Results 131 to 140 of about 10,435,760 (324)

The Interplay of Curvature, Geometry, and Topology Shapes Tissue Organisation in Epithelial Shells

Advanced Science, EarlyView.
Purely geometric 3D Voronoi models predict the organisation of epithelial shells. The interplay of curvature, geometry, and topology enriches the number of pentagons in shells with lower number of cells. Small MDCK cysts and Mouse embryos match the top polygonal configurations in a compactness‐based ranking derived from the Voronoi model. In conclusion,
Laura Morato, Jesús A. Andrés‐San Román, Juan Garrido‐García, Carmen Gordillo‐Vázquez, Ana M. Palacios, Elisabeth Lidueña‐Fernández, Katie McDole, Pedro Gómez‐Gálvez, Valentina Annese, Luis M. Escudero   +9 more
wiley   +1 more source

PUMA: Deep Metric Imitation Learning for Stable Motion Primitives

Advanced Intelligent Systems
Imitation learning (IL) facilitates intuitive robotic programming. However, ensuring the reliability of learned behaviors remains a challenge. In the context of reaching motions, a robot should consistently reach its goal, regardless of its initial ...
Rodrigo Pérez‐Dattari, Cosimo Della Santina, Jens Kober   +2 more
doaj   +1 more source

DyProL: Dynamic Ensemble Representation Learning for Protein–Nucleic Acid Binding Site Prediction

Advanced Science, EarlyView.
Protein function is represented as a dynamic conformational ensemble rather than a single static structure. A multi‐conformation geometric attention framework aligns, clusters, and learns representative states to capture residue‐ and ensemble‐level signals. Integrating structural dynamics improves interpretable protein‐NA binding prediction and reveals
Pengpai Li, Yiman Liu, Liya Liang, Rongming Liu   +3 more
wiley   +1 more source

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

Advanced Science, EarlyView.
MethyAnno enables robust and interpretable annotation of single‐cell DNA methylation data by integrating multi‐scale epigenetic information, bidirectional cross‐attention, and prototype‐based metric learning. The framework resolves rare and novel cell types across datasets while revealing cell‐type‐specific epigenetic signatures associated with disease
Yuhang Jia, Siyu Li, Songming Tang, Keju Gu, Shengquan Chen   +4 more
wiley   +1 more source

Advanced Graph Neural Networks for Smart Mining: A Systematic Literature Review of Equivariant, Topological, Symplectic, and Generative Models

Mathematics
The transition of the mining industry towards Industry 5.0 demands predictive models capable of strictly adhering to physical laws and modeling complex, non-Euclidean geometries—capabilities often lacking in standard graph neural networks.
Luis Rojas, Lorena Jorquera, José Garcia   +2 more
doaj   +1 more source

Leveraging Microphysiological Systems to Facilitate Neutrophil‐Based Cancer Immunotherapy

Advanced Science, EarlyView.
Microphysiological systems are emerging as powerful human‐relevant platforms for studying neutrophil biology in cancer. Current applications of spheroids, organoids, and organ‐on‐a‐chip models are reviewed, together with future opportunities in behaviorome profiling, multi‐omics integration, personalized medicine, immune crosstalk, and multi‐organ ...
Shuai Shao, Markus Isfeld Diehl, Caroline N. Jones   +2 more
wiley   +1 more source

Kant's Views on Non-Euclidean Geometry [PDF]

, 2012
Kant's arguments for the synthetic a priori status of geometry are generally taken to have been refuted by the development of non-Euclidean geometries.
Cuffaro, Michael
core   +1 more source

Carslaw’s non-euclidean geometry [PDF]

Bulletin of the American Mathematical Society, 1917
openaire   +2 more sources

An Unbiased Geometry‐Resolved Membrane Platform for Proteome‐Scale Discovery of Membrane Curvature Sensors

Advanced Science, EarlyView.
A novel geometry‐resolved membrane platform provides a seamlessly integrated pipeline for studying curvature‐sensing proteins. By linking shotgun proteomics with quantitative imaging, this approach enables both the unbiased discovery and rigorous validation of novel sensors across the entire curvature range—positive, negative, and zero.
Takumi Komikawa, Rikuto Kawakami, Kunanon Chattrairat, Tatsuya Niwa, Taiga Ajiri, Takao Yasui, Masayoshi Tanaka   +6 more
wiley   +1 more source

HGKAN: Hyperbolic Graph-Based Kolmogorov–Arnold Network for Social Recommendation

IEEE Access
Social recommendation utilizes social relationships to alleviate data sparsity and improve recommendation quality. Nevertheless, existing approaches still encounter several limitations.
Nikorn Kannikaklang, Sartra Wongthanavasu   +1 more
doaj   +1 more source