AIMC Topic: Computer Simulation

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Deep prior embedding method for Electrical Impedance Tomography.

Neural networks : the official journal of the International Neural Network Society
This paper presents a novel deep learning-based approach for Electrical Impedance Tomography (EIT) reconstruction that effectively integrates image priors to enhance reconstruction quality. Traditional neural network methods often rely on random init...

The reality of modeling irritable bowel syndrome: progress and challenges.

Expert opinion on drug discovery
INTRODUCTION: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is often therapeutically challenging. While research has advanced our understanding of IBS pathophysiology, developing precise models to predict drug response and...

Improving realism in abdominal ultrasound simulation combining a segmentation-guided loss and polar coordinates training.

Medical physics
BACKGROUND: Ultrasound (US) simulation helps train physicians and medical students in image acquisition and interpretation, enabling safe practice of transducer manipulation and organ identification. Current simulators generate realistic images from ...

Modeling microbiome-trait associations with taxonomy-adaptive neural networks.

Microbiome
The human microbiome, a complex ecosystem of microorganisms inhabiting the body, plays a critical role in human health. Investigating its association with host traits is essential for understanding its impact on various diseases. Although shotgun met...

Are we underestimating the driving factors and potential risks of freshwater microplastics from in situ and in silico perspective?

Water research
The high loads of heterogeneous microplastics (MPs) in water system sparked the exploration of MPs source and impact in the environment. However, the contributions of driving factors to MPs contamination and the potential risks posed by multidimensio...

Prediction and Prioritisation of Novel Anthelmintic Candidates from Public Databases Using Deep Learning and Available Bioactivity Data Sets.

International journal of molecular sciences
The control of socioeconomically important parasitic roundworms (nematodes) of animals has become challenging or ineffective due to problems associated with widespread resistance in these worms to most classes of chemotherapeutic drugs (anthelmintics...

Surrogate Model Development for Digital Experiments in Welding.

Journal of visualized experiments : JoVE
The manufacturing industry heavily relies on welding processes to join materials, forming integral components across various sectors. Many aspects will influence the quality of the weld and finally affect the structure integrity of the weldment. Weld...

A Framework for Parameter Estimation and Uncertainty Quantification in Systems Biology Using Quantile Regression and Physics-Informed Neural Networks.

Bulletin of mathematical biology
A framework for parameter estimation and uncertainty quantification is crucial for understanding the mechanisms of biological interactions within complex systems and exploring their dynamic behaviors beyond what can be experimentally observed. Despit...

Stable heteroclinic channels as a decision-making model: overcoming low signal-to-noise ratio with mutual inhibition.

Bioinspiration & biomimetics
Bio-inspired robot controllers are becoming more complex as we strive to make them more robust to, and flexible in, noisy, real-world environments. A stable heteroclinic network (SHN) is a dynamical system that produces cyclical state transitions usi...

Soft robotic brittle star shows the influence of mass distribution on underwater walking.

Bioinspiration & biomimetics
Most walking organisms tend to have relatively light limbs and heavy bodies in order to facilitate rapid limb motion. However, the limbs of brittle stars (Class Ophiuroidea) are primarily comprised of dense skeletal elements, with potentially much hi...