Detecting finite bandwidth periodic signals in stationary noise using the signal coherence spectrum

All signals that appear to be periodic have some sort of variability from period to period regardless of how stable they appear to be in a data plot. A true sinusoidal time series is a deterministic function of time that never changes and thus has zero bandwidth around the sinusoid's frequency. A zero bandwidth is impossible in nature since all signals have some intrinsic variability over time. Deterministic sinusoids are used to model cycles as a mathematical convenience. Hinich [IEEE J. Oceanic Eng. 25 (2) (2000) 256-261] introduced a parametric statistical model, called the randomly modulated periodicity (RMP) that allows one to capture the intrinsic variability of a cycle. As with a deterministic periodic signal the RMP can have a number of harmonics. The likelihood ratio test for this model when the amplitudes and phases are known is given in [M.J. Hinich, Signal Processing 83 (2003) 1349-13521. A method for detecting a RMP whose amplitudes and phases are unknown random process plus a stationary noise process is addressed in this paper. The only assumption on the additive noise is that it has finite dependence and finite moments. Using simulations based on a simple RMP model we show a case where the new method can detect the signal when the signal is not detectable in a standard waterfall spectrograrn display. (c) 2005 Elsevier B.V. All rights reserved.

Biomolecular engineering at interfaces

A broad review of technologically focused work concerning biomolecules at interfaces is presented. The emphasis is on developments in interfacial biomolecular engineering that may have a practical impact in bioanalysis, tissue engineering, emulsion processing or bioseparations. We also review methods for fabrication in an attempt to draw out those approaches that may be useful for product manufacture, and briefly review methods for analysing the resulting interfacial nanostructures. From this review we conclude that the generation of knowledge and-innovation at the nanoscale far exceeds our ability to translate this innovation into practical outcomes addressing a market need, and that significant technological challenges exist. A particular challenge in this translation is to understand how the structural properties of biomolecules control the assembled architecture, which in turn defines product performance, and how this relationship is affected by the chosen manufacturing route. This structure-architecture-process-performance (SAPP) interaction problem is the familiar laboratory scale-up challenge in disguise. A further challenge will be to interpret biomolecular self- and directed-assembly reactions using tools of chemical reaction engineering, enabling rigorous manufacturing optimization of self-assembly laboratory techniques. We conclude that many of the technological problems facing this field are addressable using tools of modem chemical and biomolecular engineering, in conjunction with knowledge and skills from the underpinning sciences. (c) 2005 Elsevier Ltd. All rights reserved.

The in-vitro bioactivity of mesoporous bioactive glasses

Ordered mesoporous bioactive glasses (MBGs) with different compositions were prepared by using nonionic block copolymer surfactants as structure-directing agents through an evaporation-induced self-assembly process. Their in-vitro bioactivities were studied in detail by electron microscopy, Fourier-transform infrared spectroscopy, and inductively coupled plasma (ICP) atomic emission spectroscopy. The ICP element analysis results were further calculated in terms of the total consumption of Ca and P, Delta[Ca]/Delta[P] ratios, and ionic activity product (IP) of hydroxyapatite. Through the above analysis, it is clear that MBGs show a different structure-bioactivity correlation compared to conventional sol-gel-derivcd BGs. The in vitro bioactivity of MBGs is dependent on the Si/Ca ratio in the network when the other material parameters such as the mesostructure and texture properties (pore size, pore volume) are controlled. MBG 80S15C with relatively lower calcium content exhibits the best in vitro bioactivity, in contrast to conventional sol-gel-derived BGs where usually higher calcium percentage BGs (e.g. 60S35C) show better bioactivity. Calcination temperature is another important factor that influences the in vitro bioactivity. According to our results, MBGs calcined at 973 K may possess the best in vitro bioactivity. The influences of the composition and calcination temperature upon bioactivity are explained in terms of the unique structures of MBGs. (c) 2006 Elsevier Ltd. All rights reserved.

A general-purpose tunable landscape generator

The research literature on metalieuristic and evolutionary computation has proposed a large number of algorithms for the solution of challenging real-world optimization problems. It is often not possible to study theoretically the performance of these algorithms unless significant assumptions are made on either the algorithm itself or the problems to which it is applied, or both. As a consequence, metalieuristics are typically evaluated empirically using a set of test problems. Unfortunately, relatively little attention has been given to the development of methodologies and tools for the large-scale empirical evaluation and/or comparison of metaheuristics. In this paper, we propose a landscape (test-problem) generator that can be used to generate optimization problem instances for continuous, bound-constrained optimization problems. The landscape generator is parameterized by a small number of parameters, and the values of these parameters have a direct and intuitive interpretation in terms of the geometric features of the landscapes that they produce. An experimental space is defined over algorithms and problems, via a tuple of parameters for any specified algorithm and problem class (here determined by the landscape generator). An experiment is then clearly specified as a point in this space, in a way that is analogous to other areas of experimental algorithmics, and more generally in experimental design. Experimental results are presented, demonstrating the use of the landscape generator. In particular, we analyze some simple, continuous estimation of distribution algorithms, and gain new insights into the behavior of these algorithms using the landscape generator.