Results 161 to 170 of about 14,349 (287)
Mixed-integer, multi-objective layerwise optimization of variable-stiffness composites with gaps and overlaps. [PDF]
Zamani D +2 more
europepmc +1 more source
Step‐Ladder Bioprinting to Align Collagen Fibers for Anisotropic Tissue Fabrication
The step‐ladder printing platform includes successive segments of channels with varying widths in a custom barrel design. This design allows for improved anisotropy of collagen fibers during extrusion. To demonstrate its effectiveness, corneal constructs with high transparency and shape fidelity, as well as articular cartilage constructs, displaying ...
Ilayda Namli +8 more
wiley +1 more source
Resource Allocation and Trajectory Planning in Integrated Sensing and Communication Enabled UAV-Assisted Vehicular Network. [PDF]
Song M, Zhang W, Bai J.
europepmc +1 more source
A stochastic first-order method with multi-extrapolated momentum for highly smooth unconstrained optimization [PDF]
C. He
openalex +1 more source
Better on Average? Average Inflation Targeting With an Unclear Averaging Window
ABSTRACT Average inflation targeting (AIT) aims to stabilize inflation expectations by offsetting past deviations from target. However, ambiguity about the averaging window can complicate expectations formation and reduce policy effectiveness. This paper integrates AIT into a benchmark DSGE model, incorporating adaptive learning and a signal extraction
James Dean
wiley +1 more source
Growing and linking optimizers: synthesis-driven molecule design. [PDF]
Descamps C +5 more
europepmc +1 more source
Abstract This study investigates species boundaries in the lichen genus Arctomia (Arctomiaceae, Ascomycota) using an integrative approach combining molecular phylogenetics, full Bayesian population delimitation, heuristic and model‐based species delimitation, and supervised machine learning applied to morphological data.
Stefan Ekman +2 more
wiley +1 more source
Quantum Computing for Transport Network Optimization. [PDF]
Ju J +7 more
europepmc +1 more source
Enhancing generalized spectral clustering with embedding Laplacian graph regularization
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang +5 more
wiley +1 more source

