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http://dx.doi.org/10.1016/S2589-7500(23)00266-2 | DOI Listing |
Mol Divers
September 2025
Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, Nanjing, 211198, China.
Drug absorption significantly influences pharmacokinetics. Accurately predicting human oral bioavailability (HOB) is essential for optimizing drug candidates and improving clinical success rates. The traditional method based on experiment is a common way to obtain HOB, but the experimental method is time-consuming and costly.
View Article and Find Full Text PDFJ Robot Surg
September 2025
ORSI Academy, Melle, Belgium.
This Letter to the Editor responds to the recent publication by Patel et al. (J Robot Surg. Jul 11;19(1):370, 2025), which outlines a framework and recommendations for telesurgery.
View Article and Find Full Text PDFChaos
September 2025
School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Although many real-world time series are complex, developing methods that can learn from their behavior effectively enough to enable reliable forecasting remains challenging. Recently, several machine-learning approaches have shown promise in addressing this problem. In particular, the echo state network (ESN) architecture, a type of recurrent neural network where neurons are randomly connected and only the read-out layer is trained, has been proposed as suitable for many-step-ahead forecasting tasks.
View Article and Find Full Text PDFPhys Chem Chem Phys
September 2025
State Key Laboratory of Materials for Integrated Circuits, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Selenium, as an important semiconductor material, exhibits significant potential for understanding lattice dynamics and thermoelectric applications through its thermal transport properties. Conventional empirical potentials are often unable to accurately describe the phonon transport properties of selenium crystals, which limits in-depth understanding of their thermal conduction mechanisms. To address this issue, this study developed a high-precision machine learning potential (MLP), with training datasets generated molecular dynamics simulations.
View Article and Find Full Text PDFNatl Sci Rev
September 2025
The Centre of Nanoscale Science and Technology and Key Laboratory of Functional Polymer Materials, Institute of Polymer Chemistry, Renewable Energy Conversion and Storage Center (RECAST), College of Chemistry, Nankai University, Tianjin 300071, China.
Contactless human-machine interfaces (C-HMIs) are revolutionizing artificial intelligence (AI)-driven domains, yet face application limitations due to narrow sensing ranges, environmental fragility, and structural rigidity. To address these obstacles, we developed a flexible photonic C-HMI (Flex-PCI) using flexible visible-blind near-infrared organic photodetectors. In addition to its unprecedented performance across key metrics, including broad detection range (0.
View Article and Find Full Text PDF