condensation of Helium in Aerogel and Athermal Dynamics of the Random-Field Ising Model
NASA Astrophysics Data System (ADS)
Aubry, Geoffroy J.; Bonnet, Fabien; Melich, Mathieu; Guyon, Laurent; Spathis, Panayotis; Despetis, Florence; Wolf, Pierre-Etienne
2014-08-01
High resolution measurements reveal that condensation isotherms of He4 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.
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.
Markov random fields for static foreground classification in surveillance systems
NASA Astrophysics Data System (ADS)
Fitzsimons, Jack K.; Lu, Thomas T.
2014-09-01
We present a novel technique for classifying static foreground in automated airport surveillance systems between abandoned and removed objects by representing the image as a Markov Random Field. The proposed algorithm computes and compares the net probability of the region of interest before and after the event occurs, hence finding which fits more naturally with their respective backgrounds. Having tested on a dataset from the PETS 2006, PETS 2007, AVSS20074, CVSG, VISOR, CANDELA and WCAM datasets, the algorithm has shown capable of matching the results of the state-of-the-art, is highly parallel and has a degree of robustness to noise and illumination changes.
Applications of random field theory to functional connectivity.
Worsley, K J; Cao, J; Paus, T; Petrides, M; Evans, A C
1998-01-01
Functional connectivity between two voxels or regions of voxels can be measured by the correlation between voxel measurements from either PET CBF or BOLD fMRI images in 3D. We propose to look at the entire 6D matrix of correlations between all voxels and search for 6D local maxima. The main result is a new theoretical formula based on random field theory for the p-value of these local maxima, which distinguishes true correlations from background noise. This can be applied to crosscorrelations between two different sets of images--such as activations under two different tasks, as well as autocorrelations within the same set of images.
v-Spread Due to Random Field Errors
Parzen, G.
1990-01-01
Previous work indicated that the random b_{k}, a_{k} field errors can produce a large v-spread within the beam. For the worse case a v-spread of Δv=21x10^{-3} has been found. The overall results are first presented, without much analysis or breakdown into contributions b_{k}, a_{k}. Later on the contribution of various b_{k}, a_{k} will be studied.
Ensemble renormalization group for the random-field hierarchical model.
Decelle, Aurélien; Parisi, Giorgio; Rocchi, Jacopo
2014-03-01
The renormalization group (RG) methods are still far from being completely understood in quenched disordered systems. In order to gain insight into the nature of the phase transition of these systems, it is common to investigate simple models. In this work we study a real-space RG transformation on the Dyson hierarchical lattice with a random field, which leads to a reconstruction of the RG flow and to an evaluation of the critical exponents of the model at T=0. We show that this method gives very accurate estimations of the critical exponents by comparing our results with those obtained by some of us using an independent method.
NASA Technical Reports Server (NTRS)
Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.
1992-01-01
The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.
NASA Technical Reports Server (NTRS)
Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.
1992-01-01
The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.
Rice, William D.; Liu, Wenyong; Baker, Thomas A.; ...
2015-11-23
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 Mn2+, Co2+ 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 √N fluctuations of N spins are expected to generate giant effective magnetic fields Beff, which should dramatically impactmore » carrier spin dynamics, even in the absence of any applied field. In this paper, we directly and unambiguously reveal the large Beff that exist in Mn2+-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. Finally, these signals arise from electron precession about the random fields due to statistically incomplete cancellation of the embedded Mn2+ moments, thereby revealing the initial coherent dynamics of magnetic polaron formation, and highlighting the importance of magnetization fluctuations on carrier spin dynamics in nanomaterials.« less
Rice, William D.; Liu, Wenyong; Baker, Thomas A.; Sinitsyn, Nikolai A.; Klimov, Victor Ivanovich; Crooker, Scott A.
2015-11-23
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 √N fluctuations of N spins are expected to generate giant effective magnetic fields B_{eff}, which should dramatically impact carrier spin dynamics, even in the absence of any applied field. In this paper, we directly and unambiguously reveal the large B_{eff} 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 B_{eff} ~ 15-30 T for electrons. Precession frequencies exceed 2 THz in applied magnetic fields. Finally, 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.
NASA Astrophysics Data System (ADS)
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 Mn2+, Co2+ 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 Mn2+-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 Mn2+ moments, thereby revealing the initial coherent dynamics of magnetic polaron formation, and highlighting the importance of magnetization fluctuations on carrier spin dynamics in nanomaterials.
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.
Nonequilibrium phase transitions in lattice systems with random-field competing kinetics
NASA Astrophysics Data System (ADS)
López-Lacomba, A. I.; Marro, J.
1992-10-01
We study a class of lattice interacting-spin systems evolving stochastically under the simultaneous operation of several spin-flip mechanisms, each acting independently and responding to a different applied magnetic field. This induces an extra randomness which may occur in real systems, e.g., a magnetic system under the action of a field varying with a much shorter period than the mean time between successive transitions. Such a situation-in which one may say in some sense that frustration has a dynamical origin- may also be viewed as a nonequilibrium version of the random-field Ising model. By following a method of investigating stationary probability distributions in systems with competing kinetics [P. L. Garrido and J. Marro, Phys. Rev. Lett. 62, 1929 (1989)], we solve one-dimensional lattices supporting different field distributions and transition rates for the elementary kinetical processes, thus revealing a rich variety of phase transitions and critical phenomena. Some exact results for lattices of arbitrary dimension, and comparisons with the standard quenched and annealed random-field models, and with a nonequilibrium diluted antiferromagnetic system, are also reported.
Measuring marine oil spill extent by Markov Random Fields
NASA Astrophysics Data System (ADS)
Moctezuma, Miguel; Parmiggiani, Flavio; Lopez Lopez, Ludwin
2014-10-01
The Deepwater Horizon oil spill of the Gulf of Mexico in the spring of 2010 was the largest accidental marine oil spill in the history of the petroleum industry. An immediate request, after the accident, was to detect the oil slick and to measure its extent: SAR images were the obvious tool to be employed for the task. This paper presents a processing scheme based on Markov Random Fields (MRF) theory. MRF theory describes the global information by probability terms involving local neighborhood representations of the SAR backscatter data. The random degradation introduced by speckle noise is dealt with a pre-processing stage which applies a nonlinear diffusion filter. Spatial context attributes are structured by the Bayes equation derived from a Maximum-A-Posteriori (MAP) estimation. The probability terms define an objective function of a MRF model whose goal is to detect contours and fine structures. The markovian segmentation problem is solved with a numerical optimization method. The scheme was applied to an Envisat/ASAR image over the Gulf of Mexico of May 9, 2010, when the oil spill was already fully developed. The final result was obtained with 51 recursion cycles, where, at each step, the segmentation consists of a 3-class label field (open sea and two oil slick thicknesses). Both the MRF model and the parameters of the stochastic optimization procedure will be provided, together with the area measurement of the two kinds of oil slick.
Salmon, Octavio R; Crokidakis, Nuno; Nobre, Fernando D
2009-02-04
A random-field Ising model that is capable of exhibiting a rich variety of multicritical phenomena, as well as a smearing of such behavior, is investigated. The model consists of an infinite-range-interaction Ising ferromagnet in the presence of a triple Gaussian random magnetic field, which is defined as a superposition of three Gaussian distributions with the same width σ, centered at H = 0 and H = ± H(0), with probabilities p and (1-p)/2, respectively. Such a distribution is very general and recovers, as limiting cases, the trimodal, bimodal and Gaussian probability distributions. In particular, the special case of the random-field Ising model in the presence of a trimodal probability distribution (limit [Formula: see text]) is able to present a rather nontrivial multicritical behavior. It is argued that the triple Gaussian probability distribution is appropriate for a physical description of some diluted antiferromagnets in the presence of a uniform external field, for which the corresponding physical realization consists of an Ising ferromagnet under random fields whose distribution appears to be well represented in terms of a superposition of two parts, namely a trimodal and a continuous contribution. The model is investigated by means of the replica method, and phase diagrams are obtained within the replica-symmetric solution, which is known to be stable for the present system. A rich variety of phase diagrams is presented, with one or two distinct ferromagnetic phases, continuous and first-order transition lines, tricritical, fourth-order, critical end points and many other interesting multicritical phenomena. Additionally, the present model carries the possibility of destroying such multicritical phenomena due to an increase in the randomness, i.e. increasing σ, which represents a very common feature in real systems.
Strong disorder effects of a Dirac fermion with a random vector field
NASA Astrophysics Data System (ADS)
Fukui, Takahiro
2003-10-01
We study a Dirac fermion model with a random vector field, especially paying attention to the strong disorder regime. Applying Bosonization techniques, we first derive an equivalent sine-Gordon model, and next average over the random vector field using the replica approach. The operator product expansion based on the replica action leads to scaling equations of the coupling constants (“fugacities”) with nonlinear terms, if we take into account the fusion of the vertex operators. These equations are converted into a nonlinear diffusion equation known as the Kolmogorov-Petrovsky-Piscounov (KPP) equation. Using the asymptotic solution of the equation, we calculate the spatial correlations of the generalized inverse participation ratios. The scaling exponent thus obtained reproduces the recent numerical calculations of the density correlation function. This implies that the freezing transition has actually revealed itself in such calculations.
Remediating Computational Deficits at Third Grade: A Randomized Field Trial
Fuchs, Lynn S.; Powell, Sarah R.; Hamlett, Carol L.; Fuchs, Douglas; Cirino, Paul T.; Fletcher, Jack M.
2011-01-01
The major purposes of this study were to assess the efficacy of tutoring to remediate 3rd-grade computational deficits and to explore whether remediation is differentially efficacious depending on whether students experience mathematics difficulty alone or concomitantly with reading difficulty. At 2 sites, 127 students were stratified on mathematics difficulty status and randomly assigned to 4 conditions: word recognition (control) tutoring or 1 of 3 computation tutoring conditions: fact retrieval, procedural computation and computational estimation, and combined (fact retrieval + procedural computation and computational estimation). Results revealed that fact retrieval tutoring enhanced fact retrieval skill, and procedural computation and computational estimation tutoring (whether in isolation or combined with fact retrieval tutoring) enhanced computational estimation skill. Remediation was not differentially efficacious as a function of students’ mathematics difficulty status. PMID:21709759
Quantum Coherence and Random Fields at Mesoscopic Scales
Rosenbaum, Thomas F.
2016-03-01
We seek to explore and exploit model, disordered and geometrically frustrated magnets where coherent spin clusters stably detach themselves from their surroundings, leading to extreme sensitivity to finite frequency excitations and the ability to encode information. Global changes in either the spin concentration or the quantum tunneling probability via the application of an external magnetic field can tune the relative weights of quantum entanglement and random field effects on the mesoscopic scale. These same parameters can be harnessed to manipulate domain wall dynamics in the ferromagnetic state, with technological possibilities for magnetic information storage. Finally, extensions from quantum ferromagnets to antiferromagnets promise new insights into the physics of quantum fluctuations and effective dimensional reduction. A combination of ac susceptometry, dc magnetometry, noise measurements, hole burning, non-linear Fano experiments, and neutron diffraction as functions of temperature, magnetic field, frequency, excitation amplitude, dipole concentration, and disorder address issues of stability, overlap, coherence, and control. We have been especially interested in probing the evolution of the local order in the progression from spin liquid to spin glass to long-range-ordered magnet.
Fuzzy Markov random fields versus chains for multispectral image segmentation.
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.
Vehicle track segmentation using higher order random fields
Quach, Tu -Thach
2017-01-09
Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less
Random Fields, Topology, and the Imry-Ma Argument
NASA Astrophysics Data System (ADS)
Proctor, Thomas C.; Garanin, Dmitry A.; Chudnovsky, Eugene M.
2014-03-01
We consider an n-component fixed-length order parameter interacting with a weak random field in d =1, 2, 3 dimensions. Relaxation from the initially ordered state and spin-spin correlation functions are studied on lattices containing hundreds of millions of sites. At n≤d the presence of topological defects leads to strong metastability and glassy behavior, with the final state depending on the initial condition. At n=d+1, when topological structures are nonsingular, the system possesses a weak metastability. At n>d+1, when topological objects are absent, the final, lowest-energy state is independent of the initial condition. It is characterized by the exponential decay of correlations that agrees quantitatively with the theory based upon the Imry-Ma argument.
Cover estimation and payload location using Markov random fields
NASA Astrophysics Data System (ADS)
Quach, Tu-Thach
2014-02-01
Payload location is an approach to find the message bits hidden in steganographic images, but not necessarily their logical order. Its success relies primarily on the accuracy of the underlying cover estimators and can be improved if more estimators are used. This paper presents an approach based on Markov random field to estimate the cover image given a stego image. It uses pairwise constraints to capture the natural two-dimensional statistics of cover images and forms a basis for more sophisticated models. Experimental results show that it is competitive against current state-of-the-art estimators and can locate payload embedded by simple LSB steganography and group-parity steganography. Furthermore, when combined with existing estimators, payload location accuracy improves significantly.
Markov random field method for dynamic PET image segmentation
NASA Astrophysics Data System (ADS)
Lin, Kang-Ping; Lou, Shyhliang A.; Yu, Chin-Lung; Chung, Being-Tau; Wu, Liang-Chi; Liu, Ren-Shyan
1998-06-01
In this paper, the Markov random field (MRF) clustering method for highly noisy medical image segmentation is presented. In MRF method, the image to be segmented is analyzed in a probabilistic way that establishes image model by a posteriori probability density function with Bayes' theorem, with relation between pixel positions as well as gray-levels involved. The adaptive threshold parameter is determined in the iterative clustering process to achieve global optimal segmentation. The presented method and other segmentation methods in use are tested on simulation images of different noise levels, and the numerical comparison result is presented. It also is applied on the highly noisy positron emission tomography images, in that the diagnostic hypoxia fraction is automatically calculated. The experimental results are acceptable, and show that the presented method is suitable and robust for noisy image segmentation.
Heat and mass transport in nonhomogeneous random velocity fields.
Mauri, Roberto
2003-12-01
The effective equation describing the transport of passive tracers in nonsolenoidal velocity fields is determined, assuming that the velocity field U(r,t) is a function of both position r and time t, albeit remaining locally random. Assuming a strong separation of scales and applying the method of homogenization, we find a Fickian constitutive relation for the coarse-grained particle flux, as the sum of a convective part, V(E)c, and a diffusive term, -D(s). Inverted Delta c, where V(E) is the Eulerian mean tracer velocity, c the average particle concentration, and D(s) the effective diffusivity. The latter can be written as D(s)(r,t)=D(0)I+D(r,r,t), where D0 is the molecular diffusivity, I the unit dyadic and D(r(1),r(2),t) the cross diffusion dyadic. Conversely, the Eulerian mean velocity V(E)(r,t) is the sum of the microscale mean tracer velocity V(r,t) and a particle drift velocity, V(d)(r,t)=-[(delta/delta r(2)).D(T)(r,r(2),t)](r(2)=r), which depends on the nonhomogeneity of the velocity field at the macroscale. The microscale mean particle velocity, in turn, is the sum of the mean fluid velocity and the ballistic tracer velocity, which is due to the local nonuniformity of the concentration field and is therefore structurally different from the tracer drift velocity. In the limit of large Peclet numbers, D(s) coincides with the self-diffusion dyadic, as it measures the local temporal growth of the mean square displacement of a tracer particle from its average position. In this case, the motion of a tracer particle is a random process in the manner of Stratonovich, where the smoothly varying mean tracer velocity equals the microscale mean tracer velocity and the fluctuating term is described through the cross diffusion dyadic D(r(1),r(2),t).
Glaucoma progression detection using nonlocal Markov random field prior
Belghith, Akram; Bowd, Christopher; Medeiros, Felipe A.; Balasubramanian, Madhusudhanan; Weinreb, Robert N.; Zangwill, Linda M.
2014-01-01
Abstract. Glaucoma is neurodegenerative disease characterized by distinctive changes in the optic nerve head and visual field. Without treatment, glaucoma can lead to permanent blindness. Therefore, monitoring glaucoma progression is important to detect uncontrolled disease and the possible need for therapy advancement. In this context, three-dimensional (3-D) spectral domain optical coherence tomography (SD-OCT) has been commonly used in the diagnosis and management of glaucoma patients. We present a new framework for detection of glaucoma progression using 3-D SD-OCT images. In contrast to previous works that use the retinal nerve fiber layer thickness measurement provided by commercially available instruments, we consider the whole 3-D volume for change detection. To account for the spatial voxel dependency, we propose the use of the Markov random field (MRF) model as a prior for the change detection map. In order to improve the robustness of the proposed approach, a nonlocal strategy was adopted to define the MRF energy function. To accommodate the presence of false-positive detection, we used a fuzzy logic approach to classify a 3-D SD-OCT image into a “non-progressing” or “progressing” glaucoma class. We compared the diagnostic performance of the proposed framework to the existing methods of progression detection. PMID:26158069
Glaucoma progression detection using nonlocal Markov random field prior.
Belghith, Akram; Bowd, Christopher; Medeiros, Felipe A; Balasubramanian, Madhusudhanan; Weinreb, Robert N; Zangwill, Linda M
2014-10-01
Glaucoma is neurodegenerative disease characterized by distinctive changes in the optic nerve head and visual field. Without treatment, glaucoma can lead to permanent blindness. Therefore, monitoring glaucoma progression is important to detect uncontrolled disease and the possible need for therapy advancement. In this context, three-dimensional (3-D) spectral domain optical coherence tomography (SD-OCT) has been commonly used in the diagnosis and management of glaucoma patients. We present a new framework for detection of glaucoma progression using 3-D SD-OCT images. In contrast to previous works that use the retinal nerve fiber layer thickness measurement provided by commercially available instruments, we consider the whole 3-D volume for change detection. To account for the spatial voxel dependency, we propose the use of the Markov random field (MRF) model as a prior for the change detection map. In order to improve the robustness of the proposed approach, a nonlocal strategy was adopted to define the MRF energy function. To accommodate the presence of false-positive detection, we used a fuzzy logic approach to classify a 3-D SD-OCT image into a "non-progressing" or "progressing" glaucoma class. We compared the diagnostic performance of the proposed framework to the existing methods of progression detection.
A dissipative random velocity field for fully developed fluid turbulence
NASA Astrophysics Data System (ADS)
Chevillard, Laurent; Pereira, Rodrigo; Garban, Christophe
2016-11-01
We investigate the statistical properties, based on numerical simulations and analytical calculations, of a recently proposed stochastic model for the velocity field of an incompressible, homogeneous, isotropic and fully developed turbulent flow. A key step in the construction of this model is the introduction of some aspects of the vorticity stretching mechanism that governs the dynamics of fluid particles along their trajectory. An additional further phenomenological step aimed at including the long range correlated nature of turbulence makes this model depending on a single free parameter that can be estimated from experimental measurements. We confirm the realism of the model regarding the geometry of the velocity gradient tensor, the power-law behaviour of the moments of velocity increments, including the intermittent corrections, and the existence of energy transfers across scales. We quantify the dependence of these basic properties of turbulent flows on the free parameter and derive analytically the spectrum of exponents of the structure functions in a simplified non dissipative case. A perturbative expansion shows that energy transfers indeed take place, justifying the dissipative nature of this random field.
NASA Technical Reports Server (NTRS)
Earl, James A.
1992-01-01
When charged particles spiral along a large constant magnetic field, their trajectories are scattered by any random field components that are superposed on the guiding field. If the random field configuration embodies helicity, the scattering is asymmetrical with respect to a plane perpendicular to the guiding field, for particles moving into the forward hemisphere are scattered at different rates from those moving into the backward hemisphere. This asymmetry gives rise to new terms in the transport equations that describe propagation of charged particles. Helicity has virtually no impact on qualitative features of the diffusive mode of propagation. However, characteristic velocities of the coherent modes that appear after a highly anisotropic injection exhibit an asymmetry related to helicity. Explicit formulas, which embody the effects of helicity, are given for the anisotropies, the coefficient diffusion, and the coherent velocities. Predictions derived from these expressions are in good agreement with Monte Carlo simulations of particle transport, but the simulations reveal certain phenomena whose explanation calls for further analytical work.
Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields
NASA Technical Reports Server (NTRS)
Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.
1994-01-01
To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.
Adaptive Thouless-Anderson-Palmer approach to inverse Ising problems with quenched random fields
NASA Astrophysics Data System (ADS)
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.
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
Kouritzin, Michael A; Newton, Fraser; Wu, Biao
2013-04-01
Herein, we propose generating CAPTCHAs through random field simulation and give a novel, effective and efficient algorithm to do so. Indeed, we demonstrate that sufficient information about word tests for easy human recognition is contained in the site marginal probabilities and the site-to-nearby-site covariances and that these quantities can be embedded directly into certain conditional probabilities, designed for effective simulation. The CAPTCHAs are then partial random realizations of the random CAPTCHA word. We start with an initial random field (e.g., randomly scattered letter pieces) and use Gibbs resampling to re-simulate portions of the field repeatedly using these conditional probabilities until the word becomes human-readable. The residual randomness from the initial random field together with the random implementation of the CAPTCHA word provide significant resistance to attack. This results in a CAPTCHA, which is unrecognizable to modern optical character recognition but is recognized about 95% of the time in a human readability study.
Conditional random fields for pattern recognition applied to structured data
Burr, Tom; Skurikhin, Alexei
2015-07-14
In order to predict labels from an output domain, Y, pattern recognition is used to gather measurements from an input domain, X. 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 betweenmore » parts of the model are often correlated. Thus, 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. Our 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
GAUSSIAN RANDOM FIELD: PHYSICAL ORIGIN OF SERSIC PROFILES
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.
Biomedical image analysis using Markov random fields & efficient linear programing.
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.
Conditional random fields for pattern recognition applied to structured data
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.
Markov random field for tumor detection in digital mammography
Li, H.D.; Kallergi, M.; Clarke, L.P.; Clark, R.A.; Jain, V.K.
1995-09-01
A technique is proposed for the detection of tumors in digital mammography. Detection is performed in two steps: segmentation and classification. In segmentation, regions of interest are first extracted from the images by adaptive thresholding. A further reliable segmentation is achieved by a modified Markov random field (MRF) model-based method. In classification, the MRF segmented regions are classified into suspicious and normal by a fuzzy binary decision tree based on a series of radiographic, density-related features. A set of normal (50) and abnormal (45) screen/film mammograms were tested. The latter contained 48 biopsy proven, malignant masses of various types and subtlety. The detection accuracy of the algorithm was evaluated by means of a free response receiver operating characteristic curve which shows the relationship between the detection of true positive masses and the number of false positive alarms per image. The results indicated that a 90% sensitivity can be achieved in the detection of different types of masses at the expense of two falsely detected signals per image. The algorithm was notably successful in the detection of minimal cancers manifested by masses {le} 10 mm in size. For the 16 such cases in their dataset, a 94% sensitivity was observed with 1.5 false alarms per image. An extensive study of the effects of the algorithm`s parameters on its sensitivity and specificity was also performed in order to optimize the method for a clinical, observer performance study.
Gaussian Random Field: Physical Origin of Sersic Profiles
NASA Astrophysics Data System (ADS)
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.
Conditional random field modelling of interactions between findings in mammography
NASA Astrophysics Data System (ADS)
Kooi, Thijs; Mordang, Jan-Jurre; Karssemeijer, Nico
2017-03-01
Recent breakthroughs in training deep neural network architectures, in particular deep Convolutional Neural Networks (CNNs), made a big impact on vision research and are increasingly responsible for advances in Computer Aided Diagnosis (CAD). Since many natural scenes and medical images vary in size and are too large to feed to the networks as a whole, two stage systems are typically employed, where in the first stage, small regions of interest in the image are located and presented to the network as training and test data. These systems allow us to harness accurate region based annotations, making the problem easier to learn. However, information is processed purely locally and context is not taken into account. In this paper, we present preliminary work on the employment of a Conditional Random Field (CRF) that is trained on top the CNN to model contextual interactions such as the presence of other suspicious regions, for mammography CAD. The model can easily be extended to incorporate other sources of information, such as symmetry, temporal change and various patient covariates and is general in the sense that it can have application in other CAD problems.
Infinite hidden conditional random fields for human behavior analysis.
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.
NASA Astrophysics Data System (ADS)
Hadjiagapiou, Ioannis A.
2014-03-01
The magnetic systems with disorder form an important class of systems, which are under intensive studies, since they reflect real systems. Such a class of systems is the spin glass one, which combines randomness and frustration. The Sherrington-Kirkpatrick Ising spin glass with random couplings in the presence of a random magnetic field is investigated in detail within the framework of the replica method. The two random variables (exchange integral interaction and random magnetic field) are drawn from a joint Gaussian probability density function characterized by a correlation coefficient ρ. The thermodynamic properties and phase diagrams are studied with respect to the natural parameters of both random components of the system contained in the probability density. The de Almeida-Thouless line is explored as a function of temperature, ρ and other system parameters. The entropy for zero temperature as well as for non zero temperatures is partly negative or positive, acquiring positive branches as h0 increases.
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.
Long term field evaluation reveals HLB resistance in Citrus relatives
USDA-ARS?s Scientific Manuscript database
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 ...
MAGNETIC FIELD LINE RANDOM WALK IN ISOTROPIC TURBULENCE WITH ZERO MEAN FIELD
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.
MRFalign: protein homology detection through alignment of Markov random fields.
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.
MRFalign: Protein Homology Detection through Alignment of Markov Random Fields
Ma, Jianzhu; Wang, Sheng; Wang, Zhiyong; Xu, Jinbo
2014-01-01
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
Cancer field effects in normal tissues revealed by Raman spectroscopy
Lieber, Chad A.; Nethercott, Hubert E.; Kabeer, Mustafa H.
2010-01-01
It has been demonstrated that the presence of cancer results in detectable changes to uninvolved tissues, collectively termed cancer field effects (CFE). In this study, we directly assessed the ability of Raman microspectroscopy to detect CFE via in-vitro study of organotypic tissue rafts approximating human skin. Raman spectra were measured from both epidermis and dermis after transfer of the rafts to dishes containing adherent cultures of either normal human fibroblasts or fibrosarcoma (HT1080) cells. Principal components analyses allowed discrimination between the groups with 86% classification accuracy in the epidermis and 94% in the dermis. These results encourage further study to evaluate the Raman capacity for detecting CFE as a possible tool for noninvasive screening for tumor presence. PMID:21258523
Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields
NASA Astrophysics Data System (ADS)
Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.
1992-12-01
During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards
Gesture Recognition using Latent-Dynamic based Conditional Random Fields and Scalar Features
NASA Astrophysics Data System (ADS)
Yulita, I. N.; Fanany, M. I.; Arymurthy, A. M.
2017-02-01
The need for segmentation and labeling of sequence data appears in several fields. The use of the conditional models such as Conditional Random Fields is widely used to solve this problem. In the pattern recognition, Conditional Random Fields specify the possibilities of a sequence label. This method constructs its full label sequence to be a probabilistic graphical model based on its observation. However, Conditional Random Fields can not capture the internal structure so that Latent-based Dynamic Conditional Random Fields is developed without leaving external dynamics of inter-label. This study proposes the use of Latent-Dynamic Conditional Random Fields for Gesture Recognition and comparison between both methods. Besides, this study also proposes the use of a scalar features to gesture recognition. The results show that performance of Latent-dynamic based Conditional Random Fields is not better than the Conditional Random Fields, and scalar features are effective for both methods are in gesture recognition. Therefore, it recommends implementing Conditional Random Fields and scalar features in gesture recognition for better performance
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.
Random Matrix Model for Superconductors in a Magnetic Field
Bahcall, S.R.
1996-12-01
We introduce a random matrix ensemble for bulk type-II superconductors in the mixed state and determine the single-particle excitation spectrum using random matrix theory. The results are compared with planar tunnel junction experiments in PbBi/Ge thin films. More low energy states appear than in the Abrikosov-Gor{close_quote}kov-Maki or Ginzburg-Landau descriptions, consistent with observations. {copyright} {ital 1996 The American Physical Society.}
Magnetic-field-dependent small-angle neutron scattering on random anisotropy ferromagnets
NASA Astrophysics Data System (ADS)
Michels, Andreas; Weissmüller, Jörg
2008-06-01
We report on the recently developed technique of magnetic-field-dependent small-angle neutron scattering (SANS), with attention to bulk ferromagnets exhibiting random magnetic anisotropy. In these materials, the various magnetic anisotropy fields (magnetocrystalline, magnetoelastic, and/or magnetostatic in origin) perturb the perfectly parallel spin alignment of the idealized ferromagnetic state. By varying the applied magnetic field, one can control one of the ordering terms which competes with the above-mentioned perturbing fields. Experiments which explore the ensuing reaction of the magnetization will therefore provide information not only on the field-dependent spin structure but, importantly, on the underlying magnetic interaction terms. This strategy, which underlies conventional studies of hysteresis loops in magnetometry, is here combined with magnetic SANS. While magnetometry generally records only a single scalar quantity, the integral magnetization, SANS provides access to a vastly richer data set, the Fourier spectrum of the response of the spin system as a function of the magnitude and orientation of the wave vector. The required data-analysis procedures have recently been established, and experiments on a number of magnetic materials, mostly nanocrystalline or nanocomposite metals, have been reported. Here, we summarize the theory of magnetic-field-dependent SANS along with the underlying description of random anisotropy magnets by micromagnetic theory. We review experiments which have explored the magnetic interaction parameters, the value of the exchange-stiffness constant as well as the Fourier components of the magnetic anisotropy field and of the magnetostatic stray field. A model-independent approach, based on the experimental autocorrelation function of the spin misalignment, provides access to the characteristic length of the spin misalignment. The field dependence of this quantity is in quantitative agreement with the predictions of
Zhang, J
1996-01-01
The Gibbs-Bogoliubov-Feynman (GBF) inequality of statistical mechanics is adopted, with an information-theoretic interpretation, as a general optimization framework for deriving and examining various mean field approximations for Markov random fields (MRF's). The efficacy of this approach is demonstrated through the compound Gauss-Markov (CGM) model, comparisons between different mean field approximations, and experimental results in image restoration.
Revealing Saturn's Rotation Period from its Gravitational Field
NASA Astrophysics Data System (ADS)
Helled, Ravit; Galanti, Eli; Kaspi, Yohai
2015-04-01
Knowledge of the rotation period of a giant planet is fundamental for constraining its internal structure and atmosphere dynamics. Until the arrival of the Cassini spacecraft to Saturn, Saturn's rotation period was set to the Voyager 2 radio period, 10h 39m 22.4s that was derived from the periodicity in Saturn's kilometric radiation (SKR). Surprisingly, Cassini's SKR measured a rotation period of 10h 47m 6s using the exact same method. It was then realized that Saturn's rotation period is unknown to within a few minutes. We show that Saturn's rotation period can be determined from its measured gravitational field. We find that without imposing any constraints on the planetary shape and internal density profile the rotation rate can be determined to within several minutes, and is 10h 43m 10s ± 4m. If we include limits based on the observed shape and possible internal density profiles, the rotation period is found to be 10h 32m 45s ± 46s. The success of our method is confirmed by applying it for Jupiter and reproducing exactly its measured rotation period that is well constrained.
NASA Astrophysics Data System (ADS)
Erichsen, R.; Lopes, Amanda Azevedo; Magalhaes, S. G.
2017-06-01
The interplay between quenched disorder provided by a random field (RF) and network connectivity in the Blume-Capel (BC) model is the subject of this paper. The replica method is used to average over the network randomness. It offers an alternative analytic route to both numerical simulations and standard mean field approaches. The results reveal a rich thermodynamic scenario with multicritical points that are strongly dependent on network connectivity. In addition, we also demonstrate that the RF has a deep effect on the inverse melting transition. This highly nontrivial type of phase transition has been proposed to exist in the BC model as a function of network topology. Our results confirm that the topological mechanism can lead to an inverse melting transition. Nevertheless, our results also show that as the RF becomes stronger, the paramagnetic phase is affected in such way that the topological mechanism for inverse melting is disabled.
Field transplants reveal summer constraints on a butterfly range expansion.
Crozier, Lisa G
2004-09-01
The geographic ranges of most species are expected to shift to higher elevations and latitudes in response to global warming. But species react to specific environmental changes in individualistic ways, and we are far from a detailed understanding of range-shifts. Summer temperature often limits the ranges of insects and plants, so many range-shifts are expected to track summer warming. I explore this potential range-limiting factor in a case study of a northwardly expanding American butterfly, Atalopedes campestris (Lepidoptera, Hesperiidae). This species has recently colonized the Pacific Northwest, USA, where the mean annual temperature has risen 0.8-1.8 degrees C over the past 100 years. Using field transplant experiments across the current range edge, I measured development time, survivorship, fecundity and predation rates along a naturally occurring thermal gradient of 3 degrees C. Development time was significantly slower outside the current range in eastern Washington (WA), as expected because of cooler temperatures there. Slower development would reduce the number of generations possible per year outside the current range, dramatically lowering the probability that a population could survive there. Differences in survivorship, fecundity and predation rate across the range edge were not significant. The interaction between summer and winter temperature appears to be crucial in defining the current range limit. The estimated difference in temperature required to affect the number of generations is greater than the extent of summer warming observed over the past century, however, and thus historically winter temperature alone probably limited the range in southeastern WA. Nonetheless, extraordinarily warm summers may have improved colonization success, increasing the probability of a range expansion. These results suggest that extreme climatic events may influence rates of response to long-term climate change. They also demonstrate that range-limiting factors
Fernique-type inequalities and moduli of continuity for anisotropic Gaussian random fields
Meerschaert, Mark M.; Wang, Wensheng; Xiao, Yimin
2013-01-01
This paper is concerned with sample path properties of anisotropic Gaussian random fields. We establish Fernique-type inequalities and utilize them to study the global and local moduli of continuity for anisotropic Gaussian random fields. Applications to fractional Brownian sheets and to the solutions of stochastic partial differential equations are investigated. PMID:24825922
Mean field theory of directed polymers with random complex weights
NASA Astrophysics Data System (ADS)
Derrida, B.; Evans, M. R.; Speer, E. R.
1993-09-01
We show that for the problem of directed polymers on a tree with i.i.d. random complex weights on each bond, three possible phases can exist; the phase of a particular system is determined by the distribution ρ of the random weights. For each of these three phases, we give the expression of the free energy per unit length in the limit of infinitely long polymers. Our proofs require several hypotheses on the distribution ρ, most importantly, that the amplitude and the phase of each complex weight be statistically independent. The main steps of our proofs use bounds on noninteger moments of the partition function and self averaging properties of the free energy. We illustrate our results by some examples and discuss possible generalizations to a larger class of distributions, to Random Energy Models, and to the finite dimensional case. We note that our results are not in agreement with the predictions of a recent replica approach to a similar problem.
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.
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.
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.
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.
Functional Redundancy Patterns Reveal Non-Random Assembly Rules in a Species-Rich Marine Assemblage
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
Combinatorial Markov Random Fields and Their Applications to Information Organization
2008-02-01
data clustering —the most important application of unsupervised learning—for which we give some necessary definitions and insights. 2.1 Markov Random...algorithm starts with data instances distributed over k clusters (where k is the desired number of clusters ) and reorga- nizes / updates the clusters ...its original ICM- based version. 4.5 Related work The study of distributional clustering based on co-occurrence data using informa- tion theoretic
Charged Particle Diffusion in Isotropic Random Magnetic Fields
NASA Astrophysics Data System (ADS)
Subedi, P.; Sonsrettee, W.; Blasi, P.; Ruffolo, D.; Matthaeus, W. H.; Montgomery, D.; Chuychai, P.; Dmitruk, P.; Wan, M.; Parashar, T. N.; Chhiber, R.
2017-03-01
The investigation of the diffusive transport 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 the diffusion of charged particles in fully three-dimensional isotropic turbulent magnetic fields with no mean field, which may be pertinent to many astrophysical situations. We identify different ranges of particle energy depending upon the ratio of Larmor radius to the characteristic outer length scale of turbulence. Two different theoretical models are proposed to calculate the diffusion coefficient, each applicable to a distinct range of particle energies. The theoretical results are compared to those from computer simulations, showing good agreement.
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.
Cosmic ray modulation in a random anisotropic magnetic field
NASA Technical Reports Server (NTRS)
Dorman, L. I.; Fedorov, Y. I.; Katz, M. I.; Nosov, S. F.; Shakhov, B. A.
1985-01-01
Inhomogeneities of the interplanetary magnetic field can be divided into small scale and large scale ones as may be required by the character of the problem of cosmic ray (CR) propagation. CR propagation in stochastic magnetic fields is of diffusion character. The main contribution into the scattering of CR particles is made by their interaction with inhomogeneities of the magnetic field H which have characteristic dimensions 1 of the order of Larmor radius R=cp/eH of particle (p is the absolute value of particle momentum, e is particle charge, c is velocity of light). Scattering of particles on such inhomogeneities leads to their diffusion mostly along a magnetic field with characteristic dimensions of variation in space exceeding the mean free path.
Spatio-temporal contextual classification based on Markov random field model. [for thematic mapping
NASA Technical Reports Server (NTRS)
Jeon, Byeungwoo; Landgrebe, D. A.
1991-01-01
A contextural classifier based on a Markov random field model, which can utilize both spatial and temporal contexts, is investigated. Spatial and temporal neighbors are defined, and the class assignment of each pixel is assumed to be dependent only on the measurement vectors of itself and those of its spatial and temporal neighbors according to the Markov random field property. Only interpixel class dependency context is used in the classification. The joint prior probability of the classes of each pixel and its spatial and temporal neighbors are modeled by a Gibbs random field. The classification is performed in a recursive manner. Experiments with multi-temporal Thematic Mapper data show promising results.
Spatio-temporal contextual classification based on Markov random field model. [for thematic mapping
NASA Technical Reports Server (NTRS)
Jeon, Byeungwoo; Landgrebe, D. A.
1991-01-01
A contextural classifier based on a Markov random field model, which can utilize both spatial and temporal contexts, is investigated. Spatial and temporal neighbors are defined, and the class assignment of each pixel is assumed to be dependent only on the measurement vectors of itself and those of its spatial and temporal neighbors according to the Markov random field property. Only interpixel class dependency context is used in the classification. The joint prior probability of the classes of each pixel and its spatial and temporal neighbors are modeled by a Gibbs random field. The classification is performed in a recursive manner. Experiments with multi-temporal Thematic Mapper data show promising results.
Modulation of electromagnetic fields by a depolarizer of random polarizer array.
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.
v-Spread Due to Random Field Multipoles
Parzen, G.
1989-07-12
Random a_{k}, b_{k} can produce an appreciable Δv spread (AD/RHIC-AP-52, 1987) the largest Δv occurs when E_{y} =0. The |v_{1}-v_{2}| found for the largest E_{x} is a v-spread, since smaller |v_{1}-v_{2}| will be found for smaller E_{x}.
Low-altitude magnetic field measurements by MESSENGER reveal Mercury’s ancient crustal field
NASA Astrophysics Data System (ADS)
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.
2015-05-01
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.
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.
Barkhausen noise in the Random Field Ising Magnet NdFeB
NASA Astrophysics Data System (ADS)
Xu, Jian; Silevitch, Daniel; Rosenbaum, Thomas
2015-03-01
With the application of a magnetic field transverse to the magnetic easy axis, sintered blocks of the rare-earth ferromagnet Nd2Fe14B form a realization of the Random-Field Ising Model at room temperature. We study domain reversal and avalanche dynamics through an analysis of the Barkhausen noise. Power-law behavior with a cutoff is observed in the avalanche energy spectrum, consistent with theoretical predictions for disordered materials. Two regimes of behavior are found, one at low temperature and high transverse field where the system shows behavior consistent with randomness-dominated dynamics, and a high-temperature, low-transverse-field regime in which thermal fluctuations dominate the dynamics. In the randomness-dominated regime, the critical exponents are consistent with mean-field predictions for heavily disordered system, whereas in the thermal-fluctuation regime, the critical exponents differ substantially from the mean-field predictions.
