Polymeric biomaterials have extensively been used in medicinal applications. However, factors that determine their biocompatibility are still not very clear. This article reviews various effects of the chemical structure and the surface properties of polymeric biomaterials on their biocompatibility, including protein adsorption, cell adhesion, cytotoxicity, blood compatibility, and tissue compatibility. Understanding these aspects of biocompatibility is important to the improvement of the biocompatibility of existing polymers and the design of new biocompatible polymers.

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A method of sensing vibration using the detection of changes in the spatial distribution of energy in the output of a multimode optical fiber has been demonstrated. Two implementations of the sensor have been built and tested. The first implementation involved simple optical processing of the output fiber speckle pattern using spatial filtering. The second implementation involved projecting the pattern on a CCD array and digitally processing observed changes in the intensity distribution. A mathematical model has been developed which has shown good agreement with observed sensor behavior. The sensor technique has been used to detect induced structural vibration in laboratory test specimens. Simple field testing has also demonstrated the ability of the technique to detect personnel and vehicles passing over a buried and electrically undetectable sensing cable. The sensing technique is compatible with off-the-shelf components and fiber cable and even allows for simultaneous telecommunication and sensing using the same optical fiber cable. Near term application of this technology could provide significant benefits for vibration sensing, intrusion detection, and acoustic sensing.

There has been considerable discussion in the technical community on a number of questions concerned with smart materials and structures, such as what they are, whether smart materials can be considered a subset of smart structures, whether a smart structure and an intelligent structure are the same thing, etc. This discussion is both fueled and confused by the technical community due to the truly multidisciplinary nature of this new field. Smart materials and structures research involves so many technically diverse fields that it is quite common for one field to completely misunderstand the terminology and start of the art in other fields. In order to ascertain whether a consensus is emerging on a number of questions, the technical community was surveyed in a variety of ways including via the internet and by direct contact. The purpose of this survey was to better define the smart materials and structures field, its current status and its potential benefits. Results of the survey are presented and discussed. Finally, a formal definition of the field of smart materials and structures is proposed.

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We study the steady state of an assembly of microtubules in a confined volume, analogous to the situation inside a cell where the cell boundary forms a natural barrier to growth. We show that the dynamical equations for growing and shrinking microtubules predict the existence of two steady states, with either exponentially decaying or exponentially increasing distribution of microtubule lengths. We identify the regimes in parameter space corresponding to these steady states. In the latter case, the apparent catastrophe frequency near the boundary was found to be significantly larger than that in the interior. Both the exponential distribution of lengths and the increase in the catastrophe frequency near the cell margin is in excellent agreement with recent experimental observations.

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Despite many years of research, a method to precisely and quantitatively determine cancer disease state remains elusive. Current practice for characterizing solid tumors involves the use of varying systems of tumor grading and staging and thus leaves diagnosis and clinical staging dependent on the experience and skill of the physicians involved. Although numerous disease markers have been identified, no combination of them has yet been found that produces a quantifiable and reliable measure of disease state. Newly developed genomic markers and other measures based on the developing sciences of complexity offer promise that this situation may soon be changed for the better. In this paper, we examine the potential of two measures of complexity, fractal dimension and percolation, for use as components of a yet to be determined "disease time" vector that more accurately quantifies disease state. The measures are applied to a set of micrographs of progressive rat hepatoma and analyzed in terms of their correlation with cell differentiation, ratio of tumor weight to rat body weight and tumor growth time. The results provide some support for the idea that measures of complexity could be important elements of any future cancer "disease time" vector.