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A graphical framework to approximate visual features from spike-based sensor data has been demonstrated. An event-based camera or dynamic vision sensor (DVS) provides the sensory input into the network which computes the intrascene optical flow, spatial gradient, and absolute intensity. The network uses the sparse, event-based input along with fundamental relations in parallel to converge upon quantities via incremental optimization. An event-based algorithm to compute optical flow was used to provide another stream of input into the network to aid convergence. A full network has been deployed in Python and parallelized to demonstrate its potential deployment on specialized hardware.

We report the proof-of-principle demonstration of a methodology, called Metal-Assisted and Microwave-Accelerated Germination, to modulate the germination of plant seeds and growth of plants using gold nanoparticles (Au NPs) and microwave heating. As a model plant seed, basil seeds were heated in a solution of 20 nm Au NPs using a microwave waveguide fiber connected to a solid-state microwave operating at 8 GHz at 20 W, which resulted in the development of longer basil gum as observed by optical microscopy. In control experiments, Au NPs or microwave heating was omitted to establish a baseline growth level under standard experimental conditions (no microwave heating or no Au NPs). Our results also show that hydroponic growth and soil growth of basil plants can be delayed with the use of 20 nm Au NPs at room temperature without microwave heating. The combined use of 20 nm Au NPs and microwave heating at 10 W for 6 minutes results in accelerated growth prolonged life of basil plants.