Results 81 to 90 of about 3,080,648 (304)
Conductive Hydrogels for Exogenous Sensing and Cell Fate Control
Advanced Materials, EarlyView.We engineer electrically conductive hydrogels by combining sulfated glycosaminoglycans with semiconducting polymers. These hydrogels bind bioactive proteins, including growth factors, whose release or retention can be modulated by low‐voltage stimulation. The hydrogels are also integrated as 3D channels in organic electrochemical transistors as part of
Teuku Fawzul Akbar +15 more
wiley +1 more source
AtmosphereThe prediction of typhoon tracks in the Northwest Pacific is key to reducing human casualties and property damage. Traditional numerical forecasting models often require substantial computational resources, are high-cost, and have significant limitations
Shengye Yan, Zhendong Zhang, Wei Zheng
doaj +1 more source
Production of n-propyl acetate by reactive distillation : experimental and theoretical study [PDF]
, 2007 First steps of the development of a catalytic reactive distillation process for the production of n-propyl acetate based on experiments and simulations are proposed.
Forner, Florian +6 more
core +1 more source
Second‐Harmonic Hyper‐Mie Optical Activity Enables Closed‐Loop Chiral Photochemistry
Advanced Materials, EarlyView.Nonlinear chiral photochemistry is demonstrated in CdTe/CdO nanohelices, where circularly polarized infrared light both drives and tracks photo‐oxidation via second‐harmonic scattering. This closed‐loop process reveals real‐time structural evolution, including shell fracturing and core exposure, accompanied by a transition from hyper‐Mie to hyper ...
Hoyeon Choi +6 more
wiley +1 more source
Reinforcement Learning via Self-Distillation
CoRRLarge language models are increasingly post-trained with reinforcement learning in verifiable domains such as code and math. Yet, current methods for reinforcement learning with verifiable rewards (RLVR) learn only from a scalar outcome reward per attempt, creating a severe credit-assignment bottleneck.
Jonas Hübotter +10 more
openaire +2 more sources
Self-Distillation Amplifies Regularization in Hilbert Space
CoRR, 2020 Knowledge distillation introduced in the deep learning context is a method to transfer knowledge from one architecture to another. In particular, when the architectures are identical, this is called self-distillation. The idea is to feed in predictions of the trained model as new target values for retraining (and iterate this loop possibly a few times).
Hossein Mobahi +2 more
openaire +3 more sources
Advanced Materials, EarlyView.A double‐sided mechanical interlocking strategy is developed to create robust electrical contact between polymer electrode and metal interconnect. The fibrous structure enables formation of thread–hole adhesion, which only breaks under bulk failure and achieves a record high interfacial energy exceeding 730 J·m−2. This adhesion secures the integrity of
Gang Li +6 more
wiley +1 more source
Advanced Materials Interfaces, EarlyView.3D conductive frameworks can maintain continuous electron transport, mechanical stability, and interfacial integrity, helping next‐generation batteries operate more efficiently. This Review examines their relevance to Si anodes, all‐solid‐state batteries, and dry‐processed electrodes, and highlights bio‐derived carbons as sustainable, structurally ...
SeoYoung Ha +5 more
wiley +1 more source
Advancing Face Parsing in Real-World: Synergizing Self-Attention and Self-Distillation
IEEE AccessFace parsing, the segmentation of facial components at the pixel level, is pivotal for comprehensive facial analysis. However, previous studies encountered challenges, showing reduced performance in areas with small or thin classes like necklaces and ...
Seungeun Han, Hosub Yoon
doaj +1 more source