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We address two important issues in causal discovery from nonstationary or heterogeneous data, where parameters associated with a causal structure may change over time or across data sets. First, we investigate how to efficiently estimate the "driving force" of the nonstationarity of a causal mechanism. That is, given a causal mechanism that varies over time or across data sets and whose...
Metallocene-catalyzed polyethylene (mPE)/metallocene-catalyzed ethylene–propylene copolymer (mEP) blends were prepared with a mixing apparatus. The morphology of the blends was observed by scanning electron microscopy and the dynamic mechanical behavior of the blends was systematically investigated. Mean-field theories developed by Kerner were applied to these binary blends of different compositions...
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