Results 101 to 110 of about 17,887 (258)
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu +3 more
wiley +1 more source
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan +8 more
wiley +1 more source
Robust Video List Decoding in Error-Prone Transmission Systems Using a Deep Learning Approach
This paper introduces a novel deep-learning assisted video list decoding method for error-prone video transmission systems. Unlike traditional list decoding techniques, our proposed system uses a Transformer-based no-reference image quality assessment ...
Yujing Zhang +4 more
doaj +1 more source
Harnessing Phase Separation for the Development of High‐Performance Hydrogels
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao +3 more
wiley +1 more source
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li +6 more
wiley +1 more source
Umbilical cord stem cell‐derived exosomes encapsulated in an immunomodulatory bioadhesive hydrogel spray enable localized therapy, sustained vesicle delivery, macrophage polarization, suppress systemic inflammation, and mitigate glucose and insulin homeostasis impairments in MAFLD.
Triya Saha +4 more
wiley +1 more source
A Generative Neuro‐Symbolic AI for Protein Sequence Design
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
Modulating Calcium Homeostasis via a Biomimetic Scaffold to Rescue Diabetic Ischemic Wounds
This strategy addresses impaired microcirculation and loss of extracellular matrix (ECM) guidance in diabetic wound healing. Musc@CP, a nanofibrous dressing combining an ECM‐mimetic chitosan‐pullulan scaffold with muscone, enhances perfusion by attenuating intracellular Ca2+ overload‐associated endothelial dysfunction.
Xiang Zheng +14 more
wiley +1 more source
Computational simulations of tumor evolution are increasingly used to infer the rules underlying cancer growth, with the goal of one day recommending tailored treatments. Here we show that the properties of lung cancer sequencing data are best replicated by a model which assumes that cells compete both to proliferate and survive. ABSTRACT Computational
Helena Coggan +5 more
wiley +1 more source

