The effect of the scalar-isovector meson field on hyperon-rich neutron star matter

We investigate the effect of the calar-isovector delta-meson field on the equation of state (EOS) and composition of hyperonic neutron star matter, and the properties of hyperonic neutron stars within the frame work of the relativistic mean field theory. The influence of the delta-field turns out to be quite different and generally weaker for hyperonic neutron star matter as compared to that for npe mu neutron star matter. We find that inclusion of the delta-field enhances the strangeness content slightly and consequently moderately softens the EOS of neutron star matter in its hyperonic phase. As for the composition of hyperonic star matter, the effect of the delta-field is shown to shift the onset of the negatively-charged (positively-charged) hyperons to slightly lower (higher) densities and to enhance (reduce) their abundances. The influence of the delta-field on the maximum mass of hyperonic neutron stars is found to be fairly weak, where as inclusion of the delta-field turns out to enhance sizably both the radii and the moments of inertia of neutron stars with given masses. It is also shown that the effects of the delta-field on the properties of hyperonic neutron stars remain similar in the case of switching off the Sigma hyperons.

Parallel Computation of Vernier Offsets, Curvature and Chevrons in Humans

A vernier offset is detected at once among straight lines, and reaction times are almost independent of the number of simultaneously presented stimuli (distractors), indicating parallel processing of vernier offsets. Reaction times for identifying a vernier offset to one side among verniers offset to the opposite side increase with the number of distractors, indicating serial processing. Even deviations below a photoreceptor diameter can be detected at once. The visual system thus attains positional accuracy below the photoreceptor diameter simultaneously at different positions. I conclude that deviation from straightness, or change of orientation, is detected in parallel over the visual field. Discontinuities or gradients in orientation may represent an elementary feature of vision.

The Alignment of Objects With Smooth Surfaces: Error Analysis of the Curvature Method

The recognition of objects with smooth bounding surfaces from their contour images is considerably more complicated than that of objects with sharp edges, since in the former case the set of object points that generates the silhouette contours changes from one view to another. The "curvature method", developed by Basri and Ullman [1988], provides a method to approximate the appearance of such objects from different viewpoints. In this paper we analyze the curvature method. We apply the method to ellipsoidal objects and compute analytically the error obtained for different rotations of the objects. The error depends on the exact shape of the ellipsoid (namely, the relative lengths of its axes), and it increases a sthe ellipsoid becomes "deep" (elongated in the Z-direction). We show that the errors are usually small, and that, in general, a small number of models is required to predict the appearance of an ellipsoid from all possible views. Finally, we show experimentally that the curvature method applies as well to objects with hyperbolic surface patches.

The VITEWRITE Model of Handwriting Production

This article describes the VITEWRITE model for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to move a hand with redundant degrees of freedom. The neural trajectory generator is the Vector Integration to Endpoint (VITE) model for synchronous variable-speed control of multijoint movements. VITE properties enable a simple control strategy to generate complex handwritten script if the hand model contains redundant degrees of freedom. The controller launches transient directional commands to independent hand synergies at times when the hand begins to move, or when a velocity peak in the outflow command to a given synergy occurs. The VITE model translates these temporally disjoint synergy commands into smooth curvilinear trajectories among temporally overlapping synergetic movements. Each synergy exhibits a unimodal velocity profile during any stroke, generates letters that are invariant under speed and size rescaling, and enables effortless connection of letter shapes into words. Speed and size rescaling are achieved by scalar GO and GRO signals that express computationally simple volitional commands. Psychophysical data such as the isochrony principle, asymmetric velocity profiles, and the two-thirds power law relating movement curvature and velocity arise as emergent properties of model interactions.

