Results 41 to 50 of about 84,782 (213)
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
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 +3 more
wiley +1 more source
High‐throughput screening led to the identification of 67 Z‐scheme heterojunctions (comprising 2D magnetic transition metal halides and non‐magnetic transition metal chalcogenides). For CrI3/MoTe2 and CrI3/WTe2, electronic structure analysis demonstrated that synergistic crystallographic point group and built‐in electric field effects generate a ...
Hongyang Ren +8 more
wiley +1 more source
Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao +9 more
wiley +1 more source
Multimodal Imaging Reveals Rapid Catecholamine Uptake and Release by Neutrophils
We show that immune cells (neutrophils) synthesize, uptake, and store catecholamine neurotransmitters such as dopamine or adrenaline. They also release them in response to specific stimuli (serotonin), which we directly visualize using fluorescent nanosensors. We further demonstrate that catecholamines affect neutrophil functions (NETosis) and platelet
Jennifer Mohr +19 more
wiley +1 more source
Dynamic Regulation of Endogenous Transcription Factor Hubs at Single‐Molecule Resolution
This study combines single‐molecule microscopy and genome editing to characterize the dynamic behaviors of endogenous oncofusion transcription factor EWS::FLI1 in Ewing sarcoma cells. EWS::FLI1 forms neomorphic hubs that dynamically assemble and dissolve. The hubs are regulated during mitosis, by RNA, and by specific chemicals.
Shawn Yoshida +4 more
wiley +1 more source
Introduction to Mathematical Probability. [PDF]
J. A. Greenwood, J. V. Uspensky
+4 more sources
Triple‐Mode Ferroelectric Thin‐Film Transistor for Hybrid Electrical–Optical Reservoir Computing
A triple‐mode ferroelectric thin‐film transistor is developed by integrating Si3N4/HZO/IGZO layers to realize three independent memory modes: electric long‐term, electric short‐term, and optical short‐term. This single‐device architecture functions as both a reservoir and readout layer, achieving 92.43% MNIST accuracy. It offers a fully hardware‐based,
Hyeonho Lee +9 more
wiley +1 more source
SpaMode introduces a versatile framework for spatial multi‐omics integration across vertical, horizontal, and mosaic scenarios. By disentangling modality‐invariant and variant features through a mixture‐of‐experts mechanism, it adaptively reconfigures spatially heterogeneous signals.
Xubin Zheng +6 more
wiley +1 more source
Integrating experimental insights with molecular dynamics simulations, we establish an advanced mathematical model for fluids confined in sub‐10‐nm channels, enabling quantitative prediction of interfacial layer thickness and viscosity by accounting for channel material, temperature, and fluid properties.
Xiang Zhang +3 more
wiley +1 more source
Introduction to Mathematical Probability
J. V. Uspensky’s Introduction to Mathematical Probability is a classic textbook that provides a rigorous yet accessible foundation in probability theory. Written in the early twentieth century, the book systematically develops the subject from basic combinatorial principles to more advanced topics such as the law of large numbers, the central limit ...
openaire +1 more source

