Scaffolds, stem cells, and tissue engineering: A potent combination!

Stem cells, either from embryonic or adult sources, have demonstrated the potential to differentiate into a wide range of tissues depending on culture conditions. This makes them prime candidates for use in tissue engineering applications. Current technology allows us to process biocompatible and biodegradable polymers into three-dimensional (3D) configurations, either as solid porous scaffolds or hydrogels, with controlled macro and/or micro spatial geometry and surface chemistry. Such control provides us with the ability to present highly controlled microenvironments to a chosen cell type. However, the precise microenvironments required for optimal expansion and/or differentiation of stem cells are only now being elucidated, and hence the controlled use of stem cells in tissue engineering remains a very young field. We present here a brief review of the current literature detailing interactions between stem cells and 3D scaffolds of varying morphology and chemical properties, concluding with remaining challenges for those interested in tissue engineering using tailored scaffolds and stem cells.

Enhanced detection-guided NLMS estimation of sparse FIR-modeled signal channels

In various signal-channel-estimation problems, the channel being estimated may be well approximated by a discrete finite impulse response (FIR) model with sparsely separated active or nonzero taps. A common approach to estimating such channels involves a discrete normalized least-mean-square (NLMS) adaptive FIR filter, every tap of which is adapted at each sample interval. Such an approach suffers from slow convergence rates and poor tracking when the required FIR filter is "long." Recently, NLMS-based algorithms have been proposed that employ least-squares-based structural detection techniques to exploit possible sparse channel structure and subsequently provide improved estimation performance. However, these algorithms perform poorly when there is a large dynamic range amongst the active taps. In this paper, we propose two modifications to the previous algorithms, which essentially remove this limitation. The modifications also significantly improve the applicability of the detection technique to structurally time varying channels. Importantly, for sparse channels, the computational cost of the newly proposed detection-guided NLMS estimator is only marginally greater than that of the standard NLMS estimator. Simulations demonstrate the favourable performance of the newly proposed algorithm. © 2006 IEEE.

On the origin of a trace inequality

Numerous authors are apparently unaware that bounds on the trace of a matrix product presented in 1995 were originally published in 1990.

A dual band 2.4/5.2GHz antenna including a radial line slot array and a patch

The design of an antenna that combines a radial line slot array and a circular patch to operate as a dual band (2.4/5.2 GHz) antenna at the access point of a WLAN is presented. The design has been accomplished using commercially available Ansoft HFSS and in-house developed software. The designed antenna shows good performance in terms of return losses, radiation pattern and circular polarization in the two, 2.4 and 5.2 GHz, frequency bands. Due to its good electrical performance and a relatively low profile and low developmental cost, it should be found attractive for use as an access point antenna for dual band operation.

RatSLAM: A hippocampal model for simultaneous localisation and mapping

The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.