Results 181 to 190 of about 366,433 (291)

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

Generalized Additive Modeling of Ecological Data With mgcv: New Adequacy Assessment Tools. [PDF]

Ecol Evol
Mainguy J, McInerney R, Millar RB, Valiquette E, Bélanger M, Moral RA.   +5 more
europepmc   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 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

Full-cycle prediction of crack healing in self-healing concrete using generalized polynomial chaos expansion. [PDF]

Commun Eng
Fu C, Xu W, Zhan Q, Chen C, Guo T, Zhang X, Pang B.   +6 more
europepmc   +1 more source

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment

Advanced Science, EarlyView.
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng, Fuze Cong, Shenbo Zhang, Rui Lv, Wenjia Zhang, Xinyi Ke, Juncheng Wu, Zhonghe Zhao, Kui Zhao, Di Dong, Ruofan Zhang, Zhengyu Jin, Max Seidensticker, Zhiwei Wang, Huanwen Wu, Xianlin Han, Nan Hong, Huadan Xue   +17 more
wiley   +1 more source

Research and Implementation of Localization of Multiple Local Discharge Sources in Switchgear Based on Ultrasound. [PDF]

Sensors (Basel)
Xu D, Huang Y, Mitra AD, Yang SX, Li P, Xiao M, Su L, Song L.   +7 more
europepmc   +1 more source

Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring

Advanced Science, EarlyView.
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen, Haoyu Wang, Guixin Xu, Yuqin Yuan, Xinmeng Cai, Zhengwu Wei, Dongheng Zhang, Qibin Sun, Tianwei Zhang, Cuntai Guan, Yan Chen   +10 more
wiley   +1 more source

Generalized 3D quasi-phase-matching model of image contrast in second harmonic generation microscopy of fibrillar collagen architectures. [PDF]

JPhys Photonics
Shelton EM, Campagnola PJ.
europepmc   +1 more source

MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion

Advanced Science, EarlyView.
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong, Ji Ma, Yidan Lu, Jiahui Zhang, Wanyue Li, Yeke Chen, Teng Zhang, Xuechao Chen, Zhangguo Yu, Peng Lu   +9 more
wiley   +1 more source