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This invention provides an application of the peptide Nod-T3 in the preparation of drugs for treating lung diseases. The Nod-T3 peptide is derived from human protein and has a significant inhibitory effect on chronic lung inflammation and fibrosis caused by smoking. It can be used to treat COPD and other smoking-related lung diseases. It also has high biocompatibility and low toxicity, and has the potential and development value to become a new type of peptide drug.

This application discloses a radar echo extrapolation method based on temporal motion decomposition and dominant fusion, relating to the field of spatiotemporal sequence prediction technology. The method proposes an innovative network fusion paradigm, specifically including: acquiring implicit long-term / short-term temporal features and explicit global / transient motion features during processing using stacked hierarchical recurrent networks; then, innovatively constructing query vectors using temporal features and key-value vectors using motion features, and fusing them using a heterogeneous cross-attention mechanism to form a fusion architecture "dominated by an implicit state modeling network and referenced by an explicit motion modeling network." Based on this, through a series of collaborative designs such as directional decoupling, reference confidence estimation, and long-term feature constraints on short-term features, noise in long-term / short-term motion features is effectively suppressed, enhancing system stability. This method can improve the problems of blurred texture details and attenuation in high-value echo regions in predicted images.