Statistical properties of the Fraunhofer diffraction field produced by random fractals.
Uno, K; Uozumi, J; Asakura, T
1993-05-20
First-order statistical properties of the speckle field and its intensity in the Fraunhofer diffraction region that is produced by random Koch fractals are investigated by means of computer simulations in comparison with the ordinary fully developed speckle.
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.
Nonstationary elementary-field light randomly triggered by Poisson impulses.
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.
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.
Phase diagram of the transverse Ising model in a random field
NASA Astrophysics Data System (ADS)
Milman, F. S.; Hauser, P. R.; Figueiredo, W.
1991-06-01
We determine the phase diagram of the transverse Ising model with a trimodal distribution (sum of three δ functions) for a longitudinal random field at T=0, using a mean-field approximation. The phase diagram includes tricritical points, ordered critical points, a fourth-order point, critical end points, and a double critical end point. Our T=0 phase diagram is completely equivalent to the one obtained by Kaufman, Klunzinger, and Khurana for the random-field Ising model. We show that the temperature and the magnitude of the transverse field play a similar role.
Restoration of dimensional reduction in the random-field Ising model at five dimensions.
Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas
2017-04-01
The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D-2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D=5. We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3≤D<6 to their values in the pure Ising model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.
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
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.
Restoration of dimensional reduction in the random-field Ising model at five dimensions
NASA Astrophysics Data System (ADS)
Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas
2017-04-01
The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D <6 to their values in the pure Ising model at D -2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.
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.
Flexible Representation of Spatio-Temporal Random Fields in the Model Web
NASA Astrophysics Data System (ADS)
Gräler, B.; Stasch, C.
2012-04-01
The Model Web envisions an infrastructure for coupling environmental models in the Web. In environmental sciences, the phenomena of interest are usually not well-bounded objects, but rather continuous phenomena in space and time. These phenomena are commonly referred to as spatial or spatio-temporal fields and are often modelled as random variables. Currently, spatio-temporal fields are usually represented and exchanged as raster data. Besides the communication overhead this imposes, exchanging rasters has also other drawbacks. For example, the interpolation method used to calculate the raster values as well as the original observations the raster originates from are usually not part of the resulting data. Furthermore, the interpolated values are commonly single moment estimates of the random variables such as their expectation values. Thus, the natural randomness in the interpolated variables and interpolation uncertainties are also not available any more after interpolation. We propose a new model for exchanging spatio-temporal random fields as the original sample data plus information about the model of spatial or spatio-temporal variance describing the random field. This allows to communicate the complete random variables and their associated uncertainties opposed to single estimates. In addition, this approach suggests a particular interpolation method to calculate rasters from the field. The desired raster resolution and projection can then be chosen by the user of the field data. This is advantageous to the classical approach, as transformations between coordinate reference systems typically distort the given raster and changing the raster's resolution usually imposes a second model assumption on the interpolated field data. Using a standardized language to describe spatio-temporal random fields allows for a fully machine readable approach. Depending on the target application, one can thus easily obtain one to several simulations of the field reflecting its
Metastable minima of the Heisenberg spin glass in a random magnetic field
NASA Astrophysics Data System (ADS)
Sharma, Auditya; Yeo, Joonhyun; Moore, M. A.
2016-11-01
We have studied zero-temperature metastable minima in classical m -vector component spin glasses in the presence of m -component random fields for two models, the Sherrington-Kirkpatrick (SK) model and the Viana-Bray (VB) model. For the SK model we have calculated analytically its complexity (the log of the number of minima) for both the annealed case where one averages the number of minima before taking the log and the quenched case where one averages the complexity itself, both for fields above and below the de Almeida-Thouless (AT) field, which is finite for m >2 . We have done numerical quenches starting from a random initial state (infinite temperature state) by putting spins parallel to their local fields until there is no further decrease of the energy and found that in zero field it always produces minima that have zero overlap with each other. For the m =2 and m =3 cases in the SK model the final energy reached in the quench is very close to the energy Ec at which the overlap of the states would acquire replica symmetry-breaking features. These minima have marginal stability and will have long-range correlations between them. In the SK limit we have analytically studied the density of states ρ (λ ) of the Hessian matrix in the annealed approximation. Despite the fact that in the presence of a random field there are no continuous symmetries, the spectrum extends down to zero with the usual √{λ } form for the density of states for fields below the AT field. However, when the random field is larger than the AT field, there is a gap in the spectrum, which closes up as the AT field is approached. The VB model behaves differently and seems rather similar to studies of the three-dimensional Heisenberg spin glass in a random vector field.
Effective realization of random magnetic fields in compounds with large single-ion anisotropy
NASA Astrophysics Data System (ADS)
Herbrych, J.; Kokalj, J.
2017-03-01
We show that spin S =1 system with large and random single-ion anisotropy can be at low energies mapped to a S =1 /2 system with random magnetic fields. This is, for example, realized in Ni (Cl1 -xBrx)2-4 SC (NH2)2 compound (DTNX) and therefore it represents a long-sought realization of random local (on-site) magnetic fields in antiferromagnetic systems. We support the mapping by numerical study of S =1 and effective S =1 /2 anisotropic Heisenberg chains and find excellent agreement for static quantities and also for the spin conductivity. Such systems can therefore be used to study the effects of local random magnetic fields on transport properties.
Second-order receptive fields reveal multidigit interactions in area 3b of the macaque monkey
Thakur, Pramodsingh H.; Fitzgerald, Paul J.
2012-01-01
Linear receptive field (RF) models of area 3b neurons reveal a three-component structure: a central excitatory region flanked by two inhibitory regions that are spatially and temporally nonoverlapping with the excitation. Previous studies also report that there is an “infield” inhibitory region throughout the neuronal RF, which is a nonlinear interactive (second order) effect whereby stimuli lagging an input to the excitatory region are suppressed. Thus linear models may be inaccurate approximations of the neurons' true RFs. In this study, we characterize the RFs of area 3b neurons, using a second-order quadratic model. Data were collected from 80 neurons of two awake, behaving macaque monkeys while a random dot pattern was scanned simultaneously across the distal pads of digits D2, 3, and 4. We used an iterative method derived from matching pursuit to identify a set of linear and nonlinear terms with significant effects on the neuronal response. For most neurons (65/80), the linear component of the quadratic RF was characterized by a single excitatory region on the dominant digit. Interactions within the dominant digit were characterized by two quadratic filters that capture the spatial aspects of the interactive infield inhibition. Interactions between the dominant (most responsive) digit and its adjacent digit(s) formed the largest class of cross-digit interactions. The results demonstrate that a significant part of area 3b responses is due to nonlinear mechanisms, and furthermore, the data support the notion that area 3b neurons have “nonclassical RF”-like input from adjacent fingers, indicating that area 3b plays a role in integrating shape inputs across digits. PMID:22457468
Phase diagram of the classical Heisenberg model in a trimodal random field distribution
NASA Astrophysics Data System (ADS)
Santos-Filho, A.; Albuquerque, D. F. de; Santos-Filho, J. B.; Batista, T. S. Araujo
2016-11-01
The classical spin 1 / 2 Heisenberg model on a simple cubic lattice, with fluctuating bond interactions between nearest neighbors and in the presence of a random magnetic field, is investigated by effective field theory based on two-spin cluster. The random field is drawn from the asymmetric and anisotropic trimodal probability distribution. The fluctuating bond is extracted from the symmetric and anisotropic bimodal probability. We estimate the transition temperatures, and the phase diagram in the Tc- h, Tc- p and Tc - α planes. We observe that the temperature of the tricritical point decreases with the increase of disorder in exchange interactions until the system ceases to display tricritical behavior. The disorder of the interactions and reentrant phenomena depends on the trimodal distribution of the random field.
Harper, Nicol S; Schoppe, Oliver; Willmore, Ben D B; Cui, Zhanfeng; Schnupp, Jan W H; King, Andrew J
2016-11-01
Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1-7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.
Willmore, Ben D. B.; Cui, Zhanfeng; Schnupp, Jan W. H.; King, Andrew J.
2016-01-01
Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1–7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context. PMID:27835647
Spectral degree of coherence of a random three-dimensional electromagnetic field.
Korotkova, Olga; Wolf, Emil
2004-12-01
The complex spectral degree of coherence of a general random, statistically stationary electromagnetic field is introduced in a manner similar to the way it is defined for a beamlike field, namely, by means of Young's interference experiment. Both its modulus and its phase are measurable. We illustrate the definition by applying it to blackbody radiation emerging from a cavity. The results are of particular interest for near-field optics.
Far-field errors due to random noise in cylindrical near-field measurements
NASA Astrophysics Data System (ADS)
Romeu, Jordi; Jofre, Luis; Cardama, Angel
1992-01-01
A full characterization of the far-field noise obtained from cylindrical near- to far-field transformation, for a white Gaussian, space stationary, near-field noise is derived. A possible source for such noise is the receiver additive noise. The noise characterization is done by obtaining the autocorrelation of the far-field noise, which is shown to be easily computed during the transformation process. Even for this simple case, the far-field noise has complex behavior dependent on the measurement probe. Once the statistical properties of the far-field noise are determined, it is possible to compute upper and lower bounds for the radiation pattern for a given probability. These bounds define a strip within the radiation pattern with the desired probability. This may be used as part of a complete near-field error analysis of a particular cylindrical near-field facility.
A flash-drag effect in random motion reveals involvement of preattentive motion processing
Fukiage, Taiki; Whitney, David; Murakami, Ikuya
2013-01-01
The flash-drag (FDE) effect refers to the phenomenon in which the position of a stationary flashed object in one location appears shifted in the direction of nearby motion. Over the past decade, it has been debated how bottom-up and top-down processes contribute to this illusion. In this study, we demonstrate that randomly phase-shifting gratings can produce the FDE. In the random motion sequence we used, the FDE inducer (a sinusoidal grating) jumped to a random phase every 125 ms and stood still until the next jump. Because this random sequence could not be tracked attentively, it was impossible for the observer to discern the jump direction at the time of the flash. By sorting the data based on the flash’s onset time relative to each jump time in the random motion sequence, we found that a large FDE with a broad temporal tuning occurred around 50 to 150 ms before the jump and that this effect was not correlated with any other jumps in the past or future. These results suggest that as few as two frames of unpredictable apparent motion can preattentively cause the FDE with a broad temporal tuning. PMID:22080448
A flash-drag effect in random motion reveals involvement of preattentive motion processing.
Fukiage, Taiki; Whitney, David; Murakami, Ikuya
2011-11-11
The flash-drag (FDE) effect refers to the phenomenon in which the position of a stationary flashed object in one location appears shifted in the direction of nearby motion. Over the past decade, it has been debated how bottom-up and top-down processes contribute to this illusion. In this study, we demonstrate that randomly phase-shifting gratings can produce the FDE. In the random motion sequence we used, the FDE inducer (a sinusoidal grating) jumped to a random phase every 125 ms and stood still until the next jump. Because this random sequence could not be tracked attentively, it was impossible for the observer to discern the jump direction at the time of the flash. By sorting the data based on the flash's onset time relative to each jump time in the random motion sequence, we found that a large FDE with a broad temporal tuning occurred around 50 to 150 ms before the jump and that this effect was not correlated with any other jumps in the past or future. These results suggest that as few as two frames of unpredictable apparent motion can preattentively cause the FDE with a broad temporal tuning.
1982-03-01
Systems and the Department of Electrical Engineering and Computer Science, M.I.T., Cambridge, MA 02139 S JUL 161982 The work of this author was supported in...the inverse scattering problem of cuantum mechanics [13], [14]. By transforming the estimation problem over a finite disk into an equivalent problem...them needs to be computed . The construction of random field estimates is considered in Section V and the special case when we want to estimate the random
van Nierop, Lotte E; Slottje, Pauline; Kingma, Herman; Kromhout, Hans
2013-07-01
We assessed postural body sway performance after exposure to movement induced time-varying magnetic fields in the static magnetic stray field in front of a 7 Tesla (T) magnetic resonance imaging scanner. Using a double blind randomized crossover design, 30 healthy volunteers performed two balance tasks (i.e., standing with eyes closed and feet in parallel and then in tandem position) after standardized head movements in a sham, low exposure (on average 0.24 T static magnetic stray field and 0.49 T·s(-1) time-varying magnetic field) and high exposure condition (0.37 T and 0.70 T·s(-1)). Personal exposure to static magnetic stray fields and time-varying magnetic fields was measured with a personal dosimeter. Postural body sway was expressed in sway path, area, and velocity. Mixed-effects model regression analysis showed that postural body sway in the parallel task was negatively affected (P < 0.05) by exposure on all three measures. The tandem task revealed the same trend, but did not reach statistical significance. Further studies are needed to investigate the possibility of independent or synergetic effects of static magnetic stray field and time-varying magnetic field exposure. In addition, practical safety implications of these findings, e.g., for surgeons and others working near magnetic resonance imaging scanners need to be investigated.
Spasojević, Djordje; Janićević, Sanja; Knežević, Milan
2014-01-01
We present a numerical analysis of spanning avalanches in a two-dimensional (2D) nonequilibrium zero-temperature random field Ising model. Finite-size scaling analysis, performed for distribution of the average number of spanning avalanches per single run, spanning avalanche size distribution, average size of spanning avalanche, and contribution of spanning avalanches to magnetization jump, is augmented by analysis of spanning field (i.e., field triggering spanning avalanche), which enabled us to collapse averaged magnetization curves below critical disorder. Our study, based on extensive simulations of sufficiently large systems, reveals the dominant role of subcritical 2D-spanning avalanches in model behavior below and at the critical disorder. Other types of avalanches influence finite systems, but their contribution for large systems remains small or vanish.
First excitations in two- and three-dimensional random-field Ising systems
NASA Astrophysics Data System (ADS)
Zumsande, M.; Alava, M. J.; Hartmann, A. K.
2008-02-01
We present results on the first excited states for the random-field Ising model. These are based on an exact algorithm, with which we study the excitation energies and the excitation sizes for two- and three-dimensional random-field Ising systems with a Gaussian distribution of the random fields. Our algorithm is based on an approach of Frontera and Vives which, in some cases, does not yield the true first excited states. Using the corrected algorithm, we find that the order disorder phase transition for three dimensions is visible via crossings of the excitation energy curves for different system sizes, while in two dimensions these crossings converge to zero disorder. Furthermore, we obtain in three dimensions a fractal dimension of the excitation cluster of ds = 2.42(2). We also provide analytical droplet arguments to understand the behavior of the excitation energies for small and large disorder as well as close to the critical point.
The Effect of the Random Magnetic Field Component on the Parker Instability
NASA Astrophysics Data System (ADS)
Kim, Jongsoo; Ryu, Dongsu
2001-11-01
The Parker instability is considered to play important roles in the evolution of the interstellar medium. Most studies on the development of the instability so far have been based on an initial equilibrium system with a uniform magnetic field. However, the Galactic magnetic field possesses a random component in addition to the mean uniform component, with comparable strength of the two components. Parker and Jokipii have recently suggested that the random component can suppress the growth of small wavelength perturbations. Here we extend their analysis by including gas pressure, which was ignored in their work, and study the stabilizing effect of the random component in the interstellar gas with finite pressure. Following Parker and Jokipii, we model the magnetic field as a mean azimuthal component, B(z), plus a random radial component, ɛ(z)B(z), where ɛ(z) is a random function of height from the equatorial plane. We show that for the observationally suggested values of <ɛ2>1/2, the tension due to the random component becomes important, so that the growth of the instability is either significantly reduced or completely suppressed. When the instability still works, the radial wavenumber of the most unstable mode is found to be zero. That is, the instability is reduced to be effectively two-dimensional. We discuss briefly the implications of our finding.
Mishchenko, Michael I; Yurkin, Maxim A
2017-02-01
Although the model of randomly oriented nonspherical particles has been used in a great variety of applications of far-field electromagnetic scattering, it has never been defined in strict mathematical terms. In this Letter, we use the formalism of Euler rigid-body rotations to clarify the concept of statistically random particle orientations and derive its immediate corollaries in the form of the most general mathematical properties of the orientation-averaged extinction and scattering matrices. Our results serve to provide a rigorous mathematical foundation for numerous publications in which the notion of randomly oriented particles and its light-scattering implications have been considered intuitively obvious.
Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields.
Rajagopalan, Srinivasan; Robb, Richard A
2006-01-01
Tissue engineering integrates the principles of engineering and life sciences toward the design, construction, modification and growth of biological substitutes that restore, maintain, or improve tissue function. The structural integrity and ultimate functionality of such tissue analogs is defined by scaffolds- porous, three-dimensional "trellis-like" structures that, on implantation, provide a viable environment to regenerate damaged tissues. The orthogonal scaffold fabrication methods currently employed can be broadly classified into two categories: (a) conventional, irreproducible, stochastic techniques producing reasonably biomorphic scaffold architecture, and (b) rapidly emerging, repeatable, computer-controlled techniques producing straight edged "contra naturam" scaffold architecture. In this paper, we present the results of the first attempt in an image-based scaffold modeling and optimization strategy that synergistically exploits the orthogonal fabrication techniques to create repeatable, biomorphic scaffolds with optimal scaffold morphology. Motivated by the use of Gaussian random fields (GRF) to model cosmological structure formation, we use appropriately ordered and clipped stacks of GRF to model the three-dimensional pore-solid scaffold labyrinths. Image-based metrology, fabrication and mechanical characterization of these scaffolds reveal the possibility of enabling the previously elusive deployment of promising benchside tissue analogs to the clinical bedside.
Automated torso organ segmentation from 3D CT images using conditional random field
NASA Astrophysics Data System (ADS)
Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Misawa, Kazunari; Mori, Kensaku
2016-03-01
This paper presents a segmentation method for torso organs using conditional random field (CRF) from medical images. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. In this paper, we propose an organ segmentation method using structured output learning which is based on probabilistic graphical model. The proposed method utilizes CRF on three-dimensional grids as probabilistic graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weight parameters of the CRF using stochastic gradient descent algorithm and estimate organ labels for a given image by maximum a posteriori (MAP) estimation. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 6.6%. The DICE coefficients of right lung, left lung, heart, liver, spleen, right kidney, and left kidney are 0.94, 0.92, 0.65, 0.67, 0.36, 0.38, and 0.37, respectively.
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.
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
Theory of weak scattering of stochastic electromagnetic fields from deterministic and random media
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.
Magnetic field line random walk in models and simulations of reduced magnetohydrodynamic turbulence
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.
Solution NMR of MPS-1 reveals a random coil cytosolic domain structure.
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.
Solution NMR of MPS-1 Reveals a Random Coil Cytosolic Domain Structure
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
Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells.
Deng, Qiaolin; Ramsköld, Daniel; Reinius, Björn; Sandberg, Rickard
2014-01-10
Expression from both alleles is generally observed in analyses of diploid cell populations, but studies addressing allelic expression patterns genome-wide in single cells are lacking. Here, we present global analyses of allelic expression across individual cells of mouse preimplantation embryos of mixed background (CAST/EiJ × C57BL/6J). We discovered abundant (12 to 24%) monoallelic expression of autosomal genes and that expression of the two alleles occurs independently. The monoallelic expression appeared random and dynamic because there was considerable variation among closely related embryonic cells. Similar patterns of monoallelic expression were observed in mature cells. Our allelic expression analysis also demonstrates the de novo inactivation of the paternal X chromosome. We conclude that independent and stochastic allelic transcription generates abundant random monoallelic expression in the mammalian cell.
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.
Field-scale experiments reveal persistent yield gaps in low-input and organic cropping systems
Kravchenko, Alexandra N.; Snapp, Sieglinde S.; Robertson, G. Philip
2017-01-01
Knowledge of production-system performance is largely based on observations at the experimental plot scale. Although yield gaps between plot-scale and field-scale research are widely acknowledged, their extent and persistence have not been experimentally examined in a systematic manner. At a site in southwest Michigan, we conducted a 6-y experiment to test the accuracy with which plot-scale crop-yield results can inform field-scale conclusions. We compared conventional versus alternative, that is, reduced-input and biologically based–organic, management practices for a corn–soybean–wheat rotation in a randomized complete block-design experiment, using 27 commercial-size agricultural fields. Nearby plot-scale experiments (0.02-ha to 1.0-ha plots) provided a comparison of plot versus field performance. We found that plot-scale yields well matched field-scale yields for conventional management but not for alternative systems. For all three crops, at the plot scale, reduced-input and conventional managements produced similar yields; at the field scale, reduced-input yields were lower than conventional. For soybeans at the plot scale, biological and conventional managements produced similar yields; at the field scale, biological yielded less than conventional. For corn, biological management produced lower yields than conventional in both plot- and field-scale experiments. Wheat yields appeared to be less affected by the experimental scale than corn and soybean. Conventional management was more resilient to field-scale challenges than alternative practices, which were more dependent on timely management interventions; in particular, mechanical weed control. Results underscore the need for much wider adoption of field-scale experimentation when assessing new technologies and production-system performance, especially as related to closing yield gaps in organic farming and in low-resourced systems typical of much of the developing world. PMID:28096409
Field-scale experiments reveal persistent yield gaps in low-input and organic cropping systems.
Kravchenko, Alexandra N; Snapp, Sieglinde S; Robertson, G Philip
2017-01-31
Knowledge of production-system performance is largely based on observations at the experimental plot scale. Although yield gaps between plot-scale and field-scale research are widely acknowledged, their extent and persistence have not been experimentally examined in a systematic manner. At a site in southwest Michigan, we conducted a 6-y experiment to test the accuracy with which plot-scale crop-yield results can inform field-scale conclusions. We compared conventional versus alternative, that is, reduced-input and biologically based-organic, management practices for a corn-soybean-wheat rotation in a randomized complete block-design experiment, using 27 commercial-size agricultural fields. Nearby plot-scale experiments (0.02-ha to 1.0-ha plots) provided a comparison of plot versus field performance. We found that plot-scale yields well matched field-scale yields for conventional management but not for alternative systems. For all three crops, at the plot scale, reduced-input and conventional managements produced similar yields; at the field scale, reduced-input yields were lower than conventional. For soybeans at the plot scale, biological and conventional managements produced similar yields; at the field scale, biological yielded less than conventional. For corn, biological management produced lower yields than conventional in both plot- and field-scale experiments. Wheat yields appeared to be less affected by the experimental scale than corn and soybean. Conventional management was more resilient to field-scale challenges than alternative practices, which were more dependent on timely management interventions; in particular, mechanical weed control. Results underscore the need for much wider adoption of field-scale experimentation when assessing new technologies and production-system performance, especially as related to closing yield gaps in organic farming and in low-resourced systems typical of much of the developing world.
Disorder fingerprint: Intensity distributions in the near field of random media
NASA Astrophysics Data System (ADS)
Naraghi, R. Rezvani; Sukhov, S.; Dogariu, A.
2016-11-01
The structural morphology of complex dielectric media determines their functionalities by driving the statistical properties of the electromagnetic fields. Our controlled experiments and full electromagnetic calculations that go beyond common dipolar approximations demonstrate that the specific characteristics of disorder lead to non-Rayleigh statistics of detected intensity, which can be directly accessed in the near field of random media and can be unambiguously related to the short-range correlations of disorder.
Nonequilibrium random-field Ising model on a diluted triangular lattice.
Kurbah, Lobisor; Thongjaomayum, Diana; Shukla, Prabodh
2015-01-01
We study critical hysteresis in the random-field Ising model on a two-dimensional periodic lattice with a variable coordination number z(eff) in the range 3≤z(eff)≤6. We find that the model supports critical behavior in the range 4
Modeling and statistical analysis of non-Gaussian random fields with heavy-tailed distributions.
Nezhadhaghighi, Mohsen Ghasemi; Nakhlband, Abbas
2017-04-01
In this paper, we investigate and develop an alternative approach to the numerical analysis and characterization of random fluctuations with the heavy-tailed probability distribution function (PDF), such as turbulent heat flow and solar flare fluctuations. We identify the heavy-tailed random fluctuations based on the scaling properties of the tail exponent of the PDF, power-law growth of qth order correlation function, and the self-similar properties of the contour lines in two-dimensional random fields. Moreover, this work leads to a substitution for the fractional Edwards-Wilkinson (EW) equation that works in the presence of μ-stable Lévy noise. Our proposed model explains the configuration dynamics of the systems with heavy-tailed correlated random fluctuations. We also present an alternative solution to the fractional EW equation in the presence of μ-stable Lévy noise in the steady state, which is implemented numerically, using the μ-stable fractional Lévy motion. Based on the analysis of the self-similar properties of contour loops, we numerically show that the scaling properties of contour loop ensembles can qualitatively and quantitatively distinguish non-Gaussian random fields from Gaussian random fluctuations.
Modeling and statistical analysis of non-Gaussian random fields with heavy-tailed distributions
NASA Astrophysics Data System (ADS)
Nezhadhaghighi, Mohsen Ghasemi; Nakhlband, Abbas
2017-04-01
In this paper, we investigate and develop an alternative approach to the numerical analysis and characterization of random fluctuations with the heavy-tailed probability distribution function (PDF), such as turbulent heat flow and solar flare fluctuations. We identify the heavy-tailed random fluctuations based on the scaling properties of the tail exponent of the PDF, power-law growth of q th order correlation function, and the self-similar properties of the contour lines in two-dimensional random fields. Moreover, this work leads to a substitution for the fractional Edwards-Wilkinson (EW) equation that works in the presence of μ -stable Lévy noise. Our proposed model explains the configuration dynamics of the systems with heavy-tailed correlated random fluctuations. We also present an alternative solution to the fractional EW equation in the presence of μ -stable Lévy noise in the steady state, which is implemented numerically, using the μ -stable fractional Lévy motion. Based on the analysis of the self-similar properties of contour loops, we numerically show that the scaling properties of contour loop ensembles can qualitatively and quantitatively distinguish non-Gaussian random fields from Gaussian random fluctuations.
Markov random field models for directional field and singularity extraction in fingerprint images.
Dass, Sarat C
2004-10-01
A Bayesian formulation is proposed for reliable and robust extraction of the directional field in fingerprint images using a class of spatially smooth priors. The spatial smoothness allows for robust directional field estimation in the presence of moderate noise levels. Parametric template models are suggested as candidate singularity models for singularity detection. The parametric models enable joint extraction of the directional field and the singularities in fingerprint impressions by dynamic updating of feature information. This allows for the detection of singularities that may have previously been missed, as well as better aligning the directional field around detected singularities. A criteria is presented for selecting an optimal block size to reduce the number of spurious singularity detections. The best rates of spurious detection and missed singularities given by the algorithm are 4.9% and 7.1%, respectively, based on the NIST 4 database.
On the unlikeliness of multi-field inflation: bounded random potentials and our vacuum
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.
Kestener, Pierre; Arneodo, Alain
2004-07-23
We use singular value decomposition techniques to generalize the wavelet transform modulus maxima method to the multifractal analysis of vector-valued random fields. The method is calibrated on synthetic multifractal 2D vector measures and monofractal 3D fractional Brownian vector fields. We report the results of some application to the velocity and vorticity fields issued from 3D isotropic turbulence simulations. This study reveals the existence of an intimate relationship between the singularity spectra of these two vector fields which are found significantly more intermittent than previously estimated from longitudinal and transverse velocity increment statistics.
Analysis of a model for transport of charged particles in a random magnetic field
NASA Technical Reports Server (NTRS)
Hanson, F. B.; Ramanathan, G. V.; Klimas, A.; Sandri, G.
1973-01-01
A model for the transport of charged particles in a random magnetic field is a Volterra integrodifferential equation with a long-range kernel. The integrodifferential equation is solved numerically with the method of Bellman, Kalaba, and Lockett (1966). The results are shown to be in excellent agreement with analytical asymptotic results.-
ERIC Educational Resources Information Center
Kim, James S.
2006-01-01
The effects of a voluntary summer reading intervention were assessed in a randomized field trial involving 552 students in 10 schools. In this study, fourth-grade children received eight books to read during their summer vacation and were encouraged by their teachers to practice oral reading at home with a family member and to use comprehension…
ERIC Educational Resources Information Center
Lesaux, Nonie K.; Kieffer, Michael J.; Kelley, Joan G.; Harris, Julie Russ
2014-01-01
We conducted a randomized field trial to test an academic vocabulary intervention designed to bolster the language and literacy skills of linguistically diverse sixth-grade students (N = 2,082; n = 1,469 from a home where English is not the primary language), many demonstrating low achievement, enrolled in 14 urban middle schools. The 20-week…
Halting the Summer Achievement Slide: A Randomized Field Trial of the KindergARTen Summer Camp
ERIC Educational Resources Information Center
Borman, Geoffrey D.; Goetz, Michael E.; Dowling, N. Maritza
2009-01-01
In this randomized field trial of KindergARTen Camp, a 6-week summer enrichment program in literacy and the fine arts, we analyzed the summer learning outcomes of 93 treatment and 35 control students from high-poverty schools in Baltimore, Maryland. This experiment offers evidence concerning the causal effect of the program on 5 measures of…
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…
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…
Stochastic Simulation Techniques for Partition Function Approximation of Gibbs Random Field Images
1991-06-01
of Physics C : Solid State Physics , vol. 10, pp. 1379-1388, 1977. [10] F.S. Cohen, "Markov random fields for image modeling and analysis." In Modeling...disorder," Journal of Applied Crystallography, vol. 6, pp. 87-96, 1973. [9] I.G. Enting, "Crystal growth models and Ising models: Disorder points," Journal
ERIC Educational Resources Information Center
Borman, Geoffrey D.; Dowling, N. Maritza
2006-01-01
Employing a randomized field trial, this 3-year study explored the effects of a multiyear summer school program in preventing the cumulative effect of summer learning losses and promoting longitudinal achievement growth, for a total treatment group of 438 students from high-poverty schools. Longitudinal outcomes for the participants were…
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…
NASA Astrophysics Data System (ADS)
Magalhaes, S. G.; Zimmer, F. M.; Coqblin, B.
2012-12-01
We study here the influence of a random applied magnetic field on the competition between the Kondo effect, the spin glass phase and a ferromagnetic order in disordered cerium systems such as CeNi1-xCux. The model used here takes an intrasite Kondo coupling and an intersite random coupling; both the intersite random coupling and the random magnetic field are described within the Sherrington-Kirkpatrick model and the one-step replica symmetry breaking procedure is also used here. We present phase diagrams giving Temperature versus the Kondo exchange parameter and the random magnetic field makes decrease particularly the importance of the spin glass and ferromagnetic phases.
Molecular diversity in the genus Nicotiana as revealed by randomly amplified polymorphic DNA.
Siva Raju, K; Sheshumadhav, M; Murthy, T G K
2008-10-01
The genus Nicotiana consists of 64 recognized species of which, only two species, tabacum and rustica are cultivated extensively. Wild Nicotiana species are storehouses of genes for several diseases and pests, besides genes for several important phytochemicals and quality traits, which are not present in cultivated varieties. Randomly amplified polymorphic DNA (RAPD) analysis was used to determine the degree of genetic variation in the genus Nicotiana and to develop species specific markers. Twenty two species and two interspecific hybrids were analyzed by using 18 random decamer primers. Genetic polymorphism abounds among the wild species of genus Nicotiana (99.5 %) as evidenced by the high degree of polymorphism in RAPD profiles. The pairwise similarity measures in the species of subgenus Rustica was 0.252 whereas in the subgenus Tabacum was 0.189, suggesting that there was significant diversity among the species of these subgenera. In the species of subgenus Petunioides, the range of pairwise similarity measures was 0.128 to 0.941. The clustering pattern coincided with the traditional classification of Nicotiana species. All the primers generated specific bands in the various species. Thirty six species-specific markers identified in the present study will be useful in interspecific breeding programs.
2012-01-01
Background Haemophilus parasuis is the causative agent of Glässer’s disease and is a pathogen of swine in high-health status herds. Reports on serotyping of field strains from outbreaks describe that approximately 30% of them are nontypeable and therefore cannot be traced. Molecular typing methods have been used as alternatives to serotyping. This study was done to compare random amplified polymorphic DNA (RAPD) profiles and whole cell protein (WCP) lysate profiles as methods for distinguishing H. parasuis reference strains and field isolates. Results The DNA and WCP lysate profiles of 15 reference strains and 31 field isolates of H. parasuis were analyzed using the Dice and neighbor joining algorithms. The results revealed unique and reproducible DNA and protein profiles among the reference strains and field isolates studied. Simpson’s index of diversity showed significant discrimination between isolates when three 10mer primers were combined for the RAPD method and also when both the RAPD and WCP lysate typing methods were combined. Conclusions The RAPD profiles seen among the reference strains and field isolates did not appear to change over time which may reflect a lack of DNA mutations in the genes of the samples. The recent field isolates had different WCP lysate profiles than the reference strains, possibly because the number of passages of the type strains may affect their protein expression. PMID:22703293
NASA Astrophysics Data System (ADS)
Zaim, N.; Zaim, A.; Kerouad, M.
2017-02-01
In this work, the magnetic behavior of the cylindrical nanowire, consisting of a ferromagnetic core of spin-1 atoms surrounded by a ferromagnetic shell of spin-1 atoms is studied in the presence of a random crystal field interaction. Based on Metropolis algorithm, the Monte Carlo simulation has been used to investigate the effects of the concentration of the random crystal field p, the crystal field D and the shell exchange interaction Js on the phase diagrams and the hysteresis behavior of the system. Some characteristic behaviors have been found, such as the first and second-order phase transitions joined by tricritical point for appropriate values of the system parameters, triple and isolated critical points can be also found. Depending on the Hamiltonian parameters, single, double and para hysteresis regions are explicitly determined.
Controlling dispersion forces between small particles with artificially created random light fields
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
Controlling dispersion forces between small particles with artificially created random light fields.
Brügger, Georges; Froufe-Pérez, Luis S; Scheffold, Frank; José Sáenz, Juan
2015-06-22
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.
Correlations in the two-dimensional random-field Ising model
Glaus, U.
1986-09-01
Using transfer matrices, we calculate the connected and disconnected correlation functions of the random-field Ising model on long strips of width N-italic< or =8. The results, where extrapolated to the thermodynamic limit, are in good qualitative agreement with neutron scattering experiments of Birgeneau e-italict-italic a-italicl-italic. (Phys. Rev. B 28, 1438 (1983)) on the two-dimensional dilute Ising-like antiferromagnet Rb/sub 2/Co/sub 0.7/Mg/sub 0.3/F/sub 4/ . For a particular probability distribution of the random field we propose that this model describes an adsorbed monolayer with a doubly degenerate ground state in the presence of frozen impurities and predict some features that could be detected with low-energy electron diffraction experiments on such systems. A modified mean-field theory gives a good qualitative account of the high-temperature behavior of the correlations of this model.
Characterization of a random anisotropic conductivity field with Karhunen-Loeve methods
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.
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
Producing a functional eukaryotic messenger RNA (mRNA) requires the coordinated activity of several large protein complexes to initiate transcription, elongate nascent transcripts, splice together exons, and cleave and polyadenylate the 3’ end. Kinetic competition between these various processes has been proposed to regulate mRNA maturation, but this model could lead to multiple, randomly determined, or stochastic, pathways or outcomes. Regulatory checkpoints have been suggested as a means of ensuring quality control. However, current methods have been unable to tease apart the contributions of these processes at a single gene or on a time scale that could provide mechanistic insight. To begin to investigate the kinetic relationship between transcription and splicing, Daniel Larson, Ph.D., of CCR’s Laboratory of Receptor Biology and Gene Expression, and his colleagues employed a single-molecule RNA imaging approach to monitor production and processing of a human β-globin reporter gene in living cells.
Thermal Non-Equilibrium Revealed by Periodic Pulses of Random Amplitudes in Solar Coronal Loops
NASA Astrophysics Data System (ADS)
Auchère, Frédéric
2016-10-01
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.
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.
Fedashchin, Andrij; Cernota, William H.; Gonzalez, Melissa C.; Leach, Benjamin I.; Kwan, Noelle; Wesley, Roy K.; Weber, J. Mark
2015-01-01
A single cycle of strain improvement was performed in Saccharopolyspora erythraea mutB and 15 genotypes influencing erythromycin production were found. Genotypes generated by transposon mutagenesis appeared in the screen at a frequency of ∼3%. Mutations affecting central metabolism and regulatory genes were found, as well as hydrolases, peptidases, glycosyl transferases and unknown genes. Only one mutant retained high erythromycin production when scaled-up from micro-agar plug fermentations to shake flasks. This mutant had a knockout of the cwh1 gene (SACE_1598), encoding a cell-wall-associated hydrolase. The cwh1 knockout produced visible growth and morphological defects on solid medium. This study demonstrated that random transposon mutagenesis uncovers strain improvement-related genes potentially useful for strain engineering. PMID:26468041
Predictors of Consent in a Randomized Field Study in Child Welfare.
McDonald, Tom; Bhattarai, Jackie; Akin, Becci
2017-01-01
Randomized controlled trials (RCTs) are often viewed as the "gold standard" for proving the efficacy and effectiveness of new interventions. However, some are skeptical of the generalizability of the findings that RCTs produce. The characteristics of those willing to participate in research studies have the potential to affect the generalizability of its findings. This study examined factors that could influence consent among families recruited to participate in a randomized field trial in a real-world child welfare setting. This study tested the Parent Management Training Oregon Model for children in foster care with serious emotional disturbance. It employed a post-randomization consent design, whereby the entire sample of eligible participants, not just those who are willing to consent to randomization, are included in the sample. Initial eligibility assessment data and data from the federally mandated reporting system for public child welfare agencies provided the pool of potential predictors of consent. Bivariate and multivariate analyses were conducted to identify statistically significant predictors of consent. Being a dual reunification family was the most significant factor in predicting consent. Unmarried individuals, younger, female parents, cases where parental incarceration was the reason for removal and cases where the removal reason was not due to their children's behavioral problem(s) were also more likely to participate. As one of the first research studies to examine predictors of consent to a randomized field study in child welfare settings, results presented here can act as a preliminary guide for conducting RCTs in child welfare settings.
Methods for testing theory and evaluating impact in randomized field trials
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
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.
Tumor segmentation on FDG-PET: usefulness of locally connected conditional random fields
NASA Astrophysics Data System (ADS)
Nishio, Mizuho; Kono, Atsushi K.; Koyama, Hisanobu; Nishii, Tatsuya; Sugimura, Kazuro
2015-03-01
This study aimed to develop software for tumor segmentation on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET). To segment the tumor from the background, we used graph cut, whose segmentation energy was generally divided into two terms: the unary and pairwise terms. Locally connected conditional random fields (LCRF) was proposed for the pairwise term. In LCRF, a three-dimensional cubic window with length L was set for each voxel, and voxels within the window were considered for the pairwise term. To evaluate our method, 64 clinically suspected metastatic bone tumors were tested, which were revealed by FDG-PET. To obtain ground truth, the tumors were manually delineated via consensus of two board-certified radiologists. To compare the LCRF accuracy, other types of segmentation were also applied such as region-growing based on 35%, 40%, and 45% of the tumor maximum standardized uptake value (RG35, RG40, and RG45, respectively), SLIC superpixels (SS), and region-based active contour models (AC). To validate the tumor segmentation accuracy, a dice similarity coefficient (DSC) was calculated between manual segmentation and result of each technique. The DSC difference was tested using the Wilcoxon signed rank test. The mean DSCs of LCRF at L = 3, 5, 7, and 9 were 0.784, 0.801, 0.809, and 0.812, respectively. The mean DSCs of other techniques were RG35, 0.633; RG40, 0.675; RG45, 0.689; SS, 0.709; and AC, 0.758. The DSC differences between LCRF and other techniques were statistically significant (p <0.05). In conclusion, tumor segmentation was more reliably performed with LCRF relative to other techniques.
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.
Random pinning glass transition: hallmarks, mean-field theory and renormalization group analysis.
