The development of biomaterials for cardiac tissue engineering (CTE) is challenging, primarily owing to the requirement of achieving a surface with favourable characteristics that enhances cell attachment and maturation. The biomaterial surface plays a crucial role as it forms the interface between the scaffold (or cardiac patch) and the cells. In the field of CTE, synthetic polymers ( polyglycerol sebacate, polyethylene glycol, polyglycolic acid, poly-L-lactide, polyvinyl alcohol, polycaprolactone, polyurethanes and poly(N-isopropylacrylamide)) have been proven to exhibit suitable biodegradable and mechanical properties. Despite the fact that they show the required biocompatible behaviour, most synthetic polymers exhibit poor cell attachment capability. These synthetic polymers are mostly hydrophobic and lack cell recognition sites, limiting their application. Therefore, biofunctionalization of these biomaterials to enhance cell attachment and cell material interaction is being widely investigated. There are numerous approaches for functionalizing a material, which can be classified as mechanical, physical, chemical and biological. In this review, recent studies reported in the literature to functionalize scaffolds in the context of CTE, are discussed. Surface, morphological, chemical and biological modifications are introduced and the results of novel promising strategies and techniques are discussed.
International audienceUsing molecular psychophysics, temporal loudness weights were measured for 2-s, 1-kHz tones with flat, increasing and decreasing time-intensity profiles. While primacy and recency effects were observed for flat profile stimuli, the so-called "level dominance" effect was observed for both increasing and decreasing profile stimuli, fully determining their temporal weights. The weighs obtained for these profiles were basically zero for all but the most intense parts of these sounds. This supports the view that the "level dominance" effect is prominent with intensity-varying sounds and that it persists over time since temporal weights are not affected by the direction of intensity change
This paper presents the construction of an aggregated indicator of a fuelefficient driving style, in order to construct an efficient Ecological Driving Assistance System (EDAS). Such an eco-index can be used to detect eco-driving behaviour, but also to give to the driver useful advices to help him improving his driving efficiency without deteriorating safety. The logistic regression is used to model our experimental dataset of twenty subjects driving twice the same route: normally or following the golden rules of eco-driving. Depending on some driving indicators, the estimated probability of being an eco-driver is used as an eco-index to characterize that driving pattern. This work show how such a simple aggregated indicator, related to driving dynamics rather than fuel consumption, can be useful for driver monitoring and information. Two models, from the simplest to the most complicated, are compared, and their performances analysed.
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