Results 241 to 250 of about 256,478 (282)

Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES

Advanced Science, EarlyView.
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu, Wanpeng Zou, Yuekai Li, Jiayi Wang, Mingxuan Cai, Hongmin Cai   +5 more
wiley   +1 more source

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

Advanced Science, EarlyView.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv, Qianyang Wu, Jian Liu, Binlu Yang, Yuanhao Li, Junlin Xu, Yajie Meng, Leyi Wei, Zilong Zhang, Quan Zou, Xiulai Li, Feifei Cui   +11 more
wiley   +1 more source

Pellet Printing for Soft Robotic Devices

Advanced Science, EarlyView.
Fused Granulate Fabrication (FGF) is established here as a reliable method for fabricating soft, airtight robotic devices. Through coordinated optimization of hardware, material selection, and process parameters, this approach enables high‐speed printing of thermoplastic elastomers with silicone‐like softness and modulus.
Yijia Wu, Ju‐Hung Chen, Ariana Olivares, Katherine Kostak, Stefan Pedicone, Savita V. Kendre, Markus P. Nemitz   +6 more
wiley   +1 more source

Biolipid Film‐Fused Electrochemiluminescence for Multipurpose In Situ Bioassays

Advanced Science, EarlyView.
An ECL‐emissive, membrane‐interactive scaffold was fabricated, and facilely fused with natural and non‐native phospholipids into multifactorial mimicries of cytomembranes and vesicles for in vitro representative membrane‐process probing. Such a biointerface‐based, state‐sensitive ECL paradigm not only pinpointed proximal phenomena, including channeling
Jialiang Chen, Bin Li, Yingying Wang, Fulin Zhu, Wenxuan Yang, Xuanyu Fu, Tiantian Man, Qiuyue Wu, Kewei Ren, Shengyuan Deng   +9 more
wiley   +1 more source

A Dynamic 3D Human Liver Sinusoid Model for Mechanistic Interrogation of Fontan‐Associated Liver Disease

Advanced Science, EarlyView.
This study presents a perfusable 3D bioengineered liver sinusoid platform that integrates biofabrication, 3D cell culture, controlled hemodynamics, and multiparametric characterization to model Fontan‐associated liver disease. By decoupling pressure and hypoxia effects, the system reveals early mechanobiological and profibrotic responses under ...
Sarah Rezapourdamanab, Mehdi Salar Amoli, Tanmay Mukherjee, Maryam Bagheri, Boeun Hwang, Linqi Jin, Yamini Singh, Sophia Norton, Ashay Vishwas Bongirwar, Shweta Karnik, Lakshmi Prasad Dasi, Reza Avazmohammadi, Rene Romero, Holly D. Bauser‐Heaton, Vahid Serpooshan   +14 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source

Some of the next articles are maybe not open access.

Related searches:

isiZulu Word Embeddings

2021 Conference on Information Communications Technology and Society (ICTAS), 2021
Word embeddings are currently the most popular vector space model in Natural Language Processing. How we encode words is important because it affects the performance of many downstream tasks such as Machine Translation (MT), Information Retrieval (IR) and Automatic Speech Recognition (ASR).
Sibonelo Dlamini, Edgar Jembere, Anban Pillay, Brett van Niekerk   +3 more
openaire   +1 more source