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The fluorophore-spacer1-receptor1-spacer2-receptor2 system (where receptor2 alone is photoredox-inactive) shows ionically tunable proton-induced fluorescence off-on switching, which is reminiscent of thermionic triode behavior. This also represents a new extension to modular switch systems based on photoinduced electron transfer (PET) towards the emulation of analogue electronic devices.

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We present a new algorithm for exactly solving decision making problems represented as influence diagrams. We do not require the usual assumptions of no forgetting and regularity; this allows us to solve problems with simultaneous decisions and limited information. The algorithm is empirically shown to outperform a state-of-the-art algorithm on randomly generated problems of up to 150 variables and 10^64 solutions. We show that these problems are NP-hard even if the underlying graph structure of the problem has low treewidth and the variables take on a bounded number of states, and that they admit no provably good approximation if variables can take on an arbitrary number of states.