Osteoblast, fibroblast and in vivo biological response to poly(vinylidene fluoride) based composite materials

Electroactivematerials can be taken to advantage for the development of sensors and actuators as well as for novel tissue engineering strategies. Composites based on poly(vinylidenefluoride),PVDF,have been evaluated with respect to their biological response. Cell viability and proliferation were performed in vitro both with Mesenchymal Stem Cells differentiated to osteoblasts and Human Fibroblast Foreskin 1. In vivo tests were also performed using 6-week-old C57Bl/6 mice. It was concluded that zeolite and clay composites are biocompatible materials promoting cell response and not showing in vivo pro-inflammatory effects which renders both of them attractive for biological applications and tissue engineering, opening interesting perspectives to development of scaffolds from these composites. Ferrite and silver nanoparticle composites decrease osteoblast cell viability and carbon nanotubes decrease fibroblast viability. Further, carbon nanotube composites result in a significant increase in local vascularization accompanied an increase of inflammatory markers after implantation.

Critical behavior of a three-dimensional hardcore-cylinder composite system

In this work the critical indices β, γ , and ν for a three-dimensional (3D) hardcore cylinder composite system with short-range interaction have been obtained. In contrast to the 2D stick system and the 3D hardcore cylinder system, the determined critical exponents do not belong to the same universality class as the lattice percolation,although they obey the common hyperscaling relation for a 3D system. It is observed that the value of the correlation length exponent is compatible with the predictions of the mean field theory. It is also shown that, by using the Alexander-Orbach conjuncture, the relation between the conductivity and the correlation length critical exponents has a typical value for a 3D lattice system.

People Detection and Tracking using Depth Camera

In this paper we present a method for real-time detection and tracking of people in video captured by a depth camera. For each object to be assessed, an ordered sequence of values that represents the distances between its center of mass to the boundary points is calculated. The recognition is based on the analysis of the total distance value between the above sequence and some pre-defined human poses, after apply the Dynamic Time Warping. This similarity approach showed robust results in people detection.