8,880 research outputs found
Scalar arguments of the mathematical functions defining molecular and turbulent transport of heat and mass in compressible fluids
The advection–diffusion equations defining control volume conservation laws in micrometeorological research are analysed to resolve discrepancies in their appropriate scalar variables for heat and mass transport. A scalar variable that is conserved during vertical motions enables the interpretation of turbulent mixing as ‘diffusion’. Gas-phase heat advection is shown to depend on gradients in the potential temperature (θ), not the temperature (T). Since conduction and radiation depend on T, advection–diffusion of heat depends on gradients of both θ and T. Conservation of θ (the first Law of Thermodynamics) requires including a pressure covariance term in the definition of the turbulent heat flux. Mass advection and diffusion are universally agreed to depend directly on gradients in the gas ‘concentration’ (c), a nonetheless ambiguous term. Depending upon author, c may be defined either as a dimensionless proportion or as a dimensional density, with non-trivial differences for the gas phase. Analyses of atmospheric law, scalar conservation and similarity theory demonstrate that mass advection–diffusion in gases depends on gradients, not in density but rather in a conserved proportion. Flux-tower researchers are encouraged to respect the meteorological tradition of writing conservation equations in terms of scalar variables that are conserved through simple air motions.The authors received funding support from Andalusian regional
government project GEOCARBO (P08-RNM-3721),
the National Institute for Agrarian Research and Technology
(INIA; SUM2006–00010-00–00), the Spanish flux-tower network
CARBORED-ES (Science Ministry project CGL2010-
22193-C04–02), and the European Commission collaborative
project GHG Europe (FP7/2007-2013; grant agreement
244122)
Extending Feynman's Formalisms for Modelling Human Joint Action Coordination
The recently developed Life-Space-Foam approach to goal-directed human action
deals with individual actor dynamics. This paper applies the model to
characterize the dynamics of co-action by two or more actors. This dynamics is
modelled by: (i) a two-term joint action (including cognitive/motivatonal
potential and kinetic energy), and (ii) its associated adaptive path integral,
representing an infinite--dimensional neural network. Its feedback adaptation
loop has been derived from Bernstein's concepts of sensory corrections loop in
human motor control and Brooks' subsumption architectures in robotics.
Potential applications of the proposed model in human--robot interaction
research are discussed.
Keywords: Psycho--physics, human joint action, path integralsComment: 6 pages, Late
A two step algorithm for learning from unspecific reinforcement
We study a simple learning model based on the Hebb rule to cope with
"delayed", unspecific reinforcement. In spite of the unspecific nature of the
information-feedback, convergence to asymptotically perfect generalization is
observed, with a rate depending, however, in a non- universal way on learning
parameters. Asymptotic convergence can be as fast as that of Hebbian learning,
but may be slower. Moreover, for a certain range of parameter settings, it
depends on initial conditions whether the system can reach the regime of
asymptotically perfect generalization, or rather approaches a stationary state
of poor generalization.Comment: 13 pages LaTeX, 4 figures, note on biologically motivated stochastic
variant of the algorithm adde
Collective pinning dynamics of charge-density waves in 1T-TaS 2
Using high-resolution x-ray scattering and x-ray photon correlation spectroscopy (XPCS), we have investigated the structure and dynamics of charge density wave (CDW) dynamics in pure and titanium-doped 1T-TaS 2. Time-averaged scattering measurements of pure and doped samples reveal that 1T-TaS 2 is a weakly pinned two-dimensional CDW system. Using XPCS, we find that after long anneals the CDW domain structure in the incommensurate phase is pinned and stable against spontaneous fluctuations thus rejecting phasons as spontaneous excitations in higher-dimensional CDW systems. By examining the dynamics of deeply quenched samples upon heating, we find that metastable CDW configurations collectively rearrange in a nonequilibrium manner. For nominally pure samples, we determine an energy barrier to relaxation of 4600 K that is considerably greater than that found for lower-dimensional CDW
Transverse Double-Spin Asymmetries for Muon Pair Production in pp-Collisions
We calculate the rapidity dependence of the transverse double-spin asymmetry
for the Drell-Yan process to next-to-leading order in the strong coupling.
