Results 101 to 110 of about 19,691 (265)

Iterative generation of virtual reference for a manipulator

open access: yesIterative generation of virtual reference for a manipulator
identifier:oai:t2r2.star.titech.ac.jp ...
openaire  

Transcription Factor Promiscuity Drives Regulatory Rewiring and Evolvability in Gene Networks in Bacteria

open access: yesAdvanced Science, EarlyView.
When a master transcription factor (TF) is lost, bacteria can rapidly rewire gene regulatory networks by co‐opting related regulators. Using experimental evolution in Pseudomonas fluorescens, we show that TF promiscuity (low‐level, non‐cognate binding) provides the raw material for rewiring. Successful co‐option follows a predictable hierarchy governed
Tiffany B. Taylor, Alan M. Rice
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan   +8 more
wiley   +1 more source

Isosteric Substitution Enables Rational Design of Two‐Dimensional Energetic Crystals

open access: yesAdvanced Science, EarlyView.
Isosteric substitution transforms a classical nitro–amine motif into two‐dimensional aminofurazans with performance beyond TATB. ABSTRACT Two‐dimensional (2D) energetic crystals dissipate mechanical insult via interlayer slip, yet their molecular design space remains narrow.
Linyuan Wen   +6 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu   +8 more
wiley   +1 more source

Reinnervation of Muscle Targets Enhances the Separability of Motor Unit Signals Following Peripheral Nerve Transfers

open access: yesAdvanced Science, EarlyView.
Injured or cut peripheral nerves can be surgically rerouted to reinnervate new muscle targets. This study demonstrates reinnervated muscles exhibit enhanced separability between individual motor unit signals, which can simplify signal recording and decomposition. These findings highlight the potential of reinnervated muscle to serve as a key biological
Kiara N Quinn   +11 more
wiley   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

open access: yesAdvanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu   +16 more
wiley   +1 more source

Design Resource Deployment for Virtual Fitting Applications in the Era of Digital Fashion: An Analysis Based on Kano-QFD

open access: yesSAGE Open
Virtual fitting applications have brought new vitality and immersive experiences to the fashion industry. As users adapt to the new fashion consumption experience enabled by virtual fitting, their demands are becoming increasingly diverse and complex ...
Yudian Zhang, Zeyu Zheng, Lixian Liu
doaj   +1 more source

Revisiting Target‐Aware de novo Molecular Generation with TarPass: Between Rational Design and Texas Sharpshooter

open access: yesAdvanced Science, EarlyView.
TarPass provides a rigorous benchmark for target‐aware de novo molecular generation by jointly evaluating protein‐ligand interactions, molecular plausibility, and drug‐likeness on 18 well‐studied targets. Results show that current models often fail to consistently surpass random baseline in target‐specific enrichment, while post hoc multi‐tier virtual ...
Rui Qin   +11 more
wiley   +1 more source

Decoupling Intrinsic Molecular Efficacy From Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery

open access: yesAdvanced Science, EarlyView.
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang   +5 more
wiley   +1 more source

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