Results 201 to 210 of about 295,852 (287)
Development of a stochastic multi-objective optimization model for managing the water, food, and energy nexus in agriculture. [PDF]
Dogouri MA +3 more
europepmc +1 more source
Machine learning‐assisted surface‐enhanced Raman spectroscopy analysis of exosomal sialic acid for ovarian cancer diagnosis, as well as independent monitoring of exosomal sialic acid expression levels across different treatment periods, reveals a potential correlation with treatment response.
Lili Cong +6 more
wiley +1 more source
Operating strategy for load service entities using flexible real-time pricing through stochastic dual dynamic programming. [PDF]
Choi W, Im J, Lee J, Chung JH, Lee D.
europepmc +1 more source
Atomic‐scale mechanisms governing multilevel resistive switching in HfOx‐based RRAM are reveal through advanced TEM. Thermally driven m‐phase rotation ([101]↔[011]) enables selective oxygen vacancy migration, which reconstructs atomic electric fields and dictates conduction—from Schottky/Poole‐Frenkel emission to Ohmic transport.
Wen Sun +9 more
wiley +1 more source
Optimizing patient flow logistics: strategic challenges, tactical solutions, and future directions. [PDF]
Zamani H, Parvaresh F, Isfahani MN.
europepmc +1 more source
RegGAIN is a novel and powerful deep learning framework for inferring gene regulatory networks (GRNs) from single‐cell RNA sequencing data. By integrating self‐supervised contrastive learning with dual‐role gene representations, it consistently outperforms existing methods in both accuracy and robustness.
Qiyuan Guan +9 more
wiley +1 more source
Optimization of unit commitment considering multiple stochastic factors and interruptible load under chance constraints. [PDF]
Ding B, Zhao M, Qin X, Chen S.
europepmc +1 more source
Generating Dynamic Structures Through Physics‐Based Sampling of Predicted Inter‐Residue Geometries
While static structure prediction has been revolutionized, modeling protein dynamics remains elusive. trRosettaX2‐Dynamics is presented to address this challenge. This framework leverages a Transformer‐based network to predict inter‐residue geometric constraints, guiding conformation generation via physics‐based iterative sampling. The resulting method
Chenxiao Xiang +3 more
wiley +1 more source
Error-aware probabilistic training for memristive neural networks. [PDF]
Liu J +8 more
europepmc +1 more source
This study constructed the first D‐amino acid antimicrobial peptide dataset and developed an AI model for efficient screening of substitution sites, with 80% of candidate peptides showing enhanced activity. The lead peptide dR2‐1 demonstrated potent antimicrobial activity in vitro and in vivo, high stability, and low toxicity.
Yinuo Zhao +14 more
wiley +1 more source

