Morphology, characterization, and distribution of retinal photoreceptors in the Australian lungfish Neoceratodus forsteri (Krefft, 1870)

The Australian lungfish Neoceratodus forsteri (Dipnoi) is an ancient fish that has a unique phylogenetic relationship among the basal Sarcopterygii. Here we examine the ultrastructure, histochemistry, and distribution of the retinal photoreceptors using a combination of light and electron microscopy in order to determine the characteristics of the photoreceptor layer in this living fossil. Similar proportions of rods (53%) and cones (47%) reveal that N. forsteri optimizes both scotopic and photopic sensitivity according to its visual demands. Scotopic sensitivity is optimized by a tapetum lucidum and extremely large rods (18.62 +/- 2.68 mu m ellipsoid diameter). Photopic sensitivity is optimized with a theoretical spatial resolving power of 3.28 +/- 0.66 cycles degree(-1), which is based on the spacing of at least three different cone types: a red cone containing a red oil droplet, a yellow cone containing a yellow ellipsoidal pigment, and a colorless cone containing multiple clear oil droplets. Topographic analysis reveals a heterogeneous distribution of all photoreceptor types, with peak cone densities predominantly found in temporal retina (6,020 rods MM 2, 4,670 red cones mm(-2), 900 yellow cones mm(-2), and 320 colorless cones mm(-2)), but ontogenetic changes in distribution are revealed. Spatial resolving power and the diameter of all photoreceptor types (except yellow cones) increases linearly with growth. The presence of at least three morphological types of cones provides the potential for color vision, which could play a role in the clearer waters of its freshwater environment.

Power system sensitivity analysis for probabilistic small signal stability assessment in a deregulated environment

Deregulations and market practices in power industry have brought great challenges to the system planning area. In particular, they introduce a variety of uncertainties to system planning. New techniques are required to cope with such uncertainties. As a promising approach, probabilistic methods are attracting more and more attentions by system planners. In small signal stability analysis, generation control parameters play an important role in determining the stability margin. The objective of this paper is to investigate power system state matrix sensitivity characteristics with respect to system parameter uncertainties with analytical and numerical approaches and to identify those parameters have great impact on system eigenvalues, therefore, the system stability properties. Those identified parameter variations need to be investigated with priority. The results can be used to help Regional Transmission Organizations (RTOs) and Independent System Operators (ISOs) perform planning studies under the open access environment.

Schrodinger cats and their power for quantum information processing

We outline a toolbox comprised of passive optical elements, single photon detection and superpositions of coherent states (Schrodinger cat states). Such a toolbox is a powerful collection of primitives for quantum information processing tasks. We illustrate its use by outlining a proposal for universal quantum computation. We utilize this toolbox for quantum metrology applications, for instance weak force measurements and precise phase estimation. We show in both these cases that a sensitivity at the Heisenberg limit is achievable.

Eigenvalue sensitivity analysis for probabilistic small signal stability assessment

This paper presents a method to analyze the first order eigenvalue sensitivity with respect to the operating parameters of a power system. The method is based on explicitly expressing the system state matrix into sub-matrices. The eigenvalue sensitivity is calculated based on the explicitly formed system state matrix. The 4th order generator model and 4th order exciter system model are used to form the system state matrix. A case study using New England 10-machine 39-bus system is provided to demonstrate the effectiveness of the proposed method. This method can be applied into large scale power system eigenvalue sensitivity with respect to operating parameters.