Network and psychological effects in urban movement

Correlations are regularly found in space syntax studies between graph-based configurational measures of street networks, represented as lines, and observed movement patterns. This suggests that topological and geometric complexity are critically involved in how people navigate urban grids. This has caused difficulties with orthodox urban modelling, since it has always been assumed that insofar as spatial factors play a role in navigation, it will be on the basis of metric distance. In spite of much experimental evidence from cognitive science that geometric and topological factors are involved in navigation, and that metric distance is unlikely to be the best criterion for navigational choices, the matter has not been convincingly resolved since no method has existed for extracting cognitive information from aggregate flows. Within the space syntax literature it has also remained unclear how far the correlations that are found with syntactic variables at the level of aggregate flows are due to cognitive factors operating at the level of individual movers, or they are simply mathematically probable network effects, that is emergent statistical effects from the structure of line networks, independent of the psychology of navigational choices. Here we suggest how both problems can be resolved, by showing three things: first, how cognitive inferences can be made from aggregate urban flow data and distinguished from network effects; second by showing that urban movement, both vehicular and pedestrian, are shaped far more by the geometrical and topological properties of the grid than by its metric properties; and third by demonstrating that the influence of these factors on movement is a cognitive, not network, effect

Backflow and dissipation during the quantum decay of a metastable Fermi liquid

The particle current in a metastable Fermi liquid against a first-order phase transition is calculated at zero temperature. During fluctuations of a droplet of the stable phase, in accordance with the conservation law, not only does an unperturbed current arise from the continuity at the boundary, but a backflow is induced by the density response. Quasiparticles carrying these currents are scattered by the boundary, yielding a dissipative backflow around the droplet. An energy of the hydrodynamic mass flow of the liquid and a friction force exerted on the droplet by the quasiparticles have been obtained in terms of a potential of their interaction with the droplet.Comment: 5 pages (REVTeX), to be published in Phys. Rev.

The Nagoya cosmic-ray muon spectrometer 3, part 2: Track detector

The twelve wide gap spark chambers were utilized as the track detectors of the Nagoya cosmic-ray muon spectrometer not only to obtain the precise locations of particles, but also to get some information about the correspondences between segments of trajectories. The area of each chamber is 150 x 70 sq cm and the width of a gap is 5 cm. The gas used is He at the atmospheric pressure. Each three pairs of them are placed on both sides of the deflection magnet. All images of sparks for each event are projected through the mirror system and recorded by two cameras stereoscopically. The mean detection efficiency of each chamber is 95 + or - 2% and the spacial resolution (jitter and drift) obtained from the prototype-experiment is 0.12 mm. Maximum detectable momentum of the spectrometer is estimated at about 10 TeV/c taking into account these characteristics together with the effects of the energy loss and multiple Coulomb scattering of muons in the iron magnet

Simulation, Learning and Control Methods to Improve Robotic Vegetable Harvesting

Agricultural robots are subject to a much harsher envi- ronment than those in the factory or lab and control strategies need to take this into account while maintaining a low cycle time. Three control strategies were tested on Vegebot, a lettuce-picking robot, in both simulation and on the real robot. Between a fast open loop that was vulnerable to environmental noise and a slow but robust visual servoing technique, a Learned Open Loop strategy was tested where the robot learned from successful picks to pick at an intermediate speed. This reduced the projected cycle time from 31s to 17.2s, a 45% reduction.This project was possible thanks to EPSRC Grant EP/L015889/1, the Royal Society ERA Foundation Translation Award (TA160113), EPSRC Doctoral Training Program ICASE AwardRG84492 (cofunded by G’s Growers), EPSRC Small Partnership AwardRG86264 (in collaboration with G’s Growers), and the BBSRC Small Partnership GrantRG81275. Special thanks to G Growers, George Walker and Josie Hughes for their invaluable assistance