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Rationally designed molecular circuits describable by well-mixed chemical reaction kinetics can realize arbitrary Boolean function computation yet differ significantly from their electronic counterparts. The design, preparation, and purification of new molecular components poses significant barriers. Consequently, it is desirable to synthesize circuits from an existing “fridge” inventory of distinguishable parts, while satisfying constraints such as component compatibility. Heuristic synthesis techniques intended for large electronic circuits often result in non-optimal molecular circuits, invalid circuits that violate domain-specific constraints, or circuits that cannot be built with the current inventory. Existing “exact” synthesis techniques are able to find minimal feedforward Boolean circuits with complex constraints, but do not map to distinguishable inventory components. We present the Fridge Compiler, an SMT-based approach to find optimal Boolean circuits within a given molecular inventory. Empirical results demonstrate the Fridge Compiler’s versatility in synthesizing arbitrary Boolean functions using three different molecular architectures, while satisfying user-specified constraints. We showcase the successful synthesis of all 256 three-bit and 65,536 four-bit predicate functions using a large custom inventory, with worst-case completion times of only seconds on a modern laptop. In addition, we introduce a unique class of cyclic molecular circuits that cover a larger number of Boolean functions than their conventional counterparts over a common inventory, often with significantly smaller implementations. Importantly, and absent in previous approaches specific to molecular circuits, the Fridge Compiler is logically sound, complete, and optimal for the user-specified cost function and component inventory. 

Abstract DNA has emerged as a powerful substrate for programming information processing machines at the nanoscale. Among the DNA computing primitives used today, DNA strand displacement (DSD) is arguably the most popular, with DSD-based circuit applications ranging from disease diagnostics to molecular artificial neural networks. The outputs of DSD circuits are generally read using fluorescence spectroscopy. However, due to the spectral overlap of typical small-molecule fluorescent reporters, the number of unique outputs that can be detected in parallel is limited, requiring complex optical setups or spatial isolation of reactions to make output bandwidths scalable. Here, we present a multiplexable sequencing-free readout method that enables real-time, kinetic measurement of DSD circuit activity through highly parallel, direct detection of barcoded output strands using nanopore sensor array technology (Oxford Nanopore Technologies’ MinION device). These results increase DSD output bandwidth by an order of magnitude over what is currently feasible with fluorescence spectroscopy. 

Compressed videos constitute 70% of Internet traffic, and video upload growth rates far outpace compute and storage improvement trends. Past work in leveraging perceptual cues like saliency, i.e., regions where viewers focus their perceptual attention, reduces compressed video size while maintaining perceptual quality, but requires significant changes to video codecs and ignores the data management of this perceptual information. In this paper, we propose Vignette, a compression technique and storage manager for perception-based video compression in the cloud. Vignette complements off-the-shelf compression software and hardware codec implementations. Vignette's compression technique uses a neural network to predict saliency information used during transcoding, and its storage manager integrates perceptual information into the video storage system. Our results demonstrate the benefit of embedding information about the human visual system into the architecture of cloud video storage systems.