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Natural organs are spatially heterogeneous, both in material composition and in the cell types within. Engineered tissues, in contrast, remain challenging to create, especially if the goal is to spatially position multiple cell types in a heterogeneous pattern in three dimensions (3D). Here, we describe a simple, inexpensive , yet extremely precise method(More)
In this brief, conic section function neural network (CSFNN) circuitry was designed for offline signature recognition. CSFNN is a unified framework for multilayer perceptron (MLP) and radial basis function (RBF) networks to make simultaneous use of advantages of both. The CSFNN circuitry architecture was developed using a mixed mode circuit implementation.(More)
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