Results 41 to 50 of about 55,134 (231)
Triply‐twinned architected lattices transform deformation from bending to stretching of struts, delivering up to threefold increases in stiffness and strength across polymeric and metallic systems. High‐resolution synchrotron XCT and image‐based simulations reveal how meta‐grain architecture, defects, and AM build orientation govern failure pathways ...
David McArthur +7 more
wiley +1 more source
A fully flexible ion‐gel‐gated graphene‐channel transistor driven by a triboelectric nanogenerator enables self‐powered tactile sensing and synaptic learning. Mimicking spike‐rate‐dependent plasticity, the device exhibits frequency‐selective potentiation and depression, supporting rate‐coded neuromorphic computation even under flex.
Hanseong Cho +3 more
wiley +1 more source
Positive Definite Kernels in Machine Learning [PDF]
This survey is an introduction to positive definite kernels and the set of methods they have inspired in the machine learning literature, namely kernel methods.
Cuturi, Marco
core +1 more source
An active learning framework, grounded in independently generated in‐house experimental data, enables reliable discovery of high‐performance interfacial materials for perovskite solar cells. Iterative model refinement autonomously converges toward structurally robust quaternary ammonium architectures, establishing a new design principle for interfacial
Jongbeom Kim +8 more
wiley +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Lepskii Principle in Supervised Learning
In the setting of supervised learning using reproducing kernel methods, we propose a data-dependent regularization parameter selection rule that is adaptive to the unknown regularity of the target function and is optimal both for the least-square ...
Blanchard, Gilles +2 more
core
Ductility Tuning via Cluster Network Characteristics of Porous Components
Network optimization via cluster characteristics induced by interaction of stress concentration is proposed, demonstrating increased cluster size and dispersion in non‐uniform porous components. The optimized structures exhibit, for the first time, that enhanced ductility and damage progression is controllable through zigzag cluster network designed by
Ryota Toyoba +4 more
wiley +1 more source
The hydroporator platform employs controlled hydrodynamic deformation for efficient mRNA and CRISPR/Cas9 delivery into primary human T cells, enabling allogeneic CAR‐T cell manufacturing. It preserves cell functionality and drives potent gene editing, CAR expression, and tumor cytotoxicity, while feature‐based analysis links these functional outcomes ...
Soohyun Jeon +6 more
wiley +1 more source
Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification [PDF]
Functional data are difficult to manage for many traditional statistical techniques given their very high (or intrinsically infinite) dimensionality. The reason is that functional data are essentially functions and most algorithms are designed to work ...
Alberto Muñoz, Javier González
core
TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications
TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince +3 more
wiley +1 more source