Cammarota, Chiara; Biroli, Giulio
2013-03-28
We present a detailed analysis of glass transitions induced by pinning particles at random from an equilibrium configuration. We first develop a mean-field analysis based on the study of p-spin spherical disordered models and then obtain the three-dimensional critical behavior by the Migdal-Kadanoff real space renormalization group method. We unveil the important physical differences with the case in which particles are pinned from a random (or very high temperature) configuration. We contrast the pinning particles approach to the ones based on biasing dynamical trajectories with respect to their activity and on coupling to equilibrium configurations. Finally, we discuss numerical and experimental tests.
Random walk of magnetic field-lines for different values of the energy range spectral index
Shalchi, A.; Kourakis, I.
2007-11-15
An analytical nonlinear description of field-line wandering in partially statistically magnetic systems was proposed recently. In this article the influence of the wave spectrum in the energy range onto field-line random walk is investigated by applying this formulation. It is demonstrated that in all considered cases we clearly obtain a superdiffusive behavior of the field-lines. If the energy range spectral index exceeds unity a free-streaming behavior of the field-lines can be found for all relevant length-scales of turbulence. Since the superdiffusive results obtained for the slab model are exact, it seems that superdiffusion is the normal behavior of field-line wandering.
Choo, Y; Klug, A
1994-01-01
In the preceding paper [Choo, Y. & Klug, A. (1994) Proc. Natl. Acad. Sci. USA 91, 11163-11167], we showed how selections from a library of zinc fingers displayed on phage yielded fingers able to bind to a number of DNA triplets. Here, we describe a technique to deal efficiently with the converse problem--namely, the selection of a DNA binding site for a given zinc finger. This is done by screening against libraries of DNA triplet binding sites randomized in two positions but having one base fixed in the third position. The technique is applied here to determine the specificity of fingers previously selected by phage display. We find that some of these fingers are able to specify a unique base in each position of the cognate triplet. This is further illustrated by examples of fingers which can discriminate between closely related triplets as measured by their respective equilibrium dissociation constants. Comparing the amino acid sequences of fingers which specify a particular base in a triplet, we infer that in most instances, sequence-specific binding of zinc fingers to DNA can be achieved by using a small set of amino acid-nucleotide base contacts amenable to a code. Images PMID:7972028
Sampling distributions of random electromagnetic fields in mesoscopic or dynamical systems.
Arnaut, Luk R
2009-09-01
We derive the sampling probability density function (pdf) of an ideal localized random electromagnetic field, its amplitude, and intensity in an electromagnetic environment that is quasistatically time-varying statistically homogeneous or static statistically inhomogeneous. The results allow for the estimation of field statistics and confidence intervals when a single spatial or temporal stochastic process produces randomization of the field. Sampling distributions are particularly significant when the number of degrees of freedom nu is relatively small (typically, nu<40 ), e.g., in mesoscopic systems when the sample set size N is relatively small by choice or by force. Results for both coherent and incoherent detection methods are derived for Cartesian, planar, and full-vectorial fields. We show that the functional form of the sampling pdf depends on whether the random variable is dimensioned (e.g., the sampled electric field proper) or is expressed in dimensionless standardized or normalized form (e.g., the sampled electric field divided by its sample standard deviation or sample mean). For dimensioned quantities, the electric field, its amplitude, and intensity exhibit different types of Bessel K sampling pdfs, which differ significantly from the asymptotic Gauss normal and chi2p(2) ensemble pdfs when nu is relatively small. By contrast, for the corresponding standardized quantities, Student t , Fisher-Snedecor F , and root- F sampling pdfs are obtained that exhibit heavier tails than comparable Bessel K pdfs. Statistical uncertainties obtained from classical small-sample theory for dimensionless quantities are shown to be overestimated compared to dimensioned quantities. Differences in the sampling pdfs arising from denormalization versus destandardization are identified.
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. © 2015 FEBS.
NASA Astrophysics Data System (ADS)
Hübsch, Florian; Marheineke, Nicole; Ritter, Klaus; Wegener, Raimund
2013-03-01
In melt-blowing very thin liquid fiber jets are spun due to high-velocity air streams. In literature there is a clear, unsolved discrepancy between the measured and computed jet attenuation (thinning). In this paper we will verify numerically that the turbulent velocity fluctuations causing a random aerodynamic drag on the fiber jets—that has been neglected so far—are the crucial effect to close this gap. For this purpose, we model the velocity fluctuations as vector Gaussian random fields on top of a k- ɛ turbulence description and develop an efficient sampling procedure. Taking advantage of the special covariance structure the effort of the sampling is linear in the discretization and makes the realization possible. Numerical results are discussed for a simplified melt-blowing model consisting of a system of random ordinary differential equations.
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.
NASA Astrophysics Data System (ADS)
Yang, Yongchao; Sun, Peng; Nagarajaiah, Satish; Bachilo, Sergei M.; Weisman, R. Bruce
2017-07-01
Structural damage is typically a local phenomenon that initiates and propagates within a limited area. As such high spatial resolution measurement and monitoring is often needed for accurate damage detection. This requires either significantly increased costs from denser sensor deployment in the case of global simultaneous/parallel measurements, or increased measurement time and labor in the case of global sequential measurements. This study explores the feasibility of an alternative approach to this problem: a computational solution in which a limited set of randomly positioned, low-resolution global strain measurements are used to reconstruct the full-field, high-spatial-resolution, two-dimensional (2D) strain field and rapidly detect local damage. The proposed approach exploits the implicit low-rank and sparse data structure of the 2D strain field: it is highly correlated without many edges and hence has a low-rank structure, unless damage-manifesting itself as sparse local irregularity-is present and alters such a low-rank structure slightly. Therefore, reconstruction of the full-field, high-spatial-resolution strain field from a limited set of randomly positioned low-resolution global measurements is modeled as a low-rank matrix completion framework and damage detection as a sparse decomposition formulation, enabled by emerging convex optimization techniques. Numerical simulations on a plate structure are conducted for validation. The results are discussed and a practical iterative global/local procedure is recommended. This new computational approach should enable the efficient detection of local damage using limited sets of strain measurements.
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.
SBN:Ce, A uniaxial random-field dominated relaxor ferroelectric
NASA Astrophysics Data System (ADS)
Kleemann, W.; Dec, J.; Lehnen, P.; Woike, Th.; Pankrath, R.
2000-09-01
Relaxor properties of Sr0.61-xBa0.39Nb2O6:Cex3 (SBN61:Ce) are examined by dielectric spectroscopy and linear birefringence (LB) as a function of frequency and temperature before and after poling. Relaxor behavior with large polydispersivity is observed above the ferroelectric phase transition temperature Tc. Below Tc a long-range ordered ferroelectric state with low polydispersivity prevails. An Ornstein-Zenike analysis of LB data suggests that pure SBN61 belongs to the 3D Ising universality class. Doping with Ce3- ions, which seem to act as random fields, enhances the relaxor properties and drives the system towards the random-field Ising model (RFIM) universality class.
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.
NASA Astrophysics Data System (ADS)
Staber, Brian; Guilleminot, Johann
2017-06-01
In this Note, we present a unified approach to the information-theoretic modeling and simulation of a class of elasticity random fields, for all physical symmetry classes. The new stochastic representation builds upon a Walpole tensor decomposition, which allows the maximum entropy constraints to be decoupled in accordance with the tensor (sub)algebras associated with the class under consideration. In contrast to previous works where the construction was carried out on the scalar-valued Walpole coordinates, the proposed strategy involves both matrix-valued and scalar-valued random fields. This enables, in particular, the construction of a generation algorithm based on a memoryless transformation, hence improving the computational efficiency of the framework. Two applications involving weak symmetries and sampling over spherical and cylindrical geometries are subsequently provided. These numerical experiments are relevant to the modeling of elastic interphases in nanocomposites, as well as to the simulation of spatially dependent wood properties for instance.
Specific-heat exponent and modified hyperscaling in the 4D random-field Ising model
NASA Astrophysics Data System (ADS)
Fytas, N. G.; Martín-Mayor, V.; Picco, M.; Sourlas, N.
2017-03-01
We report a high-precision numerical estimation of the critical exponent α of the specific heat of the random-field Ising model in four dimensions. Our result α =0.12(1) indicates a diverging specific-heat behavior and is consistent with the estimation coming from the modified hyperscaling relation using our estimate of θ via the anomalous dimensions η and \\barη . Our analysis benefited from a high-statistics zero-temperature numerical simulation of the model for two distributions of the random fields, namely a Gaussian and Poissonian distribution, as well as recent advances in finite-size scaling and reweighting methods for disordered systems. An original estimate of the critical slowing down exponent z of the maximum-flow algorithm used is also provided.
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.
Phase diagram of the random field Ising model on the Bethe lattice
NASA Astrophysics Data System (ADS)
Nowotny, Thomas; Patzlaff, Heiko; Behn, Ulrich
2002-01-01
The phase diagram of the random field Ising model on the Bethe lattice with a symmetric dichotomous random field is closely investigated with respect to the transition between the ferromagnetic and paramagnetic regimes. Refining arguments of Bleher, Ruiz, and Zagrebnov [J. Stat. Phys. 93, 33 (1998)], an exact upper bound for the existence of a unique paramagnetic phase is found, which considerably improves the earlier results. Several numerical estimates of transition lines between a ferromagnetic and a paramagnetic regime are presented. The results obtained do not coincide with the lower bound for the onset of ferromagnetism proposed by Bruinsma [Phys. Rev. B 30, 289 (1984)]. If Bruinsma's estimate proves correct, this would hint at a region of coexistence of stable ferromagnetic phases and a stable paramagnetic phase.
Percolation in sign-symmetric random fields: topological aspects and numerical modeling
Milovanov; Zimbardo
2000-07-01
The topology of percolation in random scalar fields psi(x) with sign symmetry [i.e., that the statistical properties of the functions psi(x) and -psi(x) are identical] is analyzed. Based on methods of general topology, we show that the zero set psi(x)=0 of the n-dimensional (n>/=2) sign-symmetric random field psi(x) contains a (connected) percolating subset under the condition |nablapsi(x)| not equal0 everywhere except in domains of negligible measure. The fractal geometry of percolation is analyzed in more detail in the particular case of the two-dimensional (n=2) fields psi(x). The improved Alexander-Orbach conjecture [Phys. Rev. E 56, 2437 (1997)] is applied analytically to obtain estimates of the main fractal characteristics of the percolating fractal sets generated by the horizontal "cuts," psi(x)=h, of the field psi(x). These characteristics are the Hausdorff fractal dimension of the set, D, and the index of connectivity, straight theta. We advocate an unconventional approach to studying the geometric properties of fractals, which involves methods of homotopic topology. It is shown that the index of connectivity, straight theta, of a fractal set is the topological invariant of this set, i.e., it remains unchanged under the homeomorphic deformations of the fractal. This issue is explicitly used in our study to find the Hausdorff fractal dimension of the single isolevels of the field psi(x), as well as the related geometric quantities. The results obtained are analyzed numerically in the particular case when the random field psi(x) is given by a fractional Brownian surface whose topological properties recover well the main assumptions of our consideration.
Motion of a Josephson vortex in the field of a random potential
Mineev, M.B.; Feigel'man, M.V.; Shmidt, V.V.
1981-07-01
We consider the motion and pinning of a Josephson vortex in a field produced by random inhomogeneities in a long junction. We find the distribution function of the force of vortex pinning on the inhomogeneities. We construct the current-voltage characteristic (CVC) of the junction. For inhomogeneities which are weak compared to the ohmic losses the CVC has a single hysteresis, in the opposite case it has two.
Rare-event Analysis and Computational Methods for Stochastic Systems Driven by Random Fields
2014-12-29
research develops asymptotic theories and numerical methods for computing rare- event probabilities associated with random fields and the associated...dynamics, neuroscience, fiber optics, astronomy , further civil engineering, engineer design, ocean-earth sciences, and so forth. We perform risk analysis...of such systems by investigating the asymptotic behavior of certain interesting rare events . For instance, 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND
A heuristic for the distribution of point counts for random curves over a finite field
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
Fluctuations of the partition function in the generalized random energy model with external field
NASA Astrophysics Data System (ADS)
Bovier, Anton; Klimovsky, Anton
2008-12-01
We study Derrida's generalized random energy model (GREM) in the presence of uniform external field. We compute the fluctuations of the ground state and of the partition function in the thermodynamic limit for all admissible values of parameters. We find that the fluctuations are described by a hierarchical structure which is obtained by a certain coarse graining of the initial hierarchical structure of the GREM with external field. We provide an explicit formula for the free energy of the model. We also derive some large deviation results providing an expression for the free energy in a class of models with Gaussian Hamiltonians and external field. Finally, we prove that the coarse-grained parts of the system emerging in the thermodynamic limit tend to have a certain optimal magnetization, as prescribed by the strength of the external field and by parameters of the GREM.
Matérn Class Tensor-Valued Random Fields and Beyond
NASA Astrophysics Data System (ADS)
Leonenko, Nikolai; Malyarenko, Anatoliy
2017-09-01
We construct classes of homogeneous random fields on a three-dimensional Euclidean space that take values in linear spaces of tensors of a fixed rank and are isotropic with respect to a fixed orthogonal representation of the group of 3× 3 orthogonal matrices. The constructed classes depend on finitely many isotropic spectral densities. We say that such a field belongs to either the Matérn or the dual Matérn class if all of the above densities are Matérn or dual Matérn. Several examples are considered.
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.
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.
Field Line Random Walk in Isotropic Magnetic Turbulence up to Infinite Kubo Number
NASA Astrophysics Data System (ADS)
Sonsrettee, W.; Wongpan, P.; Ruffolo, D. J.; Matthaeus, W. H.; Chuychai, P.; Rowlands, G.
2013-12-01
In astrophysical plasmas, the magnetic field line random walk (FLRW) plays a key role in the transport of energetic particles. In the present, we consider isotropic magnetic turbulence, which is a reasonable model for interstellar space. Theoretical conceptions of the FLRW have been strongly influenced by studies of the limit of weak fluctuations (or a strong mean field) (e.g, Isichenko 1991a, b). In this case, the behavior of FLRW can be characterized by the Kubo number R = (b/B0)(l_∥ /l_ \\bot ) , where l∥ and l_ \\bot are turbulence coherence scales parallel and perpendicular to the mean field, respectively, and b is the root mean squared fluctuation field. In the 2D limit (R ≫ 1), there has been an apparent conflict between concepts of Bohm diffusion, which is based on the Corrsin's independence hypothesis, and percolative diffusion. Here we have used three non-perturbative analytic techniques based on Corrsin's independence hypothesis for B0 = 0 (R = ∞ ): diffusive decorrelation (DD), random ballistic decorrelation (RBD) and a general ordinary differential equation (ODE), and compared them with direct computer simulations. All the analytical models and computer simulations agree that isotropic turbulence for R = ∞ has a field line diffusion coefficient that is consistent with Bohm diffusion. Partially supported by the Thailand Research Fund, NASA, and NSF.
NASA Astrophysics Data System (ADS)
Sivakumar, Krishnamoorthy; Goutsias, John I.
1998-09-01
We study the problem of simulating a class of Gibbs random field models, called morphologically constrained Gibbs random fields, using Markov chain Monte Carlo sampling techniques. Traditional single site updating Markov chain Monte Carlo sampling algorithm, like the Metropolis algorithm, tend to converge extremely slowly when used to simulate these models, particularly at low temperatures and for constraints involving large geometrical shapes. Moreover, the morphologically constrained Gibbs random fields are not, in general, Markov. Hence, a Markov chain Monte Carlo sampling algorithm based on the Gibbs sampler is not possible. We prose a variant of the Metropolis algorithm that, at each iteration, allows multi-site updating and converges substantially faster than the traditional single- site updating algorithm. The set of sites that are updated at a particular iteration is specified in terms of a shape parameter and a size parameter. Computation of the acceptance probability involves a 'test ratio,' which requires computation of the ratio of the probabilities of the current and new realizations. Because of the special structure of our energy function, this computation can be done by means of a simple; local iterative procedure. Therefore lack of Markovianity does not impose any additional computational burden for model simulation. The proposed algorithm has been used to simulate a number of image texture models, both synthetic and natural.
Schwinger-Dyson equations in large-N quantum field theories and nonlinear random processes
Buividovich, P. V.
2011-02-15
We propose a stochastic method for solving Schwinger-Dyson equations in large-N quantum field theories. Expectation values of single-trace operators are sampled by stationary probability distributions of the so-called nonlinear random processes. The set of all the histories of such processes corresponds to the set of all planar diagrams in the perturbative expansions of the expectation values of singlet operators. We illustrate the method on examples of the matrix-valued scalar field theory and the Weingarten model of random planar surfaces on the lattice. For theories with compact field variables, such as sigma models or non-Abelian lattice gauge theories, the method does not converge in the physically most interesting weak-coupling limit. In this case one can absorb the divergences into a self-consistent redefinition of expansion parameters. A stochastic solution of the self-consistency conditions can be implemented as a 'memory' of the random process, so that some parameters of the process are estimated from its previous history. We illustrate this idea on the two-dimensional O(N) sigma model. The extension to non-Abelian lattice gauge theories is discussed.
Exact mean field concept to compute defect energetics in random alloys on rigid lattices
NASA Astrophysics Data System (ADS)
Bonny, G.; Castin, N.; Pascuet, M. I.; Çelik, Y.
2017-07-01
In modern materials science modeling, the evolution of the energetics of random alloys with composition are desirable input parameters for several meso-scale and continuum scale models. When using atomistic methods to parameterize the above mentioned concentration dependent function, a mean field theory can significantly reduce the computational burden associated to obtaining the desired statistics in a random alloy. In this work, a mean field concept is developed to obtain the energetics of point-defect clusters in perfect random alloys. It is demonstrated that for a rigid lattice the concept is mathematically exact. In addition to the accuracy of the presented method, it is also computationally efficient as a small box can be used and perfect statistics are obtained in a single run. The method is illustrated by computing the formation and binding energy of solute and vacancy pairs in FeCr and FeW binaries. Also, the dissociation energy of small vacancy clusters was computed in FeCr and FeCr-2%W alloys, which are considered model alloys for Eurofer steels. As a result, it was concluded that the dissociation energy is not expected to vary by more than 0.1 eV in the 0-10% Cr and 0-2% W composition range. The present mean field concept can be directly applied to parameterize meso-scale models, such as cluster dynamics and object kinetic Monte Carlo models.
Random field disorder at an absorbing state transition in one and two dimensions.
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.
Hayashida, Morihiro; Kamada, Mayumi; Song, Jiangning; Akutsu, Tatsuya
2011-06-20
For understanding cellular systems and biological networks, it is important to analyze functions and interactions of proteins and domains. Many methods for predicting protein-protein interactions have been developed. It is known that mutual information between residues at interacting sites can be higher than that at non-interacting sites. It is based on the thought that amino acid residues at interacting sites have coevolved with those at the corresponding residues in the partner proteins. Several studies have shown that such mutual information is useful for identifying contact residues in interacting proteins. We propose novel methods using conditional random fields for predicting protein-protein interactions. We focus on the mutual information between residues, and combine it with conditional random fields. In the methods, protein-protein interactions are modeled using domain-domain interactions. We perform computational experiments using protein-protein interaction datasets for several organisms, and calculate AUC (Area Under ROC Curve) score. The results suggest that our proposed methods with and without mutual information outperform EM (Expectation Maximization) method proposed by Deng et al., which is one of the best predictors based on domain-domain interactions. We propose novel methods using conditional random fields with and without mutual information between domains. Our methods based on domain-domain interactions are useful for predicting protein-protein interactions.
Dense percolation in large-scale mean-field random networks is provably "explosive".
Veremyev, Alexander; Boginski, Vladimir; Krokhmal, Pavlo A; Jeffcoat, David E
2012-01-01
Recent reports suggest that evolving large-scale networks exhibit "explosive percolation": a large fraction of nodes suddenly becomes connected when sufficiently many links have formed in a network. This phase transition has been shown to be continuous (second-order) for most random network formation processes, including classical mean-field random networks and their modifications. We study a related yet different phenomenon referred to as dense percolation, which occurs when a network is already connected, but a large group of nodes must be dense enough, i.e., have at least a certain minimum required percentage of possible links, to form a "highly connected" cluster. Such clusters have been considered in various contexts, including the recently introduced network modularity principle in biological networks. We prove that, contrary to the traditionally defined percolation transition, dense percolation transition is discontinuous (first-order) under the classical mean-field network formation process (with no modifications); therefore, there is not only quantitative, but also qualitative difference between regular and dense percolation transitions. Moreover, the size of the largest dense (highly connected) cluster in a mean-field random network is explicitly characterized by rigorously proven tight asymptotic bounds, which turn out to naturally extend the previously derived formula for the size of the largest clique (a cluster with all possible links) in such a network. We also briefly discuss possible implications of the obtained mathematical results on studying first-order phase transitions in real-world linked systems.
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.
Fluorescence microscopy image noise reduction using a stochastically-connected random field model
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
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.
Sub-pixel porosity revealed by x-ray scatter dark field imaging
Revol, V.; Jerjen, I.; Schuetz, P.; Luethi, T.; Sennhauser, U.; Kottler, C.; Kaufmann, R.; Urban, C.; Straumann, U.
2011-08-15
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.
Pulsed electromagnetic fields after rotator cuff repair: a randomized, controlled study.
Osti, Leonardo; Buono, Angelo Del; Maffulli, Nicola
2015-03-01
The current study tested the hypothesis that the use of pulsed electromagnetic fields after rotator cuff repair is effective in the short term as an adjuvant treatment to reduce local inflammation, postoperative joint swelling, and recovery time, as well as to induce pain relief. Sixty-six patients who underwent shoulder arthroscopy for repair of small to medium rotator cuff tears were randomly divided into 2 groups with a block randomization procedure. Thirty-two patients underwent arthroscopic rotator cuff repair and application of pulsed electromagnetic fields postoperatively; 34 patients underwent rotator cuff repair and placebo treatment (placebo group). All patients had the same postoperative rehabilitation protocol. At 3 months from the index procedure, visual analog scale, range of motion, and University of California at Los Angeles and Constant scores were significantly better in the pulsed electromagnetic fields group than in the placebo group (P<.05). Three patients in the pulsed electromagnetic fields group and 7 patients in the placebo group had mild to moderate capsulitis (P=.2). Severe capsulitis occurred in 1 patient in the pulsed electromagnetic fields group and 2 patients in the placebo group (P=.6). At the last follow-up (minimum, 2 years), clinical and functional outcomes were further improved in both groups, with no significant intergroup differences. Application of pulsed electromagnetic fields after rotator cuff repair is safe and reduces postoperative pain, analgesic use, and stiffness in the short term. At 2 years, no difference was seen in outcomes in patients who did or did not undergo treatment with pulsed electromagnetic fields. Copyright 2015, SLACK Incorporated.
Effects of Preferential Solvation Revealed by Time-Resolved Magnetic Field Effects
2017-01-01
External magnetic fields can impact recombination yields of photoinduced electron transfer reactions by affecting the spin dynamics in transient, spin-correlated radical pair intermediates. For exciplex-forming donor–acceptor systems, this magnetic field effect (MFE) can be investigated sensitively by studying the delayed recombination fluorescence. Here, we investigate the effect of preferential solvation in microheterogeneous solvent mixtures on the radical pair dynamics of the system 9,10-dimethylanthracene (fluorophore)/N,N-dimethylaniline (quencher) by means of time-resolved magnetic field effect (TR-MFE) measurements, wherein the exciplex emission is recorded in the absence and the presence of an external magnetic field using time-correlated single photon counting (TCSPC). In microheterogeneous environments, the MFE of the exciplex emission occurs on a faster time scale than in iso-dielectric homogeneous solvents. In addition, the local polarity reported by the exciplex is enhanced compared to homogeneous solvent mixtures of the same macroscopic permittivity. Detailed analyses of the TR-MFE reveal that the quenching reaction directly yielding the radical ion pair is favored in microheterogeneous environments. This is in stark contrast to homogeneous media, for which the MFE predominantly involves direct formation of the exciplex, its subsequent dissociation to the magneto-sensitive radical pair, and re-encounters. These observations provide evidence for polar microdomains and enhanced caging, which are shown to have a significant impact on the reaction dynamics in microheterogeneous binary solvents. PMID:28263599
Effects of Preferential Solvation Revealed by Time-Resolved Magnetic Field Effects.
Pham, Van Thi Bich; Hoang, Hao Minh; Grampp, Günter; Kattnig, Daniel Rudolf
2017-03-06
External magnetic fields can impact recombination yields of photo-induced electron transfer reactions by affecting the spin dynamics in transient, spin-correlated radical pair intermediates. For exciplex-forming donor-acceptor systems, this magnetic field effect (MFE) can be investigated sensitively by studying the delayed recombination fluorescence. Here, we investigate the effect of preferential solvation in micro-heterogeneous solvent mixtures on the radical pair dynamics of the system 9,10-dimethylanthracene (fluorophore) / N,N-dimethylaniline (quencher) by means of time-resolved magnetic field effect (TR-MFE) measurements, wherein the exciplex emission is recorded in the absence and the presence of an external magnetic field using Time-Correlated Single Photon Counting (TCSPC). In micro-heterogeneous environments, the MFE of the exciplex emission occurs on a faster timescale than in iso-dielectric homogeneous solvents. In addition, the local polarity reported by the exciplex is enhanced compared to homogeneous solvent mixtures of the same macroscopic permittivity. Detailed analyses of the TR-MFE reveal that the quenching reaction directly yielding the radical ion pair is favored in micro-heterogeneous environments. This is in stark contrast to homogeneous media, for which the MFE predominantly involves direct formation of the exciplex, its subsequent dissociation to the magneto-sensitive radical pair, and re-encounters. These observations provide evidence for polar micro-domains and enhanced caging, which are shown to have a significant impact on the reaction dynamics in micro-heterogeneous binary solvents.
Magnetization-driven random-field Ising model at T=0
NASA Astrophysics Data System (ADS)
Illa, Xavier; Rosinberg, Martin-Luc; Shukla, Prabodh; Vives, Eduard
2006-12-01
We study the hysteretic evolution of the random field Ising model at T=0 when the magnetization M is controlled externally and the magnetic field H becomes the output variable. The dynamics is a simple modification of the single-spin-flip dynamics used in the H -driven situation and consists in flipping successively the spins with the largest local field. This allows one to perform a detailed comparison between the microscopic trajectories followed by the system with the two protocols. Simulations are performed on random graphs with connectivity z=4 (Bethe lattice) and on the three-dimensional cubic lattice. The same internal energy U(M) is found with the two protocols when there is no macroscopic avalanche and it does not depend on whether the microscopic states are stable or not. On the Bethe lattice, the energy inside the macroscopic avalanche also coincides with the one that is computed analytically with the H -driven algorithm along the unstable branch of the hysteresis loop. The output field, defined here as ΔU/ΔM , exhibits very large fluctuations with the magnetization and is not self-averaging. The relation to the experimental situation is discussed.
Gaps between avalanches in one-dimensional random-field Ising models
NASA Astrophysics Data System (ADS)
Nampoothiri, Jishnu N.; Ramola, Kabir; Sabhapandit, Sanjib; Chakraborty, Bulbul
2017-09-01
We analyze the statistics of gaps (Δ H ) between successive avalanches in one-dimensional random-field Ising models (RFIMs) in an external field H at zero temperature. In the first part of the paper we study the nearest-neighbor ferromagnetic RFIM. We map the sequence of avalanches in this system to a nonhomogeneous Poisson process with an H -dependent rate ρ (H ) . We use this to analytically compute the distribution of gaps P (Δ H ) between avalanches as the field is increased monotonically from -∞ to +∞ . We show that P (Δ H ) tends to a constant C (R ) as Δ H →0+ , which displays a nontrivial behavior with the strength of disorder R . We verify our predictions with numerical simulations. In the second part of the paper, motivated by avalanche gap distributions in driven disordered amorphous solids, we study a long-range antiferromagnetic RFIM. This model displays a gapped behavior P (Δ H )=0 up to a system size dependent offset value Δ Hoff , and P (Δ H ) ˜(ΔH -Δ Hoff) θ as Δ H →Hoff+ . We perform numerical simulations on this model and determine θ ≈0.95 (5 ) . We also discuss mechanisms which would lead to a nonzero exponent θ for general spin models with quenched random fields.
Stochastic polarized line formation. I. Zeeman propagation matrix in a random magnetic field
NASA Astrophysics Data System (ADS)
Frisch, H.; Sampoorna, M.; Nagendra, K. N.
2005-10-01
This paper considers the effect of a random magnetic field on Zeeman line transfer, assuming that the scales of fluctuations of the random field are much smaller than photon mean free paths associated to the line formation (micro-turbulent limit). The mean absorption and anomalous dispersion coefficients are calculated for random fields with a given mean value, isotropic or anisotropic Gaussian distributions azimuthally invariant about the direction of the mean field. Following Domke & Pavlov (1979, Ap&SS, 66, 47), the averaging process is carried out in a reference frame defined by the direction of the mean field. The main steps are described in detail. They involve the writing of the Zeeman matrix in the polarization matrix representation of the radiation field and a rotation of the line of sight reference frame. Three types of fluctuations are considered : fluctuations along the direction of the mean field, fluctuations perpendicular to the mean field, and isotropic fluctuations. In each case, the averaging method is described in detail and fairly explicit expressions for the mean coefficients are established, most of which were given in Dolginov & Pavlov (1972, Soviet Ast., 16, 450) or Domke & Pavlov (1979, Ap&SS, 66, 47). They include the effect of a microturbulent velocity field with zero mean and a Gaussian distribution. A detailed numerical investigation of the mean coefficients illustrates the two effects of magnetic field fluctuations: broadening of the σ-components by fluctuations of the magnetic field intensity, leaving the π-components unchanged, and averaging over the angular dependence of the π and σ components. For longitudinal fluctuations only the first effect is at play. For isotropic and perpendicular fluctuations, angular averaging can modify the frequency profiles of the mean coefficients quite drastically with the appearance of an unpolarized central component in the diagonal absorption coefficient, even when the mean field is in
NASA Astrophysics Data System (ADS)
Khrennikov, Andrei
2017-02-01
The scientific methodology based on two descriptive levels, ontic (reality as it is) and epistemic (observational), is briefly presented. Following Schrödinger, we point to the possible gap between these two descriptions. Our main aim is to show that, although ontic entities may be unaccessible for observations, they can be useful for clarification of the physical nature of operational epistemic entities. We illustrate this thesis by the concrete example: starting with the concrete ontic model preceding quantum mechanics (the latter is treated as an epistemic model), namely, prequantum classical statistical field theory (PCSFT), we propose the natural physical interpretation for the basic quantum mechanical entity-the quantum state ("wave function"). The correspondence PCSFT ↦ QM is not straightforward, it couples the covariance operators of classical (prequantum) random fields with the quantum density operators. We use this correspondence to clarify the physical meaning of the pure quantum state and the superposition principle-by using the formalism of classical field correlations.
Random source generating far field with elliptical flat-topped beam profile
NASA Astrophysics Data System (ADS)
Zhang, Yongtao; Cai, Yangjian
2014-07-01
Circular and rectangular multi-Gaussian Schell-model (MGSM) sources which generate far fields with circular and rectangular flat-topped beam profiles were introduced just recently (Sahin and Korotkova 2012 Opt. Lett. 37 2970; Korotkova 2014 Opt. Lett. 39 64). In this paper, a random source named an elliptical MGSM source is introduced. An analytical expression for the propagation factor of an elliptical MGSM beam is derived. Furthermore, an analytical propagation formula for an elliptical MGSM beam passing through a stigmatic ABCD optical system is derived, and its propagation properties in free space are studied. It is interesting to find that an elliptical MGSM source generates a far field with an elliptical flat-topped beam profile, being qualitatively different from that of circular and rectangular MGSM sources. The ellipticity and the flatness of the elliptical flat-topped beam profile in the far field are determined by the initial coherence widths and the beam index, respectively.
Heating of a trapped ion by random fields: The influence of the micromotion
NASA Astrophysics Data System (ADS)
Brouard, S.; Plata, J.
2001-04-01
For an ion in a Paul trap, the effect of the micromotion on the heating by stray electric fields is studied analytically. A sequence of unitary transformations, set up from the solutions to the classical dynamics, leads to the exact quantum time propagator for each realization of the random classical field; subsequently, a statistical average is performed to obtain the fidelity of the motional ground state. In this nonperturbative approach, the role of the micromotion in the depopulation is understood as an effective change in the time dependence of the external field and an intrinsic modulation of the heating rate; it is shown that the consequent enhanced complexity of the dynamics can result in a reduction of the heating time.
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).
93Nb NMR of the random-field-dominated relaxor transition in pure and doped SBN
NASA Astrophysics Data System (ADS)
Blinc, R.; Gregorovič, A.; Zalar, B.; Pirc, R.; Seliger, J.; Kleemann, W.; Lushnikov, S. G.; Pankrath, R.
2001-10-01
The ferroelectric relaxor transitions in Sr0.61Ba0.39Nb2O6 (SBN61) and Sr0.61-yCeyBa0.39Nb2O6 (SBN61:Ce y=0.0066) have been studied by quadrupole perturbed 93Nb NMR. The spectra are inhomogeneous frequency distributions f(ν) consisting of a central component due to the 1/2<-->-1/2 transition and a broad background due to the satellite transitions. From the temperature dependence of the width and position of the central component spectrum and from the T dependence of T2 we determined the T dependence of the Edwards-Anderson order parameter and of the normalized spontaneous polarization P. The random bond-random field Ising model parameters are J0=485 K, J=388 K, and Δ/J2=0.14. The random-field contribution Δ~=Δ/J2 is here by two orders of magnitude larger than in the perovskite relaxor PbMg1/3Nb2/3O3 (PMN).
Multi-fidelity modelling via recursive co-kriging and Gaussian-Markov random fields.
Perdikaris, P; Venturi, D; Royset, J O; Karniadakis, G E
2015-07-08
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.
Multi-fidelity modelling via recursive co-kriging and Gaussian–Markov random fields
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
Polynomial chaos representation of spatio-temporal random fields from experimental measurements
Das, Sonjoy Ghanem, Roger Finette, Steven
2009-12-10
Two numerical techniques are proposed to construct a polynomial chaos (PC) representation of an arbitrary second-order random vector. In the first approach, a PC representation is constructed by matching a target joint probability density function (pdf) based on sequential conditioning (a sequence of conditional probability relations) in conjunction with the Rosenblatt transformation. In the second approach, the PC representation is obtained by having recourse to the Rosenblatt transformation and simultaneously matching a set of target marginal pdfs and target Spearman's rank correlation coefficient (SRCC) matrix. Both techniques are applied to model an experimental spatio-temporal data set, exhibiting strong non-stationary and non-Gaussian features. The data consists of a set of oceanographic temperature records obtained from a shallow-water acoustics transmission experiment. The measurement data, observed over a finite denumerable subset of the indexing set of the random process, is treated as a collection of observed samples of a second-order random vector that can be treated as a finite-dimensional approximation of the original random field. A set of properly ordered conditional pdfs, that uniquely characterizes the target joint pdf, in the first approach and a set of target marginal pdfs and a target SRCC matrix, in the second approach, are estimated from available experimental data. Digital realizations sampled from the constructed PC representations based on both schemes capture the observed statistical characteristics of the experimental data with sufficient accuracy. The relative advantages and disadvantages of the two proposed techniques are also highlighted.
Fisher, D S; Le Doussal, P; Monthus, C
2001-12-01
The nonequilibrium dynamics of classical random Ising spin chains with nonconserved magnetization are studied using an asymptotically exact real space renormalization group (RSRG). We focus on random field Ising model (RFIM) spin chains with and without a uniform applied field, as well as on Ising spin glass chains in an applied field. For the RFIM we consider a universal regime where the random field and the temperature are both much smaller than the exchange coupling. In this regime, the Imry-Ma length that sets the scale of the equilibrium correlations is large and the coarsening of domains from random initial conditions (e.g., a quench from high temperature) occurs over a wide range of length scales. The two types of domain walls that occur diffuse in opposite random potentials, of the form studied by Sinai, and domain walls annihilate when they meet. Using the RSRG we compute many universal asymptotic properties of both the nonequilibrium dynamics and the equilibrium limit. We find that the configurations of the domain walls converge rapidly toward a set of system-specific time-dependent positions that are independent of the initial conditions. Thus the behavior of this nonequilibrium system is pseudodeterministic at long times because of the broad distributions of barriers that occur on the long length scales involved. Specifically, we obtain the time dependence of the energy, the magnetization, and the distribution of domain sizes (found to be statistically independent). The equilibrium limits agree with known exact results. We obtain the exact scaling form of the two-point equal time correlation function
Phu, Jack; Khuu, Sieu K.; Nivison-Smith, Lisa; Zangerl, Barbara; Choi, Agnes Yiu Jeung; Jones, Bryan W.; Pfeiffer, Rebecca L.; Marc, Robert E.; Kalloniatis, Michael
2017-01-01
Purpose To determine the locus of test locations that exhibit statistically similar age-related decline in sensitivity to light increments and age-corrected contrast sensitivity isocontours (CSIs) across the central visual field (VF). We compared these CSIs with test point clusters used by the Glaucoma Hemifield Test (GHT). Methods Sixty healthy observers underwent testing on the Humphrey Field Analyzer 30-2 test grid using Goldmann (G) stimulus sizes I-V. Age-correction factors for GI-V were determined using linear regression analysis. Pattern recognition analysis was used to cluster test locations across the VF exhibiting equal age-related sensitivity decline (age-related CSIs), and points of equal age-corrected sensitivity (age-corrected CSIs) for GI-V. Results There was a small but significant test size–dependent sensitivity decline with age, with smaller stimuli declining more rapidly. Age-related decline in sensitivity was more rapid in the periphery. A greater number of unique age-related CSIs was revealed when using smaller stimuli, particularly in the mid-periphery. Cluster analysis of age-corrected sensitivity thresholds revealed unique CSIs for GI-V, with smaller stimuli having a greater number of unique clusters. Zones examined by the GHT consisted of test locations that did not necessarily belong to the same CSI, particularly in the periphery. Conclusions Cluster analysis reveals statistically significant groups of test locations within the 30-2 test grid exhibiting the same age-related decline. CSIs facilitate pooling of sensitivities to reduce the variability of individual test locations. These CSIs could guide future structure-function and alternate hemifield asymmetry analyses by comparing matched areas of similar sensitivity signatures. PMID:28973333
The random energy model in a magnetic field and joint source channel coding
NASA Astrophysics Data System (ADS)
Merhav, Neri
2008-09-01
We demonstrate that there is an intimate relationship between the magnetic properties of Derrida’s random energy model (REM) of spin glasses and the problem of joint source-channel coding in Information Theory. In particular, typical patterns of erroneously decoded messages in the coding problem have “magnetization” properties that are analogous to those of the REM in certain phases, where the non-uniformity of the distribution of the source in the coding problem plays the role of an external magnetic field applied to the REM. We also relate the ensemble performance (random coding exponents) of joint source-channel codes to the free energy of the REM in its different phases.
Zouhar, Alexander; Baloch, Sajjad; Tsin, Yanghai; Fang, Tong; Fuchs, Siegfried
2010-01-01
We address the problem of 3-D Mesh segmentation for categories of objects with known part structure. Part labels are derived from a semantic interpretation of non-overlapping subsurfaces. Our approach models the label distribution using a Conditional Random Field (CRF) that imposes constraints on the relative spatial arrangement of neighboring labels, thereby ensuring semantic consistency. To this end, each label variable is associated with a rich shape descriptor that is intrinsic to the surface. Randomized decision trees and cross validation are employed for learning the model, which is eventually applied using graph cuts. The method is flexible enough for segmenting even geometrically less structured regions and is robust to local and global shape variations.
