Band 40/41 Surface Acoustic Wave Filters on 42°YX-Lithium Tantalate Substrate with Suppression of Transverse Leakage.

The transverse leakage of leaky surface acoustic waves (LSAWs) occurs on 42°YX-lithium tantalate substrates (42LT), which increases the insertion loss, narrows the bandwidth and flattens the roll-off of band 40/41 SAW filters and duplexers. In this work, LSAW characteristics with different metal materials and thicknesses are calculated by the finite element method (FEM), which determines the IDT material and thickness used for band 40/41 SAW filter design. To deeply understand transverse leakage and suppress it, the effects of different gap and dummy lengths on transverse leakage are simulated and discussed.

The role of amygdala-ventral pallidum pathway in depression-like behaviors in male mice.

The basolateral amygdala (BLA) appears to serve an important function in the pathophysiology of depression. Depressive symptoms, such as anhedonia are largely caused by dysfunction in the brain's reward system, in which the ventral pallidum (VP) participates in by controlling dopamine release. However, the role of the BLA-VP pathway in the development of depression remains poorly understood.

Learning Rat-Like Behavioral Interaction Using a Small-Scale Robotic Rat.

In this paper, we propose a novel method for emulating rat-like behavioral interactions in robots using reinforcement learning. Specifically, we develop a state decision method to optimize the interaction process among 6 known behavior types that have been identified in previous research on rat interactions. The novelty of our method lies in using the temporal difference (TD) algorithm to optimize the state decision process, which enables the robots to make informed decisions about their behavior choices.

5G Traffic Prediction Based on Deep Learning.

The demand of wireless access users is increasing explosively. The 5G network traffic is increasing exponentially and showing a trend of diversity and heterogeneity, which makes network traffic forecasting face many challenges. By studying the actual performance of the 5G network, this paper makes an accurate prediction of the 5G network and builds a smoothed long short-term memory (SLSTM) traffic prediction model.