Graded/Gradient Porous Biomaterials

Biomaterials include bioceramics, biometals, biopolymers and biocomposites and they play important roles in the replacement and regeneration of human tissues. However, dense bioceramics and dense biometals pose the problem of stress shielding due to their high Young's moduli compared to those of bones. On the other hand, porous biomaterials exhibit the potential of bone ingrowth, which will depend on porous parameters such as pore size, pore interconnectivity, and porosity. Unfortunately, a highly porous biomaterial results in poor mechanical properties. To optimise the mechanical and the biological properties, porous biomaterials with graded/gradient porosity, pores size, and/or composition have been developed. Graded/gradient porous biomaterials have many advantages over graded/gradient dense biomaterials and uniform or homogenous porous biomaterials. The internal pore surfaces of graded/gradient porous biomaterials can be modified with organic, inorganic, or biological coatings and the internal pores themselves can also be filled with biocompatible and biodegradable materials or living cells. However, graded/gradient porous biomaterials are generally more difficult to fabricate than uniform or homogenous porous biomaterials. With the development of cost-effective processing techniques, graded/gradient porous biomaterials can find wide applications in bone defect filling, implant fixation, bone replacement, drug delivery, and tissue engineering.

Semi batch learning with store management using enhanced conjugate gradient

This paper explores the performance of sliding-window based training, termed as semi batch, using multilayer perceptron (MLP) neural network in the presence of correlated data. The sliding window training is a form of higher order instantaneous learning strategy without the need of covariance matrix, usually employed for modeling and tracking purposes. Sliding-window framework is implemented to combine the robustness of offline learning algorithms with the ability to track online the underlying process of a function. This paper adopted sliding window training with recent advances in conjugate gradient direction with application of data store management e.g. simple distance measure, angle evaluation and the novel prediction error test. The simulation results show the best convergence performance is gained by using store management techniques. © 2012 Springer-Verlag.

Electromagnetic Focusing and Imaging in Stratified Media Using Gradient Phase Profiled Conjugating Lens

High-resolution imaging of a dipole source in stratified medium based on negative refraction is presented in this paper. Compensation of the material parameter contrast at the stratified media interface is achieved using a gradient phase profiled conjugating lens (GPCL). It is shown both analytically and numerically that the phase gradient applied across the GPCL positioned at the interface of vertically stratified media enables a high-quality image of a dipole source in a mirror symmetric position with respect to the lens plane. The analytical closed form expression of the phase gradient function is derived using Huygens-Kirchhoff principle. The result is applicable to media with arbitrary stratification and material parameters, including lossy materials. The mechanism for formation of the dipole image in the stratified medium and aberration due to the dielectric contrast at the interface, particularly electromagnetic loss, is discussed in detail. The efficacy of gradient phase and amplitude aberration compensations mechanisms available through the GPCL is articulated. The results of the study are of importance in a wide range of imaging problems in stratified media for medical, civil, and military applications.

Direct Observation of Density-Gradient Effects in Harmonic Generation from Plasma Mirrors

High-order harmonics and attosecond pulses of light can be generated when ultraintense, ultrashort laser pulses reflect off a solid-density plasma with a sharp vacuum interface, i.e., a plasma mirror. We demonstrate experimentally the key influence of the steepness of the plasma-vacuum interface on the interaction, by measuring the spectral and spatial properties of harmonics generated on a plasma mirror whose initial density gradient scale length L is continuously varied. Time-resolved interferometry is used to separately measure this scale length. 

On the Merit of Selecting Different Belief Merging Operators

Belief merging operators combine multiple belief bases (a profile) into a collective one. When the conjunction of belief bases is consistent, all the operators agree on the result. However, if the conjunction of belief bases is inconsistent, the results vary between operators. There is no formal manner to measure the results and decide on which operator to select. So, in this paper we propose to evaluate the result of merging operators by using three ordering relations (fairness, satisfaction and strength) over operators for a given profile. Moreover, a relation of conformity over operators is introduced in order to classify how well the operator conforms to the definition of a merging operator. By using the four proposed relations we provide a comparison of some classical merging operators and evaluate the results for some specific profiles.

A comparison of merging operators in possibilistic logic.

In this paper, we compare merging operators in possibilistic logic. We rst propose an approach to evaluating the discriminating power of a merging operator. After that, we analyze the computational complexity of existing possibilistic merging operators. Finally, we consider the compatibility of possibilistic merging operators with propositional merging operators.