Luo, Zhihui; Johnson, Stephen B; Lai, Albert M; Weng, Chunhua
2011-01-01
Temporal constraints are present in 38% of clinical research eligibility criteria and are crucial for screening patients. However, eligibility criteria are often written as free text, which is not amenable for computer processing. In this paper, we present an ontology-based approach to extracting temporal information from clinical research eligibility criteria. We generated temporal labels using a frame-based temporal ontology. We manually annotated 150 free-text eligibility criteria using the temporal labels and trained a parser using Conditional Random Fields (CRFs) to automatically extract temporal expressions from eligibility criteria. An evaluation of an additional 60 randomly selected eligibility criteria using manual review achieved an overall precision of 83%, a recall of 79%, and an F-score of 80%. We illustrate the application of temporal extraction with the use cases of question answering and free-text criteria querying.
Combination of fractional Brownian random field and lacunarity for iris recognition
NASA Astrophysics Data System (ADS)
Liu, Kai; Zhou, Weidong; Wang, Yu
2011-10-01
Feature extraction plays a vital role in iris recognition, affecting the performance of iris recognition algorithm strongly. In this paper, we present an individual recognition algorithm using fractal dimension based on fractional Brownian random field and lacunarity in feature extraction. Making use of the fractal feature of iris, such as self-similarity and random patterns, fractal dimension can extract texture information effectively. Lacunarity overcomes the limitation of fractal dimension that fractal sets with different textures may share the same fractal dimension value. The combination of fractal dimension and lacunarity makes the feature extraction more comprehensive and distinguishable. The experimental results show that this recognition algorithm can obtain great performance on CASIA 1.0 iris database
Submicron structure random field on granular soil material with retinex algorithm optimization
NASA Astrophysics Data System (ADS)
Liang, Yu; Tao, Chenyuan; Zhou, Bingcheng; Huang, Shuai; Huang, Linchong
2017-06-01
In this paper, a Retinex scale optimized image enhancement algorithm is proposed, which can enhance the micro vision image and eliminate the influence of the uneven illumination. Based on that, a random geometric model of the microstructure of granular materials is established with Monte-Carlo method, the numerical simulation including consolidation process of granular materials is compared with the experimental data. The results have proved that the random field method with Retinex image enhancement algorithm is effective, the image of microstructure of granular materials becomes clear and the contrast ratio is improved, after using Retinex image enhancement algorithm to enhance the CT image. The fidelity of enhanced image is higher than that dealing with other method, which have explained that the algorithm can preserve the microstructure information of the image well. The result of numerical simulation is similar with the one obtained from conventional three axis consolidation test, which proves that the simulation result is reliable.
Spin pair geometry revealed by high-field DEER in the presence of conformational distributions
NASA Astrophysics Data System (ADS)
Polyhach, Ye.; Godt, A.; Bauer, C.; Jeschke, G.
2007-03-01
Orientation selection on two nitroxide-labelled shape-persistent molecules is demonstrated by high-field pulsed electron-electron double resonance experiments at a frequency of 95 GHz with a commercial spectrometer. The experiments are performed with fixed observer and pump frequencies by variation of the magnetic field, so that the variation of both the dipolar frequencies and the modulation depths can be analyzed. By applying the deadtime-free four-pulse double electron-electron resonance (DEER) sequence, the lineshapes of the dipolar spectra are obtained. In the investigated linear biradical and equilateral triradical the nitroxide labels undergo restricted dynamics, so that their relative orientations are not fixed, but are correlated to some extent. In this situation, the general dependence of the dipolar spectra on the observer field can be satisfyingly modelled by simple geometrical models that involve only one rotational degree of freedom for the biradical and two rotational degrees of freedom for the triradical. A somewhat better agreement of the dipolar lineshapes for the biradical is obtained by simulations based on a molecular dynamics trajectory. For the triradical, small but significant deviations of the lineshape are observed with both models, indicating that the technique can reveal deficiencies in modelling of the conformational ensemble of a macromolecule.
Spatiotemporal receptive fields of barrel cortex revealed by reverse correlation of synaptic input.
Ramirez, Alejandro; Pnevmatikakis, Eftychios A; Merel, Josh; Paninski, Liam; Miller, Kenneth D; Bruno, Randy M
2014-06-01
Of all of the sensory areas, barrel cortex is among the best understood in terms of circuitry, yet least understood in terms of sensory function. We combined intracellular recording in rats with a multi-directional, multi-whisker stimulator system to estimate receptive fields by reverse correlation of stimuli to synaptic inputs. Spatiotemporal receptive fields were identified orders of magnitude faster than by conventional spike-based approaches, even for neurons with little spiking activity. Given a suitable stimulus representation, a linear model captured the stimulus-response relationship for all neurons with high accuracy. In contrast with conventional single-whisker stimuli, complex stimuli revealed markedly sharpened receptive fields, largely as a result of adaptation. This phenomenon allowed the surround to facilitate rather than to suppress responses to the principal whisker. Optimized stimuli enhanced firing in layers 4-6, but not in layers 2/3, which remained sparsely active. Surround facilitation through adaptation may be required for discriminating complex shapes and textures during natural sensing.
Aging and random-field magnetism in ferromagnet/antiferromagnet bilayers
NASA Astrophysics Data System (ADS)
Ma, Tianyu; Freeman, Ryan; Cheng, Xiang; Boettcher, Stefan; Urazhdin, Sergei
Exchange interaction at the interface between a ferromagnet (F) and an antiferromagnet (AF) results in a random effective exchange field acting on both F and AF, which can produce complex equilibrium and dynamical states. We utilized anisotropic magnetoresistance to look for signatures of such states in epitaxial Py =Permalloy/Fe50Mn50 and polycrystalline CoO/Py bilayers. For thin AF layers, both systems exhibit slow cooperative aging indicative of a complex glassy state. Aging follows the same small power-law or logarithmic dependence and is observed over a wide range of temperatures and fields, suggesting a universal aging mechanism. Glassy relaxation is not observed at any temperature for AF thickness above 3.5nm. We argue that these observations are inconsistent with the usual ``granular'' and ``domain-state'' models of F/AF systems. We discuss the implications of our results for the random field magnetism, and the relationship between the dimensionality and the topological properties of magnetic systems. Supported by NSF DMR-1504449.
Certified randomness from a two-level system in a relativistic quantum field
NASA Astrophysics Data System (ADS)
Thinh, Le Phuc; Bancal, Jean-Daniel; Martín-Martínez, Eduardo
2016-08-01
Randomness is an indispensable resource in modern science and information technology. Fortunately, an experimentally simple procedure exists to generate randomness with well-characterized devices: measuring a quantum system in a basis complementary to its preparation. Towards realizing this goal one may consider using atoms or superconducting qubits, promising candidates for quantum information processing. However, their unavoidable interaction with the electromagnetic field affects their dynamics. At large time scales, this can result in decoherence. Smaller time scales in principle avoid this problem, but may not be well analyzed under the usual rotating wave and single mode approximation (RWA and SMA) which break the relativistic nature of quantum field theory. Here, we use a fully relativistic analysis to quantify the information that an adversary with access to the field could get on the result of an atomic measurement. Surprisingly, we find that the adversary's guessing probability is not minimized for atoms initially prepared in the ground state (an intuition derived from the RWA and SMA model).
Crokidakis, Nuno; Nobre, Fernando D
2008-04-01
The effects of random magnetic fields are considered in an Ising spin-glass model defined in the limit of infinite-range interactions. The probability distribution for the random magnetic fields is a double Gaussian, which consists of two Gaussian distributions centered, respectively, at +H0 and -H0, presenting the same width sigma . It is argued that such a distribution is more appropriate for a theoretical description of real systems than its simpler particular two well-known limits, namely, the single Gaussian distribution (sigma>H0) and the bimodal one (sigma=0) . The model is investigated by means of the replica method, and phase diagrams are obtained within the replica-symmetric solution. Critical frontiers exhibiting tricritical points occur for different values of sigma , with the possibility of two tricritical points along the same critical frontier. To our knowledge, it is the first time that such a behavior is verified for a spin-glass model in the presence of a continuous-distribution random field, which represents a typical situation of a real system. The stability of the replica-symmetric solution is analyzed, and the usual Almeida-Thouless instability is verified for low temperatures. It is verified that the higher-temperature tricritical point always appears in the region of stability of the replica-symmetric solution; a condition involving the parameters H0 and sigma , for the occurrence of this tricritical point only, is obtained analytically. Some of our results are discussed in view of experimental measurements available in the literature.
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
NASA Astrophysics Data System (ADS)
Gustavsson, Magnus; Kristensson, Gerhard; Wellander, Niklas
2016-12-01
A numerical implementation of a method to analyze scattering by randomly located obstacles in a slab geometry is presented. In general, the obstacles can be of arbitrary shape, but, in this first implementation, the obstacles are dielectric spheres. The coherent part of the reflected and transmitted intensity at normal incidence is treated. Excellent agreement with numerical results found in the literature of the effective wave number is obtained. Moreover, comparisons with the results of the Bouguer-Beer (B-B) law are made. The present theory also gives a small reflected coherent field, which is not predicted by the Bouguer-Beer law, and these results are discussed in some detail.
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
Reduced Wiener Chaos representation of random fields via basis adaptation and projection
NASA Astrophysics Data System (ADS)
Tsilifis, Panagiotis; Ghanem, Roger G.
2017-07-01
A new characterization of random fields appearing in physical models is presented that is based on their well-known Homogeneous Chaos expansions. We take advantage of the adaptation capabilities of these expansions where the core idea is to rotate the basis of the underlying Gaussian Hilbert space, in order to achieve reduced functional representations that concentrate the induced probability measure in a lower dimensional subspace. For a smooth family of rotations along the domain of interest, the uncorrelated Gaussian inputs are transformed into a Gaussian process, thus introducing a mesoscale that captures intermediate characteristics of the quantity of interest.
Conditional Random Field-Based Offline Map Matching for Indoor Environments
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
NASA Technical Reports Server (NTRS)
Kaiser, T. B.; Jones, F. C.; Birmingham, T. J.
1972-01-01
The problem of deriving a kinetic equation for the cosmic ray distribution function in a random magnetic field is considered. A model is adopted which is mathematically simple but which contains the essential physics. The perturbation expansion upon which the quasi-linear treatment is based is investigated. The existence of resonant particles causes the breakdown of the adiabatic approximation frequently used in this theory. Resonant particles cause a general secular growth of higher order terms in the expansion which invalidates the entire perturbative approach.
Conditional Random Field-Based Offline Map Matching for Indoor Environments.
Bataineh, Safaa; Bahillo, Alfonso; Díez, Luis Enrique; Onieva, Enrique; Bataineh, Ikram
2016-08-16
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.
Theory of Distribution Estimation of Hyperparameters in Markov Random Field Models
NASA Astrophysics Data System (ADS)
Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato
2016-06-01
We investigated the performance of distribution estimation of hyperparameters in Markov random field models proposed by Nakanishi-Ohno et al., http://doi.org/10.1088/1751-8113/47/4/045001, J. Phys. A 47, 045001 (2014) when used to evaluate the confidence of data. We analytically calculated the configurational average, with respect to data, of the negative logarithm of the posterior distribution, which is called free energy based on an analogy with statistical mechanics. This configurational average of free energy shrinks as the amount of data increases. Our results theoretically confirm the numerical results from that previous study.
Scalable data parallel algorithms for texture synthesis using Gibbs random fields.
Bader, D A; Jaja, J; Chellappa, R
1995-01-01
This article introduces scalable data parallel algorithms for image processing. Focusing on Gibbs and Markov random field model representation for textures, we present parallel algorithms for texture synthesis, compression, and maximum likelihood parameter estimation, currently implemented on Thinking Machines CM-2 and CM-5. The use of fine-grained, data parallel processing techniques yields real-time algorithms for texture synthesis and compression that are substantially faster than the previously known sequential implementations. Although current implementations are on Connection Machines, the methodology presented enables machine-independent scalable algorithms for a number of problems in image processing and analysis.
Light absorption in disordered semiconductors with a random coulomb-type field
Arbuzov, Yu.D.; Evdokimov, V.M.; Kolenkin, M.Yu.
1988-07-01
A method is proposed for the formulation of an asymptotic series for the light absorption coefficient in disordered semiconductors with a random field of the Coulomb type. It is shown that the series is obtained by expanding the exponent of an exponential function in powers of a parameter proportional to (E/sub g/ /minus/ /Dirac h//omega/)/sup /minus/1/3/, where E/sub g/ is the band gap of the semiconductor, and /Dirac-H//omega/ is the photon energy. The first three terms of the series are calculated in explicit form.
Sharp Trapping Boundaries in the Random Walk of Interplanetary Magnetic Field Lines
NASA Astrophysics Data System (ADS)
Ruffolo, D.; Chuychai, P.; Meechai, J.; Pongkitiwanichkul, P.; Kimpraphan, N.; Matthaeus, W. H.; Rowlands, G.
2004-05-01
Although magnetic field lines in space are believed to undergo a diffusive random walk in the long-distance limit, observed dropouts of solar energetic particles, as well as computer simulations, indicate sharply defined filaments in which interplanetary magnetic field lines have been temporarily trapped. We identify mechanisms that can explain such sharp boundaries in the framework of 2D+slab turbulence, a model that provides a good explanation of solar wind turbulence spectra and the parallel transport of solar energetic particles. Local trapping boundaries (LTBs) are empirically defined as trajectories of 2D turbulence where the mean 2D field is a local maximum. In computer simulations, the filaments (or ``islands'' in the two dimensions perpendicular to the mean field) that are most resistant to slab diffusion correspond closely to the mathematically defined LTBs, that is, there is a mathematical prescription for defining the trapping regions. Furthermore, we provide computational evidence and a theoretical explanation that strong 2D turbulence can inhibit diffusion due to the slab component. Therefore, while these filaments are basically defined by the small-scale topology of 2D turbulence, there can be sharp trapping boundaries where the 2D field is strongest. This work was supported by the Thailand Research Fund, the Rachadapisek Sompoj Fund of Chulalongkorn University, and NASA Grant NAG5-11603. G.R. thanks Mahidol University for its hospitality and the Thailand Commission for Higher Education for travel support.
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.
Glassy phases and driven response of the phase-field-crystal model with random pinning.
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.
The diffusive idealization of charged particle transport in random magnetic fields
NASA Technical Reports Server (NTRS)
Earl, J. A.
1974-01-01
The transport of charged particles diffusing in a random magnetic field parallel to a relatively large guiding field is presented. The same coefficient of diffusion is obtained by three methods. Two corrections must be added to the expression in which the diffusive flux is proportional to the gradient of the density. Explicit expressions are given for a characteristic time and a characteristic length which describe the corrections. The well known divergence of the coefficient of diffusion, which is implied by the quasilinear analysis of pitch angle scattering, does not occur if the scattering rate is finite at 90 deg pitch angle. This effect is illustrated by formulas which give the coefficient of diffusion when the quasilinear expression is perturbed by a variable amount of isotropic scattering.
Mixture model and Markov random field-based remote sensing image unsupervised clustering method
NASA Astrophysics Data System (ADS)
Hou, Y.; Yang, Y.; Rao, N.; Lun, X.; Lan, J.
2011-03-01
In this paper, a novel method for remote sensing image clustering based on mixture model and Markov random field (MRF) is proposed. A remote sensing image can be considered as Gaussian mixture model. The image clustering result corresponding to the image label field is a MRF. So, the image clustering procedure is transformed to a maximum a posterior (MAP) problem by Bayesian theorem. The intensity difference and the spatial distance between the two pixels in the same clique are introduced into the traditional MRF potential function. The iterative conditional model (ICM) is employed to find the solution of MAP. We use the max entropy criterion to choose the optimal clustering number. In the experiments, the method is compared with the traditional MRF clustering method using ICM and simulated annealing (SA). The results show that this method is better than the traditional MRF model both in noise filtering and miss-classification ratio.
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.
Markov random field and Gaussian mixture for segmented MRI-based partial volume correction in PET
NASA Astrophysics Data System (ADS)
Bousse, Alexandre; Pedemonte, Stefano; Thomas, Benjamin A.; Erlandsson, Kjell; Ourselin, Sébastien; Arridge, Simon; Hutton, Brian F.
2012-10-01
In this paper we propose a segmented magnetic resonance imaging (MRI) prior-based maximum penalized likelihood deconvolution technique for positron emission tomography (PET) images. The model assumes the existence of activity classes that behave like a hidden Markov random field (MRF) driven by the segmented MRI. We utilize a mean field approximation to compute the likelihood of the MRF. We tested our method on both simulated and clinical data (brain PET) and compared our results with PET images corrected with the re-blurred Van Cittert (VC) algorithm, the simplified Guven (SG) algorithm and the region-based voxel-wise (RBV) technique. We demonstrated our algorithm outperforms the VC algorithm and outperforms SG and RBV corrections when the segmented MRI is inconsistent (e.g. mis-segmentation, lesions, etc) with the PET image.
3D Mesh Segmentation Based on Markov Random Fields and Graph Cuts
NASA Astrophysics Data System (ADS)
Shi, Zhenfeng; Le, Dan; Yu, Liyang; Niu, Xiamu
3D Mesh segmentation has become an important research field in computer graphics during the past few decades. Many geometry based and semantic oriented approaches for 3D mesh segmentation has been presented. However, only a few algorithms based on Markov Random Field (MRF) has been presented for 3D object segmentation. In this letter, we present a definition of mesh segmentation according to the labeling problem. Inspired by the capability of MRF combining the geometric information and the topology information of a 3D mesh, we propose a novel 3D mesh segmentation model based on MRF and Graph Cuts. Experimental results show that our MRF-based schema achieves an effective segmentation.
Comment on "Diffusion by a random velocity field" [Phys. Fluids 13, 22 (1970)
NASA Astrophysics Data System (ADS)
Saad, Tony; Sutherland, James C.
2016-11-01
This comment aims at addressing a mass conservation issue in a paper published in the physics of fluids. The paper [R. H. Kraichnan, "Diffusion by a random velocity field," Phys. Fluids 13(1), 22 (1970)] introduces a novel method to generate synthetic isotropic turbulence for computational purposes. The method has been used in the literature to generate inlet boundary conditions and to model aeroacoustic noise as well as for validation and verification purposes. However, the technique uses a continuous formulation to derive the mass conservation constraint. In this comment, we argue that the continuous constraint is invalid on a discrete grid and provide an alternative derivation using the discrete divergence. In addition, we present an analysis to quantify the impact of a pressure projection on the kinetic energy of a non-solenoidal velocity field.
Magnetic field line random walk in two-dimensional dynamical turbulence
NASA Astrophysics Data System (ADS)
Wang, J. F.; Qin, G.; Ma, Q. M.; Song, T.; Yuan, S. B.
2017-08-01
The field line random walk (FLRW) of magnetic turbulence is one of the important topics in plasma physics and astrophysics. In this article, by using the field line tracing method, the mean square displacement (MSD) of FLRW is calculated on all possible length scales for pure two-dimensional turbulence with the damping dynamical model. We demonstrate that in order to describe FLRW with the damping dynamical model, a new dimensionless quantity R is needed to be introduced. On different length scales, dimensionless MSD shows different relationships with the dimensionless quantity R. Although the temporal effect affects the MSD of FLRW and even changes regimes of FLRW, it does not affect the relationship between the dimensionless MSD and dimensionless quantity R on all possible length scales.
An exact solution of solute transport by one-dimensional random velocity fields
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.
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.
Duarte Queirós, Sílvio M; Crokidakis, Nuno; Soares-Pinto, Diogo O
2009-07-01
The influence of the tail features of the local magnetic field probability density function (PDF) on the ferromagnetic Ising model is studied in the limit of infinite range interactions. Specifically, we assign a quenched random field whose value is in accordance with a generic distribution that bears platykurtic and leptokurtic distributions depending on a single parameter tau<3 to each site. For tau<5/3, such distributions, which are basically Student-t and r distribution extended for all plausible real degrees of freedom, present a finite standard deviation, if not the distribution has got the same asymptotic power-law behavior as a alpha-stable Lévy distribution with alpha=(3-tau)/(tau-1). For every value of tau, at specific temperature and width of the distribution, the system undergoes a continuous phase transition. Strikingly, we impart the emergence of an inflexion point in the temperature-PDF width phase diagrams for distributions broader than the Cauchy-Lorentz (tau=2) which is accompanied with a divergent free energy per spin (at zero temperature).
NASA Astrophysics Data System (ADS)
Bohleber, Pascal; Sold, Leo; Hardy, Douglas R.; Schwikowski, Margit; Klenk, Patrick; Fischer, Andrea; Sirguey, Pascal; Cullen, Nicolas J.; Potocki, Mariusz; Hoffmann, Helene; Mayewski, Paul
2017-02-01
Although its Holocene glacier history is still subject to debate, the ongoing iconic decline of Kilimanjaro's largest remaining ice body, the Northern Ice Field (NIF), has been documented extensively based on surface and photogrammetric measurements. The study presented here adds, for the first time, ground-penetrating radar (GPR) data at centre frequencies of 100 and 200 MHz to investigate bed topography, ice thickness and internal stratigraphy at NIF. The direct comparison of the GPR signal to the visible glacier stratigraphy at NIF's vertical walls is used to validate ice thickness and reveals that the major internal reflections seen by GPR can be associated with dust layers. Internal reflections can be traced consistently within our 200 MHz profiles, indicating an uninterrupted, spatially coherent internal layering within NIF's central flat area. We show that, at least for the upper 30 m, it is possible to follow isochrone layers between two former NIF ice core drilling sites and a sampling site on NIF's vertical wall. As a result, these isochrone layers provide constraints for future attempts at linking age-depth information obtained from multiple locations at NIF. The GPR profiles reveal an ice thickness ranging between (6.1 ± 0.5) and (53.5 ± 1.0) m. Combining these data with a very high resolution digital elevation model we spatially extrapolate ice thickness and give an estimate of the total ice volume remaining at NIF's southern portion as (12.0 ± 0.3) × 106 m3.
Hidden Markov models revealing the stress field underlying the earthquake generation
NASA Astrophysics Data System (ADS)
Votsi, I.; Limnios, N.; Tsaklidis, G.; Papadimitriou, E.
2013-07-01
The application of the hidden Markov models (HMMs) is attempted for revealing key features for the earthquake generation which are not accessible to direct observation. Considering that the states of the HMM correspond to levels of the stress field, our objective is to identify these states. The observations are considered after grouping earthquake magnitudes and the cases of different number of states are examined. The problems of HMMs theory are solved and the ensuing HMMs are compared on the basis of Akaike and Bayesian information criteria. A new insight on the evaluation of future seismic hazard is given by calculating the mean number of steps for the first visit to a particular state, along with the respective variance. We further calculate an estimator of the mean number of steps for the first visit to a particular state and we construct its confidence interval. Additionally, a second approach to the problem is followed by assuming a different determination of observations. The HMMs applied to both approaches, contribute significantly to seismic hazard assessment via revealing the number of the stress levels as well as the way in which these levels are associated with certain earthquake occurrence.
Yokoyama, Sho; Matsui, Tsubasa S; Deguchi, Shinji
2017-01-22
Physical forces play crucial roles in coordinating collective migration of epithelial cells, but details of such force-related phenomena remain unclear partly due to the lack of robust methodologies to probe the underlying force fields. Here we develop a method for fabricating silicone substrates that detect cellular traction forces with a high sensitivity. Specifically, a silicone elastomer is exposed to oxygen plasma under heating. Removal of the heat shrinks the substrate so as to reduce its critical buckling strain in a spatially uniform manner. Thus, even small cellular traction forces can be visualized as micro-wrinkles that are reversibly emerged on the substrate in a direction orthogonal to the applied forces. Using this technique, we show that so-called leader cells in MDCK-II cell clusters exert significant magnitudes of traction forces distinct from those of follower cells. We reveal that the direction of traction forces is highly correlated with the long axis of the local, individual cells within clusters. These results suggest that the force fields in collective migration of MDCK-II cells are predominantly determined locally at individual cell scale rather than globally at the whole cell cluster scale. Copyright © 2016 Elsevier Inc. All rights reserved.
GENERAL: Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure
NASA Astrophysics Data System (ADS)
Yang, Xu-Hua; Sun, Bao; Wang, Bo; Sun, You-Xian
2010-04-01
Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks (BTNs) evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper.
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
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.
Taylor, Marcus K; Stanfill, Katherine E; Padilla, Genieleah A; Markham, Amanda E; Ward, Michael D; Koehler, Matthew M; Anglero, Antonio; Adams, Barry D
2011-12-01
In this randomized, controlled field study, we examined the effects of a brief psychological skills training (PST) intervention on stress responses during military survival school. A second purpose was to build upon prior research in this unique environment by extending the follow-up window to 3 months. Baseline subjective distress (dissociative) symptoms were measured in 65 male military subjects, who were then randomized either to PST or a control group that received no training beyond the normal survival school curriculum. PST received training in arousal control, mental imagery, goal setting, and positive self-talk in two separate 40-minute sessions before stressful field exercises. Stress symptoms were then assessed during a mock-captivity phase of training, as well as 24 hours, 1 month, and 3 months after completion of training. Repeated-measures analyses of variance with follow-up paired t tests examined differences between groups and across time. Survival training precipitated remarkable increases in subjective distress, but few substantive group differences emerged. This study extends prior work quantifying the human stress response to intense military training.
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.
NASA Astrophysics Data System (ADS)
da Silva, W. P.; de Arruda, P. H. Z.; Tunes, T. M.; Godoy, M.; de Arruda, A. S.
2017-01-01
We have studied the effects of the random single-ion anisotropy and random magnetic field in the phase diagram and in the thermodynamic properties of the spin-3/2 Blume-Capel model via Curie-Weiss mean-field approximation. The phase diagrams were built in the planes temperature versus single-ion anisotropy, temperature versus magnetic field, temperature versus random parameters and the dependencies of magnetization were plotted versus temperature and single-ion anisotropy. These diagrams show that, in the space (D / J - T / J) , the type (first- or second-order) of the phase transition between the ferromagnetic and paramagnetic phases is dependent on the random parameters. Therefore, within these conditions the model presents tricritical behavior. For large values, and a certain critical value of the random parameters, the phase transition is only of second-order, but it is of first-order within the ordered phase, between the phase with m = 1 / 2 and m = 3 / 2 , which ends in a terminal critical point.
Geiger, D.; Girosi, F.
1989-05-01
In recent years many researchers have investigated the use of Markov random fields (MRFs) for computer vision. They can be applied for example in the output of the visual processes to reconstruct surfaces from sparse and noisy depth data, or to integrate early vision processes to label physical discontinuities. Drawbacks of MRFs models have been the computational complexity of the implementation and the difficulty in estimating the parameters of the model. This paper derives deterministic approximations to MRFs models. One of the considered models is shown to give in a natural way the graduate non convexity (GNC) algorithm. This model can be applied to smooth a field preserving its discontinuities. A new model is then proposed: it allows the gradient of the field to be enhanced at the discontinuities and smoothed elsewhere. All the theoretical results are obtained in the framework of the mean field theory, that is a well known statistical mechanics technique. A fast, parallel, and iterative algorithm to solve the deterministic equations of the two models is presented, together with experiments on synthetic and real images. The algorithm is applied to the problem of surface reconstruction is in the case of sparse data. A fast algorithm is also described that solves the problem of aligning the discontinuities of different visual models with intensity edges via integration.
The effect of convection upon charged particle transport in random magnetic fields
NASA Technical Reports Server (NTRS)
Earl, J. A.
1984-01-01
In a coordinate system moving with the plasma and random magnetic fields of a wind that blows with constant velocity in the direction of the guiding field, transport of energetic particles is described by a Boltzmann equation which is similar to the one that describes unconvected transport. Although this formulation is mathematically identical to that developed by Luhmann, which refers to the system where the guiding field is static, there are both practical and fundamental reasons to adopt the new approach. It leads to first-order approximate transport equations which are similar to those that apply in the absence of convection. However, these equations are more general than Parker's description of diffusion and convection, for they describe the coherent modes of transport that appear when the mean free path is large compared to the scale length for spatial variations of the guiding field, and they are valid for arbitrary wind velocity. The latter characteristic opens up new possibilities for analyzing particle transport in relativistic flows seen in some astronomical objects.
Local Autoencoding for Parameter Estimation in a Hidden Potts-Markov Random Field.
Song, Sanming; Si, Bailu; Herrmann, J Michael; Feng, Xisheng
2016-03-22
A local-autoencoding (LAE) method is proposed for the parameter estimation in a Hidden Potts-Markov random field (MRF) model. Due to sampling cost, Markov chain Monte Carlo (MCMC) 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 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 pseudo-likelihood (MPL) 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.
Local Autoencoding for Parameter Estimation in a Hidden Potts-Markov Random Field.
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.
Spin dynamics of polarons and polaron pairs in a random hyperfine field
NASA Astrophysics Data System (ADS)
Roundy, Robert C.
Spin-dependent recombination of polaron pairs and spin relaxation of a single polaron are the most fundamental processes are responsible for the performance of organic spintronics-based devices such as light-emitting diodes and organic spin valves. In organic materials, with no spin-orbit coupling, both processes are due to random hyperfine fields created by protons neighboring the polaron sites. The essence of spin-dependent recombination is that in order to recombine the pair must be in the singlet state. Hyperfine fields acting on the electron and hole govern the spin-dynamics of localized pairs during the waiting time for recombination. We demonstrate that for certain domain of trapping configurations of hyperfine fields, crossover to the singlet state is quenched. This leads to the blocking of current. The phenomenon of organic magnetoresistance (OMAR) is described by counting the weights of trapping configurations as a function of magnetic field. This explains the universality of the lineshapes of the OMAR curves. In finite samples incomplete averaging over the hyperfine fields gives rise to mesoscopic fluctuations of the current response. We also demonstrate that under the condition of magnetic resonance, new trapping configurations emerge. This leads to nontrivial evolution of current through the sample with microwave power. When discussing spin-relaxation two questions can be asked: (a) How does the local spin polarization decay as a function of distance from the spin-polarized injector? (b) How does the injected spin decay as a function of time after spatial averaging? With regard to (a), we demonstrate that, while decaying exponentially on average, local spin-polarization exhibits giant fluctuations from point to point. Concerning (b), we find that for a spin-carrier which moves diffusively in low dimensions the decay is faster than a simple exponent. The underlying physics for both findings is that in describing spin evolution it is necessary to add up
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.
Pacheco, A B; Guth, B E; Soares, K C; Nishimura, L; de Almeida, D F; Ferreira, L C
1997-01-01
The genetic diversity of 47 enterotoxigenic Escherichia coli (ETEC) strains of serotypes O6:H16, O27:H7, O29:H21, O128ac:H12, and O153:H45, previously isolated from diarrheic patients in Brazil over a period of 15 years, was investigated by random amplification of polymorphic DNA (RAPD). Informative band arrays were obtained with three 10-mer primers with G+C contents of 50, 60, and 70%. Based on the combination of the band profiles generated by the three primers 22 RAPD types were detected, and 5 major clonal clusters, each one with at least 80% identical bands, were established. The clonal clusters corresponded to strains having the same serotype which, in most cases, also had the same virulence factors (colonization factors and toxin types) and outer membrane protein and lipopolysaccharide sodium dodecyl sulfate-polyacrylamide gel electrophoresis profiles. The results suggested a correlation between phenotypic properties and genetic relatedness of ETEC isolates of human origin and indicated that a reduced number of clonally related strains are found in areas of ETEC endemicity in Brazil. Moreover, the RAPD technique revealed intraserotype-specific variations, undetectable by the combination of several phenotypic typing methods, among the ETEC strains analyzed. These results show that RAPD typing represents a useful tool for population genetics as well as for epidemiological studies of ETEC. PMID:9163473
Auge, H; Neuffer, B; Erlinghagen, F; Grupe, R; Brandl, R
2001-07-01
We performed demographic and molecular investigations on woodland populations of the clonal herb Viola riviniana in central Germany. We investigated the pattern of seedling recruitment, the amount of genotypic (clonal) variation and the partitioning of genetic variation among and within populations. Our demographic study was carried out in six violet populations of different ages and habitat conditions. It revealed that repeated seedling recruitment takes place in all of these populations, and that clonal propagation is accompanied by high ramet mortality. Our molecular investigations were performed on a subset of three of these six violet populations. Random amplified polymorphic DNA analyses using six primers yielded 45 scorable bands that were used to identify multilocus genotypes, i.e. putative clones. Consistent with our demographic results and independent of population age, we found a large genotypic diversity with a mean proportion of distinguishable genotypes of 0.93 and a mean Simpson's diversity index of 0.99. Using AMOVA we found a strong genetic differentiation among these violet populations with a PhiST value of 0.41. We suggest that a high selfing rate, limited gene flow due to short seed dispersal distances and drift due to founder effects are responsible for this pattern. Although Viola riviniana is a clonal plant, traits associated with sexual reproduction rather than clonality per se are moulding the pattern of genetic variation in this species.
Lencina, K H; Konzen, E R; Tsai, S M; Bisognin, D A
2016-12-19
Apuleia leiocarpa (Vogel) J.F. MacBride is a hardwood species native to South America, which is at serious risk of extinction. Therefore, it is of prime importance to examine the genetic diversity of this species, information required for developing conservation, sustainable management, and breeding strategies. Although scarcely used in recent years, random amplified polymorphic DNA markers are useful resources for the analysis of genetic diversity and structure of tree species. This study represents the first genetic analysis based on DNA markers in A. leiocarpa that aimed to investigate the levels of polymorphism and to select markers for the precise characterization of its genetic structure. We adapted the original DNA extraction protocol based on cetyltrimethyl ammonium bromide, and describe a simple procedure that can be used to obtain high-quality samples from leaf tissues of this tree. Eighteen primers were selected, revealing 92 bands, from which 75 were polymorphic and 61 were sufficient to represent the overall genetic structure of the population without compromising the precision of the analysis. Some fragments were conserved among individuals, which can be sequenced and used to analyze nucleotide diversity parameters through a wider set of A. leiocarpa individuals and populations. The individuals were separated into 11 distinct groups with variable levels of genetic diversity, which is important for selecting desirable genotypes and for the development of a conservation and sustainable management program. Our results are of prime importance for further investigations concerning the genetic characterization of this important, but vulnerable species.
NASA Astrophysics Data System (ADS)
Wen, J.-J.; Koohpayeh, S. M.; Ross, K. A.; Trump, B. A.; McQueen, T. M.; Kimura, K.; Nakatsuji, S.; Qiu, Y.; Pajerowski, D. M.; Copley, J. R. D.; Broholm, C. L.
2017-03-01
Inelastic neutron scattering reveals a broad continuum of excitations in Pr2Zr2O7, the temperature and magnetic field dependence of which indicate a continuous distribution of quenched transverse fields (Δ ) acting on the non-Kramers Pr3 + crystal field ground state doublets. Spin-ice correlations are apparent within 0.2 meV of the Zeeman energy. A random phase approximation provides an excellent account of the data with a transverse field distribution ρ (Δ )∝(Δ2+Γ2)-1 , where Γ =0.27 (1 ) meV . Established during high temperature synthesis due to an underlying structural instability, it appears disorder in Pr2Zr2O7 actually induces a quantum spin liquid.
Wen, J-J; Koohpayeh, S M; Ross, K A; Trump, B A; McQueen, T M; Kimura, K; Nakatsuji, S; Qiu, Y; Pajerowski, D M; Copley, J R D; Broholm, C L
2017-03-10
Inelastic neutron scattering reveals a broad continuum of excitations in Pr_{2}Zr_{2}O_{7}, the temperature and magnetic field dependence of which indicate a continuous distribution of quenched transverse fields (Δ) acting on the non-Kramers Pr^{3+} crystal field ground state doublets. Spin-ice correlations are apparent within 0.2 meV of the Zeeman energy. A random phase approximation provides an excellent account of the data with a transverse field distribution ρ(Δ)∝(Δ^{2}+Γ^{2})^{-1}, where Γ=0.27(1) meV. Established during high temperature synthesis due to an underlying structural instability, it appears disorder in Pr_{2}Zr_{2}O_{7} actually induces a quantum spin liquid.
Wen, J. -J.; Koohpayeh, S. M.; Ross, K. A.; ...
2017-03-08
Inelastic neutron scattering reveals a broad continuum of excitations in Pr 2 Zr 2 O 7 , the temperature and magnetic field dependence of which indicate a continuous distribution of quenched transverse fields ( Δ ) acting on the non-Kramers Pr 3 + crystal field ground state doublets. Spin-ice correlations are apparent within 0.2 meV of the Zeeman energy. In a random phase approximation an excellent account of the data is provided and contains a transverse field distribution ρ ( Δ ) ∝ ( Δ 2 + Γ 2 ) - 1 , where Γ = 0.27 ( 1 )more » meV . Established during high temperature synthesis due to an underlying structural instability, it appears disorder in Pr 2 Zr 2 O 7 actually induces a quantum spin liquid.« less
NASA Astrophysics Data System (ADS)
Magalhaes, S. G.; Morais, C. V.; Zimmer, F. M.; Lazo, M. J.; Nobre, F. D.
2017-02-01
The interplay between quantum fluctuations and disorder is investigated in a quantum spin-glass model, in the presence of a uniform transverse field Γ , as well as of a longitudinal random field hi, which follows a Gaussian distribution characterized by a width proportional to Δ . The interactions are infinite-ranged, and the 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 applied fields is analyzed. This study is motivated by experimental investigations on the LiHoxY1 -xF4 compound, where the application of a transverse magnetic field yields rather intriguing effects, particularly related to the behavior of the nonlinear magnetic susceptibility χ3, which have led to a considerable experimental and theoretical debate. We have analyzed two physically distinct situations, namely, Δ and Γ considered as independent, as well as these two quantities related, as proposed recently by some authors. In both cases, a spin-glass phase transition is found at a temperature Tf, with such phase being characterized by a nontrivial ergodicity breaking; moreover, Tf decreases by increasing Γ towards a quantum critical point at zero temperature. The situation where Δ and Γ are related [Δ ≡Δ (Γ )] appears to reproduce better the experimental observations on the LiHoxY1 -xF4 compound, with the theoretical results coinciding qualitatively with measurements of the nonlinear susceptibility χ3. In this later case, by increasing Γ gradually, χ3 becomes progressively rounded, presenting a maximum at a temperature T* (T*>Tf ), with both the amplitude of the maximum and the value of T* decreasing gradually. Moreover, we also show that the random field is the main responsible for the smearing of the nonlinear susceptibility, acting significantly inside the paramagnetic phase, leading to two regimes delimited by the temperature T*, one for Tf
NASA Astrophysics Data System (ADS)
Bai, Mingsian R.; Lin, Jia-Hong; Liu, Kwan-Liang
2010-07-01
Arrays with sparse and random sensor deployment are known to be capable of delivering high quality far-field images without grating lobes. This raises the question of whether or not this idea can be applied to near-field imaging as well. To answer this question that has not yet been widely investigated in previous research, numerical simulations are undertaken in this paper to optimize the microphone deployment for both far-field and near-field arrays with the latter being the main focus. In the simulation, a recently introduced near-field equivalent source imaging (NESI) technique is employed for the near-field imaging. Global optimization techniques including the simulated annealing (SA) algorithm and the intra-block Monte Carlo (IBMC) algorithm are exploited to find the optimal microphone position efficiently. The combined use of the SA and the IBMC algorithms enables efficient search for satisfactory deployment with excellent beam pattern and relatively uniform distribution of microphones. In the near-field optimization, a special kind of beam pattern and cost function definition is used for the multiple-input-multiple-output (MIMO) imaging problem. As indicated by the simulation results, random deployment of microphones is necessary to avoid grating lobes in far-field imaging. In the near-field simulation, all results suggest that the optimal near-field array is the uniform rectangular array (URA) and the random deployment presents no particular benefit in near-field imaging.
