Results 181 to 190 of about 90,034,892 (319)

A Generative Neuro‐Symbolic AI for Protein Sequence Design

open access: yesAdvanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne   +12 more
wiley   +1 more source

Everything All at Once: On Choosing an Estimand for Multi-component Environmental Exposures. [PDF]

open access: yesEpidemiology
Rudolph KE   +6 more
europepmc   +1 more source

A note on close-to-convex functions.

open access: yesJournal of the Mathematical Society of Japan, 1956
openaire   +3 more sources

Scalable MoS2/Si Photodiode Arrays From Roll‐to‐Roll Mechanical Exfoliation

open access: yesAdvanced Science, EarlyView.
A dry roll‐to‐roll route transforms mechanically exfoliated MoS2 flake networks into silicon‐integrated photodiode arrays. The MoS2/Si junctions generate photovoltaic output without applied bias, allowing illuminated pixels to locate light spots and reconstruct simple images.
Yigit Sozen   +2 more
wiley   +1 more source

A Rigid–Foldable Kirigami‐Inspired Metamorphic Mechanism With Programmable Motion Modes and Self‐Locking

open access: yesAdvanced Science, EarlyView.
Geometric constraint reconfiguration enables a rigid–foldable kirigami‐inspired mechanism to switch between twisting, directional translation, and self‐locking states. By encoding multifunctionality directly into its architecture, the mechanism achieves multimodal motion and passive locking without reassembly, providing a compact platform for adaptive ...
Jianlin Wang, Zhongmin Song, Ketao Zhang
wiley   +1 more source

Bistable Networks Enable Complex Shape Changes

open access: yesAdvanced Science, EarlyView.
Transition‐controlled metamaterials are networks of bistable mechanical memory that store local binary states and express them as global shape change. By decoupling low‐force programming from high‐force holding, a single lattice is reconfigured into distinct 2D profiles and 3D surfaces without continuous actuation, enabling reusable morphing materials ...
Sawyer Thomas, Jeffrey Lipton
wiley   +1 more source

Physics‐Aware Machine‐Learning‐Driven Inverse Design of Broadband Ultra‐Open Acoustic Metamaterials

open access: yesAdvanced Science, EarlyView.
A physics‐aware machine‐learning framework enables inverse design of ultra‐open acoustic silencers by decoupling spectral and radial design spaces. The approach rapidly identifies broadband, compact, and highly ventilated architectures, while revealing hidden linear design rules that link geometry, impedance matching, and acoustic performance.
Zhiwei Yang   +5 more
wiley   +1 more source

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