A Neural Network Model for Cursive Script Production

This article describes a neural network model, called the VITEWRITE model, for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to move a. hand with redundant degrees of freedom. The neural trajectory generator is the Vector Integration to Endpoint (VITE) model for synchronous variable-speed control of multijoint movements. VITE properties enable a simple control strategy to generate complex handwritten script if the hand model contains redundant degrees of freedom. The proposed controller launches transient directional commands to independent hand synergies at times when the hand begins to move, or when a velocity peak in a given synergy is achieved. The VITE model translates these temporally disjoint synergy commands into smooth curvilinear trajectories among temporally overlapping synergetic movements. The separate "score" of onset times used in most prior models is hereby replaced by a self-scaling activity-released "motor program" that uses few memory resources, enables each synergy to exhibit a unimodal velocity profile during any stroke, generates letters that are invariant under speed and size rescaling, and enables effortless. connection of letter shapes into words. Speed and size rescaling are achieved by scalar GO and GRO signals that express computationally simple volitional commands. Psychophysical data concerning band movements, such as the isochrony principle, asymmetric velocity profiles, and the two-thirds power law relating movement curvature and velocity arise as emergent properties of model interactions.

Accommodating curvature in a highly ordered functionalized metal oxide nanofiber: synthesis, characterization and multi-scale modeling of layered nanosheets

A key element in the rational design of hybrid organic-inorganic nanostructures, is control of surfactant packing and adsorption onto the inorganic phase in crystal growth and assembly. In layered single crystal nanofibers and bilayered 2D nanosheets of vanadium oxide, we show how the chemisorption of preferred densities of surfactant molecules can direct formation of ordered, curved layers. The atom-scale features of the structures are described using molecular dynamics simulations that quantify surfactant packing effects and confirm the preference for a density of 5 dodecanethiol molecules per 8 vanadium attachment sites in the synthesised structures. This assembly maintains a remarkably well ordered interlayer spacing, even when curved. The assemblies of interdigitated organic bilayers on V2O5 are shown to be sufficiently flexible to tolerate curvature while maintaining a constant interlayer distance without rupture, delamination or cleavage. The accommodation of curvature and invariant structural integrity points to a beneficial role for oxide-directed organic film packing effects in layered architectures such as stacked nanofibers and hybrid 2D nanosheet systems.

Uncertainty visualization in 3D scalar data

One problem in most three-dimensional (3D) scalar data visualization techniques is that they often overlook to depict uncertainty that comes with the 3D scalar data and thus fail to faithfully present the 3D scalar data and have risks which may mislead users’ interpretations, conclusions or even decisions. Therefore this thesis focuses on the study of uncertainty visualization in 3D scalar data and we seek to create better uncertainty visualization techniques, as well as to find out the advantages/disadvantages of those state-of-the-art uncertainty visualization techniques. To do this, we address three specific hypotheses: (1) the proposed Texture uncertainty visualization technique enables users to better identify scalar/error data, and provides reduced visual overload and more appropriate brightness than four state-of-the-art uncertainty visualization techniques, as demonstrated using a perceptual effectiveness user study. (2) The proposed Linked Views and Interactive Specification (LVIS) uncertainty visualization technique enables users to better search max/min scalar and error data than four state-of-the-art uncertainty visualization techniques, as demonstrated using a perceptual effectiveness user study. (3) The proposed Probabilistic Query uncertainty visualization technique, in comparison to traditional Direct Volume Rendering (DVR) methods, enables radiologists/physicians to better identify possible alternative renderings relevant to a diagnosis and the classification probabilities associated to the materials appeared on these renderings; this leads to improved decision support for diagnosis, as demonstrated in the domain of medical imaging. For each hypothesis, we test it by following/implementing a unified framework that consists of three main steps: the first main step is uncertainty data modeling, which clearly defines and generates certainty types of uncertainty associated to given 3D scalar data. The second main step is uncertainty visualization, which transforms the 3D scalar data and their associated uncertainty generated from the first main step into two-dimensional (2D) images for insight, interpretation or communication. The third main step is evaluation, which transforms the 2D images generated from the second main step into quantitative scores according to specific user tasks, and statistically analyzes the scores. As a result, the quality of each uncertainty visualization technique is determined.

