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Solid-state transformers (SSTs) have multiple advantages compared to conventional bulky electromagnetic transformers, including higher efficiency, higher power density, and improved power quality. However, hardware reliability has been a challenge constraining broad applications of SSTs. Such reliability concern mainly arises from a large number of semiconductor switches utilized in SSTs. To address this challenge, an innovative online diagnostic method for open-circuit switch faults will be presented for a multiport SST system, which possesses four isolated power ports to interconnect various energy sources. Specifically, in this new diagnostic method, the variations of the high-frequency transformer AC current and voltage will be monitored and analyzed under various switching patterns, in order to identify potential switch faults with a fast diagnostic speed. Simulation and experimental results are presented to characterize and validate the proposed open-circuit fault diagnostic method. 

While the thermodynamics for bosonic systems with weak $s$ -wave interactions has been known for decades, a general and systematic extension to higher partial waves has not yet been reported. We provide closed-form expressions for the equations of state for weakly interacting systems with arbitrary partial waves in the normal phase. Thermodynamics, including contact, loss rate, and compressibility, are derived over the entire temperature regime. Our results offer an improved thermometer for ultracold atoms and molecules with weak high-partial wave interactions. Published by the American Physical Society2024 

Inverse molecular generation is an essential task for drug discovery, and generative models offer a very promising avenue, especially when diffusion models are used. Despite their great success, existing methods are inherently limited by the lack of a semantic latent space that can not be navigated and perform targeted exploration to generate molecules with desired properties. Here, we present a property-guided diffusion model for generating desired molecules, which incorporates a sophisticated diffusion process capturing intricate interactions of nodes and edges within molecular graphs and leverages a time-dependent molecular property classifier to integrate desired properties into the diffusion sampling process. Furthermore, we extend our model to a multi-property-guided paradigm. Experimental results underscore the competitiveness of our approach in molecular generation, highlighting its superiority in generating desired molecules without the need for additional optimization steps. 

A bstract We establish an orientifold Calabi-Yau threefold database for h 1 , 1 ( X ) ≤ 6 by considering non-trivial ℤ 2 divisor exchange involutions, using a toric Calabi-Yau database ( www.rossealtman.com/tcy ). We first determine the topology for each individual divisor (Hodge diamond), then identify and classify the proper involutions which are globally consistent across all disjoint phases of the Kähler cone for each unique geometry. Each of the proper involutions will result in an orientifold Calabi-Yau manifold. Then we clarify all possible fixed loci under the proper involution, thereby determining the locations of different types of O -planes. It is shown that under the proper involutions, one typically ends up with a system of O 3 /O 7-planes, and most of these will further admit naive Type IIB string vacua. The geometries with freely acting involutions are also determined. We further determine the splitting of the Hodge numbers into odd/even parity in the orbifold limit. The final result is a class of orientifold Calabi-Yau threefolds with non-trivial odd class cohomology ( $$ {h}_{-}^{1,1} $$ h − 1 , 1 ( X/σ * ) ≠ 0).