Results 41 to 50 of about 16,579 (242)
Parallel Accelerated Virtual Physarum Lab Based on Cellular Automata Agents
IEEE Access, 2019 Self-aware and self-expressive physical systems are inspiring new methodologies for engineering solutions of complex computing problems. Among many other examples, the slime mold Physarum Polycephalum exhibits self-awareness and self-expressiveness while
Nikolaos I. Dourvas +2 more
doaj +1 more source
Fluid flows shaping organism morphology
, 2018 A dynamic self-organized morphology is the hallmark of network-shaped organisms like slime moulds and fungi. Organisms continuously re-organize their flexible, undifferentiated body plans to forage for food. Among these organisms the slime mould Physarum
Alim, Karen
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Engineered Protein‐Based Ionic Conductors for Sustainable Energy Storage Applications
Advanced Materials, EarlyView.Rational incorporation of charged residues into an engineered, self‐assembling protein scaffold yields solid‐state protein films with outstanding ionic conductivity. Salt‐doping further enhances conductivity, an effect amplified in the engineered variants. These properties enable the material integration into an efficient supercapacitor.
Juan David Cortés‐Ossa +14 more
wiley +1 more source
Chromatin Structure in the Cellular Slime Mold Dictyostelium discoideum [PDF]
, 1978 The structure of Dictyostelium discoideum chromatin has been studied by the following techniques: electron microscopy, staphylococcal nuclease digestion, acrylamide gel electrophoresis, sucrose gradient centrifugation, and melting.
Bakke, Antony C. +2 more
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Miniature Soft Robot With Magnetically Reprogrammable Surgical Functions
Advanced Materials, EarlyView.Miniature soft robots have great prospects to revolutionize minimally invasive treatments. Here we present a miniature soft robot, which can be reprogrammed to perform five surgical functionalities with six‐degrees‐of‐freedom motions. This soft robot can prospectively make minimally invasive surgery considerably safer and painless, and enable ...
Chelsea Shan Xian Ng +4 more
wiley +1 more source
Slime mould solves maze in one pass ... assisted by gradient of chemo-attractants
, 2011 Plasmodium of Physarum polycephalum is a large cell, visible by unaided eye, which exhibits sophisticated patterns of foraging behaviour. The plasmodium's behaviour is well interpreted in terms of computation, where data are spatially extended ...
Adamatzky, Andrew
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The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?
Advanced Robotics Research, EarlyView.Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley +1 more source
A Slime Mold-Ant Colony Fusion Algorithm for Solving Traveling Salesman Problem
IEEE Access, 2020 The Ant Colony Optimization (ACO) is easy to fall into the local optimum and its convergence speed is slow in solving the Travelling Salesman Problem (TSP). Therefore, a Slime Mold-Ant Colony Fusion Algorithm (SMACFA) is proposed in this paper.
Meijiao Liu +7 more
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Engineering Microbial Particles for Next‐Generation Biomedical Platforms
Advanced Science, EarlyView.Microbe‐derived particles (MDPs), which include extracellular vesicles, outer membrane vesicles, inclusion bodies, polysaccharide particles, and virus‐like particles, represent a rapidly expanding category of bioinspired nanomaterials. With their natural origin, intrinsic biocompatibility, and highly programmable functionality, MDPs serve as a ...
Yuting Li +7 more
wiley +1 more source
Exploiting Environmental Computation in a Multi-Agent Model of Slime Mould
, 2015 Very simple organisms, such as the single-celled amoeboid slime mould Physarum polycephalum possess no neural tissue yet, despite this, are known to exhibit complex biological and computational behaviour.
Jones, Jeff
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