Pupil response to color signals in cone-contrast space

Purpose: It is widely accepted that pupil responses to visual stimuli are determined by the ambient illuminance, and recently it has been shown that changes in stimulus color also contributes to a pupillary control mechanism. However, the role of pupillary responses to chromatic stimuli is not clear. The aim of this study was to investigate how color and luminance signals contribute to the pupillary control mechanism. Methods: We measured pupillary iso-response contours in M-and L-cone contrast space. The iso-response contours in cone-contrast space have been determined to examine what mechanisms contribute to the pupillary pathway. The shapes of the iso-response contour change when different mechanisms determine the response. Results: It was shown that for all subjects, the pupillary iso-response contours form an ellipse with positive slope in cone-contrast space, indicating that the sensitivities to the chromatic stimuli are higher than those for the luminance stimuli. The pupil responds maximally to a grating that has a stronger L-cone modulation than the red-green isoluminant grating. Conclusions: The sensitivity of the chromatic pathway, in terms of pupillary response, is three times larger than that of the luminance pathway, a property that might have utility in clinical applications. Copyright © Taylor & Francis Group, LLC.

Numerical Approximation of a Fractional-In-Space Diffusion Equation, I

2000 Mathematics Subject Classification: 26A33 (primary), 35S15 (secondary)

Regular Averaging and Regular Extension Operators in Weakly Compact Subsets of Hilbert Spaces

2000 Mathematics Subject Classification: Primary 46E15, 54C55; Secondary 28B20.

An Invariant Theory of Surfaces in the Four-Dimensional Euclidean or Minkowski Space

2010 Mathematics Subject Classification: 53A07, 53A35, 53A10.

Weakly Compact Generating and Shrinking Markusevic Bases

2000 Mathematics Subject Classification: 46B30, 46B03.

Subvarieties of the Hyperelliptic Moduli Determined by Group Actions

2000 Mathematics Subject Classification: 14Q05, 14Q15, 14R20, 14D22.

Sobolev Type Decomposition of Paley-Wiener-Schwartz Space with Application to Sampling Theory

2000 Mathematics Subject Classification: 94A12, 94A20, 30D20, 41A05.

Self-adapting parallel metric-space search engine for variable query loads

This research focuses on automatically adapting a search engine size in response to fluctuations in query workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computer resources to or from the engine. Our solution is to contribute an adaptive search engine that will repeatedly re-evaluate its load and, when appropriate, switch over to a dierent number of active processors. We focus on three aspects and break them out into three sub-problems as follows: Continually determining the Number of Processors (CNP), New Grouping Problem (NGP) and Regrouping Order Problem (ROP). CNP means that (in the light of the changes in the query workload in the search engine) there is a problem of determining the ideal number of processors p active at any given time to use in the search engine and we call this problem CNP. NGP happens when changes in the number of processors are determined and it must also be determined which groups of search data will be distributed across the processors. ROP is how to redistribute this data onto processors while keeping the engine responsive and while also minimising the switchover time and the incurred network load. We propose solutions for these sub-problems. For NGP we propose an algorithm for incrementally adjusting the index to t the varying number of virtual machines. For ROP we present an ecient method for redistributing data among processors while keeping the search engine responsive. Regarding the solution for CNP, we propose an algorithm determining the new size of the search engine by re-evaluating its load. We tested the solution performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud. Our experiments show that when we compare our NGP solution with computing the index from scratch, the incremental algorithm speeds up the index computation 2{10 times while maintaining a similar search performance. The chosen redistribution method is 25% to 50% faster than other methods and reduces the network load around by 30%. For CNP we present a deterministic algorithm that shows a good ability to determine a new size of search engine. When combined, these algorithms give an adapting algorithm that is able to adjust the search engine size with a variable workload.

