Results 221 to 230 of about 3,047,766 (352)

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

open access: yesAdvanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi   +4 more
wiley   +1 more source

Put you in the problem: Effects of self-pronouns on mathematical problem-solving. [PDF]

open access: yesQ J Exp Psychol (Hove)
Cunningham SJ   +6 more
europepmc   +1 more source

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

open access: yesAdvanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao   +9 more
wiley   +1 more source

Problem solving in mathematics education : learning problem solving and learning through problem solving

open access: yes, 2012
Proceedings from the 13th ProMath conference, September 2 – 4, 2011, in Umeå, Sweden.
openaire   +2 more sources

SPADE: A Deep Learning Framework for Spatial Mapping and Quantitative Cell–Cell Interaction Inference

open access: yesAdvanced Science, EarlyView.
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley   +1 more source

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

open access: yesAdvanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang   +11 more
wiley   +1 more source

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

open access: yesAdvanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao   +4 more
wiley   +1 more source

A Versatile‐Designable Framework for Active and Programmable Shape‐Morphing Soft Matter Systems: From Inverse Design to Closed‐Loop Control

open access: yesAdvanced Science, EarlyView.
A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu   +5 more
wiley   +1 more source

A General and Efficient Framework for the Rapid Design of Miniaturized, Wideband, and High‐Bit RIS

open access: yesAdvanced Electronic Materials, EarlyView.
A general and efficient framework is proposed for the rapid design of high‐performance reconfigurable intelligent surfaces (RISs). This framework integrates advanced antenna design techniques and incorporates various load types, quantities, and values to achieve the design of high‐performance RISs.
Jun Wei Zhang   +14 more
wiley   +1 more source

Updatable Closed‐Form Evaluation of Arbitrarily Complex Multiport Network Connections

open access: yesAdvanced Electronic Materials, EarlyView.
The inverse design of electrically large wave devices often uses reduced‐order multiport models with discrete optimization, requiring many evaluations of complex interconnections between subsystems that differ only in a few blocks. This paper introduces a closed‐form framework enabling efficient Woodbury low‐rank updates of related, previous ...
Hugo Prod'homme, Philipp del Hougne
wiley   +1 more source

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