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This paper reports results of a network theory approach to the study of the United States patent system. We model the patent citation network as a discrete time, discrete space stochastic dynamic system. From patent data we extract an attractiveness function, A(k,l), which determines the likelihood that a patent will be cited. A(k,l) shows power law aging and preferential attachment. The exponent of the latter is increasing since 1993, suggesting that patent citations are increasingly concentrated on a relatively small number of patents. In particular, our results appear consistent with an increasing patent “thicket”, in which more and more patents are issued on minor technical advances. 相似文献
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Measurements of the low temperature heat capacity and powder magnetic susceptibility of CTS (Cu(NH3)4SO4·H2O) are shown to be consistent with quadratic nets of Heisenberg exchange-coupled spins (). 相似文献
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