Wide-field Ca2+ imaging reveals visually evoked activity in the retrosplenial area
Murakami, Tomonari; Yoshida, Takashi; Matsui, Teppei; Ohki, Kenichi
2015-01-01
Due to recent advances of genetic manipulation, mouse brain has become a useful model for studying brain function, which demands whole brain functional mapping techniques in the mouse brain. In the present study, to finely map visual responsive areas in the mouse brain, we combined high-resolution wide-field optical imaging with transgenic mice containing the genetically encoded Ca2+ indicator, GCaMP3. With the high signal amplitude of GCaMP3 expressing in excitatory neurons, this system allowed neural activity to be observed with relatively fine spatial resolution and cell-type specificity. To evaluate this system, we examined whether non-visual areas exhibited a visual response over the entire surface of the mouse hemisphere. We found that two association areas, the retrosplenial area (RS) and secondary motor/anterior cingulate area (M2/AC), were significantly responsive to drifting gratings. Examination using gratings with distinct spatiotemporal frequency parameters revealed that the RS strongly responded to high-spatial and low-temporal frequency gratings. The M2/AC exhibited a response property similar to that of the RS, though it was not statistically significant. Finally, we performed cellular imaging using two-photon microscopy to examine orientation and direction selectivity of individual neurons, and found that a minority of neurons in the RS clearly showed visual responses sharply selective for orientation and direction. These results suggest that neurons in RS encode visual information of fine spatial details in images. Thus, the present study shows the usefulness of the functional mapping method using a combination of wide-field and two-photon Ca2+ imaging, which allows for whole brain mapping with high spatiotemporal resolution and cell-type specificity. PMID:26106292
Table Extraction from Web Pages Using Conditional Random Fields to Extract Toponym Related Data
NASA Astrophysics Data System (ADS)
Luthfi Hanifah, Hayyu’; Akbar, Saiful
2017-01-01
Table is one of the ways to visualize information on web pages. The abundant number of web pages that compose the World Wide Web has been the motivation of information extraction and information retrieval research, including the research for table extraction. Besides, there is a need for a system which is designed to specifically handle location-related information. Based on this background, this research is conducted to provide a way to extract location-related data from web tables so that it can be used in the development of Geographic Information Retrieval (GIR) system. The location-related data will be identified by the toponym (location name). In this research, a rule-based approach with gazetteer is used to recognize toponym from web table. Meanwhile, to extract data from a table, a combination of rule-based approach and statistical-based approach is used. On the statistical-based approach, Conditional Random Fields (CRF) model is used to understand the schema of the table. The result of table extraction is presented on JSON format. If a web table contains toponym, a field will be added on the JSON document to store the toponym values. This field can be used to index the table data in accordance to the toponym, which then can be used in the development of GIR system.
The statistics of peaks of Gaussian random fields. [cosmological density fluctuations
NASA Technical Reports Server (NTRS)
Bardeen, J. M.; Bond, J. R.; Kaiser, N.; Szalay, A. S.
1986-01-01
A set of new mathematical results on the theory of Gaussian random fields is presented, and the application of such calculations in cosmology to treat questions of structure formation from small-amplitude initial density fluctuations is addressed. The point process equation is discussed, giving the general formula for the average number density of peaks. The problem of the proper conditional probability constraints appropriate to maxima are examined using a one-dimensional illustration. The average density of maxima of a general three-dimensional Gaussian field is calculated as a function of heights of the maxima, and the average density of 'upcrossing' points on density contour surfaces is computed. The number density of peaks subject to the constraint that the large-scale density field be fixed is determined and used to discuss the segregation of high peaks from the underlying mass distribution. The machinery to calculate n-point peak-peak correlation functions is determined, as are the shapes of the profiles about maxima.
Apelian, Clement; Harms, Fabrice; Thouvenin, Olivier; Boccara, A. Claude
2016-01-01
We developed a new endogenous approach to reveal subcellular metabolic contrast in fresh ex vivo tissues taking advantage of the time dependence of the full field optical coherence tomography interferometric signals. This method reveals signals linked with local activity of the endogenous scattering elements which can reveal cells where other OCT-based techniques fail or need exogenous contrast agents. We benefit from the micrometric transverse resolution of full field OCT to image intracellular features. We used this time dependence to identify different dynamics at the millisecond scale on a wide range of organs in normal or pathological conditions. PMID:27446672
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
Some Trends in Radioactive Waste Form Behavior Revealed in Long-Term Field Tests
Ojovan, M. I.; Ojovan, N. V.; Startceva, I. V.; Barinov, A. S.
2002-02-25
Results from long-term field tests with borosilicate glass, cement and bitumen waste forms containing actual intermediate-level radioactive waste are summarized and discussed in the paper. Leaching behavior of the waste forms was evaluated by monitoring the contamination of contacting water. Measured leach rates of the three waste-form materials were in a narrow range in shallow subsurface repositories, but varied in a wide range at an open testing site owing to weathering of bitumen and cement materials. The repositories were opened after 12-year testing for visual examination, sampling and analysis. All retrieved waste forms were in good physical condition. The study has not revealed any negative changes in the waste glass. Some ageing processes were detected in cement and bitumen waste forms, which can positively (bitumen) or negatively (cement) affect physical and containment properties of these waste materials. It has been established that a significant proportion of the radioactive inventory in the bitumen waste form became associated with the bitumen phase. Phase separation of this radioactive bitumen has shown, than the asphaltene fraction is responsible for the major part of the radioactivity retained by the bitumen.
Du, Chang; Fan, Daming; Sun, Zhi; Fan, Yuwei; Lakshminarayanan, Rajamani; Moradian-Oldak, Janet
2008-01-01
The present study describes a method using immunohistochemical labeling in combination with high-resolution imaging (field emission scanning electron microscopy) to investigate the spatial localization of amelogenins on apatite crystallites in developing porcine enamel. Cross-sections of developing enamel tissue from freeze-fractured pig third molar were treated with antiserum against recombinant mouse amelogenin and immunoreactivity confirmed by Western blot analysis. The samples were then treated with the goat anti-rabbit IgG conjugated with 10-nm gold particles. The control samples were treated with the secondary antibody only. The in-lens secondary electrons detector and quadrant back-scattering detector were employed to reveal the high-resolution morphology of enamel structures and gold particle distribution. The immunolabeling showed a preference of the gold particle localization along the side faces of the ribbon-like apatite crystals. The preferential localization of amelogenin in vivo on enamel crystals strongly supports its direct function in controlling crystal morphology. PMID:18701812
Revealing spectral field features and mechanistic insights by control pulse cleaning
Lindinger, Albrecht; Weber, Stefan M.; Lupulescu, Cosmin; Vetter, Franziska; Plewicki, Mateusz; Merli, Andrea; Woeste, Ludger; Bartelt, Andreas F.; Rabitz, Herschel
2005-01-01
Control pulse cleaning (CPC) is the process of experimentally removing extraneous control field features in a closed-loop quantum dynamics optimization experiment. We demonstrate CPC in ionization processes in the model systems K{sub 2} and NaK by applying evolution strategies during the closed loop shaping of fs pulses. The CPC technique operates by applying genetic pressure on the spectral components with appropriate cost functions, and CPC is investigated in the case of weak (K{sub 2}) and of strong cleaning (NaK). A Pareto-optimal curve is constructed for the latter case, which reveals the correlation of the two generally conflicting goals of meeting the physical objective versus cleaning the control pulse. At weak genetic pressure unnecessary pulse components could be removed with marginal influence on the ionization process, whereas at strong genetic pressure the optimal degree of ionization is affected and, interestingly, electronic transitions to particular vibrational states are exposed. Thus, employing CPC while seeking optimal controls allows for extracting information about the chosen dynamical pathways including the significant intermediate states.
NASA Astrophysics Data System (ADS)
Anudu, Goodluck K.; Stephenson, Randell A.; Macdonald, David I. M.; Oakey, Gordon N.
2016-11-01
The northeastern Canadian Arctic margin is bordered to the north by Alpha Ridge, a dominantly magmatic complex within the Amerasia Basin of the Arctic Ocean, which forms part of the High Arctic Large Igneous Province (HALIP). The characteristics of the gravity and magnetic anomaly fields change notably along the Arctic margin, with two main segments recognised. Aeromagnetic and gravity data in the transition zone between these contrasting domains of the Canadian Arctic margin are analysed here in detail. Results obtained using a variety of edge enhancement (derivative) methods highlight several magnetic domains and a major offshore sedimentary basin as well as some known and a number of previously unknown tectonic and magmatic elements. A magmatic intrusion distribution map derived from the edge enhanced magnetic anomaly maps reveals that magmatic rocks are much more widespread in the relatively shallow subsurface than implied by surface geological mapping. Magmatic intrusions (mainly dykes) and other geological structures have NW-SE, NE-SW and N-S major trends. Broad gravity and pseudogravity lows across most of the Sverdrup Basin region are due to thick, less dense sedimentary succession and low magnetised crust. Magnetic and pseudogravity highs observed over Alpha Ridge indicate high crustal magnetisation associated with the occurrence of extensive and voluminous crustal magmatic bodies. Absence of these volcanic and intrusive rocks in the imaged sedimentary basin beneath the northeast Canadian Arctic margin region suggests that the basin probably formed after the cessation of HALIP magmatism.
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.
A novel approach to assess the treatment response using Gaussian random field in PET
Wang, Mengdie; Guo, Ning; Hu, Guangshu; Zhang, Hui E-mail: li.quanzheng@mgh.harvard.edu; El Fakhri, Georges; Li, Quanzheng E-mail: li.quanzheng@mgh.harvard.edu
2016-02-15
Purpose: The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robust approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects. Methods: The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (128{sup 2} pixels) with lesions of various diameters (2–6 mm), multiple tumor-to-background contrasts (3–10), and different changes in intensity (6.25%–30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response
NASA Astrophysics Data System (ADS)
Zhang, Y.; Li, F.; Zhang, S.; Hao, W.; Zhu, T.; Yuan, L.; Xiao, F.
2017-09-01
In this paper, Statistical Distribution based Conditional Random Fields (STA-CRF) algorithm is exploited for improving marginal ice-water classification. Pixel level ice concentration is presented as the comparison of methods based on CRF. Furthermore, in order to explore the effective statistical distribution model to be integrated into STA-CRF, five statistical distribution models are investigated. The STA-CRF methods are tested on 2 scenes around Prydz Bay and Adélie Depression, where contain a variety of ice types during melt season. Experimental results indicate that the proposed method can resolve sea ice edge well in Marginal Ice Zone (MIZ) and show a robust distinction of ice and water.
Brain tumor segmentation in 3D MRIs using an improved Markov random field model
NASA Astrophysics Data System (ADS)
Yousefi, Sahar; Azmi, Reza; Zahedi, Morteza
2011-10-01
Markov Random Field (MRF) models have been recently suggested for MRI brain segmentation by a large number of researchers. By employing Markovianity, which represents the local property, MRF models are able to solve a global optimization problem locally. But they still have a heavy computation burden, especially when they use stochastic relaxation schemes such as Simulated Annealing (SA). In this paper, a new 3D-MRF model is put forward to raise the speed of the convergence. Although, search procedure of SA is fairly localized and prevents from exploring the same diversity of solutions, it suffers from several limitations. In comparison, Genetic Algorithm (GA) has a good capability of global researching but it is weak in hill climbing. Our proposed algorithm combines SA and an improved GA (IGA) to optimize the solution which speeds up the computation time. What is more, this proposed algorithm outperforms the traditional 2D-MRF in quality of the solution.
NASA Astrophysics Data System (ADS)
Yasuda, Muneki; Kataoka, Shun
2017-08-01
In this paper, we address the inverse problem, or the statistical machine learning problem, in Markov random fields with a non-parametric pair-wise energy function with continuous variables. The inverse problem is formulated by maximum likelihood estimation. The exact treatment of maximum likelihood estimation is intractable because of two problems: (1) it includes the evaluation of the partition function and (2) it is formulated in the form of functional optimization. We avoid Problem (1) by using Bethe approximation. Bethe approximation is an approximation technique equivalent to the loopy belief propagation. Problem (2) can be solved by using orthonormal function expansion. Orthonormal function expansion can reduce a functional optimization problem to a function optimization problem. Our method can provide an analytic form of the solution of the inverse problem within the framework of Bethe approximation as a result of variational optimization.
RANDOM AND SYSTEMATIC FIELD ERRORS IN THE SNS RING: A STUDY OF THEIR EFFECTS AND COMPENSATION
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.
Document page structure learning for fixed-layout e-books using conditional random fields
NASA Astrophysics Data System (ADS)
Tao, Xin; Tang, Zhi; Xu, Canhui
2013-12-01
In this paper, a model is proposed to learn logical structure of fixed-layout document pages by combining support vector machine (SVM) and conditional random fields (CRF). Features related to each logical label and their dependencies are extracted from various original Portable Document Format (PDF) attributes. Both local evidence and contextual dependencies are integrated in the proposed model so as to achieve better logical labeling performance. With the merits of SVM as local discriminative classifier and CRF modeling contextual correlations of adjacent fragments, it is capable of resolving the ambiguities of semantic labels. The experimental results show that CRF based models with both tree and chain graph structures outperform the SVM model with an increase of macro-averaged F1 by about 10%.
Evaluating Consumer m-Health Services for Promoting Healthy Eating: A Randomized Field Experiment
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
System for Detecting Potential Lost Person based on Conditional Random Field
NASA Astrophysics Data System (ADS)
Kusuma, R. S.; Saptawati, G. A. P.
2017-01-01
Global Positioning System (GPS) technology has been used widely in transsportation industry to help company in managing taxis. The most popular GPS utilization for taxi company is to identify the position of taxis and monitor theirs the mobility. Nowdays, data collected from GPS tracker is combined with data from taxi meter are analyzed to provide region information regarding potential passengers. Zicheng Liao’s proposed a system based on GPS taxi data to detect anomalous area/region which was then interpreted as region with to predict rare passengers. The system was developed based on conditional random field (CRF) method and features position, velocity, passenger loading information. Our research was aimed to develop tool based on GPS data to detect potential lost person. We motivated by Liao research and modified the algorithms and features of CRF. Our experiments showed that the system has precision of 98.86% and recall of 87.478%.
SkipCor: Skip-Mention Coreference Resolution Using Linear-Chain Conditional Random Fields
Žitnik, Slavko; Šubelj, Lovro; Bajec, Marko
2014-01-01
Coreference resolution tries to identify all expressions (called mentions) in observed text that refer to the same entity. Beside entity extraction and relation extraction, it represents one of the three complementary tasks in Information Extraction. In this paper we describe a novel coreference resolution system SkipCor that reformulates the problem as a sequence labeling task. None of the existing supervised, unsupervised, pairwise or sequence-based models are similar to our approach, which only uses linear-chain conditional random fields and supports high scalability with fast model training and inference, and a straightforward parallelization. We evaluate the proposed system against the ACE 2004, CoNLL 2012 and SemEval 2010 benchmark datasets. SkipCor clearly outperforms two baseline systems that detect coreferentiality using the same features as SkipCor. The obtained results are at least comparable to the current state-of-the-art in coreference resolution. PMID:24956272
Incorporating conditional random fields and active learning to improve sentiment identification.
Zhang, Kunpeng; Xie, Yusheng; Yang, Yi; Sun, Aaron; Liu, Hengchang; Choudhary, Alok
2014-10-01
Many machine learning, statistical, and computational linguistic methods have been developed to identify sentiment of sentences in documents, yielding promising results. However, most of state-of-the-art methods focus on individual sentences and ignore the impact of context on the meaning of a sentence. In this paper, we propose a method based on conditional random fields to incorporate sentence structure and context information in addition to syntactic information for improving sentiment identification. We also investigate how human interaction affects the accuracy of sentiment labeling using limited training data. We propose and evaluate two different active learning strategies for labeling sentiment data. Our experiments with the proposed approach demonstrate a 5%-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods.
Many-body localization in a long range XXZ model with random-field
NASA Astrophysics Data System (ADS)
Li, Bo
2016-12-01
Many-body localization (MBL) in a long range interaction XXZ model with random field are investigated. Using the exact diagonal method, the MBL phase diagram with different tuning parameters and interaction range is obtained. It is found that the phase diagram of finite size results supplies strong evidence to confirm that the threshold interaction exponent α = 2. The tuning parameter Δ can efficiently change the MBL edge in high energy density stats, thus the system can be controlled to transfer from thermal phase to MBL phase by changing Δ. The energy level statistics data are consistent with result of the MBL phase diagram. However energy level statistics data cannot detect the thermal phase correctly in extreme long range case.
Bayesian Clustering Using Hidden Markov Random Fields in Spatial Population Genetics
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
Large-scale magnetic field generation by randomly forced shearing waves.
Heinemann, T; McWilliams, J C; Schekochihin, A A
2011-12-16
A rigorous theory for the generation of a large-scale magnetic field by random nonhelically forced motions of a conducting fluid combined with a linear shear is presented in the analytically tractable limit of low magnetic Reynolds number (Rm) and weak shear. The dynamo is kinematic and due to fluctuations in the net (volume-averaged) electromotive force. This is a minimal proof-of-concept quasilinear calculation aiming to put the shear dynamo, a new effect recently found in numerical experiments, on a firm theoretical footing. Numerically observed scalings of the wave number and growth rate of the fastest-growing mode, previously not understood, are derived analytically. The simplicity of the model suggests that shear dynamo action may be a generic property of sheared magnetohydrodynamic turbulence.
Daniels, Noah M; Gallant, Andrew; Ramsey, Norman; Cowen, Lenore J
2015-01-01
We introduce MRFy, a tool for protein remote homology detection that captures beta-strand dependencies in the Markov random field. Over a set of 11 SCOP beta-structural superfamilies, MRFy shows a 14 percent improvement in mean Area Under the Curve for the motif recognition problem as compared to HMMER, 25 percent improvement as compared to RAPTOR, 14 percent improvement as compared to HHPred, and a 18 percent improvement as compared to CNFPred and RaptorX. MRFy was implemented in the Haskell functional programming language, and parallelizes well on multi-core systems. MRFy is available, as source code as well as an executable, from http://mrfy.cs.tufts.edu/.
Markov random field model for segmenting large populations of lipid vesicles from micrographs.
Zupanc, Jernej; Drobne, Damjana; Ster, Branko
2011-12-01
Giant unilamellar lipid vesicles, artificial replacements for cell membranes, are a promising tool for in vitro assessment of interactions between products of nanotechnologies and biological membranes. However, the effect of nanoparticles can not be derived from observations on a single specimen, vesicle populations should be observed instead. We propose an adaptation of the Markov random field image segmentation model which allows detection and segmentation of numerous vesicles in micrographs. The reliability of this model with different lighting, blur, and noise characteristics of micrographs is examined and discussed. Moreover, the automatic segmentation is tested on micrographs with thousands of vesicles and the result is compared to that of manual segmentation. The segmentation step presented is part of a methodology we are developing for bio-nano interaction assessment studies on lipid vesicles.
Broadcast News Story Segmentation Using Conditional Random Fields and Multimodal Features
NASA Astrophysics Data System (ADS)
Wang, Xiaoxuan; Xie, Lei; Lu, Mimi; Ma, Bin; Chng, Eng Siong; Li, Haizhou
In this paper, we propose integration of multimodal features using conditional random fields (CRFs) for the segmentation of broadcast news stories. We study story boundary cues from lexical, audio and video modalities, where lexical features consist of lexical similarity, chain strength and overall cohesiveness; acoustic features involve pause duration, pitch, speaker change and audio event type; and visual features contain shot boundaries, anchor faces and news title captions. These features are extracted in a sequence of boundary candidate positions in the broadcast news. A linear-chain CRF is used to detect each candidate as boundary/non-boundary tags based on the multimodal features. Important interlabel relations and contextual feature information are effectively captured by the sequential learning framework of CRFs. Story segmentation experiments show that the CRF approach outperforms other popular classifiers, including decision trees (DTs), Bayesian networks (BNs), naive Bayesian classifiers (NBs), multilayer perception (MLP), support vector machines (SVMs) and maximum entropy (ME) classifiers.
Conditional random fields as classifiers for three-class motor-imagery brain-computer interfaces
NASA Astrophysics Data System (ADS)
Awwad Shiekh Hasan, Bashar; Gan, John Q.
2011-04-01
Conditional random fields (CRFs) are demonstrated to be a discriminative model able to exploit the temporal properties of EEG data obtained during synchronous three-class motor-imagery-based brain-computer interface experiments. The advantages of CRFs over the hidden Markov model (HMM) are both theoretical and practical. Theoretically, CRFs focus on modeling latent variables (labels) rather than both observation and latent variables. Furthermore, CRFs' loss function is convex, guaranteeing convergence to the global optimum. Practically, CRFs are much less prone to singularity problems. This property allows for the use of both time- and frequency-based features, such as band power. The HMM, on the other hand, requires temporal features such as autoregressive coefficients. A CRF-based classifier is tested on 13 subjects. Significant improvement is found when applying CRFs over HMM- and LDA-based classifiers.
Evaluating Consumer m-Health Services for Promoting Healthy Eating: A Randomized Field Experiment.
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.
Depinning transition and thermal fluctuations in the random-field Ising model.
Roters, L; Hucht, A; Lübeck, S; Nowak, U; Usadel, K D
1999-11-01
We analyze the depinning transition of a driven interface in the three-dimensional (3D) random field Ising model (RFIM) with quenched disorder by means of Monte Carlo simulations. The interface initially built into the system is perpendicular to the [111] direction of a simple cubic lattice. We introduce an algorithm which is capable of simulating such an interface independent of the considered dimension and time scale. This algorithm is applied to the 3D RFIM to study both the depinning transition and the influence of thermal fluctuations on this transition. It turns out that in the RFIM characteristics of the depinning transition depend crucially on the existence of overhangs. Our analysis yields critical exponents of the interface velocity, the correlation length, and the thermal rounding of the transition. We find numerical evidence for a scaling relation for these exponents and the dimension d of the system.
Change point estimation in high dimensional Markov random-field models.
Roy, Sandipan; Atchadé, Yves; Michailidis, George
2017-09-01
This paper investigates a change-point estimation problem in the context of high-dimensional Markov random field models. Change-points represent a key feature in many dynamically evolving network structures. The change-point estimate is obtained by maximizing a profile penalized pseudo-likelihood function under a sparsity assumption. We also derive a tight bound for the estimate, up to a logarithmic factor, even in settings where the number of possible edges in the network far exceeds the sample size. The performance of the proposed estimator is evaluated on synthetic data sets and is also used to explore voting patterns in the US Senate in the 1979-2012 period.
A Markov random field approach for modeling spatio-temporal evolution of microstructures
NASA Astrophysics Data System (ADS)
Acar, Pinar; Sundararaghavan, Veera
2016-10-01
The following problem is addressed: ‘Can one synthesize microstructure evolution over a large area given experimental movies measured over smaller regions?’ Our input is a movie of microstructure evolution over a small sample window. A Markov random field (MRF) algorithm is developed that uses this data to estimate the evolution of microstructure over a larger region. Unlike the standard microstructure reconstruction problem based on stationary images, the present algorithm is also able to reconstruct time-evolving phenomena such as grain growth. Such an algorithm would decrease the cost of full-scale microstructure measurements by coupling mathematical estimation with targeted small-scale spatiotemporal measurements. The grain size, shape and orientation distribution statistics of synthesized polycrystalline microstructures at different times are compared with the original movie to verify the method.
Growth of 'dizzy dendrites' in a random field of foreign particles
NASA Astrophysics Data System (ADS)
Gránásy, László; Pusztai, Tamás; Warren, James A.; Douglas, Jack F.; Börzsönyi, Tamás; Ferreiro, Vincent
2003-02-01
Microstructure plays an essential role in determining the properties of crystalline materials. A widely used method to influence microstructure is the addition of nucleating agents. Observations on films formed from clay-polymer blends indicate that particulate additives, in addition to serving as nucleating agents, may also perturb crystal growth, leading to the formation of irregular dendritic morphologies. Here we describe the formation of these 'dizzy dendrites' using a phase-field theory, in which randomly distributed foreign particle inclusions perturb the crystallization by deflecting the tips of the growing dendrite arms. This mechanism of crystallization, which is verified experimentally, leads to a polycrystalline structure dependent on particle configuration and orientation. Using computer simulations we demonstrate that additives of controlled crystal orientation should allow for a substantial manipulation of the crystallization morphology.
A novel approach to assess the treatment response using Gaussian random field in PET
Wang, Mengdie; Guo, Ning; Hu, Guangshu; El Fakhri, Georges; Zhang, Hui; Li, Quanzheng
2016-01-01
Purpose: The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robust approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects. Methods: The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (1282 pixels) with lesions of various diameters (2–6 mm), multiple tumor-to-background contrasts (3–10), and different changes in intensity (6.25%–30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response assessment
Gupta, Lalit; Sisodia, Rajendra Singh; Pallavi, V; Firtion, Celine; Ramachandran, Ganesan
2011-01-01
This paper proposes a novel approach for segmenting fetal ultrasound images. This problem presents a variety of challenges including high noise, low contrast, and other US imaging properties such as similarity between texture and gray levels of two organs/ tissues. In this paper, we have proposed a Conditional Random Field (CRF) based framework to handle challenges in segmenting fetal ultrasound images. Clinically, it is known that fetus is surrounded by specific maternal tissues, amniotic fluid and placenta. We exploit this context information using CRFs for segmenting the fetal images accurately. The proposed CRF framework uses wavelet based texture features for representing the ultrasound image and Support Vector Machines (SVM) for initial label prediction. Initial results on a limited dataset of real world ultrasound images of fetus are promising. Results show that proposed method could handle the noise and similarity between fetus and its surroundings in ultrasound images.
Scene estimation from speckled synthetic aperture radar imagery: Markov-random-field approach.
Lankoande, Ousseini; Hayat, Majeed M; Santhanam, Balu
2006-06-01
A novel Markov-random-field model for speckled synthetic aperture radar (SAR) imagery is derived according to the physical, spatial statistical properties of speckle noise in coherent imaging. A convex Gibbs energy function for speckled images is derived and utilized to perform speckle-compensating image estimation. The image estimation is formed by computing the conditional expectation of the noisy image at each pixel given its neighbors, which is further expressed in terms of the derived Gibbs energy function. The efficacy of the proposed technique, in terms of reducing speckle noise while preserving spatial resolution, is studied by using both real and simulated SAR imagery. Using a number of commonly used metrics, the performance of the proposed technique is shown to surpass that of existing speckle-noise-filtering methods such as the Gamma MAP, the modified Lee, and the enhanced Frost.
NASA Astrophysics Data System (ADS)
Rogotis, Savvas; Ioannidis, Dimosthenis; Tzovaras, Dimitrios; Likothanassis, Spiros
2015-04-01
The aim of this work is to present a novel approach for automatic recognition of suspicious activities in outdoor perimeter surveillance systems based on infrared video processing. Through the combination of size, speed and appearance based features, like the Center-Symmetric Local Binary Patterns, short-term actions are identified and serve as input, along with user location, for modeling target activities using the theory of Hidden Conditional Random Fields. HCRFs are used to directly link a set of observations to the most appropriate activity label and as such to discriminate high risk activities (e.g. trespassing) from zero risk activities (e.g loitering outside the perimeter). Experimental results demonstrate the effectiveness of our approach in identifying suspicious activities for video surveillance systems.
Sign Language Recognition with the Kinect Sensor Based on Conditional Random Fields
Yang, Hee-Deok
2015-01-01
Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D) space. In this research, we use 3D depth information from hand motions, generated from Microsoft's Kinect sensor and apply a hierarchical conditional random field (CRF) that recognizes hand signs from the hand motions. The proposed method uses a hierarchical CRF to detect candidate segments of signs using hand motions, and then a BoostMap embedding method to verify the hand shapes of the segmented signs. Experiments demonstrated that the proposed method could recognize signs from signed sentence data at a rate of 90.4%. PMID:25609039
Quantum Phase Transition in the Two-Dimensional Random Transverse-Field Ising Model
NASA Astrophysics Data System (ADS)
Pich, C.; Young, A. P.
1998-03-01
We study the quantum phase transition in the random transverse-field Ising model by Monte Carlo simulations. In one-dimension it has been established that this system has the following striking behavior: (i) the dynamical exponent is infinite, and (ii) the exponents for the divergence of the average and typical correlation lengths are different. An important issue is whether this behavior is special to one-dimension or whether similar behavior persists in higher dimensions. Here we attempt to answer this question by studies of the two-dimensional model. Our simulations use the Wolff cluster algorithm and the results are analyzed by anisotropic finite size scaling, paying particular attention to the Binder ratio of moments of the order parameter distribution and the distribution of the spin-spin correlation functions for various distances.
High energy X-ray phase and dark-field imaging using a random absorption mask.
Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal
2016-07-28
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.
Segmentation of angiodysplasia lesions in WCE images using a MAP approach with Markov Random Fields.
Vieira, Pedro M; Goncalves, Bruno; Goncalves, Carla R; Lima, Carlos S
2016-08-01
This paper deals with the segmentation of angiodysplasias in wireless capsule endoscopy images. These lesions are the cause of almost 10% of all gastrointestinal bleeding episodes, and its detection using the available software presents low sensitivity. This work proposes an automatic selection of a ROI using an image segmentation module based on the MAP approach where an accelerated version of the EM algorithm is used to iteratively estimate the model parameters. Spatial context is modeled in the prior probability density function using Markov Random Fields. The color space used was CIELab, specially the a component, which highlighted most these type of lesions. The proposed method is the first regarding this specific type of lesions, but when compared to other state-of-the-art segmentation methods, it almost doubles the results.
Anomalous transport in fluid field with random waiting time depending on the preceding jump length
NASA Astrophysics Data System (ADS)
Zhang, Hong; Li, Guo-Hua
2016-11-01
Anomalous (or non-Fickian) transport behaviors of particles have been widely observed in complex porous media. To capture the energy-dependent characteristics of non-Fickian transport of a particle in flow fields, in the present paper a generalized continuous time random walk model whose waiting time probability distribution depends on the preceding jump length is introduced, and the corresponding master equation in Fourier-Laplace space for the distribution of particles is derived. As examples, two generalized advection-dispersion equations for Gaussian distribution and lévy flight with the probability density function of waiting time being quadratic dependent on the preceding jump length are obtained by applying the derived master equation. Project supported by the Foundation for Young Key Teachers of Chengdu University of Technology, China (Grant No. KYGG201414) and the Opening Foundation of Geomathematics Key Laboratory of Sichuan Province, China (Grant No. scsxdz2013009).
Mandell, David S; Stahmer, Aubyn C; Shin, Sujie; Xie, Ming; Reisinger, Erica; Marcus, Steven C
2013-05-01
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 Differential Ability Scales. Program fidelity was measured through video coding and use of a checklist. Outcomes were assessed using linear regression with random effects for classroom and student. Average fidelity was 57% in Strategies for Teaching based on Autism Research classrooms and 48% in Structured Teaching classrooms. There was a 9.2-point (standard deviation = 9.6) increase in Differential Ability Scales score over the 8-month study period, but no main effect of program. There was a significant interaction between fidelity and group. In classrooms with either low or high program fidelity, students in Strategies for Teaching based on Autism Research experienced a greater gain in Differential Ability Scales score than students in Structured Teaching (11.2 vs. 5.5 points and 11.3 vs. 8.9 points, respectively). In classrooms with moderate fidelity, students in Structured Teaching experienced a greater gain than students in Strategies for Teaching based on Autism Research (10.1 vs. 4.4 points). The results suggest significant variability in implementation of evidence-based practices, even with supports, and also suggest the need to address challenging issues related to implementation measurement in community settings.
Liu, Hui-Fang; Yang, Lin; He, Hong-Chen; Zhou, Jun; Liu, Ying; Wang, Chun-Yan; Wu, Yuan-Chao; He, Cheng-Qi
2013-05-01
A randomized, active-controlled clinical trial was conducted to examine the effect of pulsed electromagnetic fields (PEMFs) on women with postmenopausal osteoporosis (PMO) in southwest China. Forty-four participants were randomly assigned to receive alendronate or one course of PEMFs treatment. The primary endpoint was the mean percentage change in bone mineral density of the lumbar spine (BMDL), and secondary endpoints were the mean percentage changes in left proximal femur bone mineral density (BMDF), serum 25OH vitamin D3 (25(OH)D) concentrations, total lower-extremity manual muscle test (LE MMT) score, and Berg Balance Scale (BBS) score. The BMDL, BMDF, total LE MMT score and BBS score were recorded at baseline, 5, 12, and 24 weeks. Serum concentrations of 25(OH)D were measured at baseline and 5 weeks. Using a mixed linear model, there was no significant treatment difference between the two groups in the BMDL, BMDF, total LE MMT score, and BBS score (P ≥ 0.05). For 25(OH)D concentrations, the effects were also comparable between the two groups (P ≥ 0.05) with the Mann-Whitney's U-test. These results suggested that a course of PEMFs treatment with specific parameters was as effective as alendronate in treating PMO within 24 weeks.
T→0 mean-field population dynamics approach for the random 3 -satisfiability problem
NASA Astrophysics Data System (ADS)
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 β with fixed ratio r=y/β . 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 Σ(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 Σ(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.
The role of treatment fidelity on outcomes during a randomized field trial of an autism intervention
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 Differential Ability Scales. Program fidelity was measured through video coding and use of a checklist. Outcomes were assessed using linear regression with random effects for classroom and student. Average fidelity was 57% in Strategies for Teaching based on Autism Research classrooms and 48% in Structured Teaching classrooms. There was a 9.2-point (standard deviation = 9.6) increase in Differential Ability Scales score over the 8-month study period, but no main effect of program. There was a significant interaction between fidelity and group. In classrooms with either low or high program fidelity, students in Strategies for Teaching based on Autism Research experienced a greater gain in Differential Ability Scales score than students in Structured Teaching (11.2 vs 5.5 points and 11.3 vs 8.9 points, respectively). In classrooms with moderate fidelity, students in Structured Teaching experienced a greater gain than students in Strategies for Teaching based on Autism Research (10.1 vs 4.4 points). The results suggest significant variability in implementation of evidence-based practices, even with supports, and also suggest the need to address challenging issues related to implementation measurement in community settings. PMID:23592849
Role of polar nanoregions with weak random fields in Pb-based perovskite ferroelectrics
Helal, M. A.; Aftabuzzaman, M.; Tsukada, S.; Kojima, S.
2017-01-01
In relaxor ferroelectrics, the role of randomly orientated polar nanoregions (PNRs) with weak random fields (RFs) is one of the most puzzling issues of materials science. The relaxation time of polarization fluctuations of PNRs, which manifests themselves as a central peak (CP) in inelastic light scattering, is the important physical quantity to understand the dynamics of PNRs. Here, the angular and temperature dependences of depolarized and polarized CPs in 0.44Pb(Mg1/3Nb2/3)O3-0.56PbTiO3 single crystals with weak RFs have been studied by Raman and Brillouin scattering, respectively. The CPs observed in Raman scattering show the very clear angular dependence which is consistent with the local tetragonal symmetry. It is different from the well-known local rhombohedral symmetry with strong RFs for Pb(Mg1/3Nb2/3)O3. In Brillouin scattering, depolarized and polarized CPs show two relaxation processes corresponding to transverse and longitudinal fluctuations of PNRs. The remarkable slowing down towards the Curie temperature was observed for transverse fluctuations in local tetragonal symmetry. PMID:28300152
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.
Role of polar nanoregions with weak random fields in Pb-based perovskite ferroelectrics
NASA Astrophysics Data System (ADS)
Helal, M. A.; Aftabuzzaman, M.; Tsukada, S.; Kojima, S.
2017-03-01
In relaxor ferroelectrics, the role of randomly orientated polar nanoregions (PNRs) with weak random fields (RFs) is one of the most puzzling issues of materials science. The relaxation time of polarization fluctuations of PNRs, which manifests themselves as a central peak (CP) in inelastic light scattering, is the important physical quantity to understand the dynamics of PNRs. Here, the angular and temperature dependences of depolarized and polarized CPs in 0.44Pb(Mg1/3Nb2/3)O3-0.56PbTiO3 single crystals with weak RFs have been studied by Raman and Brillouin scattering, respectively. The CPs observed in Raman scattering show the very clear angular dependence which is consistent with the local tetragonal symmetry. It is different from the well-known local rhombohedral symmetry with strong RFs for Pb(Mg1/3Nb2/3)O3. In Brillouin scattering, depolarized and polarized CPs show two relaxation processes corresponding to transverse and longitudinal fluctuations of PNRs. The remarkable slowing down towards the Curie temperature was observed for transverse fluctuations in local tetragonal symmetry.
Sampling scale effects in random fields and implications for environmental monitoring.
Skøien, Jon Olav; Blöschl, Günter
2006-03-01
The concept of a sampling scale triplet of spacing, extent and support is used to define the spatial dimensions of a monitoring network or a field study. The spacing is the average distance between samples, the extent is the size of the domain sampled and the support is the averaging area of one sample. The aim of this paper is to examine what is the bias and the random error (uncertainty) introduced by the sampling scale triplet into estimates of the mean, the spatial variance and the integral scale of a variable in a landscape. The integral scale is a measure of the average distance over which a variable is correlated in space. A large number of two dimensional random fields are generated from which hypothetical samples, conforming to a certain sampling scale triplet, are drawn which in turn are used to estimate the sample mean, spatial variance and integral scale. The results indicate that the biases can be up to two orders of magnitude. The bias of the integral scale is positively related to the magnitude of any of the components of the scale triplet while the bias of the spatial variance is different for different components of the scale triplet. All sampling scale effects are relative to the underlying correlation length of the variable of interest which is closely related to the integral scale. The integral scale can hence be used for sampling design and data interpretation. Suggestions are given on how to adjust a monitoring network to the scales of the variables of interest and how to interpret sampling scale effects in environmental data.
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
Boulware, David R
2006-01-01
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. 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/cm(2) 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. 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. Safe Sea is a topical barrier cream effective at preventing >80% jellyfish stings under real-world conditions.
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
Stochastic generation of explicit pore structures by thresholding Gaussian random fields
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.
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
Field evaluation of a random forest activity classifier for wrist-worn accelerometer data.
Pavey, Toby G; Gilson, Nicholas D; Gomersall, Sjaan R; Clark, Bronwyn; Trost, Stewart G
2017-01-01
Wrist-worn accelerometers are convenient to wear and associated with greater wear-time compliance. Previous work has generally relied on choreographed activity trials to train and test classification models. However, validity in free-living contexts is starting to emerge. Study aims were: (1) train and test a random forest activity classifier for wrist accelerometer data; and (2) determine if models trained on laboratory data perform well under free-living conditions. Twenty-one participants (mean age=27.6±6.2) completed seven lab-based activity trials and a 24h free-living trial (N=16). Participants wore a GENEActiv monitor on the non-dominant wrist. Classification models recognising four activity classes (sedentary, stationary+, walking, and running) were trained using time and frequency domain features extracted from 10-s non-overlapping windows. Model performance was evaluated using leave-one-out-cross-validation. Models were implemented using the randomForest package within R. Classifier accuracy during the 24h free living trial was evaluated by calculating agreement with concurrently worn activPAL monitors. Overall classification accuracy for the random forest algorithm was 92.7%. Recognition accuracy for sedentary, stationary+, walking, and running was 80.1%, 95.7%, 91.7%, and 93.7%, respectively for the laboratory protocol. Agreement with the activPAL data (stepping vs. non-stepping) during the 24h free-living trial was excellent and, on average, exceeded 90%. The ICC for stepping time was 0.92 (95% CI=0.75-0.97). However, sensitivity and positive predictive values were modest. Mean bias was 10.3min/d (95% LOA=-46.0 to 25.4min/d). The random forest classifier for wrist accelerometer data yielded accurate group-level predictions under controlled conditions, but was less accurate at identifying stepping verse non-stepping behaviour in free living conditions Future studies should conduct more rigorous field-based evaluations using observation as a criterion
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
Choi, Nancy M.; Loguercio, Salvatore; Verma-Gaur, Jiyoti; Degner, Stephanie C.; Torkamani, Ali; Su, Andrew I.; Oltz, Eugene M.; Artyomov, Maxim; Feeney, Ann J.
