5,789 research outputs found
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
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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
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