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Simultaneous Unbinned Differential Cross-Section Measurement of Twenty-Four Z+jets Kinematic Observables with the ATLAS Detector.
Phys Rev Lett
December 2024
CERN, Geneva, Switzerland.
Z boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from standard model predictions. All previous measurements of Z boson production characterize the event properties using a small number of observables and present the results as differential cross sections in predetermined bins.
View Article and Find Full Text PDFCMRxRecon2024: A Multimodality, Multiview k-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI.
Radiol Artif Intell
January 2025
Human Phenome Institute and Shanghai Pudong Hospital, Fudan University, Shanghai, China.
. The released CMRxRecon2024 dataset is currently the largest and most protocol-diverse publicly available k-space dataset including multi-modality and multi-view cardiac MRI data from 330 healthy volunteers, and each one covers standardized and commonly used clinical protocols. ©RSNA, 2025.
View Article and Find Full Text PDFIntelligent Design of Lipid Nanoparticles for Enhanced Gene Therapeutics.
Mol Pharm
January 2025
ZJU-Hangzhou Global Scientific and Technological Innovation Canter, Zhejiang University, Hangzhou, Zhejiang 311215, China.
Lipid nanoparticles (LNPs) are an effective delivery system for gene therapeutics. By optimizing their formulation, the physiochemical properties of LNPs can be tailored to improve tissue penetration, cellular uptake, and precise targeting. The application of these targeted delivery strategies within the LNP framework ensures efficient delivery of therapeutic agents to specific organs or cell types, thereby maximizing therapeutic efficacy.
View Article and Find Full Text PDFDynamics and kinetics exploration of the oxygen reduction reaction at the Fe-N/C-water interface accelerated by a machine learning force field.
Chem Sci
January 2025
Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University Suzhou Jiangsu 215123 China
Understanding the oxygen reduction reaction (ORR) mechanism and accurately characterizing the reaction interface are essential for improving fuel cell efficiency. We developed an active learning framework combining machine learning force fields and enhanced sampling to explore the dynamics and kinetics of the ORR on Fe-N/C using a fully explicit solvent model. Different possible reaction paths have been explored and the O adsorption process is confirmed as the rate-determining step of the ORR at the Fe-N/C-water interface, which needs to overcome a free energy barrier of 0.
View Article and Find Full Text PDFTemperature-Enhanced Purine Metabolism-Based Versatile SERS Platform for Rapid Clinical Pathogens Diagnosis and Drug-Resistant Assessment.
Anal Chem
January 2025
School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
Label-free surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) techniques presents a promising approach for rapid pathogen identification. Previous studies have demonstrated that purine degradation metabolites are the primary contributors to SERS spectra; however, generating these distinguishable spectra typically requires a long incubation time (>10 h) at room temperature. Moreover, the lack of attention to spectral variations between strains of the same bacterial species has limited the generalizability of ML models in real-world applications.
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