Results 161 to 170 of about 9,437,008 (290)

Active Learning‐Assisted Exploration of [PO40Mo12]3− for Alzheimer's Therapy Insights

Advanced Science
Alzheimer's disease (AD), involving amyloid‐β (Aβ) aggregation, has potential therapeutic modulators in polyoxometalates (POMs) like [PMo12O40]3−. To clarify their inhibitory mechanisms, a multiscale computational strategy integrating active‐learning ...
Lincan Fang, Ruoxue Peng, Luping Xia, Gui‐lin Zhuang   +3 more
doaj   +1 more source

Efficient variational Bayesian model updating by Bayesian active learning

Mechanical Systems and Signal Processing
As a main task of inverse problem, model updating has received more and more attention in the area of inspection, sensing, and monitoring technologies during the recent decades, where the estimation of posterior probability density function (PDF) of unknown model parameters is still challenging for expensive-to-evaluate models of interest.
Fangqi Hong, Pengfei Wei, Sifeng Bi, Michael Beer   +3 more
openaire   +2 more sources

TSTScope Unifies Single‐Cell Multi‐Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

Advanced Science, EarlyView.
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao, Jinyu Cheng, Feng‐ao Wang, Chenxin Yi, Jiajun Chen, Keyue Wang, Lulu Liu, Junwei Liu, Yixue Li   +8 more
wiley   +1 more source

Bayesian active learning for Bayesian model updating: The art of acquisition functions and beyond

Mechanical Systems and Signal Processing
Estimating posteriors and the associated model evidences, with desired accuracy and affordable computational cost, is a core issue of Bayesian model updating, and can be of great challenge given expensive-to-evaluate models and posteriors with complex features such as multi-modalities of unequal importance, nonlinear dependencies and high sharpness ...
Jingwen Song, Pengfei Wei
openaire   +2 more sources

A Robotic Testing Platform for Pipelined Discovery of Resilient Dielectric Elastomer Actuators

Advanced Science, EarlyView.
This work introduces a robotic testing platform enabling high‐throughput, multi‐parameter lifetime mapping of linear dielectric elastomer actuators (DEAs). By integrating programmable high‐voltage control and automated electromechanical measurements, the system identifies material and operating conditions that double actuator lifetime.
Ang (Leo) Li, Alexander Yin, Alexander White, Sahib Sandhu, Anatol Gogoj, Denise Maria de Andrade, Matthew Francoeur, Victor Jimenez‐Santiago, Van Remenar, Codrin Tugui, Mihai Duduta   +10 more
wiley   +1 more source

Machine Learning of Temperature‐Dependent Chemical Kinetics Using Parallel Droplet Microreactors

Advanced Science, EarlyView.
An integrated droplet microfluidics and machine learning framework enables high‐throughput characterization of temperature‐dependent reaction kinetics. Time‐resolved measurements from thousands of droplets train Neural ODE models that accurately predict nonlinear reaction dynamics across diverse thermal environments, bridging large‐scale ...
Mamoru Saita, Yutaka Hori
wiley   +1 more source

Bayesian Active Learning for Optimization and Uncertainty Quantification in Protein Docking. [PDF]

J Chem Theory Comput, 2020
Cao Y, Shen Y.
europepmc   +1 more source

Drought Stress Mediated Changes in Food Crops: Mechanisms and Remediation Strategies

Advanced Science, EarlyView.
This work presents a multi‐scale framework for flavonoid‐mediated drought tolerance in staple food crops, integrating ROS redox regulation, antioxidant defense, rhizosphere microbial interactions, and sustainable agronomic practices. This interdisciplinary model provides core insights to develop climate‐resilient cropping systems and enhance global ...
Xiaoyi Duan, Litao Wang, Tuuli‐Marjaana Koski, Lizhe An, Thomas Efferth, Yujie Fu   +5 more
wiley   +1 more source

Tau Aggregate Imaging and Transcriptomics of Alzheimer's Disease Brain at Different Stages of Disease

Advanced Science, EarlyView.
The protein aggregates and gene expression in the middle temporal gyrus (MTG) and somatosensory cortex (SOM) of the postmortem brains of 13 Alzheimer's disease patients were studied in detail, revealing that small hyperphosphorylated tau aggregates increase with Braak stage driven by microglial inflammation.
Elizabeth A. English, Dorothea Böken, Matthew W. Cotton, Matthew R. Cheetham, Johanna S. Jackson, Georg Meisl, John S. H. Danial, Paul M. Matthews, Nurun N. Fancy, David Klenerman   +9 more
wiley   +1 more source

Similarity‐Enhanced Representation Learning of Non‐Canonical Amino Acids for Therapeutic Peptide Modeling

Advanced Science, EarlyView.
Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu, Lesong Wei, Jianmin Wang, Yuanpeng Xiong, Ruochi Zhang, Yu Wang, Chao Zha, Qiangcheng Zeng, Xin Gao   +8 more
wiley   +1 more source