Results 121 to 130 of about 124,846 (268)

Harnessing Large‐Scale Multi‐Omics Data for Risk Prediction and Deep Phenotyping of Valvular Heart Diseases in the General Population

open access: yesAdvanced Science, EarlyView.
Large‐scale UK Biobank analyses identify clinical and proteomic signatures for early prediction of valvular heart disease and its subtypes. Proteins add predictive value for VHD, AVS, and MVR, with outcome‐specific compact panels showing translational potential. Multi‐layer evidence highlights matrix remodeling, protease regulation, immune inflammation,
Zhihao Jiang   +10 more
wiley   +1 more source

Factors affecting timely completion of a PhD: a complex systems approach

open access: yesJournal of the Scholarship of Teaching and Learning, 2012
Completing a PhD on time is a complex process, influenced by many interacting factors. In this paper we take a Bayesian Network approach to analyzing the factors perceived to be important in achieving this aim.
Jegar Pitchforth   +7 more
doaj  

Multiscale Circuit Architecture Associated With Memory Dysfunction in Temporal Lobe Epilepsy

open access: yesAdvanced Science, EarlyView.
A multiscale precision‐mapping framework reveals that memory impairment in temporal lobe epilepsy arises from the convergence of focal medial temporal pathology, strategic white matter disconnection, and limbic‐centered metabolic network dysfunction.
Jiajie Mo   +12 more
wiley   +1 more source

Calcineurin‐Dependent Stress Adaptation Enables Caspofungin Heteroresistance Leading to Stable Resistance in Candida Glabrata

open access: yesAdvanced Science, EarlyView.
Caspofungin heteroresistance is prevalent in clinical Candida glabrata isolates and depends on calcineurin‐mediated stress adaptation. This transient phenotype serves as a reservoir for resistance evolution, enabling the emergence of stable resistant descendants under prolonged drug pressure.
Yanyu Su   +7 more
wiley   +1 more source

StackingNet: Collective Inference Across Independent AI Foundation Models

open access: yesAdvanced 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   +4 more
wiley   +1 more source

Dynamic Safety Analysis CNG Stations Using Fault Tree Approach and Bayesian Network

open access: yesبهداشت و ایمنی کار, 2019
Introduction: The safety of CNG stations is important because of their location in urban areas, as well as to prevent accidents and to protect the safety of personnel, property, and environment.
Tahereh Eskandari   +2 more
doaj  

Multi-Factor superposition influence analysis in engineering projects: a Bayesian network approach

open access: yesJournal of Asian Architecture and Building Engineering
The existing studies rarely examine whether multiple risk factors superimposed on a particular activity result in superposed or non-superposed effects.
Chaoyong Zhang, Keming Hu, Xun Liu
doaj   +1 more source

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

open access: yesAdvanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong   +11 more
wiley   +1 more source

Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations

open access: yesAdvanced Science, EarlyView.
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford   +3 more
wiley   +1 more source

Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

open access: yesAdvanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park   +3 more
wiley   +1 more source

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