The Attraction-Repulsion Model set with a long-range attraction and short-range repulsion interaction potential typically stabilizes to a well-studied flock steady state solution. The particles for a flock remain spatially coherent but have no spatial bound and explore all space. A bounded domain with specularly reflecting walls traps the particles within a specific region. A fundamental refraction law for a swarm impacting on a planar boundary is derived. The swarm reflection varies from specular for a swarm dominated by
kinetic energy to inelastic for a swarm dominated by potential energy. Inelastic collisions lead to alignment with the wall and to damped pulsating oscillations of the swarm. The fundamental refraction law provides a one-dimensional iterative map that allows for a prediction and analysis of the trajectory of the center of mass of a flock in a channel and a square domain.
The extension of the wall collisions to a scattering experiment is conducted by setting two identical flocks to collide. The two particle dynamics is studied analytically and shows a transition from scattering: diverging flocks to bound states in the form of oscillations or parallel motions. Numerical studies of collisions of flocks show the same transition where the bound states become either a single translating flock or a rotating (mill).
Single molecule FRET experiments are important for studying processes that happen on the molecular scale. By using pulsed illumination and collecting single photons, it is possible to use information gained from the fluorescence lifetime of the chromophores in the FRET pair to gain more accurate estimates of the underlying FRET rate which is used to determine information about the distance between the chromophores of the FRET pair. In this paper, we outline a method that utilizes Bayesian inference to learn parameter values for a model informed by the physics of a immobilized single-molecule FRET experiment. This method is unique in that it combines a rigorous look at the photophysics of the FRET pair and a nonparametric treatment of the molecular conformational statespace, allowing the method to learn not just relevant photophysical rates (such as relaxation rates and FRET rates), but also the number of molecular conformational states.
A statistical method is proposed to learn what the diffusion coefficient is at any point in space of a cell membrane. The method used bayesian non-parametrics to learn this value. Learning the diffusion coefficient might be useful for understanding more about cellular dynamics.
Bdellovibrio bacteriovorus (B. bacteriovorus) is a predatory bacterium that preys on other gram-negative bacteria. In order to survive and reproduce, B. bacteriovorus invades the periplasm of other bacterial cells creating the potential for it to act as a “living antibiotic”. In this work, a comparison was made between the rates of predation of B. bacteriovorus in vitro and in vivo. In vitro, the behavior of B. bacteriovorus was examined in the presence of prey. In vivo, the behavior of B. bacteriovorus was examined in the presence of prey and a living host, Caenorhabditis elegans (C. elegans). C. elegans were infected with Escherichia coli (E. coli) and treated with B. bacteriovorus. In previous studies that analyzed B. bacteriovorus in vitro, a decrease in concentrations of bacteria has been observed after introduction of B. bacteriovorus. In vivo, B. bacteriovorus were found to not have a net reduction of E. coli but to reproducibly raise the level of fluctuations in E. coli concentrations.