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The transfer of mean momentum from surface gravity waves to Eulerian mean fluxes is investigated by modeling the total wave momentum (the Stokes flux) as a thin surface layer moving with the phase speed c of the waves and with a thickness Z derived from the divergence effect. The bulk of the fluid receiving momentum from the waves is modeled by a rigid lower layer acted upon by the virtual wave stress, where the latter is related to the form stress from the wind and the time rate of change in Z through −cdZ/dt. In addition, the effects of surface wind and bottom stress are included in the model. Through the combination with measurements, this robust model may yield information about the Eulerian fluxes when the ocean surface is covered by a combination of ice and oil, and the constitutive equations for the surface cover are not easily obtained. [ABSTRACT FROM AUTHOR]

Using the principle of permutational duality as well as the analogical approach of both electrical and magnetic dipoles, it is possible to obtain a new relativistic magnetic type vector potential of an arbitrarily moving electric point dipole. The specific cases of the magnetic vector potential in the calculation of fields have been considered, and the obtained results have been compared with the research of other scholars. [ABSTRACT FROM AUTHOR]

Resistance in neuromorphic nanowire networks can be decreased when activated by voltage as multiple pathways of low resistance interconnected nanowires form, increasing nanowire to nanowire connectivity. We show that high connectivity regions are retained for a few minutes after the energy source is switched off. We have used this property to devise an associative device. With a multielectrode array, we send current through the network to connect together areas that are spatially associated with a given electrode combination forming a pattern. We correctly retrieve the stored patterns by passing a small current through the network at a later time even when we input a faulty or incomplete pattern as the network groups stored patterns into cluster of high associativity, in analogy with semantic memory association in the human brain. [ABSTRACT FROM AUTHOR]