Results 151 to 160 of about 3,120,690 (293)
CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang +4 more
wiley +1 more source
Systematic Multi‐Level Analyses Decode the Arthritis‐Neurodegeneration Axis With In Vivo Validation
Arthritis and neurodegeneration are usually studied as separate disorders, but this study connects them through population evidence, genetic inference, transcriptomic mapping, and mouse models. It highlights RNF40 as a context‐dependent joint‐brain candidate, induced in inflammatory joints yet functionally linked to dopamine‐neuron vulnerability ...
Jinwen Wang +7 more
wiley +1 more source
Bayesian MAP model selection of chain event graphs [PDF]
The class of chain event graph models is a generalisation of the class of discrete Bayesian networks, retaining most of the structural advantages of the Bayesian network for model interrogation, propagation and learning, while more naturally encoding ...
Freeman, Guy, Smith, J. Q.
core
Machine Learning of Temperature‐Dependent Chemical Kinetics Using Parallel Droplet Microreactors
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
Transformers are Bayesian Networks
Transformers are the dominant architecture in AI, yet why they work remains poorly understood. This paper offers a precise answer: a transformer is a Bayesian network. We establish this in five ways. First, we prove that every sigmoid transformer with any weights implements weighted loopy belief propagation on its implicit factor graph.
openaire +3 more sources
Drought Stress Mediated Changes in Food Crops: Mechanisms and Remediation Strategies
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 +5 more
wiley +1 more source
Optimising ITS behaviour with Bayesian networks and decision theory [PDF]
We propose and demonstrate a methodology for building tractable normative intelligent tutoring systems (ITSs). A normative ITS uses a Bayesian network for long-term student modelling and decision theory to select the next tutorial action.
Mitrovic, Antonija, Mayo, Michael
core +1 more source
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 +9 more
wiley +1 more source
Oligosaccharides with defined glycosidic bonds drive divergent gut microbial succession and shape unique metabolic profiles. Absolute time‐series profiling with Bayesian generalized Lotka–Volterra modeling identifies bond‐specific microbial responders, while monoculture validation and metaproteomics reveal linkage‐matched transport and cleavage modules.
Xiaoxuan Lu +10 more
wiley +1 more source
Accounting for multiple impacts of the Common agricultural policies in rural areas: an analysis using a Bayesian networks approach [PDF]
In evaluating the potential effects of the reforms of the Common Agricultural Policy, a particularly challenging issue is the representation of the complexity of rural systems either in a static or dynamic framework.
Viaggi, Davide +2 more
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