DYNAMIC SCALING AND FRACTAL BEHAVIOR OF SPINODAL PHASE-SEPARATION IN POLYMER MIXTURES OF POLY(METHYL METHACRYLATE) WITH POLY(STYRENE-CO-ACRYLONITRILE)

Dynamic scaling and fractal behaviour of spinodal phase separation is studied in a binary polymer mixture of poly(methyl methacrylate) (PMMA) and poly(styrene-co-acrylonitrile) (SAN). In the later stages of spinodal phase separation, a simple dynamic scaling law was found for the scattering function S(q,t):S(q,t) approximately q(m)-3S approximately (q/q(m)). The possibility of using fractal theory to describe the complex morphology of spinodal phase separation is discussed. In phase separation, morphology exhibits strong self-similarity. The two-dimensional image obtained by optical microscopy can be analysed within the framework of fractal concepts. The results give a fractal dimension of 1.64. This implies that the fractal structure may be the reason for the dynamic scaling behaviour of the structure function.

DYNAMIC SCALING OF THE STRUCTURE-FUNCTION FOR SPINODAL DECOMPOSITION IN CRITICAL AND NONCRITICAL MIXTURES OF POLY(VINYL ACETATE) POLY(METHYL METHACRYLATE)

The dynamics of phase separation in a binary polymer blend of poly(vinyl acetate) with poly(methyl methacrylate) was investigated by using a time-resolved light-scattering technique. In the later stages of spinodal decomposition, a simple dynamic scaling law was found for the scattering function S(q, t)(S(q, t) approximately I(q, t)): S(q, t)q(m)-3 S approximately (q/q(m)). The scaling function determined experimentally was in good agreement with that predicted by Furukawa, S approximately (X) approximately X2/(3 + X8) for critical concentration, and approximately in agreement with that predicted by Furukawa, S approximately (X) approximately X2/(3 + X6) for non-critical mixtures. The light-scattering invariant shows that the later stages of the spinodal decomposition were undergoing domain ripening.

Disparity Gradients and Depth Scaling

The binocular perception of shape and depth relations between objects can change considerably if the viewing direction is changed only by a small angle. We explored this effect psychophysically and found a strong depth reduction effect for large disparity gradients. The effect is found to be strongest for horizontally oriented stimuli, and stronger for line stimuli than for points. This depth scaling effect is discussed in a computational framework of stereo based on a Baysian approach which allows integration of information from different types of matching primitives weighted according to their robustness.

Trajectory Mapping ("TM''): A New Non-Metric Scaling Technique

Trajectory Mapping "TM'' is a new scaling technique designed to recover the parameterizations, axes, and paths used to traverse a feature space. Unlike Multidimensional Scaling (MDS), there is no assumption that the space is homogenous or metric. Although some metric ordering information is obtained with TM, the main output is the feature parameterizations that partition the given domain of object samples into different categories. Following an introductory example, the technique is further illustrated using first a set of colors and then a collection of textures taken from Brodatz (1966).

Computing a Uniform Scaling Parameter for 3D Registration of Lung Surfaces

A difficulty in lung image registration is accounting for changes in the size of the lungs due to inspiration. We propose two methods for computing a uniform scale parameter for use in lung image registration that account for size change. A scaled rigid-body transformation allows analysis of corresponding lung CT scans taken at different times and can serve as a good low-order transformation to initialize non-rigid registration approaches. Two different features are used to compute the scale parameter. The first method uses lung surfaces. The second uses lung volumes. Both approaches are computationally inexpensive and improve the alignment of lung images over rigid registration. The two methods produce different scale parameters and may highlight different functional information about the lungs.

A Neural Network for Synthesizing the Pitch of an Acoustic Source

This article describes a neural network model capable of generating a spatial representation of the pitch of an acoustic source. Pitch is one of several auditory percepts used by humans to separate multiple sound sources in the environment from each other. The model provides a neural instantiation of a type of "harmonic sieve". It is capable of quantitatively simulating a large body of psychoacoustical data, including new data on octave shift perception.

