Adhesion of a rigid punch to a confined elastic layer revisited

The adhesion of a punch to a linear elastic, confined layer is investigated. Numerical analysis is performed to determine the equivalent elastic modulus in terms of layer confinement. The size of the layer relative to the punch radius and its Poisson’s ratio are found to affect the layer stiffness. The results reveal that the equivalent modulus of a highly confined layer depends on its Poisson’s ratio, whereas, in contrast, an unconfined layer is only sensitive to the extent of the elastic film. The solutions of the equivalent modulus obtained from the simulations are fitted by an analytical function that, subsequently, is utilized to deduce the energy release rate for detachment of the punch via linear elastic fracture mechanics. The energy release rate strongly varies with layer confinement. Regimes for stable and unstable crack growth can be identified that, in turn, are correlated to interfacial stress distributions to distinguish between different detachment mechanisms.     

Synergistic reinforcement of surface modification on improving the bonding of veneering ceramics to zirconia

Veneering ceramics should be strongly bonded to zirconia core in order to achieve successfully long-term clinical practice. Indeed, to pursue the high zirconia core–veneering ceramic bonding is still a concerned issue. In this regard, this study was to treat zirconia surface using a 3?wt% Si₃N₄ solution in 4?M NaOH and to investigate the effect of soaking time (5, 10, and 20 days) on the surface properties of zirconia and shear bond strength between zirconia and veneering ceramics. The residual veneering ceramics on zirconia surfaces and failure modes were also examined after fracture. The results showed that the phase composition of zirconia before and after surface modification was not changed. The elemental mapping and depth profiling consistently revealed the soaking-time-dependent Si content on the zirconia surface. The surface roughness of zirconia was significantly (P?<?0.05) increased with the increasing soaking time. When zirconia was treated for 10 days, the shear bond strength value of 27.4?MPa was significantly (P?<?0.05) higher than the control (18.6?MPa), associated with greater remaining amounts of veneering ceramics on the zirconia surface. The failure mode of the treated zirconia was almost the mixed failure. On the basis of the data, surface modification using Si₃N₄ in NaOH solution for zirconia core could be a simple and effective method for enhancing the veneering ceramic–zirconia bonding.     

On Efficiency of Multi-job Grid Allocation Based on Statistical Trace Data

The ever growing number of computation-intensive applications calls for utilizing large-scale, potentially interoperable distributed infrastructures. Nowadays, such distributed systems enable the management of heterogeneous scientific workflows of considerable sizes, where job scheduling and resource management is a crucial issue. In this paper we focus on the challenges of scheduling parameter sweep applications, a specific and commonly used type of workflows where ordering of job executions is irrelevant. A parameter sweep has a large set of independent job instances, called a multi-job, submitted for execution in a single step. In order to cope with the high uncertainty and unpredictable load of resources, and the simultaneous submissions of multi-job instances, we propose a statistics-based brokering approach for allocating jobs to resources so that the makespan is minimised. Earlier studies claim that users’ predictions on job runtime are inaccurate and unusable for scheduling. Our aim is to examine, whether statistical trace data for the same purpose is efficient compared to randomized allocation.     

General distributed economic framework for dynamic spectrum allocation

The emergence of novel radio techniques enables the application of advantageous revolutionary spectrum policies. An important body of research has appeared about possible frequency management schemes, but none of them proposes solutions that meet every related criteria. In this paper we present our work on dynamic spectrum allocation and pricing that offers a distributed mechanism design, well-suited to practical employment issues. Our model handles interference effects without any restricting assumptions, provides universal scalable and incentive-compatible allocation and pricing mechanisms. We provide both analytical and numerical evaluation of the proposed framework, and in either case we prove this latter to be a suitable approach to efficient and flexible spectrum utilization.     

