Characteristics of GdGaO grown by MBE

Ga₂O₃/GdGaO dielectric stacks have been grown on GaAs for MOSFETs. This paper highlights variations in the characteristics of GdGaO as the Gd flux, Ga₂O flux and substrate temperature are changed. The growth rate, composition, crystallinity are discussed and the sheet resistance of final MOSFET structures are presented. The Gd compositional variation with depth is examined using Rutherford back scattering (RBS) and electron energy loss spectroscopy (EELS).     

Wear Performance of Laser Processed Tantalum Coatings

This first generation investigation evaluates the in vitro tribological performance of laser-processed Ta coatings on Ti for load-bearing implant applications. Linear reciprocating wear tests in simulated body fluid showed one order of magnitude less wear rate, of the order of 10(-4)mm(3)(N.m)(-1), for Ta coatings compared to Ti. Our results demonstrate that Ta coatings can potentially minimize the early-stage bone-implant interface micro-motion induced wear debris generation due to their excellent bioactivity comparable to that of hydroxyapatite (HA), high wear resistance and toughness compared to popular HA coatings.     

A Simple Compressive Sensing Algorithm for Parallel Many-Core Architectures

In this paper we consider the l ¹-compressive sensing problem. We propose an algorithm specifically designed to take advantage of shared memory, vectorized, parallel and many-core microprocessors such as the Cell processor, new generation Graphics Processing Units (GPUs) and standard vectorized multi-core processors (e.g. quad-core CPUs). Besides its implementation is easy. We also give evidence of the efficiency of our approach and compare the algorithm on the three platforms, thus exhibiting pros and cons for each of them.     

Cluster Monte Carlo and numerical mean field analysis for the water liquid-liquid phase transition

Using Wolff's cluster Monte Carlo simulations and numerical minimization within a mean field approach, we study the low temperature phase diagram of water, adopting a cell model that reproduces the known properties of water in its fluid phases. Both methods allow us to study the thermodynamic behavior of water at temperatures, where other numerical approaches - both Monte Carlo and molecular dynamics - are seriously hampered by the large increase of the correlation times. The cluster algorithm also allows us to emphasize that the liquid-liquid phase transition corresponds to the percolation transition of tetrahedrally ordered water molecules.     

Characterising pre-preg and non-crimp-fabric composite single lap bonded joints

Pre-preg and non-crimp-fabric composite single lap bonded joints were manufactured and investigated to characterise the bond quality and static failure behaviour. A two-part epoxy adhesive was employed to bond composite laminates. The composite panels, which were treated with low pressure oxygen plasma, were bonded in a hot drape former and then cut to manufacture single lap bonded joints. The joints were examined using X-ray microtomography to evaluate the bond quality achieved in the hot drape former. Quasi-static tensile tests were conducted on the pre-preg and non-crimp-fabric composite single lap bonded joints. The fracture surfaces were examined using optical and scanning electron microscopy. The static failure behaviour and failure patterns observed in the two joint types were compared and discussed.     

The Interpretation of Train Rolling Resistance from Fundamental Mechanics

Past efforts in railway improvement have focused on increased train stability and ride quality for safe and smooth operations at higher speed. The question of energy consumption has rarely been considered. In view of projections of higher fuel costs and increased rail traffic volume, energy effects caused by improved train resistance should be considered. First-order expressions for the rolling resistance of freight trains on level tangent track were derived from the basic principles of physics and engineering. The average power dissipated by the suspension system was obtained from a linear model of the track train system. Hysteresis in the soil is computed using basic principles of soil mechanics. Losses due to wheel rolling friction, imposed wheel sliding, and bearings were estimated from simple engineering and considerations. Rolling resistance as would be measured in coast down or drawbar pull tests on level tangent track is found to depend strongly on the quality of the track as well as weight and speed. On good track, most of the rolling resistance is due to bearing resistance, while on poor track, suspension losses predominate. Empirical expressions such as the Davis formula, which have been used in the past by the railroad industry, are unable to describe train rolling resistance adequately because of the way in which they are parameterized. Some of the parameter values obtained from fits to experimental data do not carry the physical meaning with which they were traditionally associated.     

