The May JASA Express Letters cover features a portion of Figure 4 from “Predicting underwater acoustic transmission loss in the SOFAR channel from ray trajectories via deep learning,” by Haitao Wang, Shiwei Peng, Qunyi He and Xiangyang Zeng. The image shows acoustic transmission loss maps. The article presents a deep learning-based underwater acoustic transmission loss prediction method, in an effort to address current challenges with predicting acoustic transmission loss in the SOFAR channel.

This month’s issue also had a couple Editor’s Picks:

• “Neural correlates of tonal loudness, intensity discrimination, and duration discrimination,” by Shigeyuki Kuwada and Constantine Trahiotis
• “An open auscultation dataset for machine learning-based respiratory diagnosis studies,” by Guanyu Zhou, Chengjian Liu, Xiaoguang Li, Sicong Liang, Ruichen Wang, and Xun Huang.

Browse the rest of the issue at https://pubs.aip.org/asa/jel/issue/4/5.