Results 141 to 150 of about 60,078 (257)

Dynamic Regulation of Endogenous Transcription Factor Hubs at Single‐Molecule Resolution

open access: yesAdvanced Science, EarlyView.
This study combines single‐molecule microscopy and genome editing to characterize the dynamic behaviors of endogenous oncofusion transcription factor EWS::FLI1 in Ewing sarcoma cells. EWS::FLI1 forms neomorphic hubs that dynamically assemble and dissolve. The hubs are regulated during mitosis, by RNA, and by specific chemicals.
Shawn Yoshida   +4 more
wiley   +1 more source

Flexoelectricity in Photoconversion: Fundamentals, Materials, and Outlooks

open access: yesAdvanced Science, EarlyView.
Mechanical bending of a flexible cantilever induces a strain gradient in the photoactive material. The resulting flexoelectric field couples with photovoltaic and photoconductive effects, modulating charge generation, separation, and collection. A comparative analysis of oxide perovskites, halide perovskites, and two‐dimensional materials is presented,
Xiang Huang, Feng Li, Rongkun Zheng
wiley   +1 more source

A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces

open access: yesAdvanced Science, EarlyView.
A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren   +5 more
wiley   +1 more source

TRIM: Simultaneous Thermometry, Ranging, and Imaging via a Monolithic Metalens

open access: yesAdvanced Science, EarlyView.
ABSTRACT While metasurfaces offer a pathway beyond the discrete architectures of conventional LWIR systems, physically fusing high‐precision thermometry and passive ranging onto a single metalens remains a formidable challenge. Here, we demonstrate a monolithic, dual‐focus metalens capable of simultaneous multidimensional sensing.
Man Yuan   +10 more
wiley   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

open access: yesAdvanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen   +7 more
wiley   +1 more source

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