An evolutionary approach to improve connectivity prediction in mobile wireless sensor networks

Connectivity is the basic factor for the proper operation of any wireless network. In a mobile wireless sensor network it is a challenge for applications and protocols to deal with connectivity problems, as links might get up and down frequently. In these scenarios, having knowledge of the node remaining connectivity time could both improve the performance of the protocols (e.g. handoff mechanisms) and save possible scarce nodes resources (CPU, bandwidth, and energy) by preventing unfruitful transmissions. The current paper provides a solution called Genetic Machine Learning Algorithm (GMLA) to forecast the remainder connectivity time in mobile environments. It consists in combining Classifier Systems with a Markov chain model of the RF link quality. The main advantage of using an evolutionary approach is that the Markov model parameters can be discovered on-the-fly, making it possible to cope with unknown environments and mobility patterns. Simulation results show that the proposal is a very suitable solution, as it overcomes the performance obtained by similar approaches.

A modular approach to study protein adsorption on surface modified hydroxyapatite

Biocompatible inorganic nano- and microcarriers can be suitable candidates for protein delivery. This study demonstrates facile methods of functionalization by using nanoscale linker molecules to change the protein adsorption capacity of hydroxyapatite (HA) powder. The adsorption capacity of bovine serum albumin as a model protein has been studied with respect to the surface modifications. The selected linker molecules (lysine, arginine, and phosphoserine) can influence the adsorption capacity by changing the electrostatic nature of the HA surface. Qualitative and quantitative analyses of linker-molecule interactions with the HA surface have been performed by using NMR spectroscopy, zeta-potential measurements, X-ray photoelectron spectroscopy, and thermogravimetric analyses. Additionally, correlations to theoretical isotherm models have been calculated with respect to Langmuir and Freundlich isotherms. Lysine and arginine increased the protein adsorption, whereas phosphoserine reduced the protein adsorption. The results show that the adsorption capacity can be controlled with different functionalization, depending on the protein-carrier selections under consideration. The scientific knowledge acquired from this study can be applied in various biotechnological applications that involve biomolecule-inorganic material interfaces.