Results 151 to 160 of about 160,416 (217)

Generation of Probabilistic Bits by Exploiting Orthogonal Spin Currents in Magnetic Trilayers

Advanced Science, EarlyView.
Fe/Ti/CoFeB trilayers generate orthogonal spin currents that drive stochastic spin–orbit‐torque switching for probabilistic‐bit operation. The switching probability is continuously controlled by the in‐plane magnetic field and drive current, enabling tunable random bit generation.
Donghyeon Han, Chaehyeon Shin, Seok‐Jong Kim, Yunho Jang, Daekyu Koh, Taehwan Kim, Jaeheon Jung, Geon‐Woo Baek, Minseok Kang, Eunseok Kim, Geun‐Hee Lee, Jeongchun Ryu, Makoto Kohda, Junsaku Nitta, Kab‐Jin Kim, Jongsun Park, Kyung‐Jin Lee, Byong‐Guk Park   +17 more
wiley   +1 more source

Construction and validation of a machine learning model to predict the sarcopenic obesity population. [PDF]

Medicine (Baltimore)
Zhang M, Dong D, Liu C, Liu Y, Zhang Z.
europepmc   +1 more source

Deciphering Short‐Range Order in 2D Transition Metal Dichalcogenides: From Origin to Multi‐Scale Property Modulation

Advanced Science, EarlyView.
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu, Linggang Zhu, Jian Zhou, Zhimei Sun   +3 more
wiley   +1 more source

Assessment of disability in the older adults using electronic health record-based data: a machine learning approach. [PDF]

Front Public Health
Chen G, Wang S, Luo L.
europepmc   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Machine learning-based temperature prediction across diverse ecosystems for the Boro Season in Bangladesh. [PDF]

Sci Rep
Rahman NMF, Haque N, Asadullah M, Hossain ABMZ, Hossain MS, Uddin MJ, Hassan SMQ, Baten MA.   +7 more
europepmc   +1 more source

Transcriptomic Profiling Combined with Machine Learning and Mendelian Randomization Identifies Diagnostic Biomarkers and Immune Infiltration Patterns in Diabetic Kidney Disease. [PDF]

Molecules
Liu H, Fu Q, Chen J.
europepmc   +1 more source

Reflections on predictive modeling for infectious diseases. [PDF]

Front Public Health
Zhao D.
europepmc   +1 more source