S3DCN-OLSR: A shallow 3D CNN method for online learning state recognition.

The repeated recurrence of COVID-19 has significantly disrupted learning for students in face-to-face instructional settings. While moving from offline to online instruction has proven to be one of the best solutions, classroom management and capturing students' learning states have emerged as important challenges with the increasing popularity of online instruction. To address these challenges, in this paper we propose an online learning status recognition method based on shallow 3D convolution (S3DC-OLSR) for online students, to identify students' online learning states by analysing their micro-expressions. Specifically, we first use the data augmentation method proposed in this paper to decompose the students' online video file into three features: horizontal component of optical flow, vertical component of optical flow and optical amplitude. Next, the students' online learning status is recognised by feeding the processed data into a shallow 3D convolution neural network. To test the performance of our method, we conduct extensive experiments on the CASME II and SMIC datasets, and the results indicate that our method outperforms the other state-of-the-art methods considered in terms of recognition accuracy, UF1 and UAR, which demonstrates the superiority of our method in identifying students' online learning states.

Trace H2 O2 -Assisted High-Capacity Tungsten Oxide Electrochromic Batteries with Ultrafast Charging in Seconds.

A recent technological trend in the field of electrochemical energy storage is to integrate energy storage and electrochromism functions in one smart device, which can establish efficient user-device interactions based on a friendly human-readable output. This type of newly born energy storage technology has drawn tremendous attention. However, there is still plenty of room for technological and material innovation, which would allow advancement of the research field. A prototype Al-tungsten oxide electrochromic battery with interactive color-changing behavior is reported. With the assistance of trace amount of H2 O2 , the battery exhibits a specific capacity almost seven times that for the reported electrochromic batteries, up to 429 mAh g(-1) . Fast decoloration of the reduced tungsten oxide affords a very quick charging time of only eight seconds, which possibly comes from an intricate combination of structure and valence state changes of tungsten oxide. This unique combination of features may further advance the development of smart energy storage devices with suitability for user-device interactions.