Results 151 to 160 of about 101,961 (306)

Anisotropic NMR as a Crucial Tool for Differentiation of Epimers With High Conformational Flexibility

Angewandte Chemie, EarlyView.
Epimer discrimination remains challenging due to subtle NMR differences. Here, we propose a methodology based on 13C‐RCSA and RDC anisotropic parameters, enabling the assignment of two flexible tetraprenyltoluquinol epimers (1a and 1b) with remote stereoclusters.
Juan Carlos C. Fuentes‐Monteverde, Abel M. Forero, Nilamoni Nath, Antonio Hernández Daranas, Carlos Jiménez, Jaime Rodríguez, Christian Griesinger   +6 more
wiley   +2 more sources

Beltrami's models of non-Euclidean geometry

, 2012
In two articles published in 1868 and 1869, Eugenio Beltrami provided three models in Euclidean plane (or space) for non-Euclidean geometry. Our main aim here is giving an extensive account of the two articles’ content.
ARCOZZI, NICOLA
core  

SCP‐Pose: Leveraging Structural Consistency Prior Knowledge for Real‐Time Category‐Level 6D Pose Estimation

Advanced Intelligent Systems, EarlyView.
This paper presents a high‐speed object pose estimation method that deconstructs objects into geometric components. Inspired by human cognitive generalization, it detects these primitives and infers the 6D pose from their stable spatial configuration.
Xuyang Li, Mingxuan Yu, Xuemei Xie, Zhaozhuo An, Qiyue Li, Xiaodan Song, Guangming Shi   +6 more
wiley   +1 more source

Non-Commutative Analysis on Quantum Spaces [PDF]

, 2004
Tools like a generalized *-product, a Leibniz rule and an integration needed for Analysis on Quantum Spaces such as n-dimensional q-deformed Euclidean space are ...
Jambor, Claudia
core  

Resource‐Aware Contrastive Scattering Meta‐Learning for Efficient Few‐Shot Acoustic Anomaly Detection

Advanced Intelligent Systems, EarlyView.
This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley   +1 more source

Carslaw’s non-euclidean geometry [PDF]

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

Visual and Visual‐Inertial SLAM Based on Enhanced Deep Learning Features and Motion Smoothness Constraints

Advanced Intelligent Systems, EarlyView.
A visual and visual‐inertial simultaneous localization and mapping (SLAM) algorithm, leveraging enhanced deep learning features and motion smoothness constraints, is proposed in this research work. This method retains the advantages of geometry‐based SLAM methods while effectively utilizing the powerful representational capabilities of data‐driven ...
Maosheng Jiang, Lei Ma, Muhua Zhang, Kai Shen   +3 more
wiley   +1 more source

Pre‐Curved Everting Robots With Embedded Steering Intelligence Fabricated by CO2 Laser Welding

Advanced Intelligent Systems, EarlyView.
Design and experimental demonstration of a laser welded growing robot for anatomically guided navigation. The robot follows an aortic arch phantom entering the branchiocephalic branch through steering by design. The figure shows the physical phantom setup, CAD defined weld geometry and full robot eversion.
Brandon Saldarriaga, Panagiotis Kalozoumis, Panagiotis Vartholomeos, Carlo Seneci, Kawal Rhode, Christos Bergeles   +5 more
wiley   +1 more source

Generalized Task‐Driven Design of Soft Robots via Reduced‐Order Finite Element Method‐Based Surrogate Modeling

Advanced Intelligent Systems, EarlyView.
A unified, reusable modeling pipeline enables task‐driven design of soft robots across actuator families and task scenarios. High‐fidelity simulations are compressed into compact pseudo‐rigid‐body joint surrogates, while a design‐conditioned meta‐model generates new surrogates from geometry parameters without rerunning finite element method.
Yao Yao, David Howard, Perla Maiolino
wiley   +1 more source

An Integrated and Robust Deep Learning Framework for Denoising and Analyzing Single‐Cell Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
Single‐cell Spatial Transcriptomics Analysis and Denoising Engine is introduced as a unified deep learning framework that jointly performs denoising, clustering, and gene prioritization in spatial transcriptomics. By integrating linear and nonlinear representations within a dual‐channel architecture, it improves robustness and accuracy, uncovers ...
Yaxuan Cui, Yang Cui, Ruheng Wang, Xin Zeng, Zheyong Zhu, Ding Yi, Ruihua Guo, Tetsuya Sakurai, Kenta Nakai, Xiucai Ye, Leyi Wei, Yong Chen   +11 more
wiley   +1 more source