Results 301 to 310 of about 649,170 (367)

Multifunctional Bioactive Dual‐Layered Nanofibrous Matrix for Effective Breast Cancer Therapy and Enhanced Wound Healing

open access: yesSmall, EarlyView.
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

Environmental Stability of the Contact Resistivity of Interconnects Based on Electrically Conductive Adhesives and its Correlation to Photovoltaic Module Power Loss under Accelerated Aging Testing†

open access: yesIEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
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

open access: yes
Mannocci P   +10 more
europepmc   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
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

Boosted unsupervised feature selection for tumor gene expression profiles

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
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

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