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Computer Simulation

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A magnetic multi-layer soft robot for on-demand targeted adhesion.

Nature communications
Magnetic soft robots have shown great potential for biomedical applications due to their high shape reconfigurability, motion agility, and multi-functionality in physiological environments. Magnetic soft robots with multi-layer structures can enhance...

Forward dynamics computational modelling of a cyclist fall with the inclusion of protective response using deep learning-based human pose estimation.

Journal of biomechanics
Single bicycle crashes, i.e., falls and impacts not involving a collision with another road user, are a significantly underestimated road safety problem. The motions and behaviours of falling people, or fall kinematics, are often investigated in the ...

Systematic review using a spiral approach with machine learning.

Systematic reviews
With the accelerating growth of the academic corpus, doubling every 9 years, machine learning is a promising avenue to make systematic review manageable. Though several notable advancements have already been made, the incorporation of machine learnin...

Pattern recognition in the nucleation kinetics of non-equilibrium self-assembly.

Nature
Inspired by biology's most sophisticated computer, the brain, neural networks constitute a profound reformulation of computational principles. Analogous high-dimensional, highly interconnected computational architectures also arise within information...

Segmenting mechanically heterogeneous domains via unsupervised learning.

Biomechanics and modeling in mechanobiology
From biological organs to soft robotics, highly deformable materials are essential components of natural and engineered systems. These highly deformable materials can have heterogeneous material properties, and can experience heterogeneous deformatio...

State identification for a class of uncertain switched systems by differential neural networks.

Network (Bristol, England)
This paper presents a non-parametric identification scheme for a class of uncertain switched nonlinear systems based on continuous-time neural networks. This scheme is based on a continuous neural network identifier. This adaptive identifier guarante...

Designing a use-error robust machine learning model for quantitative analysis of diffuse reflectance spectra.

Journal of biomedical optics
SIGNIFICANCE: Machine learning (ML)-enabled diffuse reflectance spectroscopy (DRS) is increasingly used as an alternative to the computation-intensive inverse Monte Carlo (MCI) simulation to predict tissue's optical properties, including the absorpti...

Distributed continuous-time accelerated neurodynamic approaches for sparse recovery via smooth approximation to L-minimization.

Neural networks : the official journal of the International Neural Network Society
This paper develops two continuous-time distributed accelerated neurodynamic approaches for solving sparse recovery via smooth approximation to L-norm minimization problem. First, the L-norm minimization problem is converted into a distributed smooth...

Robotic surgery education in Australia and New Zealand: primetime for a curriculum.

ANZ journal of surgery
BACKGROUND: Globally, robotic surgery (RS) has witnessed remarkable growth, yet Australia and New Zealand (ANZ) lack dedicated RS training programs, creating a workforce gap. This narrative review synthesises international research to explore trends ...

Generative artificial intelligence empowers digital twins in drug discovery and clinical trials.

Expert opinion on drug discovery
INTRODUCTION: The concept of Digital Twins (DTs) translated to drug development and clinical trials describes virtual representations of systems of various complexities, ranging from individual cells to entire humans, and enables in silico simulation...