Synchronizing climate-carbon cycle heartbeats in the Phanerozoic vegetated icehouses. [PDF]
Fang Q +7 more
europepmc +1 more source
Intrinsically Design‐Rule‐Compliant Nanophotonic Inverse Design via Learned Generative Manifolds
A generative reparameterization framework for nanophotonic inverse design is introduced, restricting optimization to a learned manifold of design‐rule‐compliant geometries. Unlike conventional penalty‐based approaches, fabrication constraints are encoded intrinsically within the design representation.
Bahrem Serhat Danis +8 more
wiley +1 more source
EM Simulation Model of a Clinically‐Used RF Head Coil at 7 T
This article has been temporarily removed pending the resolution of a potential legal issue.
Dora Ozkara +7 more
wiley +1 more source
Spatial uniformity and temporal stability of pixel-to-pixel variation in mini-SiTian CMOS detector. [PDF]
Hu G +16 more
europepmc +1 more source
ABSTRACT Purpose To improve the accuracy of diffusion‐weighted powder average signals for diffusion encoding with arbitrary b‐tensors. Methods We identify an intrinsic dihedral (D2$$ {D}_2 $$) symmetry of diffusion signals for arbitrary diffusion encoding, which defines their natural signal space (a quotient of 3D rotations).
Sune Nørhøj Jespersen +1 more
wiley +1 more source
Living in the Dark: Exploring the Factors Driving Nocturnal Activity in Three Lemur Species. [PDF]
Rakotoarisoa H +3 more
europepmc +1 more source
Human In Vivo Validation of Frequency‐Dependent QTI
ABSTRACT Purpose The aim of this work is to investigate if q‐space trajectory imaging (QTI) waveforms can be designed to probe QTI metrics at a single centroid frequency under realistic experimental conditions for in vivo human brain imaging. Methods Realistic diffusion encoding waveforms based on double‐rotation gradient waveform and magic‐angle ...
Svenja Niesen +3 more
wiley +1 more source
Tectonic-astronomical interactions in shaping late Paleozoic climate and organic carbon burial. [PDF]
Wei R +7 more
europepmc +1 more source
Deep Learning Improves Robustness of Voxelwise Kinetic Modeling for Hyperpolarized Carbon‐13 MRI
ABSTRACT Purpose To evaluate whether deep learning improves the robustness of voxelwise kinetic parameter estimation from hyperpolarized (HP) 13C MRI compared with nonlinear least‐squares (NLLS) fitting. Methods A hybrid neural network (NN) was trained on synthetic pyruvate/lactate time courses generated from an open‐system two‐compartment HP 13C ...
Kofi Deh +5 more
wiley +1 more source
An AI approach to lunar phase detection: enhancing the identification of the new crescent with astronomical data integration. [PDF]
Al-Rajab M +3 more
europepmc +1 more source

