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Braving the Storm: Quantifying Disk-wide Ionized Outflows in the Large Magellanic Cloud with ULLYSES

Autor: Zheng, Yong, Tchernyshyov, Kirill, Olsen, Knut, Choi, Yumi, Bustard, Chad, Roman-Duval, Julia, Zhu, Robert, Di Teodoro, Enrico M., Werk, Jessica, Putman, Mary, McLeod, Anna F., Faerman, Yakov, Simons, Raymond C., Peek, Joshua

The Large Magellanic Cloud (LMC) is home to many HII regions, which may lead to significant outflows. We examine the LMC's multiphase gas ($T\sim10^{4-5}$ K) in HI, SII, SiIV, and CIV using 110 stellar sight lines from the HST's Ultraviolet Legacy Li

Externí odkaz: http://arxiv.org/abs/2402.04313

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Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data

Autor: Zhang, Ling, Lu, Le, Wang, Xiaosong, Zhu, Robert M., Bagheri, Mohammadhadi, Summers, Ronald M., Yao, Jianhua

Publikováno v: IEEE Transactions on Medical Imaging, 2019

Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment and surgical planning. Recent advances of convolutional networks have demonstrated higher accuracy than traditiona

Externí odkaz: http://arxiv.org/abs/1902.08716

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