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This paper presents acoustic propulsion in air by synthesis jets produced by ultrasounds. Various ultrasonic air-borne propellers have been fabricated on 0.37-mm-thick commercial card piezoelectric speakers (APS2513S-T-R, 25.2 × 16.6 × 0.37 mm3 in size), and studied, with the propulsion force measured through a precision weight scale, as the orifice size, thickness, spacing between orifices, and number (in the orifice array) are varied. Also varied is the orifice depth profile, as the fabrication processes for the orifices produce varying profiles. Strongest acoustic propulsion of 5.4 mg is obtained at 66 kHz (far beyond audible range) with 14 × 14 orifice array made on a 0.1-mm-thick polyester plate (resulting in a propeller of 25.2 × 16.6 × 1.37 mm3 in volume and 500 mg in weight). The acoustic propulsion force, though 93 times less than the propeller weight, is capable of making the propeller jump and move laterally. 

A fully-integrated mixed reality game system called multiphysics enriched mixed reality for integrated geotechnical education (MERGE) is developed to improve student education in the context of geotechnical engineering. This work allows students to learn the design of geothermal pile in a more inclusive way while playing a game and gain an "integrated geotechnical learning experience". Several mini games are designed for students to enhance the geotechnical knowledge. Players can earn points and update their appearance by playing these mini games, which stimulates their interests in geotechnical engineering. By providing students with visualization, collaboration, and simulation tools, we hope to promote the understanding of geotechnical experiments. Based on the laboratory results, numerical experiments are conducted to help students understand the geotechnical application. The leveraging mixed reality technology offers an opportunity for students to access advanced equipment in geotechnical experiments. The main contribution of this work is a discussion of the educational technology and processes behind implementing a mixed reality educational game. We provide developmental insights and educational background to inform researchers who seek to develop similar games. 

We introduce a continuous analogue of the Learning with Errors (LWE) problem, which we name CLWE. We give a polynomial-time quantum reduction from worst-case lattice problems to CLWE, showing that CLWE enjoys similar hardness guarantees to those of LWE. Alternatively, our result can also be seen as opening new avenues of (quantum) attacks on lattice problems. Our work resolves an open problem regarding the computational complexity of learning mixtures of Gaussians without separability assumptions (Diakonikolas 2016, Moitra 2018). As an additional motivation, (a slight variant of) CLWE was considered in the context of robust machine learning (Diakonikolas et al. FOCS 2017), where hardness in the statistical query (SQ) model was shown; our work addresses the open question regarding its computational hardness (Bubeck et al. ICML 2019).