Assessing the Antimicrobial Activity of Polyisoprene Based Surfaces

There has been an intense research effort in the last decades in the field of biofouling prevention as it concerns many aspects of everyday life and causes problems to devices, the environment, and human health. Many different antifouling and antimicrobial materials have been developed to struggle against bacteria and other micro- and macro-organism attachment to different surfaces. However the “miracle solution” has still to be found. The research presented here concerns the synthesis of bio-based polymeric materials and the biological tests that showed their antifouling and, at the same time, antibacterial activity. The raw material used for the coating synthesis was natural rubber. The polyisoprene chains were fragmented to obtain oligomers, which had reactive chemical groups at their chain ends, therefore they could be modified to insert polymerizable and biocidal groups. Films were obtained by radical photopolymerization of the natural rubber derived oligomers and their structure was altered, in order to understand the mechanism of attachment inhibition and to increase the efficiency of the anti-biofouling action. The adhesion of three species of pathogenic bacteria and six strains of marine bacteria was studied. The coatings were able to inhibit bacterial attachment by contact, as it was verified that no detectable leaching of toxic molecules occurred.     

A 1.4GS/s 9-bit 45 dB power control RFDAC for digital radio transmitters

This paper presents a high speed, 9-bit RF Digital-to-Analog Converter based on a new architecture implemented in a 0.13 μm BiCMOS process and able to adjust the output power by 45 dB to meet gain control requirements of the new communications standards with a SFDR >25 dBc. The maximum test-demonstrated frequency is 1.4 GHz and the chip dissipates <25 mW.     

Improvement of measurement techniques for damping induced by micro-sliding

This paper deals with the damping caused by friction in joints. A new test bench is presented and justified by comparisons made with devices described in the literature. The purpose of this academic bench is to measure the damping induced by partial slip and friction in a planar joint. Moreover, allows uncoupling normal static and dynamic tangential forces. A new method for so-called stopped-sine excitation was developed. It allows more precise monitoring of the evolution of the vibration frequency and damping of non-linear modes. This method is associated with piezoelectric exciters for greater efficiency when stopping excitation. A large number of experimental results are presented and discussed. They are used to characterize the damping induced by micro-sliding in the bonds.     

Behavior of RC columns strengthened with different CFRP systems under eccentric loading

The present study investigates the performance of eccentrically loaded columns externally strengthened with different carbon fiber-reinforced polymer (CFRP) systems. The 10 specimens were representative-scale square columns made of normal-strength concrete with substandard (internal) reinforcement details that were designed to represent old building structural columns. Eight columns were upgraded by four types of commercially available systems of external reinforcement, using plates, unidirectional or bi-directional composite fabrics. It was considered necessary to get information on a wide spectrum of carbon fiber-reinforcement systems in order to provide a satisfactory set of experimental data for validating future suitable retrofitting design methods. Experimental results presented in this paper show that a significant improvement of the strength capacity, deformation capacity and ductility of columns can result of the CFRP application, but the observed gains strongly depend on the reinforcement systems.     

Additive Composition of Supervised Self-Organizing Maps

The learning of complex relationships can be decomposed into several neural networks. The modular organization is determined by prior knowledge of the problem that permits to split the processing into tasks of small dimensionality. The sub-tasks can be implemented with neural networks, although the learning examples cannot be used anymore to supervise directly each of the networks. This article addresses the problem of learning in a modular context, developing in particular additive compositions. A simple rule allows defining efficient training, and combining, for example, several Supervised-SOM networks. This technique is important because it introduces interesting generalizations in many modular compositions, permitting data fusion or sequential combinations of neural networks. This revised version was published online in August 2006 with corrections to the Cover Date.