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