Lovelock terms and BRST cohomology

Lovelock terms are polynomial scalar densities in the Riemann curvature tensor that have the remarkable property that their Euler-Lagrange derivatives contain derivatives of the metric of an order not higher than 2 (while generic polynomial scalar densities lead to Euler-Lagrange derivatives with derivatives of the metric of order 4). A characteristic feature of Lovelock terms is that their first nonvanishing term in the expansion g λμ = η λμ + h λμ of the metric around flat space is a total derivative. In this paper, we investigate generalized Lovelock terms defined as polynomial scalar densities in the Riemann curvature tensor and its covariant derivatives (of arbitrarily high but finite order) such that their first nonvanishing term in the expansion of the metric around flat space is a total derivative. This is done by reformulating the problem as a BRST cohomological one and by using cohomological tools. We determine all the generalized Lovelock terms. We find, in fact, that the class of nontrivial generalized Lovelock terms contains only the usual ones. Allowing covariant derivatives of the Riemann tensor does not lead to a new structure. Our work provides a novel algebraic understanding of the Lovelock terms in the context of BRST cohomology. © 2005 IOP Publishing Ltd.

Scalar glueballs: Constraints from the decays into η or η′

We study the mixing of the scalar glueball into the isosinglet mesons f0(1370), f0(1500), and f0(1710) to describe the two-body decays to pseudoscalars. We use an effective Hamiltonian and employ the two-angle mixing scheme for η and η′. In this framework, we analyze existing data and look forward to new data into η and η′ channels. For now, the f0(1710) has the largest glueball component and a sizable branching ratio into ηη′, testable at BESIII.

The Effect of Illuminant Position on Perceived Curvature

In shaded scenes surface features can appear either concave or convex, depending upon the viewers judment about the direction of the prevailing illuminant. If other curvature cues are added to the image this ambiguity can be removed. However, it is not clear to what extent, if any, illuminant positin exerts an influence on the perceived magnitude of surface curvature. Subjects were presented with pairs of spherical surface patches in a curavture matching task. The patches were defined by shading and texture cues. The percevied curvature of a standard patch was measured as a function of light source position. We found a clear effect of light source position on apparent curvature. Perceived curvature decreased as light source tilt increased and as light source slant decreased. We also found that the strength of this effect is determined partly by a surface's reflectance function and partly by the relative weight of the texture cue. When a specular component was added to the stimuli, the effect of light source orientation was weakened. The weight of the texture cue was manipulated by disrupting the regular distribution of texture elements. We found an inverse relationship between the strength of the effecct and the weight of the texture cue: lowering the texture cue weight resulted in an enhancement of the illuminant position effect.

3D Curvature Contrast - a geometric or brightness illusion?

Simultaneous contrast effects have been found across a wide range of visual dimensions. We describe a simultaneous contrast effect - three-dimensional curvature contrast - in which the apparent curvature of a surface defined by shading and texture information is influenced by the curvature of a surrounding surface. The effect is strong and easily measurable. We asked whether the effect depends upon the presence of contrast at the level of the internal representation of surface curvature or whether it could be better explained in terms of local changes in the apparent brightness of regions within the test patches induced by luminance transition at the borders. The experimental results suggest that, whicle these luminance-contrast-induced effects do contribute to the observed changes in perceived curvature, there are additional influences. In particular changes in perceived curvature induced by a pattern of curved patches were eliminated or considerably weakened when the inducing pattern was transformed into a photographic negative, a procedure which disrupts the apparent three-dimensional structure of the surface patches without changing their brightness contrast. This suggests a component of the illusion involves comparisons at the level of representation of surface curvature. The observation that three-dimensional curvature contrast presists when the inducing surfaces are spatially separate from the test surface suggests that shape perception involves global, as well as local, operations.

Uniaxial metallo-dielectric metamaterials with scalar positive permeability

The dispersion relation for plane waves in uniaxial metamaterials with indefinite dielectric tensors and scalar positive permeability is theoretically investigated. It is found, that the isofrequency surfaces of the plane extraordinary waves have a hyperbolic shape which allows the propagation of waves with infinitely long wave vectors. As an example a metallodielectric multilayer was considered and the dispersion relations were determined using an effective medium approximation and an analytically exact Bloch wave calculation. The extraordinary waves in this structure are identified as multilayer plasmons and the validity of the effective medium approximation is examined.