Results 221 to 230 of about 4,432,086 (296)

CFPR-YOLO: chili flower pose estimation for robotic pollination in unstructured environments. [PDF]

open access: yesFront Plant Sci
Kuang M   +9 more
europepmc   +1 more source

Breaking the Trade‐Off of Mechanical Robustness and Energy Storage Capacity in Phase Change Materials Through a Molecular Design Strategy of Hard‐Segment‐Anchored/Side‐Chain‐Storage

open access: yesAdvanced Science, EarlyView.
To decouple mechanical robustness and energy storage capacity in phase change materials (PCMs), a series of polyurethane‐based PCMs bearing crystallizable alkyl side chains are synthesized via a hard‐segment‐anchored/side‐chain‐storage molecular design.
Huizhou Luo   +6 more
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

Targeting Lipopolysaccharide Transport Induces Membrane Lipid Remodeling and Sensitizes Acinetobacter baumannii to Colistin Treatment

open access: yesAdvanced Science, EarlyView.
This study identifies C4 as a lead inhibitor of the Lpt system. Notably, C4 potentiates colistin activity by disrupting LPS transport and remodeling phospholipid homeostasis, revealing a functional interplay between the Lpt and Mla systems. These findings establish a mechanistic link between Lpt inhibition and membrane lipid remodeling, positioning Lpt–
Jianya Luo   +6 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

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