AIMC Topic: Paper

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Fluid-driven origami-inspired artificial muscles.

Proceedings of the National Academy of Sciences of the United States of America
Artificial muscles hold promise for safe and powerful actuation for myriad common machines and robots. However, the design, fabrication, and implementation of artificial muscles are often limited by their material costs, operating principle, scalabil...

Origami-based earthworm-like locomotion robots.

Bioinspiration & biomimetics
Inspired by the morphology characteristics of the earthworms and the excellent deformability of origami structures, this research creates a novel earthworm-like locomotion robot through exploiting the origami techniques. In this innovation, appropria...

Quantification of the 3α and 3β epimers of 25-hydroxyvitamin D in dried blood spots by LC-MS/MS using artificial whole blood calibration and chemical derivatization.

Talanta
While the biological function of the 3α epimer of 25-hydroxyvitamin D (25(OH)D) remains unknown, its presence needs to be accurately captured and separated from the main 3β epimer, to avoid positive bias in vitamin D status analyses. Several recent L...

Application of fuzzy neural networks for modeling of biodegradation and biogas production in a full-scale internal circulation anaerobic reactor.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
This paper presents the development and evaluation of three fuzzy neural network (FNN) models for a full-scale anaerobic digestion system treating paper-mill wastewater. The aim was the investigation of feasibility of the approach-based control syste...

Versatile Soft Grippers with Intrinsic Electroadhesion Based on Multifunctional Polymer Actuators.

Advanced materials (Deerfield Beach, Fla.)
A highly versatile soft gripper that can handle an unprecedented range of object types is developed based on a new design of dielectric elastomer actuators employing an interdigitated electrode geometry, simultaneously maximizing both electroadhesion...

Machine learning classification of quorum sensing-induced bacterial aggregation using flow rate assays on paper chips toward bacterial species identification in potable water sources.

Biosensors & bioelectronics
Preventing waterborne disease caused by bacteria is especially important in low-resource settings, where skilled personnel and laboratory equipment are scarce. This work reports a straightforward method for classifying bacterial species by monitoring...

ML-UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper.

Physiological reports
The void spot assay has gained popularity as a way of assessing functional bladder voiding parameters in mice, but analyzing the size and distribution of urine spot patterns on filter paper with software remains problematic due to inter-laboratory di...