Tobit modeling for dependent-sample t-tests and moderated regression with ceiling or floor data. [PDF]
Behav Res MethodsWang L, Li R.
europepmc +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
Advanced Intelligent Discovery, EarlyView.We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
Bio-RegNet: A Meta-Homeostatic Bayesian Neural Network Framework Integrating Treg-Inspired Immunoregulation and Autophagic Optimization for Adaptive Community Detection and Stable Intelligence. [PDF]
Biomimetics (Basel)Ma Y, Qu D, Pyrozhenko M.
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A Bayesian adaptive design for cancer phase I trials using a flexible range of doses
, 2017 Mourad Tighiouart +2 more
openalex +2 more sources
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Bayesian joint inversion of surface nuclear magnetic resonance and transient electromagnetic data for groundwater investigation in the Beishan area, Inner Mongolia, China. [PDF]
Sci RepLuo W, Peng R, Chen B, Liu H, Zhang Y.
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Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
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Correction: SSNdesign-An R package for pseudo-Bayesian optimal and adaptive sampling designs on stream networks. [PDF]
PLoS OnePearse AR +6 more
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Advanced Experiment Design Strategies for Drug Development
Advanced Intelligent Discovery, EarlyView.Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang +3 more
wiley +1 more source
Integration of affective cues in context-rich and dynamic scenes varies across individuals. [PDF]
Nat CommunOrtega J, Murai Y, Whitney D.
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