2013-01-01
A diverse antibody repertoire is formed through the rearrangement of V, D, and J segments at the immunoglobulin heavy chain (Igh) loci. The C57BL/6 murine Igh locus has over 100 functional VH gene segments that can recombine to a rearranged DJH. While the non-random usage of VH genes is well documented, it is not clear what elements determine recombination frequency. To answer this question we conducted deep sequencing of 5′-RACE products of the Igh repertoire in pro-B cells, amplified in an unbiased manner. ChIP-seq results for several histone modifications and RNA polymerase II binding, RNA-seq for sense and antisense non-coding germline transcripts, and proximity to CTCF and Rad21 sites were compared to the usage of individual V genes. Computational analyses assessed the relative importance of these various accessibility elements. These elements divide the Igh locus into four epigenetically and transcriptionally distinct domains, and our computational analyses reveal different regulatory mechanisms for each region. Proximal V genes are relatively devoid of active histone marks and non-coding RNA in general, but having a CTCF site near their RSS is critical, suggesting that being positioned near the base of the chromatin loops is important for rearrangement. In contrast, distal V genes have higher levels of histone marks and non-coding RNA, which may compensate for their poorer RSSs and for being distant from CTCF sites. Thus, the Igh locus has evolved a complex system for the regulation of V(D)J rearrangement that is different for each of the four domains that comprise this locus. PMID:23898036
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.
Unsupervised 4D myocardium segmentation with a Markov Random Field based deformable model.
Cordero-Grande, L; Vegas-Sánchez-Ferrero, G; Casaseca-de-la-Higuera, P; San-Román-Calvar, J Alberto; Revilla-Orodea, Ana; Martín-Fernández, M; Alberola-López, C
2011-06-01
A stochastic deformable model is proposed for the segmentation of the myocardium in Magnetic Resonance Imaging. The segmentation is posed as a probabilistic optimization problem in which the optimal time-dependent surface is obtained for the myocardium of the heart in a discrete space of locations built upon simple geometric assumptions. For this purpose, first, the left ventricle is detected by a set of image analysis tools gathered from the literature. Then, the segmentation solution is obtained by the Maximization of the Posterior Marginals for the myocardium location in a Markov Random Field framework which optimally integrates temporal-spatial smoothness with intensity and gradient related features in an unsupervised way by the Maximum Likelihood estimation of the parameters of the field. This scheme provides a flexible and robust segmentation method which has been able to generate results comparable to manually segmented images for some derived cardiac function parameters in a set of 43 patients affected in different degrees by an Acute Myocardial Infarction. Copyright © 2011 Elsevier B.V. All rights reserved.
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.
The rotation of photospheric magnetic fields: A random walk transport model
NASA Technical Reports Server (NTRS)
Wang, Y. -M.; Sheeley, N. R., Jr.
1994-01-01
In an earlier study of solar differential rotation, we showed that the transport of magnetic flux across latitudes acts to establish quasi-stationary patterns, therby accounting for the observed rigid rotation of the large-scale photospheric field. In that paper, the effect of supergranular convection was represented by a continuum diffusion, limiting the applicability of the calculations to large spatial scales. Here we extend the model to scales comparable to that of the supergranulation itself by replacing the diffusive transport with a discrete random walk process. Rotation curves are derived by cross-correlating the simulated photospheric field maps for a variety of time lags and spatial resolutions. When the lag between maps is relatively short less than or approximately = 15 days), the midlatitude correlation functions show two distinct components: a broad feature associated with the large-scale unipolar patterns and a narrow feature originating from small magnetic structures encompossing from one to several supergranular cells. By fitting the broad component we obtain the rigid rotation profile of the patterns, whereas by fitting the narrow component, we recover the differential rate of the photospheric plasma itself. For time lags of 1 month or greater, only the broad feature associated with the long-lived patterns remains clearly identifiable in the simulations.
The infinite-order conditional random field model for sequential data modeling.
Chatzis, Sotirios P; Demiris, Yiannis
2013-06-01
Sequential data labeling is a fundamental task in machine learning applications, with speech and natural language processing, activity recognition in video sequences, and biomedical data analysis being characteristic examples, to name just a few. The conditional random field (CRF), a log-linear model representing the conditional distribution of the observation labels, is one of the most successful approaches for sequential data labeling and classification, and has lately received significant attention in machine learning as it achieves superb prediction performance in a variety of scenarios. Nevertheless, existing CRF formulations can capture only one- or few-timestep interactions and neglect higher order dependences, which are potentially useful in many real-life sequential data modeling applications. To resolve these issues, in this paper we introduce a novel CRF formulation, based on the postulation of an energy function which entails infinitely long time-dependences between the modeled data. Building blocks of our novel approach are: 1) the sequence memoizer (SM), a recently proposed nonparametric Bayesian approach for modeling label sequences with infinitely long time dependences, and 2) a mean-field-like approximation of the model marginal likelihood, which allows for the derivation of computationally efficient inference algorithms for our model. The efficacy of the so-obtained infinite-order CRF (CRF(∞)) model is experimentally demonstrated.
Super-rough glassy phase of the random field XY model in two dimensions.
Perret, Anthony; Ristivojevic, Zoran; Le Doussal, Pierre; Schehr, Grégory; Wiese, Kay J
2012-10-12
We study both analytically, using the renormalization group (RG) to two loop order, and numerically, using an exact polynomial algorithm, the disorder-induced glass phase of the two-dimensional XY model with quenched random symmetry-breaking fields and without vortices. In the super-rough glassy phase, i.e., below the critical temperature T(c), the disorder and thermally averaged correlation function B(r) of the phase field θ(x), B(r)=([θ(x)-θ(x+r)](2)) behaves, for r > a, as B(r) is approximately equal to A(τ)ln(2)(r/a) where r=|r| and a is a microscopic length scale. We derive the RG equations up to cubic order in τ=(T(c)-T)/T(c) and predict the universal amplitude A(τ)=2τ(2)-2τ(3)+O(τ(4)). The universality of A(τ) results from nontrivial cancellations between nonuniversal constants of RG equations. Using an exact polynomial algorithm on an equivalent dimer version of the model we compute A(τ) numerically and obtain a remarkable agreement with our analytical prediction, up to τ≈0.5.
The effect of adiabatic focusing upon charged-particle propagation in random magnetic fields
NASA Technical Reports Server (NTRS)
Earl, J. A.
1976-01-01
The charged particles considered are scattered by random fields while they propagate along the diverging lines of force of a spatially inhomogeneous guiding field. Their longitudinal transport is described in terms of the eigenfunctions of a Sturm-Liouville operator which incorporates the effect of adiabatic focusing along with that of scattering. The relaxation times and characteristic velocities which appear in this matrix formulation of the transport problem are graphed and tabulated. Explicit formulas which describe the particle-density profile that results from a localized impulsive injection are derived for two different regimes. In the first regime, where focusing is relatively weak, a diffusive mode of propagation is dominant, but coherent modes are also present, and they become prominent as the intensity of focusing increases. In the second regime, where focusing is strong and where diffusion does not occur, the propagation is purely coherent. The existence of this supercoherent mode of particle transport opens up many possibilities for the interpretation of astrophysical phenomena.
NASA Astrophysics Data System (ADS)
Hermanowski, Piotr; Piotrowski, Jan A.; Szuman-Kalita, Izabela
2017-04-01
Numerous studies have provided insight into processes operating under contemporary and palaeo-ice sheets. Many of these studies concerned drumlins, landforms whose formation is essential to the understanding of subglacial soft-bedded systems. Despite the interdisciplinary efforts involving sophisticated analytical and interpretative tools the "drumlin problem" remains elusive and continues to generate much controversy. In this study the geological composition of two drumlins from the Stargard drumlin field (NW Poland) in the terminal area of a major last-glacial palaeo-ice stream was examined in three excavated trenches at macro- and microscales. In each trench, sediment description and fabric analyses were conducted, and samples collected for micromorphological, AMS (anisotropy of magnetic susceptibility) and grain size measurements. Both investigated drumlins are mainly composed of macroscopically homogeneous till with minor, max. 5 cm thick sand stringers and sparse silty inclusions. Distinct features are (1) a highly deformed, up to 18-cm thick till layer with clay- and pebble-sized clasts at the top, and (2) a continuous thin intra-till clay layer. Till macro-fabric measurements reveal a very high clustering strength and low isotropy index. AMS eigenvectors V1 vary significantly, but the dominant direction is consistent with the macrofabric measurements. Most of the observed microstructures indicate ductile deformation of the till. The overall observations suggest a shallow subglacial deformation not affecting the entire till thickness at any time intervening with ice/bed separation facilitating enhanced basal sliding. The intra-till clay layer of low hydraulic conductivity contributed to elevated pore-water pressure in the sediment causing its fluidization and deformation. Intervening thin-skinned sediment deformation and basal de-coupling resulted in fast ice flow that, coupled with material release from the ice sole and its accretion at the ice
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).
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.
Transverse eV ion heating by random electric field fluctuations in the plasmasphere
NASA Astrophysics Data System (ADS)
Artemyev, A. V.; Mourenas, D.; Agapitov, O. V.; Blum, L.
2017-02-01
Charged particle acceleration in the Earth inner magnetosphere is believed to be mainly due to the local resonant wave-particle interaction or particle transport processes. However, the Van Allen Probes have recently provided interesting evidence of a relatively slow transverse heating of eV ions at distances about 2-3 Earth radii during quiet times. Waves that are able to resonantly interact with such very cold ions are generally rare in this region of space, called the plasmasphere. Thus, non-resonant wave-particle interactions are expected to play an important role in the observed ion heating. We demonstrate that stochastic heating by random transverse electric field fluctuations of whistler (and possibly electromagnetic ion cyclotron) waves could explain this weak and slow transverse heating of H+ and O+ ions in the inner magnetosphere. The essential element of the proposed model of ion heating is the presence of trains of random whistler (hiss) wave packets, with significant amplitude modulations produced by strong wave damping, rapid wave growth, or a superposition of wave packets of different frequencies, phases, and amplitudes. Such characteristics correspond to measured characteristics of hiss waves in this region. Using test particle simulations with typical wave and plasma parameters, we demonstrate that the corresponding stochastic transverse ion heating reaches 0.07-0.2 eV/h for protons and 0.007-0.015 eV/h for O+ ions. This global temperature increase of the Maxwellian ion population from an initial Ti˜0.3 eV could potentially explain the observations.
Transverse eV Ion Heating by Random Electric Field Fluctuations in the Plasmasphere
NASA Technical Reports Server (NTRS)
Artemyev, A. V.; Mourenas, D.; Agapitov, O. V.; Blum, L.
2017-01-01
Charged particle acceleration in the Earth inner magnetosphere is believed to be mainly due to the local resonant wave-particle interaction or particle transport processes. However, the Van Allen Probes have recently provided interesting evidence of a relatively slow transverse heating of eV ions at distances about 2-3 Earth radii during quiet times. Waves that are able to resonantly interact with such very cold ions are generally rare in this region of space, called the plasmasphere. Thus, non-resonant wave-particle interactions are expected to play an important role in the observed ion heating. We demonstrate that stochastic heating by random transverse electric field fluctuations of whistler (and possibly electromagnetic ion cyclotron) waves could explain this weak and slow transverse heating of H+ and O+ ions in the inner magnetosphere. The essential element of the proposed model of ion heating is the presence of trains of random whistler (hiss) wave packets, with significant amplitude modulations produced by strong wave damping, rapid wave growth, or a superposition of wave packets of different frequencies, phases, and amplitudes. Such characteristics correspond to measured characteristics of hiss waves in this region. Using test particle simulations with typical wave and plasma parameters, we demonstrate that the corresponding stochastic transverse ion heating reaches 0.07-0.2 eV/h for protons and 0.007-0.015 eV/h for O+ ions. This global temperature increase of the Maxwellian ion population from an initial Ti approx. 0.3 eV could potentially explain the observations.
Ge, Mei; Mainprize, James G.; Mawdsley, Gordon E.; Yaffe, Martin J.
2014-01-01
Abstract. Accurate and automatic segmentation of the pectoralis muscle is essential in many breast image processing procedures, for example, in the computation of volumetric breast density from digital mammograms. Its segmentation is a difficult task due to the heterogeneity of the region, neighborhood complexities, and shape variability. The segmentation is achieved by pixel classification through a Markov random field (MRF) image model. Using the image intensity feature as observable data and local spatial information as a priori, the posterior distribution is estimated in a stochastic process. With a variable potential component in the energy function, by the maximum a posteriori (MAP) estimate of the labeling image, given the image intensity feature which is assumed to follow a Gaussian distribution, we achieved convergence properties in an appropriate sense by Metropolis sampling the posterior distribution of the selected energy function. By proposing an adjustable spatial constraint, the MRF-MAP model is able to embody the shape requirement and provide the required flexibility for the model parameter fitting process. We demonstrate that accurate and robust segmentation can be achieved for the curving-triangle-shaped pectoralis muscle in the medio-lateral-oblique (MLO) view, and the semielliptic-shaped muscle in cranio-caudal (CC) view digital mammograms. The applicable mammograms can be either “For Processing” or “For Presentation” image formats. The algorithm was developed using 56 MLO-view and 79 CC-view FFDM “For Processing” images, and quantitatively evaluated against a random selection of 122 MLO-view and 173 CC-view FFDM images of both presentation intent types. PMID:26158068
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
The non-equilibrium allele frequency spectrum in a Poisson random field framework.
Kaj, Ingemar; Mugal, Carina F
2016-10-01
In population genetic studies, the allele frequency spectrum (AFS) efficiently summarizes genome-wide polymorphism data and shapes a variety of allele frequency-based summary statistics. While existing theory typically features equilibrium conditions, emerging methodology requires an analytical understanding of the build-up of the allele frequencies over time. In this work, we use the framework of Poisson random fields to derive new representations of the non-equilibrium AFS for the case of a Wright-Fisher population model with selection. In our approach, the AFS is a scaling-limit of the expectation of a Poisson stochastic integral and the representation of the non-equilibrium AFS arises in terms of a fixation time probability distribution. The known duality between the Wright-Fisher diffusion process and a birth and death process generalizing Kingman's coalescent yields an additional representation. The results carry over to the setting of a random sample drawn from the population and provide the non-equilibrium behavior of sample statistics. Our findings are consistent with and extend a previous approach where the non-equilibrium AFS solves a partial differential forward equation with a non-traditional boundary condition. Moreover, we provide a bridge to previous coalescent-based work, and hence tie several frameworks together. Since frequency-based summary statistics are widely used in population genetics, for example, to identify candidate loci of adaptive evolution, to infer the demographic history of a population, or to improve our understanding of the underlying mechanics of speciation events, the presented results are potentially useful for a broad range of topics.
The magnetic field of the Large Magellanic Cloud revealed through Faraday rotation.
Gaensler, B M; Haverkorn, M; Staveley-Smith, L; Dickey, J M; McClure-Griffiths, N M; Dickel, J R; Wolleben, M
2005-03-11
We have measured the Faraday rotation toward a large sample of polarized radio sources behind the Large Magellanic Cloud (LMC) to determine the structure of this galaxy's magnetic field. The magnetic field of the LMC consists of a coherent axisymmetric spiral of field strength approximately 1 microgauss. Strong fluctuations in the magnetic field are also seen on small (<0.5 parsec) and large (approximately 100 parsecs) scales. The large bursts of recent star formation and supernova activity in the LMC argue against standard dynamo theory, adding to the growing evidence for rapid field amplification in galaxies.
Crystalline Electric-Field Randomness in the Triangular Lattice Spin-Liquid YbMgGaO4
NASA Astrophysics Data System (ADS)
Li, Yuesheng; Adroja, Devashibhai; Bewley, Robert I.; Voneshen, David; Tsirlin, Alexander A.; Gegenwart, Philipp; Zhang, Qingming
2017-03-01
We apply moderate-high-energy inelastic neutron scattering (INS) measurements to investigate Yb3 + crystalline electric field (CEF) levels in the triangular spin-liquid candidate YbMgGaO4 . Three CEF excitations from the ground-state Kramers doublet are centered at the energies ℏω =39 , 61, and 97 meV in agreement with the effective spin-1 /2 g factors and experimental heat capacity, but reveal sizable broadening. We argue that this broadening originates from the site mixing between Mg2 + and Ga3 + giving rise to a distribution of Yb-O distances and orientations and, thus, of CEF parameters that account for the peculiar energy profile of the CEF excitations. The CEF randomness gives rise to a distribution of the effective spin-1 /2 g factors and explains the unprecedented broadening of low-energy magnetic excitations in the fully polarized ferromagnetic phase of YbMgGaO4 , although a distribution of magnetic couplings due to the Mg /Ga disorder may be important as well.
Miao, Hongchen; Zhou, Xilong; Dong, Shuxiang; Luo, Haosu; Li, Faxin
2014-08-07
Controlling electric polarization (or magnetization) in multiferroic materials with external magnetic fields (or electric fields) is very important for fundamental physics and spintronic devices. Although there has been some progress on magnetic-field-induced polarization reversal in single-phase multiferroics, such behavior has so far never been realized in composites. Here we show that it is possible to reverse ferroelectric polarization using magnetic fields in a bilayer Terfenol-D/PMN-33%PT composite. We realized this by ferroelectric domain imaging using piezoresponse force microscopy (PFM) under applied magnetic field loading. The internal electric field caused by the magnetoelectric (ME) effect in the PMN-PT crystal is considered as the driving force for the 180° polarization switching, and its existence is verified by switching spectroscopy PFM testing under a series of external magnetic fields. A quantitative method is further suggested to estimate the local ME coefficient based on the switching spectroscopy PFM testing results.
NASA Astrophysics Data System (ADS)
Heinemann, Colleen
Research in material science is increasingly reliant on image-based data from experiments, demanding construction of new analysis tools that help scientists discover information from digital images. Because there is such a wide variety of materials and image modalities, detecting different compounds from imaged materials continues to be a challenging task. A vast collection of algorithms for filtering, image segmentation, and texture description have facilitated and improved accuracy for sample measurements (see Chapter 1 Introduction and Literature Review). Despite this, the community still lacks scalable, general purpose, easily configurable image analysis frameworks that allow pattern detection on different imaging modalities across multiple scales. The need for such a framework was the motivation behind the development of a distributed-memory parallel Markov Random Field based framework. Markov Random Field (MRF) algorithms provide the ability to explore contextual information about a given dataset. Given the complexity of such algorithms, however, they are limited by performance when running serial. Thus, running in some sort of parallel fashion is necessary. The effects are twofold. Not only does running the MRF algorithm in parallel provide the ability to run current datasets faster and more efficiently, it also provides the ability for datasets to continue to grow in size and still be able to be run with such frameworks. The variation of the Markov Random Field algorithm utilized in this study first oversegments the given input image and constructs a graph model based on photometric and geometric distances. Next, the resulting graph model is refactored specifically into the MRF model to target image segmentation. Finally, a distributed approach is used for the optimization process to obtain the best labeling for the graph, which is essentially the goal of using a MRF algorithm. Given the concept of using a distributed memory parallel framework, specifically
Active drumlin field revealed at the margin of Múlajökull, Iceland: a surge-type glacier
NASA Astrophysics Data System (ADS)
Schomacker, A.; Johnson, M. D.; Benediktsson, I.; Ingolfsson, O.; Geiger, A. J.; Ferguson, A.
2010-12-01
Recent marginal retreat of Múlajökull, a surge-type, outlet glacier of the Hofsjökull ice cap, central Iceland, has revealed a drumlin field consisting of over 50 drumlins. The drumlins are 90-320 m long, 30-105 m wide, 5-10 m in relief, and composed of multiple beds of till deposited by lodgement and bed deformation. The youngest till layer truncates the older units with an erosion surface that parallels the drumlin form. Thus, the drumlins are built up and formed by a combination of subglacial depositional and erosional processes. Field evidence suggests each till bed to be associated with individual, recent surges. We consider the drumlin field to be active in the sense that the drumlins are shaped by the current glacial regime. The Múlajökull field is the only known active drumlin field and is, therefore, a unique analogue to Pleistocene drumlin fields.
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.
Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas
2016-06-03
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.
NASA Astrophysics Data System (ADS)
Liang, Ya-Qiu; Wei, Guo-Zhu; Xu, Xiao-Juan; Song, Guo-Li
2010-05-01
The longitudinal-random-field mixed Ising model consisting of arbitrary spin values has been studied by the use of an effective field theory with correlations (EFT). The phase diagrams of systems with mixed spins: σ = 1/2, S = 1; σ = 1/2, S = 3/2 are plotted. Not only the discontinuity at T = 0 K, is found when both longitudinal fields are trimodal distributed, but also the tricritical behavior is observed in these phase diagrams between the bimodal and trimodal distributions of longitudinal fields, which is different from the single-spin one. The appearance of tricritical point is independent of the coordination number and spin values.
Atomic electric fields revealed by a quantum mechanical approach to electron picodiffraction.
Müller, Knut; Krause, Florian F; Béché, Armand; Schowalter, Marco; Galioit, Vincent; Löffler, Stefan; Verbeeck, Johan; Zweck, Josef; Schattschneider, Peter; Rosenauer, Andreas
2014-12-15
By focusing electrons on probes with a diameter of 50 pm, aberration-corrected scanning transmission electron microscopy (STEM) is currently crossing the border to probing subatomic details. A major challenge is the measurement of atomic electric fields using differential phase contrast (DPC) microscopy, traditionally exploiting the concept of a field-induced shift of diffraction patterns. Here we present a simplified quantum theoretical interpretation of DPC. This enables us to calculate the momentum transferred to the STEM probe from diffracted intensities recorded on a pixel array instead of conventional segmented bright-field detectors. The methodical development yielding atomic electric field, charge and electron density is performed using simulations for binary GaN as an ideal model system. We then present a detailed experimental study of SrTiO3 yielding atomic electric fields, validated by comprehensive simulations. With this interpretation and upgraded instrumentation, STEM is capable of quantifying atomic electric fields and high-contrast imaging of light atoms.
Enhancing gene regulatory network inference through data integration with markov random fields
Banf, Michael; Rhee, Seung Y.
2017-02-01
Here, a gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement). GRACE exploits biological a priori and heterogeneous data integration to generate high- confidence network predictions for eukaryotic organisms using Markov Random Fields in a semi-supervised fashion. GRACE uses a novel optimization schememore » to integrate regulatory evidence and biological relevance. It is particularly suited for model learning with sparse regulatory gold standard data. We show GRACE’s potential to produce high confidence regulatory networks compared to state of the art approaches using Drosophila melanogaster and Arabidopsis thaliana data. In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle related regulatory mechanisms and further hypothesizes several novel regulatory links, including a putative control mechanism of vascular structure formation due to modifications in cell proliferation.« less
Subject-adaptive real-time sleep stage classification based on conditional random field.
Luo, Gang; Min, Wanli
2007-10-11
Sleep staging is the pattern recognition task of classifying sleep recordings into sleep stages. This task is one of the most important steps in sleep analysis. It is crucial for the diagnosis and treatment of various sleep disorders, and also relates closely to brain-machine interfaces. We report an automatic, online sleep stager using electroencephalogram (EEG) signal based on a recently-developed statistical pattern recognition method, conditional random field, and novel potential functions that have explicit physical meanings. Using sleep recordings from human subjects, we show that the average classification accuracy of our sleep stager almost approaches the theoretical limit and is about 8% higher than that of existing systems. Moreover, for a new subject S(new) with limited training data D(new), we perform subject adaptation to improve classification accuracy. Our idea is to use the knowledge learned from old subjects to obtain from D(new) a regulated estimate of CRF's parameters. Using sleep recordings from human subjects, we show that even without any D(new), our sleep stager can achieve an average classification accuracy of 70% on S(new). This accuracy increases with the size of D(new) and eventually becomes close to the theoretical limit.
NASA Astrophysics Data System (ADS)
Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael
2009-02-01
Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.
Enhancing gene regulatory network inference through data integration with markov random fields
Banf, Michael; Rhee, Seung Y.
2017-01-01
A gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement). GRACE exploits biological a priori and heterogeneous data integration to generate high- confidence network predictions for eukaryotic organisms using Markov Random Fields in a semi-supervised fashion. GRACE uses a novel optimization scheme to integrate regulatory evidence and biological relevance. It is particularly suited for model learning with sparse regulatory gold standard data. We show GRACE’s potential to produce high confidence regulatory networks compared to state of the art approaches using Drosophila melanogaster and Arabidopsis thaliana data. In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle related regulatory mechanisms and further hypothesizes several novel regulatory links, including a putative control mechanism of vascular structure formation due to modifications in cell proliferation. PMID:28145456
NASA Astrophysics Data System (ADS)
Aghighi, Hossein; Trinder, John
2013-10-01
Markov random field (MRF) is currently the most common method to find the optimal solution for the classification of image data incorporating contextual visual information. The labeling for a site in MRF is dependent on smoothing parameters. Therefore, this paper deals with the development of a new robust two-step method to determine the smoothing parameter which balances spatial and spectral energies for the purpose of maximizing the classification accuracy. Multispectral images obtained by WorldView-2 satellite were employed in this research. In the first step, a support vector machine (SVM) was used to provide a vector of multi-class probability and a class label for each pixel. Then, the summation of the maximum probability of each pixel and its 8 neighbors is calculated for a dynamic block and this value is assigned to the central pixels of each block. The blocks of each class are sorted and an equal proportion of blocks of each class with the highest probability are selected. Then, the class codes and spectral information of the selected blocks are extracted from the classified map and multispectral image, respectively. This information is used to calculate class label co-occurrence matrices of the blocks (CLCMB), class label co-occurrence matrix (CLCM) and class separability indices. Finally, different smoothing parameters are calculated and the results show that estimated smoothing parameter can produce a more accurate map.
Beyond-mean-field corrections within the second random-phase approximation
NASA Astrophysics Data System (ADS)
Grasso, M.; Gambacurta, D.; Engel, J.
2016-06-01
A subtraction procedure, introduced to overcome double-counting problems in beyond-mean-field theories, is used in the second random-phase approximation (SRPA). Doublecounting problems arise in the energy-density functional framework in all cases where effective interactions tailored at leading order are used for higher-order calculations, such as those done in the SRPA model. It was recently shown that this subtraction procedure also guarantees that the stability condition related to the Thouless theorem is verified in extended RPA models. We discuss applications of the subtraction procedure, introduced within the SRPA model, to the nucleus 16O. The application of the subtraction procedure leads to: (i) stable results that are weakly cutoff dependent; (ii) a considerable upwards correction of the SRPA spectra (which were systematically shifted downwards by several MeV with respect to RPA spectra, in all previous calculations). With this important implementation of the model, many applications may be foreseen to analyze the genuine impact of 2 particle-2 hole configurations (without any cutoff dependences and anomalous shifts) on the excitation spectra of medium-mass and heavy nuclei.
Wei, Qikang; Chen, Tao; Xu, Ruifeng; He, Yulan; Gui, Lin
2016-01-01
The recognition of disease and chemical named entities in scientific articles is a very important subtask in information extraction in the biomedical domain. Due to the diversity and complexity of disease names, the recognition of named entities of diseases is rather tougher than those of chemical names. Although there are some remarkable chemical named entity recognition systems available online such as ChemSpot and tmChem, the publicly available recognition systems of disease named entities are rare. This article presents a system for disease named entity recognition (DNER) and normalization. First, two separate DNER models are developed. One is based on conditional random fields model with a rule-based post-processing module. The other one is based on the bidirectional recurrent neural networks. Then the named entities recognized by each of the DNER model are fed into a support vector machine classifier for combining results. Finally, each recognized disease named entity is normalized to a medical subject heading disease name by using a vector space model based method. Experimental results show that using 1000 PubMed abstracts for training, our proposed system achieves an F1-measure of 0.8428 at the mention level and 0.7804 at the concept level, respectively, on the testing data of the chemical-disease relation task in BioCreative V.Database URL: http://219.223.252.210:8080/SS/cdr.html. © The Author(s) 2016. Published by Oxford University Press.
Zeng, Jia; Liu, Zhi-Qiang
2008-05-01
This paper proposes a statistical-structural character modeling method based on Markov random fields (MRFs) for handwritten Chinese character recognition (HCCR). The stroke relationships of a Chinese character reflect its structure, which can be statistically represented by the neighborhood system and clique potentials within the MRF framework. Based on the prior knowledge of character structures, we design the neighborhood system that accounts for the most important stroke relationships. We penalize the structurally mismatched stroke relationships with MRFs using the prior clique potentials, and derive the likelihood clique potentials from Gaussian mixture models, which encode the large variations of stroke relationships statistically. In the proposed HCCR system, we use the single-site likelihood clique potentials to extract many candidate strokes from character images, and use the pairsite clique potentials to determine the best structural match between the input candidate strokes and the MRF-based character models by relaxation labeling. The experiments on the KAIST character database demonstrate that MRFs can statistically model character structures, and work well in the HCCR system.
Automatic Lung Tumor Segmentation on PET/CT Images Using Fuzzy Markov Random Field Model
Guo, Yu; Feng, Yuanming; Sun, Jian; Lin, Wang; Sa, Yu; Wang, Ping
2014-01-01
The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum. PMID:24987451
Human fixation detection model in video compressed domain based on Markov random field
NASA Astrophysics Data System (ADS)
Li, Yongjun; Li, Yunsong; Liu, Weijia; Hu, Jing; Ge, Chiru
2017-01-01
Recently, research on and applications of human fixation detection in video compressed domain have gained increasing attention. However, prediction accuracy and computational complexity still remain a challenge. This paper addresses the problem of compressed domain fixations detection in the videos based on residual discrete cosine transform coefficients norm (RDCN) and Markov random field (MRF). RDCN feature is directly extracted from the compressed video with partial decoding and is normalized. After spatial-temporal filtering, the normalized map [Smoothed RDCN (SRDCN) map] is taken to the MRF model, and the optimal binary label map is obtained. Based on the label map and the center saliency map, saliency enhancement and nonsaliency inhibition are done for the SRDCN map, and the final SRDCN-MRF salient map is obtained. Compared with the similar models, we enhance the available energy functions and introduce an energy function that indicates the positional information of the saliency. The procedure is advantageous for improving prediction accuracy and reducing computational complexity. The validation and comparison are made by several accuracy metrics on two ground truth datasets. Experimental results show that the proposed saliency detection model achieves superior performances over several state-of-the-art compressed-domain and pixel-domain algorithms on evaluation metrics. Computationally, our algorithm reduces 26% more computational complexity with comparison to similar algorithms.
Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model
Cheng, Hongju; Su, Zhihuang; Lloret, Jaime; Chen, Guolong
2014-01-01
Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime. PMID:25384005
High energy X-ray phase and dark-field imaging using a random absorption mask
Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal
2016-01-01
High energy X-ray imaging has unique advantage over conventional X-ray imaging, since it enables higher penetration into materials with significantly reduced radiation damage. However, the absorption contrast in high energy region is considerably low due to the reduced X-ray absorption cross section for most materials. Even though the X-ray phase and dark-field imaging techniques can provide substantially increased contrast and complementary information, fabricating dedicated optics for high energies still remain a challenge. To address this issue, we present an alternative X-ray imaging approach to produce transmission, phase and scattering signals at high X-ray energies by using a random absorption mask. Importantly, in addition to the synchrotron radiation source, this approach has been demonstrated for practical imaging application with a laboratory-based microfocus X-ray source. This new imaging method could be potentially useful for studying thick samples or heavy materials for advanced research in materials science. PMID:27466217
CHEMDNER system with mixed conditional random fields and multi-scale word clustering.
Lu, Yanan; Ji, Donghong; Yao, Xiaoyuan; Wei, Xiaomei; Liang, Xiaohui
2015-01-01
The chemical compound and drug name recognition plays an important role in chemical text mining, and it is the basis for automatic relation extraction and event identification in chemical information processing. So a high-performance named entity recognition system for chemical compound and drug names is necessary. We developed a CHEMDNER system based on mixed conditional random fields (CRF) with word clustering for chemical compound and drug name recognition. For the word clustering, we used Brown's hierarchical algorithm and Skip-gram model based on deep learning with massive PubMed articles including titles and abstracts. This system achieved the highest F-score of 88.20% for the CDI task and the second highest F-score of 87.11% for the CEM task in BioCreative IV. The performance was further improved by multi-scale clustering based on deep learning, achieving the F-score of 88.71% for CDI and 88.06% for CEM. The mixed CRF model represents both the internal complexity and external contexts of the entities, and the model is integrated with word clustering to capture domain knowledge with PubMed articles including titles and abstracts. The domain knowledge helps to ensure the performance of the entity recognition, even without fine-grained linguistic features and manually designed rules.
Szeliski, Richard; Zabih, Ramin; Scharstein, Daniel; Veksler, Olga; Kolmogorov, Vladimir; Agarwala, Aseem; Tappen, Marshall; Rother, Carsten
2008-06-01
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation. It has been known for decades that such problems can be elegantly expressed as Markov random fields, yet the resulting energy minimization problems have been widely viewed as intractable. Recently, algorithms such as graph cuts and loopy belief propagation (LBP) have proven to be very powerful: for example, such methods form the basis for almost all the top-performing stereo methods. However, the tradeoffs among different energy minimization algorithms are still not well understood. In this paper we describe a set of energy minimization benchmarks and use them to compare the solution quality and running time of several common energy minimization algorithms. We investigate three promising recent methods graph cuts, LBP, and tree-reweighted message passing in addition to the well-known older iterated conditional modes (ICM) algorithm. Our benchmark problems are drawn from published energy functions used for stereo, image stitching, interactive segmentation, and denoising. We also provide a general-purpose software interface that allows vision researchers to easily switch between optimization methods. Benchmarks, code, images, and results are available at http://vision.middlebury.edu/MRF/.
Legendre, Alfred M.; Kuritz, Tanya; Heidel, Robert Eric; Baylor, Vivian M.
2017-01-01
Feline rhinotracheitis is a ubiquitous disease caused by feline herpesvirus type 1 (FHV-1). The disease is easily transmissible and common in multi-cat environments where even vaccinated cats can develop clinical signs of respiratory or ocular disease or both when exposed to the virus. Prior to the work reported here, there was no licensed treatment for the disease on the market. We hypothesized that polyprenyl immunostimulant (PI), an immunomodulatory veterinary biologic, would be useful in treating feline rhinotracheitis by reducing the severity of respiratory or/and ocular disease. We conducted double-blinded, randomized, placebo-controlled clinical trials in experimentally infected cats to establish the efficacy of PI. Specific pathogen-free cats were administered a placebo (n = 20) or PI (n = 20) starting on the day of FHV-1 experimental challenge. Trained, masked observers applied a standardized scoring system daily in clinical examinations for 14 days after the FHV-1 challenge. The cats treated with PI had significantly lower disease severity scores over the course of the experiment compared to the cats in the placebo group (p = 0.05). The safety studies, including a field safety study involving 390 owned cats in 10 states, showed that PI was safe to use in cats as young as 8 weeks of age. PMID:28289684
Surface roughness extraction based on Markov random field model in wavelet feature domain
NASA Astrophysics Data System (ADS)
Yang, Lei; Lei, Li-qiao
2014-12-01
Based on the computer texture analysis method, a new noncontact surface roughness measurement technique is proposed. The method is inspired by the nonredundant directional selectivity and highly discriminative nature of the wavelet representation and the capability of the Markov random field (MRF) model to capture statistical regularities. Surface roughness information contained in the texture features may be extracted based on an MRF stochastic model of textures in the wavelet feature domain. The model captures significant intrascale and interscale statistical dependencies between wavelet coefficients. To investigate the relationship between the texture features and surface roughness Ra, a simple research setup, which consists of a charge-coupled diode camera without a lens and a diode laser, was established, and the laser speckle texture patterns are acquired from some standard grinding surfaces. The research results have illustrated that surface roughness Ra has a good monotonic relationship with the texture features of the laser speckle pattern. If this measuring system is calibrated with the surface standard samples roughness beforehand, the surface roughness actual value Ra can be deduced in the case of the same material surfaces ground at the same manufacture conditions.
A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking
Shafiee, Mohammad Javad; Azimifar, Zohreh; Wong, Alexander
2015-01-01
In this work, we introduce a deep-structured conditional random field (DS-CRF) model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering. PMID:26313943
Action unit classification using active appearance models and conditional random fields.
van der Maaten, Laurens; Hendriks, Emile
2012-10-01
In this paper, we investigate to what extent modern computer vision and machine learning techniques can assist social psychology research by automatically recognizing facial expressions. To this end, we develop a system that automatically recognizes the action units defined in the facial action coding system (FACS). The system uses a sophisticated deformable template, which is known as the active appearance model, to model the appearance of faces. The model is used to identify the location of facial feature points, as well as to extract features from the face that are indicative of the action unit states. The detection of the presence of action units is performed by a time series classification model, the linear-chain conditional random field. We evaluate the performance of our system in experiments on a large data set of videos with posed and natural facial expressions. In the experiments, we compare the action units detected by our approach with annotations made by human FACS annotators. Our results show that the agreement between the system and human FACS annotators is higher than 90% and underlines the potential of modern computer vision and machine learning techniques to social psychology research. We conclude with some suggestions on how systems like ours can play an important role in research on social signals.
Enhancing gene regulatory network inference through data integration with markov random fields.
Banf, Michael; Rhee, Seung Y
2017-02-01
A gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement). GRACE exploits biological a priori and heterogeneous data integration to generate high- confidence network predictions for eukaryotic organisms using Markov Random Fields in a semi-supervised fashion. GRACE uses a novel optimization scheme to integrate regulatory evidence and biological relevance. It is particularly suited for model learning with sparse regulatory gold standard data. We show GRACE's potential to produce high confidence regulatory networks compared to state of the art approaches using Drosophila melanogaster and Arabidopsis thaliana data. In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle related regulatory mechanisms and further hypothesizes several novel regulatory links, including a putative control mechanism of vascular structure formation due to modifications in cell proliferation.
Wang, Zhiyong; Xu, Jinbo
2011-07-01
Accurate tertiary structures are very important for the functional study of non-coding RNA molecules. However, predicting RNA tertiary structures is extremely challenging, because of a large conformation space to be explored and lack of an accurate scoring function differentiating the native structure from decoys. The fragment-based conformation sampling method (e.g. FARNA) bears shortcomings that the limited size of a fragment library makes it infeasible to represent all possible conformations well. A recent dynamic Bayesian network method, BARNACLE, overcomes the issue of fragment assembly. In addition, neither of these methods makes use of sequence information in sampling conformations. Here, we present a new probabilistic graphical model, conditional random fields (CRFs), to model RNA sequence-structure relationship, which enables us to accurately estimate the probability of an RNA conformation from sequence. Coupled with a novel tree-guided sampling scheme, our CRF model is then applied to RNA conformation sampling. Experimental results show that our CRF method can model RNA sequence-structure relationship well and sequence information is important for conformation sampling. Our method, named as TreeFolder, generates a much higher percentage of native-like decoys than FARNA and BARNACLE, although we use the same simple energy function as BARNACLE. zywang@ttic.edu; j3xu@ttic.edu Supplementary data are available at Bioinformatics online.
Singular-potential random-matrix model arising in mean-field glassy systems
NASA Astrophysics Data System (ADS)
Akemann, Gernot; Villamaina, Dario; Vivo, Pierpaolo
2014-06-01
We consider an invariant random matrix ensemble where the standard Gaussian potential is distorted by an additional single pole of arbitrary fixed order. Potentials with first- and second-order poles have been considered previously and found applications in quantum chaos and number theory. Here we present an application to mean-field glassy systems. We derive and solve the loop equation in the planar limit for the corresponding class of potentials. We find that the resulting mean or macroscopic spectral density is generally supported on two disconnected intervals lying on the two sides of the repulsive pole, whose edge points can be completely determined imposing the additional constraint of traceless matrices on average. For an unbounded potential with an attractive pole, we also find a possible one-cut solution for certain values of the couplings, which is ruled out when the traceless condition is imposed. Motivated by the calculation of the distribution of the spin-glass susceptibility in the Sherrington-Kirkpatrick spin-glass model, we consider in detail a second-order pole for a zero-trace model and provide the most explicit solution in this case. In the limit of a vanishing pole, we recover the standard semicircle. Working in the planar limit, our results apply to matrices with orthogonal, unitary, and symplectic invariance. Numerical simulations and an independent analytical Coulomb fluid calculation for symmetric potentials provide an excellent confirmation of our results.
