Results 111 to 120 of about 177,625 (277)

Isosteric Substitution Enables Rational Design of Two‐Dimensional Energetic Crystals

Advanced Science, EarlyView.
Isosteric substitution transforms a classical nitro–amine motif into two‐dimensional aminofurazans with performance beyond TATB. ABSTRACT Two‐dimensional (2D) energetic crystals dissipate mechanical insult via interlayer slip, yet their molecular design space remains narrow.
Linyuan Wen, Wentong Tu, Tao Yu, Chao Chen, Zhixiang Zhang, Zhixiang Xie, Yingzhe Liu   +6 more
wiley   +1 more source

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

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

PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping

Advanced Science, EarlyView.
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su, Qi Qi, Yi Fan, Yubo Wang, Gaoyang Hao, Ka‐Chun Wong, Yunhe Wang, Xiangtao Li   +7 more
wiley   +1 more source

Probability Thermodynamics and Probability Quantum Field

, 2019
In this paper, we introduce probability thermodynamics and probability quantum fields. By probability we mean that there is an unknown operator, physical or nonphysical, whose eigenvalues obey a certain statistical distribution. Eigenvalue spectra define
Dai, Wu-Sheng, Li, Wen-Du, Liu, Tong, Zhang, Ping   +3 more
core  

Artificial Intelligence Predictions in Huge Chemical Spaces: Chiroptical Properties of [6]‐helicene Family

Advanced Science, EarlyView.
This study shows that a local, data‐driven AI model can accurately predict diverse optical and chiroptical properties of [6]helicenes using information from close structural neighbours. Combined with genetic algorithms, it enables inverse design for tailored properties, establishing practical structure–property rules for efficient molecular discovery ...
Rafael G. Uceda, Sandra Míguez‐Lago, Carlos M. Cruz, Boris Pérez‐Cañedo, Alfonso Gijón, Luis Álvarez de Cienfuegos, Antonio J. Mota, Delia Miguel, Juan M. Cuerva   +8 more
wiley   +1 more source

Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning

Advanced Science, EarlyView.
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng, Mingwei He, Jeff Zhu, Sujit K. Sahoo, Liheng Bian, Cuong Dang   +5 more
wiley   +1 more source

MODEL FOR BIONOMY OF PRIVET SAWFLY (Macrophya punctumalbum L.) (Hymenoptera, Tenthredinidae)

Acta Scientiarum Polonorum: Hortorum Cultus, 2010
The aim of the paper is to construct a model which describes the life expectancy of privet sawfly females (Macrophya punctumalbum L.), including additional information on the number of eggs.
Hanna Piekarska-Boniecka, Idzi Siatkowski, Joanna Zyprych   +2 more
doaj  

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source