A Spectral Network Model of Pitch Perception

A model of pitch perception, called the Spatial Pitch Network or SPINET model, is developed and analyzed. The model neurally instantiates ideas front the spectral pitch modeling literature and joins them to basic neural network signal processing designs to simulate a broader range of perceptual pitch data than previous spectral models. The components of the model arc interpreted as peripheral mechanical and neural processing stages, which arc capable of being incorporated into a larger network architecture for separating multiple sound sources in the environment. The core of the new model transforms a spectral representation of an acoustic source into a spatial distribution of pitch strengths. The SPINET model uses a weighted "harmonic sieve" whereby the strength of activation of a given pitch depends upon a weighted sum of narrow regions around the harmonics of the nominal pitch value, and higher harmonics contribute less to a pitch than lower ones. Suitably chosen harmonic weighting functions enable computer simulations of pitch perception data involving mistuned components, shifted harmonics, and various types of continuous spectra including rippled noise. It is shown how the weighting functions produce the dominance region, how they lead to octave shifts of pitch in response to ambiguous stimuli, and how they lead to a pitch region in response to the octave-spaced Shepard tone complexes and Deutsch tritones without the use of attentional mechanisms to limit pitch choices. An on-center off-surround network in the model helps to produce noise suppression, partial masking and edge pitch. Finally, it is shown how peripheral filtering and short term energy measurements produce a model pitch estimate that is sensitive to certain component phase relationships.

Development of hemispheric specialization for lexical pitch-accent in Japanese infants.

Infants' speech perception abilities change through the first year of life, from broad sensitivity to a wide range of speech contrasts to becoming more finely attuned to their native language. What remains unclear, however, is how this perceptual change relates to brain responses to native language contrasts in terms of the functional specialization of the left and right hemispheres. Here, to elucidate the developmental changes in functional lateralization accompanying this perceptual change, we conducted two experiments on Japanese infants using Japanese lexical pitch-accent, which changes word meanings with the pitch pattern within words. In the first behavioral experiment, using visual habituation, we confirmed that infants at both 4 and 10 months have sensitivities to the lexical pitch-accent pattern change embedded in disyllabic words. In the second experiment, near-infrared spectroscopy was used to measure cortical hemodynamic responses in the left and right hemispheres to the same lexical pitch-accent pattern changes and their pure tone counterparts. We found that brain responses to the pitch change within words differed between 4- and 10-month-old infants in terms of functional lateralization: Left hemisphere dominance for the perception of the pitch change embedded in words was seen only in the 10-month-olds. These results suggest that the perceptual change in Japanese lexical pitch-accent may be related to a shift in functional lateralization from bilateral to left hemisphere dominance.

Scaling limits of a model for selection at two scales

The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval $[0,1]$ with dependence on a single parameter, $\lambda$. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on $\lambda$ and the behavior of the initial data around $1$. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.

Accurate localized resolution of identity approach for linear-scaling hybrid density functionals and for many-body perturbation theory

© 2015 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.A key component in calculations of exchange and correlation energies is the Coulomb operator, which requires the evaluation of two-electron integrals. For localized basis sets, these four-center integrals are most efficiently evaluated with the resolution of identity (RI) technique, which expands basis-function products in an auxiliary basis. In this work we show the practical applicability of a localized RI-variant ('RI-LVL'), which expands products of basis functions only in the subset of those auxiliary basis functions which are located at the same atoms as the basis functions. We demonstrate the accuracy of RI-LVL for Hartree-Fock calculations, for the PBE0 hybrid density functional, as well as for RPA and MP2 perturbation theory. Molecular test sets used include the S22 set of weakly interacting molecules, the G3 test set, as well as the G2-1 and BH76 test sets, and heavy elements including titanium dioxide, copper and gold clusters. Our RI-LVL implementation paves the way for linear-scaling RI-based hybrid functional calculations for large systems and for all-electron many-body perturbation theory with significantly reduced computational and memory cost.