Heterogeneous Memorized Continuous Time Random Walks in an External Force Fields
NASA Astrophysics Data System (ADS)
Wang, Jun; Zhou, Ji; Lv, Long-Jin; Qiu, Wei-Yuan; Ren, Fu-Yao
2014-09-01
In this paper, we study the anomalous diffusion of a particle in an external force field whose motion is governed by nonrenewal continuous time random walks with correlated memorized waiting times, which involves Reimann-Liouville fractional derivative or Reimann-Liouville fractional integral. We show that the mean squared displacement of the test particle which is dependent on its location of the form (El-Wakil and Zahran, Chaos Solitons Fractals, 12, 1929-1935, 2001) where is the anomalous exponent, the diffusion exponent is dependent on the model parameters. We obtain the Fokker-Planck-type dynamic equations, and their stationary solutions are of the Boltzmann-Gibbs form. These processes obey a generalized Einstein-Stokes-Smoluchowski relation and the second Einstein relation. We observe that the asymptotic behavior of waiting times and subordinations are of stretched Gaussian distributions. We also discuss the time averaged in the case of an harmonic potential, and show that the process exhibits aging and ergodicity breaking.
Wei, Qikang; Chen, Tao; Xu, Ruifeng; He, Yulan; Gui, Lin
2016-01-01
The recognition of disease and chemical named entities in scientific articles is a very important subtask in information extraction in the biomedical domain. Due to the diversity and complexity of disease names, the recognition of named entities of diseases is rather tougher than those of chemical names. Although there are some remarkable chemical named entity recognition systems available online such as ChemSpot and tmChem, the publicly available recognition systems of disease named entities are rare. This article presents a system for disease named entity recognition (DNER) and normalization. First, two separate DNER models are developed. One is based on conditional random fields model with a rule-based post-processing module. The other one is based on the bidirectional recurrent neural networks. Then the named entities recognized by each of the DNER model are fed into a support vector machine classifier for combining results. Finally, each recognized disease named entity is normalized to a medical subject heading disease name by using a vector space model based method. Experimental results show that using 1000 PubMed abstracts for training, our proposed system achieves an F1-measure of 0.8428 at the mention level and 0.7804 at the concept level, respectively, on the testing data of the chemical-disease relation task in BioCreative V. Database URL: http://219.223.252.210:8080/SS/cdr.html PMID:27777244
NASA Astrophysics Data System (ADS)
Diaz, P. M. A.; Feitosa, R. Q.; Sanches, I. D.; Costa, G. A. O. P.
2016-06-01
This paper presents a method to estimate the temporal interaction in a Conditional Random Field (CRF) based approach for crop recognition from multitemporal remote sensing image sequences. This approach models the phenology of different crop types as a CRF. Interaction potentials are assumed to depend only on the class labels of an image site at two consecutive epochs. In the proposed method, the estimation of temporal interaction parameters is considered as an optimization problem, whose goal is to find the transition matrix that maximizes the CRF performance, upon a set of labelled data. The objective functions underlying the optimization procedure can be formulated in terms of different accuracy metrics, such as overall and average class accuracy per crop or phenological stages. To validate the proposed approach, experiments were carried out upon a dataset consisting of 12 co-registered LANDSAT images of a region in southeast of Brazil. Pattern Search was used as the optimization algorithm. The experimental results demonstrated that the proposed method was able to substantially outperform estimates related to joint or conditional class transition probabilities, which rely on training samples.
NASA Astrophysics Data System (ADS)
Zhu, Leqing; Wang, Xun; Wang, Dadong; Wang, Huiyan
2016-10-01
Deep convolutional neural networks (DCNNs) have attracted significant interest in the computer vision community in the recent years and have exhibited high performance in resolving many computer vision problems, such as image classification. We address the pixel-level depth prediction from a single image by combining DCNN and sparse connected conditional random field (CRF). Owing to the invariance properties of DCNNs that make them suitable for high-level tasks, their outputs are generally not localized enough for detailed pixel-level regression. A multiscale DCNN and sparse connected CRF are combined to overcome this localization weakness. We have evaluated our framework using the well-known NYU V2 depth dataset, and the results show that the proposed method can improve the depth prediction accuracy both qualitatively and quantitatively, as compared to previous works. This finding shows the potential use of the proposed method in three-dimensional (3-D) modeling or 3-D video production from the given two-dimensional (2-D) images or 2-D videos.
An efficient conditional random field approach for automatic and interactive neuron segmentation.
Uzunbas, Mustafa Gokhan; Chen, Chao; Metaxas, Dimitris
2016-01-01
We present a new graphical-model-based method for automatic and interactive segmentation of neuron structures from electron microscopy (EM) images. For automated reconstruction, our learning based model selects a collection of nodes from a hierarchical merging tree as the proposed segmentation. More specifically, this is achieved by training a conditional random field (CRF) whose underlying graph is the watershed merging tree. The maximum a posteriori (MAP) prediction of the CRF is the output segmentation. Our results are comparable to the results of state-of-the-art methods. Furthermore, both the inference and the training are very efficient as the graph is tree-structured. The problem of neuron segmentation requires extremely high segmentation quality. Therefore, proofreading, namely, interactively correcting mistakes of the automatic method, is a necessary module in the pipeline. Based on our efficient tree-structured inference algorithm, we develop an interactive segmentation framework which only selects locations where the model is uncertain for a user to proofread. The uncertainty is measured by the marginals of the graphical model. Only giving a limited number of choices makes the user interaction very efficient. Based on user corrections, our framework modifies the merging tree and thus improves the segmentation globally.
Colloids in light fields: Particle dynamics in random and periodic energy landscapes
NASA Astrophysics Data System (ADS)
Evers, F.; Hanes, R. D. L.; Zunke, C.; Capellmann, R. F.; Bewerunge, J.; Dalle-Ferrier, C.; Jenkins, M. C.; Ladadwa, I.; Heuer, A.; Castañeda-Priego, R.; Egelhaaf, S. U.
2013-11-01
The dynamics of colloidal particles in potential energy landscapes have mainly been investigated theoretically. In contrast, here we discuss the experimental realization of potential energy landscapes with the help of laser light fields and the observation of the particle dynamics by video microscopy. The experimentally observed dynamics in periodic and random potentials are compared to simulation and theoretical results in terms of, e.g. the mean-squared displacement, the time-dependent diffusion coefficient or the non-Gaussian parameter. The dynamics are initially diffusive followed by intermediate subdiffusive behaviour which again becomes diffusive at long times. How pronounced and extended the different regimes are, depends on the specific conditions, in particular the shape of the potential as well as its roughness or amplitude but also the particle concentration. Here we focus on dilute systems, but the dynamics of interacting systems in external potentials, and thus the interplay between particle-particle and particle-potential interactions, are also mentioned briefly. Furthermore, the observed dynamics of dilute systems resemble the dynamics of concentrated systems close to their glass transition, with which it is compared. The effect of certain potential energy landscapes on the dynamics of individual particles appears similar to the effect of interparticle interactions in the absence of an external potential.
Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.
Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping
2014-01-01
The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.
Chang, Ju Yong
2016-08-01
We present a new gesture recognition method that is based on the conditional random field (CRF) model using multiple feature matching. Our approach solves the labeling problem, determining gesture categories and their temporal ranges at the same time. A generative probabilistic model is formalized and probability densities are nonparametrically estimated by matching input features with a training dataset. In addition to the conventional skeletal joint-based features, the appearance information near the active hand in an RGB image is exploited to capture the detailed motion of fingers. The estimated likelihood function is then used as the unary term for our CRF model. The smoothness term is also incorporated to enforce the temporal coherence of our solution. Frame-wise recognition results can then be obtained by applying an efficient dynamic programming technique. To estimate the parameters of the proposed CRF model, we incorporate the structured support vector machine (SSVM) framework that can perform efficient structured learning by using large-scale datasets. Experimental results demonstrate that our method provides effective gesture recognition results for challenging real gesture datasets. By scoring 0.8563 in the mean Jaccard index, our method has obtained the state-of-the-art results for the gesture recognition track of the 2014 ChaLearn Looking at People (LAP) Challenge.
Singular-potential random-matrix model arising in mean-field glassy systems.
Akemann, Gernot; Villamaina, Dario; Vivo, Pierpaolo
2014-06-01
We consider an invariant random matrix ensemble where the standard Gaussian potential is distorted by an additional single pole of arbitrary fixed order. Potentials with first- and second-order poles have been considered previously and found applications in quantum chaos and number theory. Here we present an application to mean-field glassy systems. We derive and solve the loop equation in the planar limit for the corresponding class of potentials. We find that the resulting mean or macroscopic spectral density is generally supported on two disconnected intervals lying on the two sides of the repulsive pole, whose edge points can be completely determined imposing the additional constraint of traceless matrices on average. For an unbounded potential with an attractive pole, we also find a possible one-cut solution for certain values of the couplings, which is ruled out when the traceless condition is imposed. Motivated by the calculation of the distribution of the spin-glass susceptibility in the Sherrington-Kirkpatrick spin-glass model, we consider in detail a second-order pole for a zero-trace model and provide the most explicit solution in this case. In the limit of a vanishing pole, we recover the standard semicircle. Working in the planar limit, our results apply to matrices with orthogonal, unitary, and symplectic invariance. Numerical simulations and an independent analytical Coulomb fluid calculation for symmetric potentials provide an excellent confirmation of our results.
Spatio-temporal fMRI analysis using Markov random fields.
Descombes, X; Kruggel, F; von Cramon, D Y
1998-12-01
Functional magnetic resonance images (fMRI's) provide high-resolution datasets which allow researchers to obtain accurate delineation and sensitive detection of activation areas involved in cognitive processes. To preserve the resolution of this noninvasive technique, refined methods are required in the analysis of the data. In this paper, we first discuss the widely used methods based on a statistical parameter map (SPM) analysis exposing the different shortcomings of this approach when considering high-resolution data. First, the often used Gaussian filtering results in a blurring effect and in delocalization of the activated area. Secondly, the SPM approach only considers false alarms due to noise but not rejections of activated voxels. We propose to embed the fMRI analysis problem into a Bayesian framework consisting of two steps: i) data restoration and ii) data analysis. We, therefore, propose two Markov random fields (MRF's) to solve these two problems. Results on three protocols (visual, motor and word recognition) are shown for two SPM approaches and compared with the proposed MRF approach.
Building Roof Boundary Extraction from LiDAR and Image Data Based on Markov Random Field
NASA Astrophysics Data System (ADS)
Dal Poz, A. P.; Fernandes, V. J. M.
2017-05-01
In this paper a method for automatic extraction of building roof boundaries is proposed, which combines LiDAR data and highresolution aerial images. The proposed method is based on three steps. In the first step aboveground objects are extracted from LiDAR data. Initially a filtering algorithm is used to process the original LiDAR data for getting ground and non-ground points. Then, a region-growing procedure and the convex hull algorithm are sequentially used to extract polylines that represent aboveground objects from the non-ground point cloud. The second step consists in extracting corresponding LiDAR-derived aboveground objects from a high-resolution aerial image. In order to avoid searching for the interest objects over the whole image, the LiDAR-derived aboveground objects' polylines are photogrammetrically projected onto the image space and rectangular bounding boxes (sub-images) that enclose projected polylines are generated. Each sub-image is processed for extracting the polyline that represents the interest aboveground object within the selected sub-image. Last step consists in identifying polylines that represent building roof boundaries. We use the Markov Random Field (MRF) model for modelling building roof characteristics and spatial configurations. Polylines that represent building roof boundaries are found by optimizing the resulting MRF energy function using the Genetic Algorithm. Experimental results are presented and discussed in this paper.
Medina, Rubén; Garreau, Mireille; Toro, Javier; Le Breton, Hervé; Coatrieux, Jean-Louis; Jugo, Diego
2006-01-01
This paper reports on a method for left ventricle three-dimensional reconstruction from two orthogonal ventriculograms. The proposed algorithm is voxel-based and takes into account the conical projection geometry associated with the biplane image acquisition equipment. The reconstruction process starts with an initial ellipsoidal approximation derived from the input ventriculograms. This model is subsequently deformed in such a way as to match the input projections. To this end, the object is modeled as a three-dimensional Markov-Gibbs random field, and an energy function is defined so that it includes one term that models the projections compatibility and another one that includes the space–time regularity constraints. The performance of this reconstruction method is evaluated by considering the reconstruction of mathematically synthesized phantoms and two 3-D binary databases from two orthogonal synthesized projections. The method is also tested using real biplane ventriculograms. In this case, the performance of the reconstruction is expressed in terms of the projection error, which attains values between 9.50% and 11.78 % for two biplane sequences including a total of 55 images. PMID:16895001
Random-field Ising model on isometric lattices: Ground states and non-Porod scattering.
Bupathy, Arunkumar; Banerjee, Varsha; Puri, Sanjay
2016-01-01
We use a computationally efficient graph cut method to obtain ground state morphologies of the random-field Ising model (RFIM) on (i) simple cubic (SC), (ii) body-centered cubic (BCC), and (iii) face-centered cubic (FCC) lattices. We determine the critical disorder strength Δ_{c} at zero temperature with high accuracy. For the SC lattice, our estimate (Δ_{c}=2.278±0.002) is consistent with earlier reports. For the BCC and FCC lattices, Δ_{c}=3.316±0.002 and 5.160±0.002, respectively, which are the most accurate estimates in the literature to date. The small-r behavior of the correlation function exhibits a cusp regime characterized by a cusp exponent α signifying fractal interfaces. In the paramagnetic phase, α=0.5±0.01 for all three lattices. In the ferromagnetic phase, the cusp exponent shows small variations due to the lattice structure. Consequently, the interfacial energy E_{i}(L) for an interface of size L is significantly different for the three lattices. This has important implications for nonequilibrium properties.
Context-aware patch-based image inpainting using Markov random field modeling.
Ružić, Tijana; Pižurica, Aleksandra
2015-01-01
In this paper, we first introduce a general approach for context-aware patch-based image inpainting, where textural descriptors are used to guide and accelerate the search for well-matching (candidate) patches. A novel top-down splitting procedure divides the image into variable size blocks according to their context, constraining thereby the search for candidate patches to nonlocal image regions with matching context. This approach can be employed to improve the speed and performance of virtually any (patch-based) inpainting method. We apply this approach to the so-called global image inpainting with the Markov random field (MRF) prior, where MRF encodes a priori knowledge about consistency of neighboring image patches. We solve the resulting optimization problem with an efficient low-complexity inference method. Experimental results demonstrate the potential of the proposed approach in inpainting applications like scratch, text, and object removal. Improvement and significant acceleration of a related global MRF-based inpainting method is also evident.
Handwritten Chinese/Japanese text recognition using semi-Markov conditional random fields.
Zhou, Xiang-Dong; Wang, Da-Han; Tian, Feng; Liu, Cheng-Lin; Nakagawa, Masaki
2013-10-01
This paper proposes a method for handwritten Chinese/Japanese text (character string) recognition based on semi-Markov conditional random fields (semi-CRFs). The high-order semi-CRF model is defined on a lattice containing all possible segmentation-recognition hypotheses of a string to elegantly fuse the scores of candidate character recognition and the compatibilities of geometric and linguistic contexts by representing them in the feature functions. Based on given models of character recognition and compatibilities, the fusion parameters are optimized by minimizing the negative log-likelihood loss with a margin term on a training string sample set. A forward-backward lattice pruning algorithm is proposed to reduce the computation in training when trigram language models are used, and beam search techniques are investigated to accelerate the decoding speed. We evaluate the performance of the proposed method on unconstrained online handwritten text lines of three databases. On the test sets of databases CASIA-OLHWDB (Chinese) and TUAT Kondate (Japanese), the character level correct rates are 95.20 and 95.44 percent, and the accurate rates are 94.54 and 94.55 percent, respectively. On the test set (online handwritten texts) of ICDAR 2011 Chinese handwriting recognition competition, the proposed method outperforms the best system in competition.
A new method for direction finding based on Markov random field model
NASA Astrophysics Data System (ADS)
Ota, Mamoru; Kasahara, Yoshiya; Goto, Yoshitaka
2015-07-01
Investigating the characteristics of plasma waves observed by scientific satellites in the Earth's plasmasphere/magnetosphere is effective for understanding the mechanisms for generating waves and the plasma environment that influences wave generation and propagation. In particular, finding the propagation directions of waves is important for understanding mechanisms of VLF/ELF waves. To find these directions, the wave distribution function (WDF) method has been proposed. This method is based on the idea that observed signals consist of a number of elementary plane waves that define wave energy density distribution. However, the resulting equations constitute an ill-posed problem in which a solution is not determined uniquely; hence, an adequate model must be assumed for a solution. Although many models have been proposed, we have to select the most optimum model for the given situation because each model has its own advantages and disadvantages. In the present study, we propose a new method for direction finding of the plasma waves measured by plasma wave receivers. Our method is based on the assumption that the WDF can be represented by a Markov random field model with inference of model parameters performed using a variational Bayesian learning algorithm. Using computer-generated spectral matrices, we evaluated the performance of the model and compared the results with those obtained from two conventional methods.
The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS.
Aravkin, Aleksandr Y; Bell, Bradley M; Burke, James V; Pillonetto, Gianluigi
2015-07-01
Reconstruction of a function from noisy data is key in machine learning and is often formulated as a regularized optimization problem over an infinite-dimensional reproducing kernel Hilbert space (RKHS). The solution suitably balances adherence to the observed data and the corresponding RKHS norm. When the data fit is measured using a quadratic loss, this estimator has a known statistical interpretation. Given the noisy measurements, the RKHS estimate represents the posterior mean (minimum variance estimate) of a Gaussian random field with covariance proportional to the kernel associated with the RKHS. In this brief, we provide a statistical interpretation when more general losses are used, such as absolute value, Vapnik or Huber. Specifically, for any finite set of sampling locations (that includes where the data were collected), the maximum a posteriori estimate for the signal samples is given by the RKHS estimate evaluated at the sampling locations. This connection establishes a firm statistical foundation for several stochastic approaches used to estimate unknown regularization parameters. To illustrate this, we develop a numerical scheme that implements a Bayesian estimator with an absolute value loss. This estimator is used to learn a function from measurements contaminated by outliers.
Video object tracking in the compressed domain using spatio-temporal Markov random fields.
Khatoonabadi, Sayed Hossein; Bajić, Ivan V
2013-01-01
Despite the recent progress in both pixel-domain and compressed-domain video object tracking, the need for a tracking framework with both reasonable accuracy and reasonable complexity still exists. This paper presents a method for tracking moving objects in H.264/AVC-compressed video sequences using a spatio-temporal Markov random field (ST-MRF) model. An ST-MRF model naturally integrates the spatial and temporal aspects of the object's motion. Built upon such a model, the proposed method works in the compressed domain and uses only the motion vectors (MVs) and block coding modes from the compressed bitstream to perform tracking. First, the MVs are preprocessed through intracoded block motion approximation and global motion compensation. At each frame, the decision of whether a particular block belongs to the object being tracked is made with the help of the ST-MRF model, which is updated from frame to frame in order to follow the changes in the object's motion. The proposed method is tested on a number of standard sequences, and the results demonstrate its advantages over some of the recent state-of-the-art methods.
NASA Astrophysics Data System (ADS)
Nuzhnaya, Tatyana; Bakic, Predrag; Kontos, Despina; Megalooikonomou, Vasileios; Ling, Haibin
2012-02-01
This work is a part of our ongoing study aimed at understanding a relation between the topology of anatomical branching structures with the underlying image texture. Morphological variability of the breast ductal network is associated with subsequent development of abnormalities in patients with nipple discharge such as papilloma, breast cancer and atypia. In this work, we investigate complex dependence among ductal components to perform segmentation, the first step for analyzing topology of ductal lobes. Our automated framework is based on incorporating a conditional random field with texture descriptors of skewness, coarseness, contrast, energy and fractal dimension. These features are selected to capture the architectural variability of the enhanced ducts by encoding spatial variations between pixel patches in galactographic image. The segmentation algorithm was applied to a dataset of 20 x-ray galactograms obtained at the Hospital of the University of Pennsylvania. We compared the performance of the proposed approach with fully and semi automated segmentation algorithms based on neural network classification, fuzzy-connectedness, vesselness filter and graph cuts. Global consistency error and confusion matrix analysis were used as accuracy measurements. For the proposed approach, the true positive rate was higher and the false negative rate was significantly lower compared to other fully automated methods. This indicates that segmentation based on CRF incorporated with texture descriptors has potential to efficiently support the analysis of complex topology of the ducts and aid in development of realistic breast anatomy phantoms.
Financial versus health motivation to quit smoking: a randomized field study.
Sindelar, Jody L; O'Malley, Stephanie S
2014-02-01
Smoking is the most preventable cause of death, thus justifying efforts to effectively motivate quitting. We compared the effectiveness of financial versus health messages to motivate smoking cessation. Low-income individuals disproportionately smoke and, given their greater income constraints, we hypothesized that making financial costs of smoking more salient would encourage more smokers to try quitting. Further, we predicted that financial messages would be stronger in financial settings where pecuniary constraints are most salient. We conducted a field study in low-income areas of New Haven, Connecticut using brochures with separate health vs. financial messages to motivate smoking cessation. Displays were rotated among community settings-check-cashing, health clinics, and grocery stores. We randomized brochure displays with gain-framed cessation messages across locations. Our predictions were confirmed. Financial messages attracted significantly more attention than health messages, especially in financial settings. These findings suggest that greater emphasis on the financial gains to quitting and use of financial settings to provide cessation messages may be more effective in motivating quitting. Importantly, use of financial settings could open new, non-medical venues for encouraging cessation. Encouraging quitting could improve health, enhance spending power of low-income smokers, and reduce health disparities in both health and purchasing power. © 2013.
Impact of Markov Random Field Optimizer on MRI-based Tissue Segmentation in the Aging Brain
Schwarz, Christopher G.; Tsui, Alex; Fletcher, Evan; Singh, Baljeet; DeCarli, Charles; Carmichael, Owen
2013-01-01
Automatically segmenting brain magnetic resonance images into grey matter, white matter, and cerebrospinal fluid compartments is a fundamentally important neuroimaging problem whose difficulty is heightened in the presence of aging and neurodegenerative disease. Current methods overlap greatly in terms of identifiable algorithmic components, and the impact of specific components on performance is generally unclear in important real-world scenarios involving serial scanning, multiple scanners, and neurodegenerative disease. Therefore we evaluated the impact that one such component, the Markov Random Field (MRF) optimizer that encourages spatially-smooth tissue labelings, has on brain tissue segmentation performance. Two challenging elderly sets were used to test segmentation consistency across scanners and biological plausibility of tissue change estimates; and a simulated young brain data set was used to test accuracy against ground truth. Comparisons among Graph Cuts (GC), Belief Propagation (BP), and Iterative Conditional Modes (ICM) suggested that in the elderly brain, BP and GC provide the highest segmentation performance, with a slight advantage to BP, and that performance is often superior to that provided by popular methods SPM and FAST. Conversely, SPM and FAST excelled in the young brain, thus emphasizing the unique challenges involved in imaging the aging brain. PMID:22256150
Random-field Ising model on isometric lattices: Ground states and non-Porod scattering
NASA Astrophysics Data System (ADS)
Bupathy, Arunkumar; Banerjee, Varsha; Puri, Sanjay
2016-01-01
We use a computationally efficient graph cut method to obtain ground state morphologies of the random-field Ising model (RFIM) on (i) simple cubic (SC), (ii) body-centered cubic (BCC), and (iii) face-centered cubic (FCC) lattices. We determine the critical disorder strength Δc at zero temperature with high accuracy. For the SC lattice, our estimate (Δc=2.278 ±0.002 ) is consistent with earlier reports. For the BCC and FCC lattices, Δc=3.316 ±0.002 and 5.160 ±0.002 , respectively, which are the most accurate estimates in the literature to date. The small-r behavior of the correlation function exhibits a cusp regime characterized by a cusp exponent α signifying fractal interfaces. In the paramagnetic phase, α =0.5 ±0.01 for all three lattices. In the ferromagnetic phase, the cusp exponent shows small variations due to the lattice structure. Consequently, the interfacial energy Ei(L ) for an interface of size L is significantly different for the three lattices. This has important implications for nonequilibrium properties.
NASA Astrophysics Data System (ADS)
Tao, R.; Tang, H.
Chocolate is one of the most popular food types and flavors in the world. Unfortunately, at present, chocolate products contain too much fat, leading to obesity. For example, a typical molding chocolate has various fat up to 40% in total and chocolate for covering ice cream has fat 50 -60%. Especially, as children are the leading chocolate consumers, reducing the fat level in chocolate products to make them healthier is important and urgent. While this issue was called into attention and elaborated in articles and books decades ago and led to some patent applications, no actual solution was found unfortunately. Why is reducing fat in chocolate so difficult? What is the underlying physical mechanism? We have found that this issue is deeply related to the basic science of soft matters, especially to their viscosity and maximally random jammed (MRJ) density φx. All chocolate productions are handling liquid chocolate, a suspension with cocoa solid particles in melted fat, mainly cocoa butter. The fat level cannot be lower than 1-φxin order to have liquid chocolate to flow. Here we show that that with application of an electric field to liquid chocolate, we can aggregate the suspended particles into prolate spheroids. This microstructure change reduces liquid chocolate's viscosity along the flow direction and increases its MRJ density significantly. Hence the fat level in chocolate can be effectively reduced. We are looking forward to a new class of healthier and tasteful chocolate coming to the market soon. Dept. of Physics, Temple Univ, Philadelphia, PA 19122.
NASA Astrophysics Data System (ADS)
Han, Meng; Ge, Peipei; Shao, Yun; Liu, Ming-Ming; Deng, Yongkai; Wu, Chengyin; Gong, Qihuang; Liu, Yunquan
2017-08-01
We measure photoelectron momentum distributions of Ar atoms in orthogonally polarized two-color laser fields with comparable intensities. The synthesized laser field is used to manipulate the oscillating tunneling barrier and the subsequent motion of electrons onto two spatial dimensions. The subcycle structures associated with the temporal double-slit interference are spatially separated and enhanced. We use such a spatiotemporal interferometer to reveal sub-barrier phase of strong-field tunneling ionization. This study shows that the tunneling process transfers the initial phase onto momentum distribution. Our work has the implication that the sub-barrier phase plays an indispensable role in photoelectron interference processes.
The Spectrovideomagnetograph Reveals the True Strength of Quiet Sun Magnetic Fields
NASA Astrophysics Data System (ADS)
Zirin, H.; Cameron, R.
2000-12-01
We present new observations of weak solar magnetic fields with a technique, which we term the spectro-videomagnetograph (SPVMG) which permits direct measurement of splittings as small as 200 gauss. Using the technique of Stenflo we compared the Stokes V-component for the 5250 and 5247 lines. Contrary to Stenflo's results, we find no evidence for strong fields with small filling factor; i. e., the field strengths measured as 200 gaussare really 200 gauss and not some stronger field partly filling the sample. For the weakest measured fields this cannot be absolutely established, but the evidence supports the existence of field elements at least as weak as 200 gauss. Observations of active regions also yield new results. In many cases of fields near inversion lines, we find doubled sets of Zeeman components, as well as `flags,' broad components, usually confined to one side of the line, extending to displacements corresponding to thousands of gauss, with no corresponding component on the opposite side of the line. We show examples of these spectra, along with slit jaw images, but have only a limited understanding of the field structures they represent. We also have examples of the V-splitting increasing as we approach the inversion line. We are struggling to understand these and will at least show them, with or without explanation. Finally, the regions involving these anomalous Zeeman patterns seem to flare more frequently, although statistics are limited. This work has been supported by the NSF under ATM-9726147.
The role of magnetic fields in starburst galaxies as revealed by OH megamasers
McBride, James; Quataert, Eliot; Heiles, Carl; Bauermeister, Amber E-mail: eliot@astro.berkeley.edu
2014-01-10
We present estimates of magnetic field strengths in the interstellar media of starburst galaxies derived from measurements of Zeeman splitting associated with OH megamasers. The results for eight galaxies with Zeeman detections suggest that the magnetic energy density in the interstellar medium of starburst galaxies is comparable to their hydrostatic gas pressure, as in the Milky Way. We discuss the significant uncertainties in this conclusion, and possible measurements that could reduce these uncertainties. We also compare the Zeeman splitting derived magnetic field estimates to magnetic field strengths estimated using synchrotron fluxes and assuming that the magnetic field and cosmic rays have comparable energy densities, known as the 'minimum energy' argument. We find that the minimum energy argument systematically underestimates magnetic fields in starburst galaxies, and that the conditions that would be required to produce agreement between the minimum energy estimate and the Zeeman derived estimate of interstellar medium magnetic fields are implausible. The conclusion that magnetic fields in starburst galaxies exceed the minimum energy magnetic fields is consistent with starburst galaxies adhering to the linearity of the far-infrared-radio correlation.
Asteroseismology can reveal strong internal magnetic fields in red giant stars.
Fuller, Jim; Cantiello, Matteo; Stello, Dennis; Garcia, Rafael A; Bildsten, Lars
2015-10-23
Internal stellar magnetic fields are inaccessible to direct observations, and little is known about their amplitude, geometry, and evolution. We demonstrate that strong magnetic fields in the cores of red giant stars can be identified with asteroseismology. The fields can manifest themselves via depressed dipole stellar oscillation modes, arising from a magnetic greenhouse effect that scatters and traps oscillation-mode energy within the core of the star. The Kepler satellite has observed a few dozen red giants with depressed dipole modes, which we interpret as stars with strongly magnetized cores. We find that field strengths larger than ~10(5) gauss may produce the observed depression, and in one case we infer a minimum core field strength of ≈10(7) gauss. Copyright © 2015, American Association for the Advancement of Science.
Asteroseismology can reveal strong internal magnetic fields in red giant stars
NASA Astrophysics Data System (ADS)
Fuller, Jim; Cantiello, Matteo; Stello, Dennis; Garcia, Rafael A.; Bildsten, Lars
2015-10-01
Internal stellar magnetic fields are inaccessible to direct observations, and little is known about their amplitude, geometry, and evolution. We demonstrate that strong magnetic fields in the cores of red giant stars can be identified with asteroseismology. The fields can manifest themselves via depressed dipole stellar oscillation modes, arising from a magnetic greenhouse effect that scatters and traps oscillation-mode energy within the core of the star. The Kepler satellite has observed a few dozen red giants with depressed dipole modes, which we interpret as stars with strongly magnetized cores. We find that field strengths larger than ~105 gauss may produce the observed depression, and in one case we infer a minimum core field strength of ≈107 gauss.
The effects of random field at surface on the magnetic properties in the Ising nanotube and nanowire
NASA Astrophysics Data System (ADS)
Kaneyoshi, T.
2016-12-01
The phase diagrams and temperature dependences of total magnetization mT in two nanosystems (nanotube and nanowire) with a random magnetic field at the surface shell are studied by the uses of the effective-field theory with correlations. Some characteristic phenomena (reentrant phenomena and unconventional thermal variation of total magnetization) are found in the two systems. They are rather different between the two systems, which mainly come from the structural differences of the cores
NASA Astrophysics Data System (ADS)
Vigneau, Florian; Gül, Önder; Niquet, Yann-Michel; Car, Diana; Plissard, Sebastien R.; Escoffier, Walter; Bakkers, Erik P. A. M.; Duchemin, Ivan; Raquet, Bertrand; Goiran, Michel
2016-12-01
The charge transport properties of individual InSb nanowires based transistors are studied at 4.2 K in the quasiballistic regime. The energy level separations at zero magnetic field are extracted from a bias voltage spectroscopy. The magnetoconductance under a magnetic field applied perpendicularly to the nanowire axis is investigated up to 50 T. Owing to the magnetic reduction of the backscattering, the electronic states of the quasi-one-dimensional electron gas are revealed by Landauer-Büttiker conductance quantization. The results are compared to theoretical predictions revealing the spin and orbital degeneracy lifting. At sufficiently high magnetic field the measurements show the evolution to the quantum Hall effect regime with the formation of Landau orbits and conducting edge states.
ERIC Educational Resources Information Center
Roeser, Robert W.; Schonert-Reichl, Kimberly A.; Jha, Amishi; Cullen, Margaret; Wallace, Linda; Wilensky, Rona; Oberle, Eva; Thomson, Kimberly; Taylor, Cynthia; Harrison, Jessica
2013-01-01
The effects of randomization to mindfulness training (MT) or to a waitlist-control condition on psychological and physiological indicators of teachers' occupational stress and burnout were examined in 2 field trials. The sample included 113 elementary and secondary school teachers (89% female) from Canada and the United States. Measures were…
Vink, R L C; Fischer, T; Binder, K
2010-11-01
In systems belonging to the universality class of the random field Ising model, the standard hyperscaling relation between critical exponents does not hold, but is replaced with a modified hyperscaling relation. As a result, standard formulations of finite-size scaling near critical points break down. In this work, the consequences of modified hyperscaling are analyzed in detail. The most striking outcome is that the free-energy cost ΔF of interface formation at the critical point is no longer a universal constant, but instead increases as a power law with system size, ΔF∝L(θ), with θ as the violation of hyperscaling critical exponent and L as the linear extension of the system. This modified behavior facilitates a number of numerical approaches that can be used to locate critical points in random field systems from finite-size simulation data. We test and confirm the approaches on two random field systems in three dimensions, namely, the random field Ising model and the demixing transition in the Widom-Rowlinson fluid with quenched obstacles.
ERIC Educational Resources Information Center
Al Otaiba, Stephanie; Connor, Carol M.; Folsom, Jessica S.; Greulich, Luana; Meadows, Jane; Li, Zhi
2011-01-01
The purpose of this cluster-randomized control field trial was to examine whether kindergarten teachers could learn to differentiate classroom reading instruction using Individualized Student Instruction for Kindergarten (ISI-K) and to test the efficacy of differentiation on reading outcomes. The study involved 14 schools, 23 ISI-K (n = 305…
ERIC Educational Resources Information Center
Roeser, Robert W.; Schonert-Reichl, Kimberly A.; Jha, Amishi; Cullen, Margaret; Wallace, Linda; Wilensky, Rona; Oberle, Eva; Thomson, Kimberly; Taylor, Cynthia; Harrison, Jessica
2013-01-01
The effects of randomization to mindfulness training (MT) or to a waitlist-control condition on psychological and physiological indicators of teachers' occupational stress and burnout were examined in 2 field trials. The sample included 113 elementary and secondary school teachers (89% female) from Canada and the United States. Measures were…
ERIC Educational Resources Information Center
Vaden-Kiernan, Michael; Jones, Debra Hughes; Rudo, Zena
2008-01-01
SEDL is providing analytic and technical support to three large-scale randomized controlled trials assessing the efficacy of promising literacy curriculum in afterschool settings on student academic achievement. In the field of educational research, competition among research organizations and researchers can often impede collaborative efforts in…
ERIC Educational Resources Information Center
Al Otaiba, Stephanie; Connor, Carol M.; Folsom, Jessica S.; Greulich, Luana; Meadows, Jane; Li, Zhi
2011-01-01
The purpose of this cluster-randomized control field trial was to examine whether kindergarten teachers could learn to differentiate classroom reading instruction using Individualized Student Instruction for Kindergarten (ISI-K) and to test the efficacy of differentiation on reading outcomes. The study involved 14 schools, 23 ISI-K (n = 305…
Zimmermann, Elke; Asbach, Patrick; Diederichs, Gerd; Wetz, Christoph; Siebert, Eberhard; Wagner, Moritz; Hamm, Bernd; Dewey, Marc
2013-01-01
Background The purpose of the present study was to compare the image quality of spinal magnetic resonance (MR) imaging performed on a high-field horizontal open versus a short-bore MR scanner in a randomized controlled study setup. Methods Altogether, 93 (80% women, mean age 53) consecutive patients underwent spine imaging after random assignement to a 1-T horizontal open MR scanner with a vertical magnetic field or a 1.5-T short-bore MR scanner. This patient subset was part of a larger cohort. Image quality was assessed by determining qualitative parameters, signal-to-noise (SNR) and contrast-to-noise ratios (CNR), and quantitative contour sharpness. Results The image quality parameters were higher for short-bore MR imaging. Regarding all sequences, the relative differences were 39% for the mean overall qualitative image quality, 53% for the mean SNR values, and 34–37% for the quantitative contour sharpness (P<0.0001). The CNR values were also higher for images obtained with the short-bore MR scanner. No sequence was of very poor (nondiagnostic) image quality. Scanning times were significantly longer for examinations performed on the open MR scanner (mean: 32±22 min versus 20±9 min; P<0.0001). Conclusions In this randomized controlled comparison of spinal MR imaging with an open versus a short-bore scanner, short-bore MR imaging revealed considerably higher image quality with shorter scanning times. Trial Registration ClinicalTrials.gov NCT00715806 PMID:24391767
Terçariol, César Augusto Sangaletti; Martinez, Alexandre Souto
2008-09-01
Consider a random medium consisting of N points randomly distributed so that there is no correlation among the distances separating them. This is the random link model, which is the high dimensionality limit (mean-field approximation) for the Euclidean random point structure. In the random link model, at discrete time steps, a walker moves to the nearest point, which has not been visited in the last mu steps (memory), producing a deterministic partially self-avoiding walk (the tourist walk). We have analytically obtained the distribution of the number n of points explored by the walker with memory mu=2 , as well as the transient and period joint distribution. This result enables us to explain the abrupt change in the exploratory behavior between the cases mu=1 (memoryless walker, driven by extreme value statistics) and mu=2 (walker with memory, driven by combinatorial statistics). In the mu=1 case, the mean newly visited points in the thermodynamic limit (N1) is just n=e=2.72... while in the mu=2 case, the mean number n of visited points grows proportionally to N;{12} . Also, this result allows us to establish an equivalence between the random link model with mu=2 and random map (uncorrelated back and forth distances) with mu=0 and the abrupt change between the probabilities for null transient time and subsequent ones.
SPECTRO-POLARIMETRIC IMAGING REVEALS HELICAL MAGNETIC FIELDS IN SOLAR PROMINENCE FEET
González, M. J. Martínez; Sainz, R. Manso; Ramos, A. Asensio; Beck, C.; Díaz, A. J.
2015-03-20
Solar prominences are clouds of cool plasma levitating above the solar surface and insulated from the million-degree corona by magnetic fields. They form in regions of complex magnetic topology, characterized by non-potential fields, which can evolve abruptly, disintegrating the prominence and ejecting magnetized material into the heliosphere. However, their physics is not yet fully understood because mapping such complex magnetic configurations and their evolution is extremely challenging, and must often be guessed by proxy from photometric observations. Using state-of-the-art spectro-polarimetric data, we reconstruct the structure of the magnetic field in a prominence. We find that prominence feet harbor helical magnetic fields connecting the prominence to the solar surface below.
NASA Astrophysics Data System (ADS)
Soler, J. D.; Alves, F.; Boulanger, F.; Bracco, A.; Falgarone, E.; Franco, G. A. P.; Guillet, V.; Hennebelle, P.; Levrier, F.; Martin, P. G.; Miville-Deschênes, M.-A.
