Results 301 to 310 of about 649,170 (367)
DC algorithm for estimation of sparse Gaussian graphical models. [PDF]
Shiratori T, Takano Y.
europepmc +1 more source
The multifunctional dual‐layered nanomatrix addresses post‐surgical challenges in triple‐negative breast cancer by integrating shape control, wound adherence, and tunable drug release. It delivers anticancer and antibacterial therapies through chemodynamic therapy, photothermal therapy, ferroptosis, cuproptosis, and sustained chemotherapy, enhancing ...
Sungyun Kim+8 more
wiley +1 more source
An Adaptive Robust Event-Triggered Variational Bayesian Filtering Method with Heavy-Tailed Noise. [PDF]
Deng D, Yi P, Xiong J.
europepmc +1 more source
This study presents a detailed evaluation of electrically conductive adhesives (ECAs) in photovoltaic (PV) modules, focusing on their impact on module power loss under standard accelerated aging conditions used in industry. The study was enabled by using an innovative analytical method to determine the contact resistivity of ECA‐based interconnects ...
M. Ignacia Devoto Acevedo+4 more
wiley +1 more source
An SRAM-based fully-integrated analog closed-loop in-memory computing accelerator
Mannocci P+10 more
europepmc +1 more source
Dynamical behaviors of a stochastic SIVS epidemic model with the Ornstein-Uhlenbeck process and vaccination of newborns. [PDF]
Li S, Li W.
europepmc +1 more source
Enhancing generalized spectral clustering with embedding Laplacian graph regularization
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang+5 more
wiley +1 more source
An Improved Reduced-Dimension Robust Capon Beamforming Method Using Krylov Subspace Techniques. [PDF]
Wang X, Jiang X, Chen Y.
europepmc +1 more source
Boosted unsupervised feature selection for tumor gene expression profiles
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi+5 more
wiley +1 more source
A Regularized MANOVA Test for Semicontinuous High-Dimensional Data. [PDF]
Sabbioni E, Agostinelli C, Farcomeni A.
europepmc +1 more source