Results 111 to 120 of about 66,511 (264)
Optimal control prevents itself from eradicating stochastic disease epidemics.
The resources available for managing disease epidemics - whether in animals, plants or humans - are limited by a range of practical and financial constraints.
Rachel Russell, Nik J Cunniffe
doaj +1 more source
A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn +2 more
wiley +1 more source
A dyed nylon fiber is implemented inside the scattering phantom and skin tissue. The deep‐tissue light generation via whispering gallery mode lasing is demonstrated, achieving a depth of >50 times transport mean free path in scattering phantom and 3 mm beneath skin.
Dongqin Ni +4 more
wiley +1 more source
Low‐Pressure Plasma‐Based Wrinkling of PDMS and Machine Learning‐Driven Property Engineering
Wrinkled surfaces are well‐suited for controlled surface deformations in the µm range. The key challenge is the relation between the resulting wrinkle features and the necessary process conditions. Machine learning techniques have solved the prediction and inverse design problems for various preparation conditions, opening a precisely controlled ...
Fabian Kopsch +7 more
wiley +1 more source
Rotating Fluorescent Nanodiamond Assemblies With Focused Laguerre–Gaussian Beams
Self‐assembled fluorescent nanodiamond clusters are optically trapped and driven into controlled two‐dimensional rotation with Laguerre–Gaussian beams. With localized optical excitation, optically detected magnetic resonance spectra are collected at defined points along the orbit in a uniform external magnetic field.
Adam Stewart +5 more
wiley +1 more source
Stochastic control optimal in the Kullback sense
Summary: The paper solves the problem of minimization of the Kullback divergence between a partially known and a completely known probability distribution. It considers two probability distributions of a random vector \((u_1,x_1,\dots,u_T,x_T)\) on a sample space of \(2T\) dimensions. One of the distributions is known, the other is known only partially.
Šindelář, J. (Jan) +2 more
openaire +3 more sources
Deterministic Integration of Quantum Emitters and Optical Cavities in a Van Der Waals Crystal
The work demonstrates fabrication of Circular Bragg Grating (CBG) cavities with embedded emitters in hBN. The cavities are fabricated around a pre‐characterised quantum emitter. The integrated platform enables light matter interaction and access to brighter emitters and spins in hBN.
James Liddle‐Wesolowski +8 more
wiley +1 more source
On‐Chip Photonic Neural Network Architectures
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
Optimal control for solutions to Sobolev stochastic equations
Evgeniy Bychkov +2 more
doaj
Multimodal Branched Transport Infers Anatomically Aligned Brain Reaction Maps. [PDF]
Mendico C.
europepmc +1 more source

