Results 121 to 130 of about 2,194,170 (284)

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Equation of State Independent Determination on the Radius of a 1.4 M⊙ Neutron Star Using Mass–Radius Measurements

The Astrophysical Journal Letters
Traditional methods for determining the radius of a 1.4 M _⊙ neutron star ( R _1.4 ) rely on specific equation-of-state (EOS) models that describe various types of dense nuclear matter.
Chun Huang
doaj   +1 more source

Bayesian Statistics Improves Biological Interpretability of Metabolomics Data from Human Cohorts. [PDF]

Metabolites, 2023
Brydges C, Che X, Lipkin WI, Fiehn O.
europepmc   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

Why modelling space is hard: no evidence for a serial founder effect in Polynesian phoneme inventories

Linguistics
In recent years there has been an increased interest in computational modeling of spatial phenomena in typology. While the main focus of most work so far has been on direct language contact, there are two different types of spatial dynamics of interest ...
Guzmán Naranjo Matías, Becker Laura, Schiele Miriam L., Lin I-Ying   +3 more
doaj   +1 more source

Bayesian Statistics [PDF]

Medical Decision Making, 2006
openaire   +2 more sources

Multi‐Omics Profiling of High‐Grade Serous Ovarian Cancer Reveals an Inflammation‐Related Lipid Metabolism Subtype Associated With Platinum Resistance

Advanced Science, EarlyView.
Through integrated proteomic and metabolomic profiling, Zhao et al. identified three molecular subtypes of high‐grade serous ovarian cancer. The high‐risk subtype exhibits activated arachidonic acid metabolism and cyclooxygenase‐2 overexpression. This metabolic axis promotes M2‐like macrophage infiltration, which contributes to platinum resistance ...
Yuxi Zhao, Junyi Li, Bo Zheng, Wanshan Liu, Yaru Wang, Shufeng Wang, Ying Cui, Huiqin Guo, Hongxia Wang, Ting Xiao, Kun Qian, Jing Zuo   +11 more
wiley   +1 more source

Bayesian efficiency analysis with a flexible form: The aim cost function [PDF]

Sampling;Bayesian ...
Osiewalski, J., Koop, G., Steel, M.F.J.
core  

Challenges and Opportunities for Bayesian Statistics in Proteomics. [PDF]

J Proteome Res, 2022
Crook OM, Chung CW, Deane CM.
europepmc   +1 more source

StackingNet: Collective Inference Across Independent AI Foundation Models

Advanced Science, EarlyView.
ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li, Chenhao Liu, Dongrui Wu, Zhigang Zeng, Lieyun Ding   +4 more
wiley   +1 more source