2016-12-01
Within four nearby (d < 160 pc) molecular clouds, we statistically evaluated the structure of the interstellar magnetic field, projected on the plane of the sky and integrated along the line of sight, as inferred from the polarized thermal emission of Galactic dust observed by Planck at 353 GHz and from the optical and near-infrared polarization of background starlight. We compared the dispersion of the field orientation directly in vicinities with an area equivalent to that subtended by the Planck effective beam at 353 GHz (10') and using the second-order structure functions of the field orientation angles. We found that the average dispersion of the starlight-inferred field orientations within 10'-diameter vicinities is less than 20°, and that at these scales the mean field orientation is on average within 5° of that inferred from the submillimetre polarization observations in the considered regions. We also found that the dispersion of starlight polarization orientations and the polarization fractions within these vicinities are well reproduced by a Gaussian model of the turbulent structure of the magnetic field, in agreement with the findings reported by the Planck Collaboration at scales ℓ > 10' and for comparable column densities. At scales ℓ > 10', we found differences of up to 14.̊7 between the second-order structure functions obtained from starlight and submillimetre polarization observations in the same positions in the plane of the sky, but comparison with a Gaussian model of the turbulent structure of the magnetic field indicates that these differences are small and are consistent with the difference in angular resolution between both techniques. The differences between the second-order structure functions calculated with each technique suggests that the increase in the angular resolution obtained with the starlight polarization observations does not introduce significant corrections to the dispersion of polarization orientations used in the
NASA Astrophysics Data System (ADS)
Hida, Kazuo
2006-07-01
The multiple reentrant quantum phase transitions in the S=1/2 antiferromagnetic Heisenberg chains with random bond alternation in the magnetic field are investigated by the density matrix renormalization group method combined with interchain mean field approximation. It is assumed that odd numbered bonds are antiferromagnetic with strength J and even numbered bonds can take the values JS and JW (JS > J > JW > 0) randomly with the probabilities p and 1- p, respectively. The pure version ( p=0 and 1) of this model has a spin gap but exhibits a field-induced antiferromagnetism in the presence of interchain coupling if Zeeman energy due to the magnetic field exceeds the spin gap. For 0 < p < 1, antiferromagnetism is induced by randomness at the small field region where the ground state is disordered due to the spin gap in the pure version. At the same time, this model exhibits randomness-induced plateaus at several values of magnetization. The antiferromagnetism is destroyed on the plateaus. As a consequence, we find a series of reentrant quantum phase transitions between transverse antiferromagnetic phases and disordered plateau phases with the increase of magnetic field for a moderate strength of interchain coupling. Above the main plateaus, the magnetization curve consists of a series of small plateaus and jumps between them. It is also found that antiferromagnetism is induced by infinitesimal interchain coupling at the jumps between the small plateaus. We conclude that this antiferromagnetism is supported by the mixing of low-lying excited states by the staggered interchain mean field even though the spin correlation function is short ranged in the ground state of each chain.
Atomic electric fields revealed by a quantum mechanical approach to electron picodiffraction
Müller, Knut; Krause, Florian F.; Béché, Armand; Schowalter, Marco; Galioit, Vincent; Löffler, Stefan; Verbeeck, Johan; Zweck, Josef; Schattschneider, Peter; Rosenauer, Andreas
2014-01-01
By focusing electrons on probes with a diameter of 50 pm, aberration-corrected scanning transmission electron microscopy (STEM) is currently crossing the border to probing subatomic details. A major challenge is the measurement of atomic electric fields using differential phase contrast (DPC) microscopy, traditionally exploiting the concept of a field-induced shift of diffraction patterns. Here we present a simplified quantum theoretical interpretation of DPC. This enables us to calculate the momentum transferred to the STEM probe from diffracted intensities recorded on a pixel array instead of conventional segmented bright-field detectors. The methodical development yielding atomic electric field, charge and electron density is performed using simulations for binary GaN as an ideal model system. We then present a detailed experimental study of SrTiO3 yielding atomic electric fields, validated by comprehensive simulations. With this interpretation and upgraded instrumentation, STEM is capable of quantifying atomic electric fields and high-contrast imaging of light atoms. PMID:25501385
Random field theory to interpret the spatial variability of lacustrine soils
NASA Astrophysics Data System (ADS)
Russo, Savino; Vessia, Giovanna
2015-04-01
The lacustrine soils are quaternary soils, dated from Pleistocene to Holocene periods, generated in low-energy depositional environments and characterized by soil mixture of clays, sands and silts with alternations of finer and coarser grain size layers. They are often met at shallow depth filling several tens of meters of tectonic or erosive basins typically placed in internal Appenine areas. The lacustrine deposits are often locally interbedded by detritic soils resulting from the failure of surrounding reliefs. Their heterogeneous lithology is associated with high spatial variability of physical and mechanical properties both along horizontal and vertical directions. The deterministic approach is still commonly adopted to accomplish the mechanical characterization of these heterogeneous soils where undisturbed sampling is practically not feasible (if the incoherent fraction is prevalent) or not spatially representative (if the cohesive fraction prevails). The deterministic approach consists on performing in situ tests, like Standard Penetration Tests (SPT) or Cone Penetration Tests (CPT) and deriving design parameters through "expert judgment" interpretation of the measure profiles. These readings of tip and lateral resistances (Rp and RL respectively) are almost continuous but highly variable in soil classification according to Schmertmann (1978). Thus, neglecting the spatial variability cannot be the best strategy to estimated spatial representative values of physical and mechanical parameters of lacustrine soils to be used for engineering applications. Hereafter, a method to draw the spatial variability structure of the aforementioned measure profiles is presented. It is based on the theory of the Random Fields (Vanmarcke 1984) applied to vertical readings of Rp measures from mechanical CPTs. The proposed method relies on the application of the regression analysis, by which the spatial mean trend and fluctuations about this trend are derived. Moreover, the
NASA Astrophysics Data System (ADS)
Hartford, Edward John
This position-space renormalization-group study focuses on two systems with quenched disorder: the Ising spin glass and the asymmetric random-field Ising model. We have employed the Migdal-Kadanoff approach to determine local recursion relations and have retained the full correlated probability distribution of interactions and fields at each iteration in a series of histograms. We find an equilibrium spin-glass phase in three dimensions, but not in two. The spin glass is characterized by a distribution of effective interactions that broadens under iteration, signaling both the long-range order of the phase and the importance of competing interactions on all length scales. We have introduced a method to calculate the distribution of local properties by differentiating the free energy with respect to a particular magnetic field or interaction. Within the spin-glass phase, the nearest neighbor correlation < S_ {i}S_{j}> ranges from negative one to one, showing the strong correlations and the local variation within the phase. The spin-glass-to-paramagnet phase transition is second order, with a smooth specific heat indicated by a negative critical exponent alpha. The multicritical point separating the spin-glass, paramagnetic, and ferromagnetic phases lies along the Nishimori line and also has a nondivergent specific heat. When the system undergoes quenched dilution, the resulting critical and multicritical behaviors are identical to those of the undiluted system. Even the addition of an infinitesimal magnetic field destroys the long-range spin-glass order; however, the characteristic broadening of the distribution continues for several iterations for small fields and low temperatures, suggesting the persistence of sizable spin-glass domains. Our study of the asymmetric random-field Ising model is motivated by recent experiments on phase transitions in porous media and mean-field treatments, which suggest that new critical behavior could occur when the distribution of
Adaptive multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model
NASA Astrophysics Data System (ADS)
Navarro, Cristóbal A.; Huang, Wei; Deng, Youjin
2016-08-01
This work presents an adaptive multi-GPU Exchange Monte Carlo approach for the simulation of the 3D Random Field Ising Model (RFIM). The design is based on a two-level parallelization. The first level, spin-level parallelism, maps the parallel computation as optimal 3D thread-blocks that simulate blocks of spins in shared memory with minimal halo surface, assuming a constant block volume. The second level, replica-level parallelism, uses multi-GPU computation to handle the simulation of an ensemble of replicas. CUDA's concurrent kernel execution feature is used in order to fill the occupancy of each GPU with many replicas, providing a performance boost that is more notorious at the smallest values of L. In addition to the two-level parallel design, the work proposes an adaptive multi-GPU approach that dynamically builds a proper temperature set free of exchange bottlenecks. The strategy is based on mid-point insertions at the temperature gaps where the exchange rate is most compromised. The extra work generated by the insertions is balanced across the GPUs independently of where the mid-point insertions were performed. Performance results show that spin-level performance is approximately two orders of magnitude faster than a single-core CPU version and one order of magnitude faster than a parallel multi-core CPU version running on 16-cores. Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99 % efficiency as long as the number of GPUs and L increase together. The combination of the adaptive approach with the parallel multi-GPU design has extended our possibilities of simulation to sizes of L = 32 , 64 for a workstation with two GPUs. Sizes beyond L = 64 can eventually be studied using larger multi-GPU systems.
Tikk, Domonkos; Solt, Illés
2010-01-01
In the i2b2 Medication Extraction Challenge, medication names together with details of their administration were to be extracted from medical discharge summaries. The task of the challenge was decomposed into three pipelined components: named entity identification, context-aware filtering and relation extraction. For named entity identification, first a rule-based (RB) method that was used in our overall fifth place-ranked solution at the challenge was investigated. Second, a conditional random fields (CRF) approach is presented for named entity identification (NEI) developed after the completion of the challenge. The CRF models are trained on the 17 ground truth documents, the output of the rule-based NEI component on all documents, a larger but potentially inaccurate training dataset. For both NEI approaches their effect on relation extraction performance was investigated. The filtering and relation extraction components are both rule-based. In addition to the official entry level evaluation of the challenge, entity level analysis is also provided. On the test data an entry level F(1)-score of 80% was achieved for exact matching and 81% for inexact matching with the RB-NEI component. The CRF produces a significantly weaker result, but CRF outperforms the rule-based model with 81% exact and 82% inexact F(1)-score (p<0.02). This study shows that a simple rule-based method is on a par with more complicated machine learners; CRF models can benefit from the addition of the potentially inaccurate training data, when only very few training documents are available. Such training data could be generated using the outputs of rule-based methods.
Jin, Ick Hoon; Yuan, Ying; Bandyopadhyay, Dipankar
2016-01-01
Research in dental caries generates data with two levels of hierarchy: that of a tooth overall and that of the different surfaces of the tooth. The outcomes often exhibit spatial referencing among neighboring teeth and surfaces, i.e., the disease status of a tooth or surface might be influenced by the status of a set of proximal teeth/surfaces. Assessments of dental caries (tooth decay) at the tooth level yield binary outcomes indicating the presence/absence of teeth, and trinary outcomes at the surface level indicating healthy, decayed, or filled surfaces. The presence of these mixed discrete responses complicates the data analysis under a unified framework. To mitigate complications, we develop a Bayesian two-level hierarchical model under suitable (spatial) Markov random field assumptions that accommodates the natural hierarchy within the mixed responses. At the first level, we utilize an autologistic model to accommodate the spatial dependence for the tooth-level binary outcomes. For the second level and conditioned on a tooth being non-missing, we utilize a Potts model to accommodate the spatial referencing for the surface-level trinary outcomes. The regression models at both levels were controlled for plausible covariates (risk factors) of caries, and remain connected through shared parameters. To tackle the computational challenges in our Bayesian estimation scheme caused due to the doubly-intractable normalizing constant, we employ a double Metropolis-Hastings sampler. We compare and contrast our model performances to the standard non-spatial (naive) model using a small simulation study, and illustrate via an application to a clinical dataset on dental caries. PMID:27807470
Heiner, Jason D; Simmons, Emily A; Hile, David C; Wedmore, Ian S
2011-12-01
Halogen-based water disinfection tablets may render an unpleasant taste to treated water. Proposed safe additives such as ascorbic acid may reduce this objectionable taste. We compared the palatability of 2 field water disinfectants: iodine-based tetraglycine hydroperiodide (TGHP) and chlorine-based chlorine dioxide (CD) both with and without the concomitant use of an ascorbic acid taste neutralizer. Blinded participants randomly sampled 5 different distilled water samples containing combinations of disinfectant tablets and ascorbic acid: 1) water; 2) water with TGHP; 3) water with CD; 4) water with TGHP plus ascorbic acid; and 5) water with CD plus ascorbic acid. Participants rated beverage taste via a 100 mm visual analogue scale (VAS) and ranked the samples from "most pleasant" to "least pleasant." Sixty participants evaluated the samples. On the VAS, water with TGHP tasted worst and water with CD tasted second worst. Water with TGHP plus ascorbic acid, water alone, and water with CD plus ascorbic acid measured similarly as significantly best tasting. Water with TGHP was ranked by 58% as "least pleasant" tasting, while water with TGHP and ascorbic acid was ranked by 40% as "most pleasant" tasting. Participants found halogen-based disinfected water significantly less palatable prior to the addition of ascorbic acid. Addition of ascorbic acid to treated water created a beverage of similar preference to distilled water. These results may increase compliance with the use of disinfecting tablets by increasing the palatability of drinking water made potable via addition of ascorbic acid to halogen-based chemical disinfection. Copyright © 2011 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.
Mersky, Joshua P; Topitzes, James; Janczewski, Colleen E; McNeil, Cheryl B
2015-01-01
Research indicates that foster parents often do not receive sufficient training and support to help them meet the demands of caring for foster children with emotional and behavioral disturbances. Parent-Child Interaction Therapy (PCIT) is a clinically efficacious intervention for child externalizing problems, and it also has been shown to mitigate parenting stress and enhance parenting attitudes and behaviors. However, PCIT is seldom available to foster families, and it rarely has been tested under intervention conditions that are generalizable to community-based child welfare service contexts. To address this gap, PCIT was adapted and implemented in a field experiment using 2 novel approaches-group-based training and telephone consultation-both of which have the potential to be integrated into usual care. This study analyzes 129 foster-parent-child dyads who were randomly assigned to 1 of 3 conditions: (a) waitlist control, (b) brief PCIT, and (c) extended PCIT. Self-report and observational data were gathered at multiple time points up to 14 weeks post baseline. Findings from mixed-model, repeated measures analyses indicated that the brief and extended PCIT interventions were associated with a significant decrease in self-reported parenting stress. Results from mixed-effects generalized linear models showed that the interventions also led to significant improvements in observed indicators of positive and negative parenting. The brief course of PCIT was as efficacious as the extended PCIT intervention. The findings suggest that usual training and support services can be improved upon by introducing foster parents to experiential, interactive PCIT training.
Mersky, Joshua P.; Topitzes, James; Janczewski, Colleen E.; McNeil, Cheryl B.
2015-01-01
Objective Research indicates that foster parents often do not receive sufficient training and support to help them meet the demands of caring for foster children with emotional and behavioral disturbances. Parent-Child Interaction Therapy (PCIT) is a clinically efficacious intervention for child externalizing problems, and it also has been shown to mitigate parenting stress and enhance parenting attitudes and behaviors. However, PCIT is seldom available to foster families, and it rarely has been tested under intervention conditions that are generalizable to community-based child welfare service contexts. To address this gap, PCIT was adapted and implemented in a field experiment using 2 novel approaches—group-based training and telephone consultation—both of which have the potential to be integrated into usual care. Method This study analyzes 129 foster-parent-child dyads who were randomly assigned to 1 of 3 conditions: (a) waitlist control, (b) brief PCIT, and (c) extended PCIT. Self-report and observational data were gathered at multiple time points up to 14 weeks post baseline. Results Findings from mixed-model, repeated measures analyses indicated that the brief and extended PCIT interventions were associated with a significant decrease in self-reported parenting stress. Results from mixed-effects generalized linear models showed that the interventions also led to significant improvements in observed indicators of positive and negative parenting. The brief course of PCIT was as efficacious as the extended PCIT intervention. Conclusions The findings suggest that usual training and support services can be improved upon by introducing foster parents to experiential, interactive PCIT training. PMID:26977251
SAR-based change detection using hypothesis testing and Markov random field modelling
NASA Astrophysics Data System (ADS)
Cao, W.; Martinis, S.
2015-04-01
The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step.
Addressing the unmet need for visualizing conditional random fields in biological data.
Ray, William C; Wolock, Samuel L; Callahan, Nicholas W; Dong, Min; Li, Q Quinn; Liang, Chun; Magliery, Thomas J; Bartlett, Christopher W
2014-07-10
The biological world is replete with phenomena that appear to be ideally modeled and analyzed by one archetypal statistical framework - the Graphical Probabilistic Model (GPM). The structure of GPMs is a uniquely good match for biological problems that range from aligning sequences to modeling the genome-to-phenome relationship. The fundamental questions that GPMs address involve making decisions based on a complex web of interacting factors. Unfortunately, while GPMs ideally fit many questions in biology, they are not an easy solution to apply. Building a GPM is not a simple task for an end user. Moreover, applying GPMs is also impeded by the insidious fact that the "complex web of interacting factors" inherent to a problem might be easy to define and also intractable to compute upon. We propose that the visualization sciences can contribute to many domains of the bio-sciences, by developing tools to address archetypal representation and user interaction issues in GPMs, and in particular a variety of GPM called a Conditional Random Field(CRF). CRFs bring additional power, and additional complexity, because the CRF dependency network can be conditioned on the query data. In this manuscript we examine the shared features of several biological problems that are amenable to modeling with CRFs, highlight the challenges that existing visualization and visual analytics paradigms induce for these data, and document an experimental solution called StickWRLD which, while leaving room for improvement, has been successfully applied in several biological research projects. Software and tutorials are available at http://www.stickwrld.org/.
Spatial analysis in a Markov random field framework: The case of burning oil wells in Kuwait
NASA Astrophysics Data System (ADS)
Dezzani, Raymond J.; Al-Dousari, Ahmad
This paper discusses a modeling approach for spatial-temporal prediction of environmental phenomena using classified satellite images. This research was prompted by the analysis of change and landscape redistribution of petroleum residues formed from the residue of the burning oil wells in Kuwait (1991). These surface residues have been termed ``tarcrete'' (El-Baz etal. 1994). The tarcrete forms a thick layer over sand and desert pavement covering a significant portion of south-central Kuwait. The purpose of this study is to develop a method that utilizes satellite images from different time steps to examine the rate-of-change of the oil residue deposits and determine where redistribution is are likely to occur. This problem exhibits general characteristics of environmental diffusion and dispersion phenomena so a theoretical framework for a general solution is sought. The use of a lagged-clique, Markov random field framework and entropy measures is deduced to be an effective solution to satisfy the criteria of determination of time-rate-of-change of the surface deposits and to forecast likely locations of redistribution of dispersed, aggraded residues. The method minimally requires image classification, the determination of time stationarity of classes and the measurement of the level of organization of the state-space information derived from the images. Analysis occurs at levels of both the individual pixels and the system to determine specific states and suites of states in space and time. Convergence of the observed landscape disorder with respect to an analytical maximum provide information on the total dispersion of the residual system.
Markov random field-based clustering applied to the segmentation of masses in digital mammograms.
Suliga, M; Deklerck, R; Nyssen, E
2008-09-01
In this paper we propose a new pixel clustering model applied to the analysis of digital mammograms. The clustering represents here the first step in a more general method and aims at the creation of a concise data-set (clusters) for automatic detection and classification of masses, which are typically among the first symptoms analysed in early diagnosis of breast cancer. For the purpose of this work, a set of mammographic images has been employed, that are 12-bit gray level digital scans and as such, are inherently inhomogeneous and affected by the noise resulting from the film scanning. The image pixels are described only by their intensity (gray level), therefore, the available information is limited to one dimension. We propose a Markov random field (MRF)-based technique that is suitable for performing clustering in an environment which is described by poor or limited data. The proposed method is a statistical classification model, that labels the image pixels based on the description of their statistical and contextual information. Apart from evaluating the pixel statistics, that originate from the definition of the K-means clustering scheme, the model expands the analysis by the description of the spatial dependence between pixels and their labels (context), hence leading to the reduction of the inhomogeneity of the output. Moreover, we define a probabilistic description of the model, that is characterised by a remarkable simplicity, such that its realisation can be easily and efficiently implemented in any high- or low-level programming language, thus allowing it to be run on virtually any kind of platform. Finally, we evaluate the algorithm against the classical K-means clustering routine. We point out similarities between the two methods and, moreover, show the advantages and superiority of the MRF scheme.
A stochastically fully connected conditional random field framework for super resolution OCT
NASA Astrophysics Data System (ADS)
Boroomand, A.; Tan, B.; Wong, A.; Bizheva, K.
2017-02-01
A number of factors can degrade the resolution and contrast of OCT images, such as: (1) changes of the OCT pointspread function (PSF) resulting from wavelength dependent scattering and absorption of light along the imaging depth (2) speckle noise, as well as (3) motion artifacts. We propose a new Super Resolution OCT (SR OCT) imaging framework that takes advantage of a Stochastically Fully Connected Conditional Random Field (SF-CRF) model to generate a Super Resolved OCT (SR OCT) image of higher quality from a set of Low-Resolution OCT (LR OCT) images. The proposed SF-CRF SR OCT imaging is able to simultaneously compensate for all of the factors mentioned above, that degrade the OCT image quality, using a unified computational framework. The proposed SF-CRF SR OCT imaging framework was tested on a set of simulated LR human retinal OCT images generated from a high resolution, high contrast retinal image, and on a set of in-vivo, high resolution, high contrast rat retinal OCT images. The reconstructed SR OCT images show considerably higher spatial resolution, less speckle noise and higher contrast compared to other tested methods. Visual assessment of the results demonstrated the usefulness of the proposed approach in better preservation of fine details and structures of the imaged sample, retaining biological tissue boundaries while reducing speckle noise using a unified computational framework. Quantitative evaluation using both Contrast to Noise Ratio (CNR) and Edge Preservation (EP) parameter also showed superior performance of the proposed SF-CRF SR OCT approach compared to other image processing approaches.
Detecting Hedge Cues and their Scope in Biomedical Literature with Conditional Random Fields
Agarwal, Shashank; Yu, Hong
2010-01-01
Objective Hedging is frequently used in both the biological literature and clinical notes to denote uncertainty or speculation. It is important for text-mining applications to detect hedge cues and their scope; otherwise, uncertain events are incorrectly identified as factual events. However, due to the complexity of language, identifying hedge cues and their scope in a sentence is not a trivial task. Our objective was to develop an algorithm that would automatically detect hedge cues and their scope in biomedical literature. Methodology We used conditional random fields (CRF), a supervised machine-learning algorithm, to train models to detect hedge cue phrases and their scope in biomedical literature. The models were trained on the publicly available BioScope corpus. We evaluated the performance of the CRF models in identifying hedge cue phrases and their scope by calculating recall, precision and F1-score. We compared our models with three competitive baseline systems. Results Our best CRF-based model performed statistically better than the baseline systems, achieving an F1-score of 88% and 86% in detecting hedge cue phrases and their scope in biological literature and an F1-score of 93% and 90% in detecting hedge cue phrases and their scope in clinical notes. Conclusions Our approach is robust, as it can identify hedge cues and their scope in both biological and clinical text. To benefit text-mining applications, our system is publicly available as a Java API and as an online application at http://hedgescope.askhermes.org. To our knowledge, this is the first publicly available system to detect hedge cues and their scope in biomedical literature. PMID:20709188
Quantum-Chemical Calculations Revealing the Effects of Magnetic Fields on Methanol
NASA Astrophysics Data System (ADS)
Lankhaar, Boy; van der Avoird, Ad; Vlemmings, Wouter H. T.; Groenenboom, Gerrit; van Langevelde, Huib Jan; Surcis, Gabriele
2017-06-01
Maser observations of both linear and circular emission have provided unique information on the magnetic field in the densest regions of star forming regions. While linear polarization observations provide morphological constraints, the magnetic field strength determination is done by comparing the Zeeman-induced velocity shifts between left- and right-circularly polarized emission of molecular maser species. Soon, full-polarization observations with be possible with ALMA, making magnetic field measurements with unprecedented spatial resolution possible. In particular, methanol is of special interest as it is the most abundant maser species and its different transitions probe unique areas of high-mass proto-stellar disks and outflows. However, its exact Zeeman-parameters are unknown. Experimental efforts to determine the Zeeman-parameters have failed. Here we present quantum chemical calculations to the Zeeman-parameters of methanol, along with calculations to the hyperfine structure, which are also necessary to interpret the Zeeman effect in methanol. We present the proper treatment of the torsional motion in computing hyperfine and Zeeman effects. Our results on the hyperfine structure show good agreement with recent experimental data. We find that the Zeeman-effect in methanol is non-linear and comment on its applicability in astronomical magnetic field studies. We give an outlook on rigorously treating non-linear Zeeman effects in radiative transfer modeling of maser-species interacting with a magnetic field.
UNNOTICED MAGNETIC FIELD OSCILLATIONS IN THE VERY QUIET SUN REVEALED BY SUNRISE/IMaX
Martinez Gonzalez, M. J.; Asensio Ramos, A.; Manso Sainz, R.; Khomenko, E.; MartInez Pillet, V.; Lopez Ariste, A.
2011-04-01
We present observational evidence for oscillations of magnetic flux density in the quiet areas of the Sun. The majority of magnetic fields on the solar surface have strengths of the order of or lower than the equipartition field (300-500 G). This results in a myriad of magnetic fields whose evolution is largely determined by the turbulent plasma motions. When granules evolve they squash the magnetic field lines together or pull them apart. Here, we report on the periodic deformation of the shapes of features in circular polarization observed at high resolution with SUNRISE. In particular, we note that the area of patches with a constant magnetic flux oscillates with time, which implies that the apparent magnetic field intensity oscillates in antiphase. The periods associated with this oscillatory pattern are compatible with the granular lifetime and change abruptly, which suggests that these oscillations might not correspond to characteristic oscillatory modes of magnetic structures, but to the forcing by granular motions. In one particular case, we find three patches around the same granule oscillating in phase, which means that the spatial coherence of these oscillations can reach 1600 km. Interestingly, the same kind of oscillatory phenomenon is also found in the upper photosphere.
Narechania, Apurva; Baker, Richard H; Sit, Ryan; Kolokotronis, Sergios-Orestis; DeSalle, Rob; Planet, Paul J
2012-01-01
Recent whole-genome approaches to microbial phylogeny have emphasized partitioning genes into functional classes, often focusing on differences between a stable core of genes and a variable shell. To rigorously address the effects of partitioning and combining genes in genome-level analyses, we developed a novel technique called Random Addition Concatenation Analysis (RADICAL). RADICAL operates by sequentially concatenating randomly chosen gene partitions starting with a single-gene partition and ending with the entire genomic data set. A phylogenetic tree is built for every successive addition, and the entire process is repeated creating multiple random concatenation paths. The result is a library of trees representing a large variety of differently sized random gene partitions. This library can then be mined to identify unique topologies, assess overall agreement, and measure support for different trees. To evaluate RADICAL, we used 682 orthologous genes across 13 cyanobacterial genomes. Despite previous assertions of substantial differences between a core and a shell set of genes for this data set, RADICAL reveals the two partitions contain congruent phylogenetic signal. Substantial disagreement within the data set is limited to a few nodes and genes involved in metabolism, a functional group that is distributed evenly between the core and the shell partitions. We highlight numerous examples where RADICAL reveals aspects of phylogenetic behavior not evident by examining individual gene trees or a "'total evidence" tree. Our method also demonstrates that most emergent phylogenetic signal appears early in the concatenation process. The software is freely available at http://desalle.amnh.org.
Implementing Random Assignment: A Computer-Based Approach in a Field Experimental Setting.
ERIC Educational Resources Information Center
Dobson, Douglas; Cook, Thomas J.
1979-01-01
A major problem in social science research is that of successfully carrying out the random assignment of persons to experimental and control groups. In this study a computer-based random assignment procedure operated successfully on a weekly basis for 17 consecutive weeks in a program serving over 360 ex-offenders. (CTM)
2 s exciton-polariton revealed in an external magnetic field
NASA Astrophysics Data System (ADS)
Pietka, B.; Molas, M. R.; Bobrovska, N.; Król, M.; Mirek, R.; Lekenta, K.; Stepnicki, P.; Morier-Genoud, F.; Szczytko, J.; Deveaud, B.; Matuszewski, M.; Potemski, M.
2017-08-01
We demonstrate the existence of the excited state of an exciton-polariton in a semiconductor microcavity. The strong coupling of the quantum well heavy-hole exciton in an excited 2 s state to the cavity photon is observed in nonzero magnetic field due to surprisingly fast increase of Rabi energy of the 2 s exciton-polariton in magnetic field. This effect is explained by a strong modification of the wave function of the relative electron-hole motion for the 2 s exciton state.
NASA Astrophysics Data System (ADS)
Bakhtiar, Nurizatul Syarfinas Ahmad; Abdullah, Farah Aini; Hasan, Yahya Abu
2017-08-01
In this paper, we consider the dynamical behaviour of the random field on the pulsating and snaking solitons in a dissipative systems described by the one-dimensional cubic-quintic complex Ginzburg-Landau equation (cqCGLE). The dynamical behaviour of the random filed was simulated by adding a random field to the initial pulse. Then, we solve it numerically by fixing the initial amplitude profile for the pulsating and snaking solitons without losing any generality. In order to create the random field, we choose 0 ≤ ɛ ≤ 1.0. As a result, multiple soliton trains are formed when the random field is applied to a pulse like initial profile for the parameters of the pulsating and snaking solitons. The results also show the effects of varying the random field of the transient energy peaks in pulsating and snaking solitons.
Callister, Stephen J; Wilkins, Mike; Nicora, Carrie D.; Williams, Ken; Banfield, Jillian F.; Verberkmoes, Nathan C; Hettich, Robert {Bob} L; N'Guessan, A. Lucie; Mouser, Paula J; Elifantz, Hila; Smith, Richard D.; Lovley, Derek; Lipton, Mary S; Long, Phil
2010-01-01
Stimulated by an acetate-amendment field experiment conducted in 2007, anaerobic microbial populations in the aquifer at the Rifle Integrated Field Research Challenge site in Colorado reduced mobile U(VI) to insoluble U(IV). During this experiment, planktonic biomass was sampled at various time points to quantitatively evaluate proteomes. In 2008, an acetateamended field experiment was again conducted in a similar manner to the 2007 experiment. As there was no comprehensive metagenome sequence available for use in proteomics analysis, we systematically evaluated 12 different organism genome sequences to generate sets of aggregate genomes, or pseudo-metagenomes , for supplying relative quantitative peptide and protein identifications. Proteomics results support previous observations of the dominance of Geobacteraceae during biostimulation using acetate as sole electron donor, and revealed a shift from an early stage of iron reduction to a late stage of iron reduction. Additionally,ashift from iron reduction to sulfate reduction was indicated by changes in the contribution of proteome information contributed by different organism genome sequences within the aggregate set. In addition, the comparison of proteome measurements made between the 2007 field experiment and 2008 field experiment revealed differences in proteome profiles. These differences may be the result of alterations in abundance and population structure within the planktonic biomass samples collected for analysis.
Callister, S.J.; Wilkins, M.J.; Nicora, C.D.; Williams, K.H.; Banfield, J.F.; VerBerkmoes, N.C.; Hettich, R.L.; NGuessan, A.L.; Mouser, P.J.; Elifantz, H.; Smith, R.D.; Lovley, D.R.; Lipton, M.S.; Long, P.E.
2010-07-15
Stimulated by an acetate-amendment field experiment conducted in 2007, anaerobic microbial populations in the aquifer at the Rifle Integrated Field Research Challenge site in Colorado reduced mobile U(VI) to insoluble U(IV). During this experiment, planktonic biomass was sampled at various time points to quantitatively evaluate proteomes. In 2008, an acetate-amended field experiment was again conducted in a similar manner to the 2007 experiment. As there was no comprehensive metagenome sequence available for use in proteomics analysis, we systematically evaluated 12 different organism genome sequences to generate sets of aggregate genomes, or “pseudo-metagenomes”, for supplying relative quantitative peptide and protein identifications. Proteomics results support previous observations of the dominance of Geobacteraceae during biostimulation using acetate as sole electron donor, and revealed a shift from an early stage of iron reduction to a late stage of iron reduction. Additionally, a shift from iron reduction to sulfate reduction was indicated by changes in the contribution of proteome information contributed by different organism genome sequences within the aggregate set. In addition, the comparison of proteome measurements made between the 2007 field experiment and 2008 field experiment revealed differences in proteome profiles. These differences may be the result of alterations in abundance and population structure within the planktonic biomass samples collected for analysis.
Verberk, Wilco C E P; Durance, Isabelle; Vaughan, Ian P; Ormerod, Steve J
2016-05-01
Aquatic ecological responses to climatic warming are complicated by interactions between thermal effects and other environmental stressors such as organic pollution and hypoxia. Laboratory experiments have demonstrated how oxygen limitation can set heat tolerance for some aquatic ectotherms, but only at unrealistic lethal temperatures and without field data to assess whether oxygen shortages might also underlie sublethal warming effects. Here, we test whether oxygen availability affects both lethal and nonlethal impacts of warming on two widespread Eurasian mayflies, Ephemera danica, Müller 1764 and Serratella ignita (Poda 1761). Mayfly nymphs are often a dominant component of the invertebrate assemblage in streams, and play a vital role in aquatic and riparian food webs. In the laboratory, lethal impacts of warming were assessed under three oxygen conditions. In the field, effects of oxygen availability on nonlethal impacts of warming were assessed from mayfly occurrence in 42 293 UK stream samples where water temperature and biochemical oxygen demand were measured. Oxygen limitation affected both lethal and sublethal impacts of warming in each species. Hypoxia lowered lethal limits by 5.5 °C (±2.13) and 8.2 °C (±0.62) for E. danica and S. ignita respectively. Field data confirmed the importance of oxygen limitation in warmer waters; poor oxygenation drastically reduced site occupancy, and reductions were especially pronounced under warm water conditions. Consequently, poor oxygenation lowered optimal stream temperatures for both species. The broad concordance shown here between laboratory results and extensive field data suggests that oxygen limitation not only impairs survival at thermal extremes but also restricts species abundance in the field at temperatures well below upper lethal limits. Stream oxygenation could thus control the vulnerability of aquatic ectotherms to global warming. Improving water oxygenation and reducing pollution can provide
The many assembly histories of massive void galaxies as revealed by integral field spectroscopy
NASA Astrophysics Data System (ADS)
Fraser-McKelvie, Amelia; Pimbblet, Kevin A.; Penny, Samantha J.; Brown, Michael J. I.
2016-06-01
We present the first detailed integral field spectroscopy study of nine central void galaxies with M⋆ > 1010 M⊙ using the Wide Field Spectrograph to determine how a range of assembly histories manifest themselves in the current day Universe. While the majority of these galaxies are evolving secularly, we find a range of morphologies, merger histories and stellar population distributions, though similarly low Hα-derived star formation rates (<1 M⊙ yr-1). Two of our nine galaxies host active galactic nuclei, and two have kinematic disruptions to their gas that are not seen in their stellar component. Most massive void galaxies are red and discy, which we attribute to a lack of major mergers. Some have disturbed morphologies and may be in the process of evolving to early-type thanks to ongoing minor mergers at present times, likely fed by tendrils leading off filaments. The diversity in our small galaxy sample, despite being of similar mass and environment means that these galaxies are still assembling at present day, with minor mergers playing an important role in their evolution. We compare our sample to a mass and magnitude-matched sample of field galaxies, using data from the Sydney-AAO Multi-object Integral field spectrograph galaxy survey. We find that despite environmental differences, galaxies of mass M⋆ > 1010 M⊙ have similarly low star formation rates (<3 M⊙ yr-1). The lack of distinction between the star formation rates of the void and field environments points to quenching of massive galaxies being a largely mass-related effect.
Shibukawa, Atsushi; Okamoto, Atsushi; Takabayashi, Masanori; Tomita, Akihisa
2014-02-24
We propose a spatial cross modulation method using a random diffuser and a phase-only spatial light modulator (SLM), by which arbitrary complex-amplitude fields can be generated with higher spatial resolution and diffraction efficiency than off-axis and double-phase computer-generated holograms. Our method encodes the original complex object as a phase-only diffusion image by scattering the complex object using a random diffuser. In addition, all incoming light to the SLM is consumed for a single diffraction order, making a diffraction efficiency of more than 90% possible. This method can be applied for holographic data storage, three-dimensional displays, and other such applications.
Vierling, R A; Xiang, Z; Joshi, C P; Gilbert, M L; Nguyen, H T
1994-02-01
The genetic diversity of sorghum, as compared to corn, is less well characterized at the genetic and molecular levels despite its worldwide economic importance. The objectives of this study were to: (1) investigate genetic diversity for restriction fragment length polymorphism (RFLPs) and random amplified polymorphic DNAs (RAPDs) in elite sorghum lines, (2) compare similarities based on molecular markers with pedigree relationships, and (3) examine the potential of RFLPs and RAPDs for assigning sorghum lines to the A/B (sterile) and R (restorer) groups. Using four restriction enzymes, polymorphism was detected with 61% of the RFLP probes used, compared to 77% of the random primers. One hundred and sixteen (64%) probe-enzyme combinations yielded multiple-band profiles compared to 98% of the random primers. RFLP profiles generated 290 polymorphic bands compared to 177 polymorphic RAPDs. Pair-wise comparisons of polymorphic RFLPs and RAPDs were used to calculate Nei and Jaccard coefficients. These were employed to generate phenograms using UPGMA and neighborjoining clustering methods. Analysis of RFLP data with Jaccard's coefficient and neighbor-joining clustering produced the phenogram with the closest topology to the known pedigree.
Kaleff, C R; Aschidamini, C; Baron, J; Di Leone, C N; Leone, C N; Canavarro, S; Vargas, C D
2011-08-01
Previous assessment of verticality by means of rod and rod and frame tests indicated that human subjects can be more (field dependent) or less (field independent) influenced by a frame placed around a tilted rod. In the present study we propose a new approach to these tests. The judgment of visual verticality (rod test) was evaluated in 50 young subjects (28 males, ranging in age from 20 to 27 years) by randomly projecting a luminous rod tilted between -18 and +18° (negative values indicating left tilts) onto a tangent screen. In the rod and frame test the rod was displayed within a luminous fixed frame tilted at +18 or -18°. Subjects were instructed to verbally indicate the rod's inclination direction (forced choice). Visual dependency was estimated by means of a Visual Index calculated from rod and rod and frame test values. Based on this index, volunteers were classified as field dependent, intermediate and field independent. A fourth category was created within the field-independent subjects for whom the amount of correct guesses in the rod and frame test exceeded that of the rod test, thus indicating improved performance when a surrounding frame was present. In conclusion, the combined use of subjective visual vertical and the rod and frame test provides a specific and reliable form of evaluation of verticality in healthy subjects and might be of use to probe changes in brain function after central or peripheral lesions.
Irrational use of antimalarial drugs in rural areas of eastern Pakistan: a random field study
2012-01-01
Background Prescription of antimalarial drugs in the absence of malarial disease is a common practice in countries where malaria is endemic. However, unwarranted use of such drugs can cause side effects in some people and is a financial drain on local economies. In this study, we surveyed the prevalence of malaria parasites in humans, and the prevalence of the malaria transmitting mosquito vectors in the study area. We also investigated the use of antimalarial drugs in the local people. We focused on randomly selected rural areas of eastern Pakistan where no malaria cases had been reported since May 2004. Methods Mass blood surveys, active case detection, passive case detection, and vector density surveys were carried out in selected areas of Sargodha district from September 2008 to August 2009. Data pertaining to the quantities and types of antimalarial drugs used in these areas were collected from health centers, pharmacies, and the district CDC program of the Health Department of the Government of the Punjab. Results Seven hundred and forty four blood samples were examined, resulting in a Blood Examination Rate (BER) of 3.18; microscopic analysis of blood smears showed that none of the samples were positive for malaria parasites. Investigation of the mosquito vector density in 43 living rooms (bedrooms or rooms used for sleeping), 23 stores, and 32 animal sheds, revealed no vectors capable of transmitting malaria in these locations. In contrast, the density of Culex mosquitoes was high. Substantial consumption of a variety of antimalarial tablets, syrups, capsules and injections costing around 1000 US$, was documented for the region. Conclusion Use of antimalarial drugs in the absence of malarial infection or the vectors that transmit the disease was common in the study area. Continuous use of such drugs, not only in Pakistan, but in other parts of the world, may lead to drug-induced side effects amongst users. Better training of health care professionals is