Predictive power of polynomial machine learning potentials for liquid states in 22 elemental systems

Autor: Wakai, Hayato, Seko, Atsuto, Izuta, Hirosato, Nishiyama, Takayuki, Tanaka, Isao

The polynomial machine learning potentials (MLPs) described by polynomial rotational invariants have been systematically developed for various systems and used in diverse applications in crystalline states. In this study, we systematically investigat

Externí odkaz: http://arxiv.org/abs/2401.14877

Differential analysis of microbiomes in mucus and tissues obtained from colorectal cancer patients.

Autor: Tajima, Yosuke^1,2 (AUTHOR) yosuketajimajpn@gmail.com, Okuda, Shujiro³ (AUTHOR), Hanai, Tsunekazu¹ (AUTHOR), Hiro, Junichiro¹ (AUTHOR), Masumori, Koji¹ (AUTHOR), Koide, Yoshikazu¹ (AUTHOR), Kamiya, Tadahiro¹ (AUTHOR), Cheong, Yeongcheol¹ (AUTHOR), Inaguma, Gaku¹ (AUTHOR), Shimada, Yoshifumi² (AUTHOR), Wakai, Toshifumi² (AUTHOR), Takihara, Hayato³ (AUTHOR), Akimoto, Shingo¹ (AUTHOR), Matsuoka, Hiroshi¹ (AUTHOR), Uyama, Ichiro¹ (AUTHOR), Suda, Koichi¹ (AUTHOR)

Publikováno v: Scientific Reports. 10/28/2022, Vol. 12 Issue 1, p1-10. 10p.