1,584 research outputs found
Tungsten Behavior at High Temperature and High Stress
Recently reported results on the tungsten lifetime/fatigue tests under conditions expected in the Neutrino Factory target have strengthened the case of solid target option for a Neutrino Factory. This paper gives description of the detailed measurements of the tungsten properties at high temperature and high stress. We have performed extensive set of measurements of the surface displacement and velocity of the tungsten wires that were stressed by passing a fast, high current pulse through a thin sample. Radial and longitudinal oscillations of the wire were measured by a Laser Doppler Vibrometer. The wire was operated at temperatures of 300-2500 K by adjusting the pulse repetition rate. In doing so we have tried to simulate the conditions (high stress and temperature) expected at the Neutrino Factory. Most important result of this study is an experimental confirmation that strength of tungsten remains high at high temperature and high stress. The experimental results have been found to agree very well with LS-DYNA modelling results
Plasticity and learning in a network of coupled phase oscillators
A generalized Kuramoto model of coupled phase oscillators with slowly varying
coupling matrix is studied. The dynamics of the coupling coefficients is driven
by the phase difference of pairs of oscillators in such a way that the coupling
strengthens for synchronized oscillators and weakens for non-synchronized
pairs. The system possesses a family of stable solutions corresponding to
synchronized clusters of different sizes. A particular cluster can be formed by
applying external driving at a given frequency to a group of oscillators. Once
established, the synchronized state is robust against noise and small
variations in natural frequencies. The phase differences between oscillators
within the synchronized cluster can be used for information storage and
retrieval.Comment: 10 page
The association between driving time and unhealthy lifestyles: a cross-sectional, general population study of 386 493 UK Biobank participants
Background:
Driving is a common type of sedentary behaviour; an independent risk factor for poor health. The study explores whether driving is also associated with other unhealthy lifestyle factors.
Methods:
In a cross-sectional study of UK Biobank participants, driving time was treated as an ordinal variable and other lifestyle factors dichotomized into low/high risk based on guidelines. The associations were explored using chi-square tests for trend and binary logistic regression.
Results:
Of the 386 493 participants who drove, 153 717 (39.8%) drove <1 h/day; 140 140 (36.3%) 1 h/day; 60 973 (15.8%) 2 h/day; and 31 663 (8.2%) ≥3 h/day. Following adjustment for potential confounders, driving ≥3 h/day was associated with being overweight/obese (OR = 1.74, 95% CI: 1.64–1.85), smoking (OR = 1.48, 95% CI: 1.37–1.63), insufficient sleep (1.70, 95% CI: 1.61–1.80), low fruit/vegetable intake (OR = 1.26, 95% CI: 1.18–1.35) and low physical activity (OR = 1.05, 95% CI: 1.00–1.11), with dose relationships for the first three, but was not associated with higher alcohol consumption (OR = 0.94, 95% CI: 0.87–1.02).
Conclusions:
Sedentary behaviour, such as driving, is known to have an independent association with adverse health outcomes. It may have additional impact mediated through its effect on other aspects of lifestyle. People with long driving times are at higher risk and might benefit from targeted interventions
Dynamical mean-field theory of spiking neuron ensembles: response to a single spike with independent noises
Dynamics of an ensemble of -unit FitzHugh-Nagumo (FN) neurons subject to
white noises has been studied by using a semi-analytical dynamical mean-field
(DMF) theory in which the original -dimensional {\it stochastic}
differential equations are replaced by 8-dimensional {\it deterministic}
differential equations expressed in terms of moments of local and global
variables. Our DMF theory, which assumes weak noises and the Gaussian
distribution of state variables, goes beyond weak couplings among constituent
neurons. By using the expression for the firing probability due to an applied
single spike, we have discussed effects of noises, synaptic couplings and the
size of the ensemble on the spike timing precision, which is shown to be
improved by increasing the size of the neuron ensemble, even when there are no
couplings among neurons. When the coupling is introduced, neurons in ensembles
respond to an input spike with a partial synchronization. DMF theory is
extended to a large cluster which can be divided into multiple sub-clusters
according to their functions. A model calculation has shown that when the noise
intensity is moderate, the spike propagation with a fairly precise timing is
possible among noisy sub-clusters with feed-forward couplings, as in the
synfire chain. Results calculated by our DMF theory are nicely compared to
those obtained by direct simulations. A comparison of DMF theory with the
conventional moment method is also discussed.Comment: 29 pages, 2 figures; augmented the text and added Appendice
The stellar mass ratio of GK Persei
We study the absorption lines present in the spectra of the long-period
cataclysmic variable GK Per during its quiescent state, which are associated
with the secondary star. By comparing quiescent data with outburst spectra we
infer that the donor star appears identical during the two states and the inner
face of the secondary star is not noticeably irradiated by flux from the
accreting regions. We obtain new values for the radial velocity semi-amplitude
of the secondary star, Kk = 120.5 +- 0.7 km/s, a projected rotational velocity,
Vksin i = 61.5 +- 11.8 km/s and consequently a measurement of the stellar mass
ratio of GK Per, q = Mk/Mwd = 0.55 +- 0.21. The inferred white dwarf radial
velocities are greater than those measured traditionally using the wings of
Doppler-broadened emission lines suspected to originate in an accretion disk,
highlighting the unsuitability of emission lines for mass determinations in
cataclysmic variables. We determine mass limits for both components in the
binary, Mk >= 0.48 +- 0.32 Msolar and Mwd >= 0.87 +- 0.24 Msolar.Comment: 8 pages, 8 figures, accepted by MNRA
Quantization and Compressive Sensing
Quantization is an essential step in digitizing signals, and, therefore, an
indispensable component of any modern acquisition system. This book chapter
explores the interaction of quantization and compressive sensing and examines
practical quantization strategies for compressive acquisition systems.
