Spatio-temporal transformer traffic prediction network based on multi-level causal attention.

Traffic prediction is a core technology in intelligent transportation systems with broad application prospects. However, traffic flow data exhibits complex characteristics across both temporal and spatial dimensions, posing challenges for accurate prediction. In this paper, we propose a spatiotemporal Transformer network based on multi-level causal attention (MLCAFormer).

Cloning, expression and identification of KTX-Sp4, a selective Kv1.3 peptidic blocker from .

Background: Specific and selective peptidic blockers of Kv1.3 channels can serve as a valuable drug lead for treating T cell-mediated autoimmune diseases, and scorpion venom is an important source of kv1.3 channel inhibitors.