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A branching model for intergenerational telomere length dynamics.
J Math Biol
January 2025
Institut universitaire de France (IUF), Paris, France.
We build and study an individual based model of the telomere length's evolution in a population across multiple generations. This model is a continuous time typed branching process, where the type of an individual includes its gamete mean telomere length and its age. We study its Malthusian's behaviour and provide numerical simulations to understand the influence of biologically relevant parameters.
View Article and Find Full Text PDFMetasurface higher-order poincaré sphere polarization detection clock.
Light Sci Appl
January 2025
National Research Center for High-Efficiency Grinding, College of Mechanical and Vehicle Engineering, Hunan University, 410082, Changsha, China.
Accurately and swiftly characterizing the state of polarization (SoP) of complex structured light is crucial in the realms of classical and quantum optics. Conventional strategies for detecting SoP, which typically involves a sequence of cascaded optical elements, are bulky, complex, and run counter to miniaturization and integration. While metasurface-enabled polarimetry has emerged to overcome these limitations, its functionality predominantly remains confined to identifying SoP within the standard Poincaré sphere framework.
View Article and Find Full Text PDFExperiences of midwifery students in caring for pregnancy loss. A phenomenological study.
Midwifery
January 2025
Faculty of Nursing, University of Murcia, Department of Nursing, Spain.
Aim: To analyze the experiences of midwifery students in the care of pregnancy loss during their training.
Background: The care of pregnancy losses requires the acquisition of very specific non-technical skills by midwifery students. The training received by students about gestational grief requires the use of different methodologies to obtain the required skills.
Public value and digital health: The example of guiding values in the national digital health strategy of France.
Int J Med Inform
January 2025
ISCTE-Instituto Universitário de Lisboa, Lisbon, Portugal; Universidade da Beira Interior Faculdade de Ciências da Saúde, Covilha, Portugal.
Introduction: In the WHO European Region, 44 of 53 reporting Member States (MS) have a national digital health strategy (NDHS) or policy. Their formulation is heterogenous and evolving and should best reflect public common interest. This research aims to explore how a public value approach improves the relevance of digital health policies and services, increasing their capacity to better serve the diverse range of societal interests.
View Article and Find Full Text PDFA multiscale molecular structural neural network for molecular property prediction.
Mol Divers
January 2025
Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.
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