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Precipitation Nowcasting Using Diffusion Transformer with Causal Attention

Autor: Li, ChaoRong, Ling, XuDong, Xue, YiLan, Luo, Wenjie, Zhu, LiHong, Qin, FengQing, Zhou, Yaodong, Huang, Yuanyuan

Short-term precipitation forecasting remains challenging due to the difficulty in capturing long-term spatiotemporal dependencies. Current deep learning methods fall short in establishing effective dependencies between conditions and forecast results

Externí odkaz: http://arxiv.org/abs/2410.13314

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Akademický článek

miR-198 Targets MAPK1 to Regulate Proliferation, Apoptosis and Invasion of Cervical Cancer HeLa Cells

Autor: ZHU Lihong, DUAN Shupeng, QIN Haixia, ZHANG Xiuling, ZHAO Shuzhen, LI Shaoru, WANG Shijin

Publikováno v: Zhongliu Fangzhi Yanjiu, Vol 45, Iss 12, Pp 959-964 (2018)

Objective To investigate the effects and mechanisms of miR-198 on the proliferation, apoptosis and invasion of cervical cancer cells. Methods HeLa cells were transfected with miR-198 mimic and the mRNA levels between miR-198 and mitogen-activated pro

Externí odkaz: https://doaj.org/article/bbc5d69c4a874d4b983057fd7136ec58

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Two-stage Rainfall-Forecasting Diffusion Model

Autor: Ling, XuDong, Li, ChaoRong, Qin, FengQing, Zhu, LiHong, Huang, Yuanyuan

Deep neural networks have made great achievements in rainfall prediction.However, the current forecasting methods have certain limitations, such as with blurry generated images and incorrect spatial positions. To overcome these challenges, we propose

Externí odkaz: http://arxiv.org/abs/2402.12779

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