Specifically, we first provide a brief overview of quantization and examine
fundamental performance bounds applicable to any quantization approach. Next,
we consider several forms of scalar quantizers, namely uniform, non-uniform,
and 1-bit. We provide performance bounds and fundamental analysis, as well as
practical quantizer designs and reconstruction algorithms that account for
quantization. Furthermore, we provide an overview of Sigma-Delta
() quantization in the compressed sensing context, and also
discuss implementation issues, recovery algorithms and performance bounds. As
we demonstrate, proper accounting for quantization and careful quantizer design
has significant impact in the performance of a compressive acquisition system.Comment: 35 pages, 20 figures, to appear in Springer book "Compressed Sensing
and Its Applications", 201
Comparison of s- and d-wave gap symmetry in nonequilibrium superconductivity
Recent application of ultrafast pump/probe optical techniques to
superconductors has renewed interest in nonequilibrium superconductivity and
the predictions that would be available for novel superconductors, such as the
high-Tc cuprates. We have reexamined two of the classical models which have
been used in the past to interpret nonequilibrium experiments with some
success: the mu* model of Owen and Scalapino and the T* model of Parker.
Predictions depend on pairing symmetry. For instance, the gap suppression due
to excess quasiparticle density n in the mu* model, varies as n^{3/2} in d-wave
as opposed to n for s-wave. Finally, we consider these models in the context of
S-I-N tunneling and optical excitation experiments. While we confirm that
recent pump/probe experiments in YBCO, as presently interpreted, are in
conflict with d-wave pairing, we refute the further claim that they agree with
s-wave.Comment: 14 pages, 11 figure
Synchronization and resonance in a driven system of coupled oscillators
We study the noise effects in a driven system of globally coupled
oscillators, with particular attention to the interplay between driving and
noise. The self-consistency equation for the order parameter, which measures
the collective synchronization of the system, is derived; it is found that the
total order parameter decreases monotonically with noise, indicating overall
suppression of synchronization. Still, for large coupling strengths, there
exists an optimal noise level at which the periodic (ac) component of the order
parameter reaches its maximum. The response of the phase velocity is also
examined and found to display resonance behavior.Comment: 17 pages, 3 figure
Linear stability analysis of retrieval state in associative memory neural networks of spiking neurons
We study associative memory neural networks of the Hodgkin-Huxley type of
spiking neurons in which multiple periodic spatio-temporal patterns of spike
timing are memorized as limit-cycle-type attractors. In encoding the
spatio-temporal patterns, we assume the spike-timing-dependent synaptic
plasticity with the asymmetric time window. Analysis for periodic solution of
retrieval state reveals that if the area of the negative part of the time
window is equivalent to the positive part, then crosstalk among encoded
patterns vanishes. Phase transition due to the loss of the stability of
periodic solution is observed when we assume fast alpha-function for direct
interaction among neurons. In order to evaluate the critical point of this
phase transition, we employ Floquet theory in which the stability problem of
the infinite number of spiking neurons interacting with alpha-function is
reduced into the eigenvalue problem with the finite size of matrix. Numerical
integration of the single-body dynamics yields the explicit value of the
matrix, which enables us to determine the critical point of the phase
transition with a high degree of precision.Comment: Accepted for publication in Phys. Rev.
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