Results 161 to 170 of about 196,670 (323)
Exploring N-soliton solutions, multiple rogue wave and the linear superposition principle to the generalized hirota satsuma-ito equation. [PDF]
Guo Y +5 more
europepmc +1 more source
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang +5 more
wiley +1 more source
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
Stable aggregates of a new hydrogen‐bond mediated porphyrin‐perylenebisimide (PBI) bola‐type supra‐amphiphile have been synthesized by lyophilization of solutions of both single molecules in THF/water mixtures, followed by redispersion in pure water. Cryogenic transmission electron microscopy verifies the spherical morphology.
Erik J. Schulze +6 more
wiley +2 more sources
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
Disentangling Coincident Cell Events Using Deep Transfer Learning and Compressive Sensing
Overlapping cells during detection distort single‐cell measurements and reduce diagnostic accuracy. A hybrid framework combining a fully convolutional neural network with compressive sensing to disentangle overlapping signals directly from raw time‐series data is presented.
Moritz Leuthner +2 more
wiley +1 more source

