AIMC Topic: Models, Biological

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A Torque-actuated dissipative spring loaded inverted pendulum model with rolling contact and Its application to hexapod running.

Bioinspiration & biomimetics
We report on the development and analysis of a new torque-actuated dissipative spring loaded inverted pendulum model with rolling contact (TDR-SLIP), which is a successor to the previously developed spring loaded inverted pendulum model with rolling ...

Elasticity Versus Hyperelasticity Considerations in Quasistatic Modeling of a Soft Finger-Like Robotic Appendage for Real-Time Position and Force Estimation.

Soft robotics
Various methods based on hyperelastic assumptions have been developed to address the mathematical complexities of modeling motion and deformation of continuum manipulators. In this study, we propose a quasistatic approach for 3D modeling and real-tim...

Predictive Multitask Deep Neural Network Models for ADME-Tox Properties: Learning from Large Data Sets.

Journal of chemical information and modeling
Successful drug discovery projects require control and optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety. While volume and chemotype coverage of public and corporate ADME-Tox (absorption, distribution, excr...

Robotic device shows lack of momentum enhancement for gymnotiform swimmers.

Bioinspiration & biomimetics
Many fish generate thrust by undulating one or multiple elongated fins while keeping their body straight. This propulsion mechanism has stimulated interest in both biology and bio-inspired marine propulsion because its maneuverability and efficiency ...

A unifying framework for interpreting and predicting mutualistic systems.

Nature communications
Coarse-grained rules are widely used in chemistry, physics and engineering. In biology, however, such rules are less common and under-appreciated. This gap can be attributed to the difficulty in establishing general rules to encompass the immense div...

Advancing System Performance with Redundancy: From Biological to Artificial Designs.

Neural computation
Redundancy is a fundamental characteristic of many biological processes such as those in the genetic, visual, muscular, and nervous systems, yet its driven mechanism has not been fully comprehended. Until recently, the only understanding of redundanc...

Machine learning framework for assessment of microbial factory performance.

PloS one
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other han...

Enhancing Confusion Entropy (CEN) for binary and multiclass classification.

PloS one
Different performance measures are used to assess the behaviour, and to carry out the comparison, of classifiers in Machine Learning. Many measures have been defined on the literature, and among them, a measure inspired by Shannon's entropy named the...

Multi-task learning improves ancestral state reconstruction.

Theoretical population biology
We consider the ancestral state reconstruction problem where we need to infer phenotypes of ancestors using observations from present-day species. For this problem, we propose a multi-task learning method that uses regularized maximum likelihood to e...

Hindmarsh-Rose neuron model with memristors.

Bio Systems
We analyze single and coupled Hindmarsh-Rose neurons in the presence of a time varying electromagnetic field which results from the exchange of ions across the membrane. Memristors are used to model the relation between magnetic flux of the electroma...