Input transversity distributions are obtained by saturating the Soffer
inequality at a low hadronic mass scale. Results for the polarized BNL-RHIC
proton-proton collider and the proposed HERA-N fixed-target experiment are
presented, and the influence of the limited muon acceptance of the detectors on
measurements of the asymmetry is studied in detail.Comment: 7 pages including 5 figures; significantly shortened, to be published
in Phys. Rev.
Dynamics of Spreading of Small Droplets of Chainlike Molecules on Surfaces
Dynamics of spreading of small droplets on surfaces has been studied by the
molecular dynamics method. Simulations have been performed for mixtures of
solvent and dimer, and solvent and tetramer droplets. For solvent particles and
dimers, layering occurs leading to stepped droplet shapes. For tetramers such
shapes occur for relatively deep and strong surface potentials only. For wider
and more shallow potentials, more rapid spreading and rounded droplet shapes
occur. These results are in accordance with experimental data on small non -
volatile polymer droplets. PACS numbers: 68.10Gw, 05.70.Ln, 61.20.Ja, 68.45GdComment: to appear in Europhys. Letters (1994), Latex, 12 page
The conservation of energy-momentum and the mass for the graviton
In this work we give special attention to the bimetric theory of gravitation
with massive gravitons proposed by Visser in 1998. In his theory, a prior
background metric is necessary to take in account the massive term. Although in
the great part of the astrophysical studies the Minkowski metric is the best
choice to the background metric, it is not possible to consider this metric in
cosmology. In order to keep the Minkowski metric as background in this case, we
suggest an interpretation of the energy-momentum conservation in Visser's
theory, which is in accordance with the equivalence principle and recovers
naturally the special relativity in the absence of gravitational sources.
Although we do not present a general proof of our hypothesis we show its
validity in the simple case of a plane and dust-dominated universe, in which
the `massive term' appears like an extra contribution for the energy density.Comment: 9 pages, accepted for publishing in GR
Transition from tunneling to direct contact in tungsten nanojunctions
We apply the mechanically controllable break junctions technique to
investigate the transition from tunneling to direct contact in tungsten. This
transition is quite different from that of other metals and is determined by
the local electronic properties of the tungsten surface and the relief of the
electrodes at the point of their closest proximity. The conductance traces show
a rich variety of patterns from the avalanche-like jump to a mesoscopic contact
to the completely smooth transition between direct contact and tunneling. Due
to the occasional absence of an adhesive jump the conductance of the contact
can be continuously monitored at ultra-small electrode separations. The
conductance histograms of tungsten are either featureless or show two distinct
peaks related to the sequential opening of spatially separated groups of
conductance channels. The role of surface states of tungsten and their
contribution to the junction conductance at sub-Angstrom electrode separations
are discussed.Comment: 6 pages, 6 figure
The Challenge of Machine Learning in Space Weather Nowcasting and Forecasting
The numerous recent breakthroughs in machine learning (ML) make imperative to
carefully ponder how the scientific community can benefit from a technology
that, although not necessarily new, is today living its golden age. This Grand
Challenge review paper is focused on the present and future role of machine
learning in space weather. The purpose is twofold. On one hand, we will discuss
previous works that use ML for space weather forecasting, focusing in
particular on the few areas that have seen most activity: the forecasting of
geomagnetic indices, of relativistic electrons at geosynchronous orbits, of
solar flares occurrence, of coronal mass ejection propagation time, and of
solar wind speed. On the other hand, this paper serves as a gentle introduction
to the field of machine learning tailored to the space weather community and as
a pointer to a number of open challenges that we believe the community should
undertake in the next decade. The recurring themes throughout the review are
the need to shift our forecasting paradigm to a probabilistic approach focused
on the reliable assessment of uncertainties, and the combination of
physics-based and machine learning approaches, known as gray-box.Comment: under revie
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