Learned pseudo-random number generator: WGAN-GP for generating statistically robust random numbers.

Pseudo-random number generators (PRNGs) are software algorithms generating a sequence of numbers approximating the properties of random numbers. They are critical components in many information systems that require unpredictable and nonarbitrary behaviors, such as parameter configuration in machine learning, gaming, cryptography, and simulation. A PRNG is commonly validated through a statistical test suite, such as NIST SP 800-22rev1a (NIST test suite), to evaluate its robustness and the randomness of the numbers.

Growth control of leaf lettuce with exposure to underwater ultrasound and dissolved oxygen supersaturation.

The growth rate of vegetables in plant factories can be regulated by environmental factors including light, temperature, and chemicals, which might give rise to mutation in leaf health. Here, we aim to devise a new way that allows for controlling the growth rate of plants in hydroponics as well as maintaining the product quality; we apply underwater ultrasound and dissolved oxygen supersaturation as external stimuli to plants. As an example, we examine the growth of leaf lettuce in hydroponics with exposure to 28-kHz ultrasound and dissolved oxygen supersaturation up to 36 mg/L at 20 °C.