Morphometrics of seagrasses at species level, Moreton Bay, Australia determined from core samples collected in 2012-2013

Seagrass meadows are important marine carbon sinks, yet they are threatened and declining worldwide. Seagrass management and conservation requires adequate understanding of the physical and biological factors determining carbon content in seagrass sediments. Here, we identified key factors that influence carbon content in seagrass meadows across several environmental gradients in Moreton Bay, SE Queensland. Sampling was conducted in two regions: (1) Canopy Complexity, 98 sites on the Eastern Banks, where seagrass canopy structure and species composition varied while turbidity was consistently low; and (2) Turbidity Gradient, 11 locations across the entire bay, where turbidity varied among sampling locations. Sediment organic carbon content and seagrass structural complexity (shoot density, leaf area, and species specific characteristics) were measured from shallow sediment and seagrass biomass cores at each location, respectively. Environmental data were obtained from empirical measurements (water quality) and models (wave height). The key factors influencing carbon content in seagrass sediments were seagrass structural complexity, turbidity, water depth, and wave height. In the Canopy Complexity region, carbon content was higher for shallower sites and those with higher seagrass structural complexity. When turbidity varied along the Turbidity Gradient, carbon content was higher at sites with high turbidity. In both regions carbon content was consistently higher in sheltered areas with lower wave height. Seagrass canopy structure, water depth, turbidity, and hydrodynamic setting of seagrass meadows should therefore be considered in conservation and management strategies that aim to maximize sediment carbon content.

Existence of disjoint weakly mixing operators that fail to satisfy the Disjoint Hypercyclicity Criterion

Recently, Bès, Martin, and Sanders [11] provided examples of disjoint hypercyclic operators which fail to satisfy the Disjoint Hypercyclicity Criterion. However, their operators also fail to be disjoint weakly mixing. We show that every separable, infinite dimensional Banach space admits operators T1,T2,…,TN with N⩾2 which are disjoint weakly mixing, and still fail to satisfy the Disjoint Hypercyclicity Criterion, answering a question posed in [11]. Moreover, we provide examples of disjoint hypercyclic operators T1, T2 whose corresponding set of disjoint hypercyclic vectors is nowhere dense, answering another question posed in [11]. In fact, we explicitly describe their set of disjoint hypercyclic vectors. Those same disjoint hypercyclic operators fail to be disjoint topologically transitive. Lastly, we create examples of two families of d-hypercyclic operators which fail to have any d-hypercyclic vectors in common.

Dynamic instabilities in scalar neural field equations with space-dependent delays

In this paper we consider a class of scalar integral equations with a form of space-dependent delay. These non-local models arise naturally when modelling neural tissue with active axons and passive dendrites. Such systems are known to support a dynamic (oscillatory) Turing instability of the homogeneous steady state. In this paper we develop a weakly nonlinear analysis of the travelling and standing waves that form beyond the point of instability. The appropriate amplitude equations are found to be the coupled mean-field Ginzburg-Landau equations describing a Turing-Hopf bifurcation with modulation group velocity of O(1). Importantly we are able to obtain the coefficients of terms in the amplitude equations in terms of integral transforms of the spatio-temporal kernels defining the neural field equation of interest. Indeed our results cover not only models with axonal or dendritic delays but those which are described by a more general distribution of delayed spatio-temporal interactions. We illustrate the predictive power of this form of analysis with comparison against direct numerical simulations, paying particular attention to the competition between standing and travelling waves and the onset of Benjamin-Feir instabilities.

Numerical approximation of a fractional-in-space diffusion equation (II) - with nonhomogeneous boundary conditions

In this paper, a space fractional di®usion equation (SFDE) with non- homogeneous boundary conditions on a bounded domain is considered. A new matrix transfer technique (MTT) for solving the SFDE is proposed. The method is based on a matrix representation of the fractional-in-space operator and the novelty of this approach is that a standard discretisation of the operator leads to a system of linear ODEs with the matrix raised to the same fractional power. Analytic solutions of the SFDE are derived. Finally, some numerical results are given to demonstrate that the MTT is a computationally e±cient and accurate method for solving SFDE.