Abstract:The biocompatibility of chemoenzymatically generated dextran-acrylate hydrogels has been evaluated in vitro, using human foreskin fibroblasts, and in vivo, by subcutaneous and intramuscular implantation in Wistar rats for up to 40 days. In vitro tests show that hydrogel extracts only minimally reduced (Ͻ10%) the mitochondrial metabolic activity of fibroblasts. Direct contact of the hydrogels with cells induced a cellular proliferation inhibition index (CPII) of 50 -80%, compared with a control, whereas through indirect contact, the CPII values were Ͻ16%, suggesting that the high CPII values achieved in the direct assay test were likely due to mechanical stress or limitations in oxygen diffusion. Hence, the hydrogels were noncytotoxic. Moreover, cellmaterial interaction studies show that these hydrogels were nonadhesive. Finally, histologic evaluation of tissue response to subcutaneous and intramuscular implants showed acceptable levels of biocompatibility, as characterized by a normal cellular response and the absence of necrosis of the surrounding tissues of the implant. In the first 10 days, the foreign-body reaction in the intramuscular implantation was more severe than in subcutaneous implantation, becoming identical after 30 days. In both cases, dextran hydrogels did not show signs of degradation 6 weeks postimplantation and were surrounded by a thin fibrous capsule and some macrophages and giant cells. This response is typical with a number of nondegradable biocompatible materials. These results indicate that dextran hydrogels are biocompatible, and may have suitable applications as implantable longterm peptide/protein delivery systems or scaffolds for tissue engineering.

Vehicle number plate recognition systems are expected to have numerous applications in traffic surveying and monitoring, e.g. finding stolen cars, controlling access to car parks and gathering traffic flow statistics. The Computer Vision Group at the University of Tras-os-Montes e Alto Douro, in collaboration with the Universities of Aveiro and Bristol, has been developing a number plate reading system [3][4][5]. The system builds on the experience gained by the Computer Vision Group at the University of Bristol while developing previous transputer based prototypes [~1[~1[81[121.The main tasks of a number plate recognition system are the location of the number plate area in the image, the segmentation of the characters and their identification. These tasks are strongly inter-related, mainly because the way to check if the number plate has been correctly located is based on the result of the character identification process (it should correspond tal a predefined syntax). Algorithmic improvements to previons versions of the system, based on the results of intensive testing, are described in the paper. Por the location of the number plate area in the image, a new line-based method has been developed. The method, instead of looking for character like shapes in the image, takes advantage of the "signature" of the number plate area in a horizontal cross-section of the image. The method used for the segmentation of the characters is derived from a technique first proposed by Lu [SI. The identification of the characters uses the OCIt engine developed by Barroso et a1 [3][4], based on the critical points method [10][11].

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