AIMC Topic: Computer Simulation

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Learning contact-rich whole-body manipulation with example-guided reinforcement learning.

Science robotics
Humans use diverse skills and strategies to effectively manipulate various objects, ranging from dexterous in-hand manipulation (fine motor skills) to complex whole-body manipulation (gross motor skills). The latter involves full-body engagement and ...

A dynamic examination of the digital circuit implementing the Fitzhugh-Nagumo neuron model with emphasis on low power consumption and high precision.

PloS one
Neuromorphic computing has got more attention in various tasks during recent years. The main goal of this field is to explore neural functionality in the brain. The studies of spiking neurons and Spiking Neural Networks (SNNs) are vital to understand...

AI simulation models for diagnosing disabilities in smart electrical prosthetics using bipolar fuzzy decision making based on choquet integral.

Scientific reports
The integration of AI simulation models within smart electrical prosthetic systems represents a significant advancement in disability disease diagnosis. However, the selection and evaluation of these AI models interpret some multi-criteria decision-m...

Integrated 3D Modeling and Functional Simulation of the Human Amygdala: A Novel Anatomical and Computational Analyses.

Neuroinformatics
The amygdala plays a central role in emotion, memory, and decision-making and comprises approximately 13 distinct nuclei with connectivity. Despite its functional importance, high-resolution subnuclear mapping is challenging. This study aimed to cons...

Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study.

Scientific reports
Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle stud...

A computational framework for inferring species dynamics and interactions with applications in microbiota ecology.

NPJ systems biology and applications
We present MBPert, a generic computational framework for inferring species interactions and predicting dynamics in time-evolving ecosystems from perturbation and time-series data. In this work, we contextualize the framework in microbial ecosystem mo...

Limits on the computational expressivity of non-equilibrium biophysical processes.

Nature communications
Many biological decision-making tasks require classifying high-dimensional chemical states. The biophysical and computational mechanisms that enable classification remain enigmatic. In this work, using Markov jump processes as an abstraction of gener...

Seeker-M: A bionic mantis shrimp robot with an adjustable-mass flexible spine.

Bioinspiration & biomimetics
To enhance the motion flexibility and environmental adaptability of underwater robots, this study proposes a novel design, Seeker-M, inspired by the locomotion mechanism of the mantis shrimp. The robot imitates the mantis shrimp's multi-pleopod swimm...

Data-driven equation discovery reveals nonlinear reinforcement learning in humans.

Proceedings of the National Academy of Sciences of the United States of America
Computational models of reinforcement learning (RL) have significantly contributed to our understanding of human behavior and decision-making. Traditional RL models, however, often adopt a linear approach to updating reward expectations, potentially ...

In silico analysis of atrial fibrillation and hypertension mechanism of action secondary to ibrutinib/acalabrutinib in chronic lymphocytic leukemia.

Scientific reports
Ibrutinib and acalabrutinib are first- and next-generation Bruton Tyrosine Kinase inhibitors (BTKi), respectively, approved for chronic lymphocytic leukemia (CLL). Ibrutinib has been associated with cardiovascular events, including atrial fibrillatio...