Radiosity with Well Distributed Ray Sets

In this paper we present a new radiosity algorithm, based on the notion of a well distributed ray set (WDRS). A WDRS is a set of rays, connecting mutually visible points and patches, that forms an approximate representation of the radiosity operator and the radiosity distribution. We propose an algorithm that constructs an optimal WDRS for a given accuracy and mesh. The construction is based on discrete importance sampling as in previously proposed stochastic radiosity algorithms, and on quasi Monte Carlo sampling. Quasi Monte Carlo sampling leads to faster convergence rates and the fact that the sampling is deterministic makes it possible to represent the well distributed ray set very efficiently in computer memory. Like previously proposed stochastic radiosity algorithms, the new algorithm is well suited for computing the radiance distribution in very complex diffuse scenes, when it is not feasible to explicitly compute and store form factors as in classical radiosity algorithms. Experiments show that the new algorithm is often more efficient than previously proposed Monte Carlo radiosity algorithms by half an order of magnitude and more.     

An implementation of the coupled perturbed Kohn-Sham equations: perturbation due to nuclear displacements

The Coupled Perturbed Kohn-Sham equations have been implemented in the Amsterdam Density Functional program package. Our implementation differs from previous ones in many ways. This program uses density fitting to calculate the Coulomb and exchange integrals. Further, all matrix elements of the Fock type matrix and its derivatives are calculated by numerical integration. The frozen core approximation is also implemented. Our implementation is approximately 10 times faster than a finite difference algorithm, and the absolute CPU times also compare favorably with other reported implementations.     

Model complexity reduction of chemical reaction networks using mixed-integer quadratic programming

The model complexity reduction problem of large chemical reaction networks under isobaric and isothermal conditions is considered. With a given detailed kinetic mechanism and measured data of the key species over a finite time horizon, the complexity reduction is formulated in the form of a mixed-integer quadratic optimization problem where the objective function is derived from the parametric sensitivity matrix. The proposed method sequentially eliminates reactions from the mechanism and simultaneously tunes the remaining parameters until the pre-specified tolerance limit in the species concentration space is reached. The computational efficiency and numerical stability of the optimization are improved by a pre-reduction step followed by suitable scaling and initial conditioning of the Hessian involved. The proposed complexity reduction method is illustrated using three well-known case studies taken from reaction kinetics literature.     

Dynamic 3-D computer graphics for designing a diagnostic tool for patients with schizophrenia

We introduce a novel procedure that uses dynamic 3-D computer graphics as a diagnostic tool for assessing disease severity in schizophrenia patients, based on their reduced influence of top-down cognitive processes in interpreting bottom-up sensory input. Our procedure uses the hollow-mask illusion, in which the concave side of the mask is misperceived as convex, because familiarity with convex faces dominates sensory cues signaling a concave mask. It is known that schizophrenia patients resist this illusion and their resistance increases with illness severity. Our method uses virtual masks rendered with two competing textures: (a) realistic features that enhance the illusion; (b) random-dot visual noise that reduces the illusion. We control the relative weights of the two textures to obtain psychometric functions for controls and patients and assess illness severity. The primary novelty is the use of a rotating mask that is easy to implement on a wide variety of portable devices and avoids the use of elaborate stereoscopic devices that have been used in the past. Thus our method, which can also be used to assess the efficacy of treatments, provides clinicians the advantage to bring the test to the patient’s own environment, instead of having to bring patients to the clinic.     

Models wagging the dog: are circuits constructed with disparate parameters?

In a recent article, Prinz, Bucher, and Marder (2004) addressed the fundamental question of whether neural systems are built with a fixed blueprint of tightly controlled parameters or in a way in which properties can vary largely from one individual to another, using a database modeling approach. Here, we examine the main conclusion that neural circuits indeed are built with largely varying parameters in the light of our own experimental and modeling observations. We critically discuss the experimental and theoretical evidence, including the general adequacy of database approaches for questions of this kind, and come to the conclusion that the last word for this fundamental question has not yet been spoken.     

GPU-based simulation of the long-range Potts model via parallel tempering

We discuss the efficiency of parallelization on graphical processing units (GPUs) for the simulation of the one-dimensional Potts model with long-range interactions via parallel tempering. We investigate the behavior of some thermodynamic properties, such as equilibrium energy and magnetization, critical temperatures as well as the separation between the first- and second-order regimes. By implementing multispin coding techniques and an efficient parallelization of the interaction energy computation among threads, the GPU-accelerated approach reached speedup factors of up to 37.