ABSTRACT
Toward the future goal of creating a lung surgery system featuring multiple tentacle-like robots, we present a new folding concept for continuum robots that enables them to squeeze through openings smaller than the robot's nominal diameter (e.g., the narrow space between adjacent ribs). This is facilitated by making the disks along the robot's backbone foldable. We also demonstrate that such a robot can feature not only straight, but also curved tendon routing paths, thereby achieving a diverse family of conformations. We find that the foldable robot performs comparably, from a kinematic perspective, to an identical non-folding continuum robot at varying deployment lengths. This work paves the way for future applications with a continuum robot that can fold and fit through smaller openings, with the potential to reduce invasiveness during surgical tasks.
ABSTRACT
Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers.
Subject(s)
Bacteria/growth & development , Computer Simulation , Models, Biological , Food Microbiology , Water MicrobiologyABSTRACT
Microbial life on plant leaves is characterized by a multitude of interactions between leaf colonizers and their environment. While the existence of many of these interactions has been confirmed, their spatial scale or reach often remained unknown. In this study, we applied spatial point pattern analysis to 244 distribution patterns of Pantoea agglomerans and Pseudomonas syringae on bean leaves. The results showed that bacterial colonizers of leaves interact with their environment at different spatial scales. Interactions among bacteria were often confined to small spatial scales up to 5-20 µm, compared to interactions between bacteria and leaf surface structures such as trichomes which could be observed in excess of 100 µm. Spatial point-pattern analyses prove a comprehensive tool to determine the different spatial scales of bacterial interactions on plant leaves and will help microbiologists to better understand the interplay between these interactions.