A liquid metal motor that can "eat" aluminum food and then move spontaneously and swiftly in various solution configurations and structured channels for more than 1 h is discovered. Such a biomimetic mollusk is highly shape self-adaptive by closely conforming to the geometrical space it voyages in. The first ever self-fueled pump is illustrated as one of its typical practical utilizations.

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We consider the problem of lossless compression of binary trees, with the aim of reducing the number of code bits needed to store or transmit such trees. A lossless grammar-based code is presented which encodes each binary tree into a binary codeword in two steps. In the first step, the tree is transformed into a context-free grammar from which the tree can be reconstructed. In the second step, the context-free grammar is encoded into a binary codeword. The decoder of the grammar-based code decodes the original tree from its codeword by reversing the two encoding steps. It is shown that the resulting grammar-based binary tree compression code is a universal code on a family of probabilistic binary tree source models satisfying certain weak restrictions.

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