Adaptive spatiotemporal receptive field estimation in the visual pathway

The encoding properties of the visual pathway are under constant control from mechanisms of adaptation and systems-level plasticity. In all but the most artificial experimental conditions, these mechanisms serve to continuously modulate the spatial and temporal receptive field (RF) dynamics. Conventional reverse-correlation techniques designed to capture spatiotemporal RF properties assume invariant stimulus-response relationships over experimental trials and are thus limited in their applicability to more natural experimental conditions. Presented here is an approach to tracking time-varying encoding dynamics in the early visual pathway based on adaptive estimation of the spatiotemporal RF in the time domain. Simulations and experimental data from the lateral geniculate nucleus reveal that subtle features of encoding properties can be captured by the adaptive approach that would otherwise be undetected. Capturing the role of dynamically varying encoding mechanisms is vital to our understanding of vision on the natural setting, where there is absence of a true steady state.     

Spatially adaptive techniques for level set methods and incompressible flow

Since the seminal work of [Sussman, M, Smereka P, Osher S. A level set approach for computing solutions to incompressible two-phase flow. J Comput Phys 1994;114:146–59] on coupling the level set method of [Osher S, Sethian J. Fronts propagating with curvature-dependent speed: algorithms based on Hamilton–Jacobi formulations. J Comput Phys 1988;79:12–49] to the equations for two-phase incompressible flow, there has been a great deal of interest in this area. That work demonstrated the most powerful aspects of the level set method, i.e. automatic handling of topological changes such as merging and pinching, as well as robust geometric information such as normals and curvature. Interestingly, this work also demonstrated the largest weakness of the level set method, i.e. mass or information loss characteristic of most Eulerian capturing techniques. In fact, [Sussman M, Smereka P, Osher S. A level set approach for computing solutions to incompressible two-phase flow. J Comput Phys 1994;114:146–59] introduced a partial differential equation for battling this weakness, without which their work would not have been possible. In this paper, we discuss both historical and most recent works focused on improving the computational accuracy of the level set method focusing in part on applications related to incompressible flow due to both of its popularity and stringent accuracy requirements. Thus, we discuss higher order accurate numerical methods such as Hamilton–Jacobi WENO [Jiang G-S, Peng D. Weighted ENO schemes for Hamilton–Jacobi equations. SIAM J Sci Comput 2000;21:2126–43], methods for maintaining a signed distance function, hybrid methods such as the particle level set method [Enright D, Fedkiw R, Ferziger J, Mitchell I. A hybrid particle level set method for improved interface capturing. J Comput Phys 2002;183:83–116] and the coupled level set volume of fluid method [Sussman M, Puckett EG. A coupled level set and volume-of-fluid method for computing 3d and axisymmetric incompressible two-phase flows. J Comput Phys 2000;162:301–37], and adaptive gridding techniques such as the octree approach to free surface flows proposed in [Losasso F, Gibou F, Fedkiw R. Simulating water and smoke with an octree data structure, ACM Trans Graph (SIGGRAPH Proc) 2004;23:457–62].     

Efficient Huber-Markov edge-preserving image restoration.

The regularization of the least-squares criterion is an effective approach in image restoration to reduce noise amplification. To avoid the smoothing of edges, edge-preserving regularization using a Gaussian Markov random field (GMRF) model is often used to allow realistic edge modeling and provide stable maximum a posteriori (MAP) solutions. However, this approach is computationally demanding because the introduction of a non-Gaussian image prior makes the restoration problem shift-variant. In this case, a direct solution using fast Fourier transforms (FFTs) is not possible, even when the blurring is shift-invariant. We consider a class of edge-preserving GMRF functions that are convex and have nonquadratic regions that impose less smoothing on edges. We propose a decomposition-enabled edge-preserving image restoration algorithm for maximizing the likelihood function. By decomposing the problem into two subproblems, with one shift-invariant and the other shift-variant, our algorithm exploits the sparsity of edges to define an FFT-based iteration that requires few iterations and is guaranteed to converge to the MAP estimate.