Results 41 to 50 of about 72,374 (248)
Lagrangian study of transport and mixing in a mesoscale eddy street
We use dynamical systems approach and Lagrangian tools to study surface transport and mixing of water masses in a selected coastal region of the Japan Sea with moving mesoscale eddies associated with the Primorskoye Current.
Budyansky, M. V. +3 more
core +1 more source
Magnetic soft robots offer promise in biomedicine due to their wireless actuation and rapid response, but current fabrication methods are complex and have limited cellular compatibility. A new, contactless bioassembly strategy using hydrodynamic instabilities is introduced, enabling customizable, centimeter‐scale robots.
Wei Gao +5 more
wiley +1 more source
Relevance of Dynamic Clustering to Biological Networks
Network of nonlinear dynamical elements often show clustering of synchronization by chaotic instability. Relevance of the clustering to ecological, immune, neural, and cellular networks is discussed, with the emphasis of partially ordered states with ...
Aertsen +34 more
core +1 more source
Memristive Chaotic Circuit for Information Processing Through Time
A chaotic circuit that exploits the nonlinear characteristics of a memristive device is realized in hardware. The circuit response evolves through simple periodic, multiperiod, and chaotic regimes. The circuit also displays fading memory property. Finally, the circuit is used in a reservoir computing architecture to demonstrate nonlinear classification
Manuel Escudero +2 more
wiley +1 more source
Time lagged ordinal partition networks for capturing dynamics of continuous dynamical systems
We investigate a generalised version of the recently proposed ordinal partition time series to network transformation algorithm. Firstly we introduce a fixed time lag for the elements of each partition that is selected using techniques from traditional ...
Iu, Herbert Ho-Ching +3 more
core +1 more source
From Droplet to Diagnosis: Spatio‐Temporal Pattern Recognition in Drying Biofluids
This article integrates machine learning (ML) with the spatio‐temporal evolution of biofluid droplets to reveal how drying and self‐assembly encode distinctive compositional fingerprints. By leveraging textural features and interpretable ML, it achieves robust classification of blood abnormalities with over 95% accuracy.
Anusuya Pal +2 more
wiley +1 more source
Data-driven discovery of coordinates and governing equations
The discovery of governing equations from scientific data has the potential to transform data-rich fields that lack well-characterized quantitative descriptions.
Brunton, Steven L. +3 more
core
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source
ABSTRACT The exceptional characteristics of nanofluids have turned out to be a significant development in revolutionizing heat transfer mechanisms in several electronic cooling devices and industrial manufacturing processes. The present study deals with the investigation of the second law of thermodynamics applied to the steady MHD fluid flow above a ...
Dixita Sonowal, Bidyasagar Kumbhakar
wiley +1 more source
Computational Method for Phase Space Transport with Applications to Lobe Dynamics and Rate of Escape
Lobe dynamics and escape from a potential well are general frameworks introduced to study phase space transport in chaotic dynamical systems. While the former approach studies how regions of phase space are transported by reducing the flow to a two ...
A.M. Mancho +44 more
core +1 more source

