On the consequences of the uncertainty principle on the superconducting fluctuations well inside the normal state

We first argue that the collective behaviour of the Cooper pairs created by thermal fluctuations well above the superconducting transition temperature, Tc, is dominated by the uncertainty principle which, in particular, leads to a well-defined temperature, T^C, above which the superconducting coherence vanishes. On the grounds of the BCS approach, the corresponding reduced-temperature, ln(T^C/Tc), is estimated to be around 0.55, i.e., above T^C \approx 1.7Tc coherent Cooper pairs cannot exist. The implications of these proposals on the superfluid density are then examined using the Gaussian-Ginzburg-Landau approximation. Then we present new measurements of the thermal fluctuation effects on the electrical conductivity and on the magnetization in different low- and high-Tc superconductors with different dopings which are in excellent agreement with these proposals and that demonstrate the universality of ln(T^C/Tc).Comment: LaTeX, 10 pages, 3 figures, as published in Europhysics Letter

Nitrogen and phosphorus in Ulva sp. in the Galician Rias Bajas (northwest Spain): Seasonal fluctuations and influence on growth

Coastal eutrophication has given cause for increasing concern. The Galician rias are ecosystems very sensitive to this phenomenon. In the present paper, we evaluate the possible nutrient limitation in Ulva sp., a green-tide alga. Variations in tissue nitrogen (N) and phosphorus (P), as well as growth rate, were determined over a complete seasonal cycle for Ulva sp. collected in the Rias Bajas (northwest Spain). Minimum levels of both nutrients were reached in spring and summer and maximum in winter. The low tissue P concentrations were striking. There was a parallelism between the evolution of the growth rate and nutrient contents. The most significant correlation found between growth rate and tissue P, and the equations established by stepwise multiple regression procedures, suggest that P may play a more important role than N in the limitation of productivity of Ulva sp. in the Galician Rias Bajas.La eutrofización costera es un problema de creciente preocupación y las rías gallegas son ecosistemas sensibles a este fenómeno. En este trabajo se intenta evaluar la posible limitación nutritiva en Ulva sp., un alga que forma parte de las denominadas mareas verdes. Se realizaron análisis de nitrógeno (N) y fósforo (P), así como bioensayos de crecimiento en Ulva sp. recogida mensualmente en cuatro rías de la costa gallega durante un año. Los niveles mínimos de ambos nutrientes se registraron en primavera y verano y los máximos en invierno, destacando las bajas concentraciones de P encontradas. Se observó un paralelismo entre la evolución de las tasas de crecimiento de Ulva y las concentraciones de nutrientes en el talo a lo largo del ciclo anual estudiado. La mayor correlación encontrada entre tasa de crecimiento y concentración de P, y las ecuaciones establecidas por el procedimiento de regresión múltiple paso a paso, indican que el fósforo parece jugar un papel más importante que el nitrógeno en la producción de Ulva sp. en las rías bajas gallegas.Instituto Español de Oceanografí

Comment on "High Field Studies of Superconducting Fluctuations in High-Tc Cuprates. Evidence for a Small Gap distinct from the Large Pseudogap"

By using high magnetic field data to estimate the background conductivity, Rullier-Albenque and coworkers have recently published [Phys.Rev.B 84, 014522 (2011)] experimental evidence that the in-plane paraconductivity in cuprates is almost independent of doping. In this Comment we also show that, in contrast with their claims, these useful data may be explained at a quantitative level in terms of the Gaussian-Ginzburg-Landau approach for layered superconductors, extended by Carballeira and coworkers to high reduced-temperatures by introducing a total-energy cutoff [Phys.Rev.B 63, 144515 (2001)]. When combined, these two conclusions further suggest that the paraconductivity in cuprates is conventional, i.e., associated with fluctuating superconducting pairs above the mean-field critical temperature.Comment: 9 pages, 1 figur

People detection with omnidirectional cameras using aspatial grid ofdeep learning foveatic classifiers

A novel deep-learning people detection algorithm using omnidirectional cameras is presented, which only requires point-based annotations, unlike most of the prominent works that require bounding box annotations. Thus, the effort of manually annotating the needed training databases is significantly reduced, allowing a faster system deployment. The algorithm is based on a novel deep neural network architecture that implements the concept of Grid of Spatial-Aware Classifiers, but allowing end-to-end training that improves the performance of the whole system. The designed algorithm satisfactorily handles the severe geometric distortions of the omnidirectional images, which typically degrades the performance of state-of-the-art detectors, without requiring any camera calibration. The algorithm has been evaluated in well-known omnidirectional image databases (PIROPO, BOMNI, and MW-18Mar) and compared with several works of the state of the art.This work has been partially supported by project PID2020115132RB (SARAOS) funded by MCIN/AEI/10.13039/501100011033 of the Spanish Government

Non-ohmic critical fluctuation conductivity of layered superconductors in magnetic field

Thermal fluctuation conductivity for a layered superconductor in perpendicular magnetic field is treated in the frame of the self-consistent Hartree approximation for an arbitrarily strong in-plane electric field. The simultaneous application of the two fields results in a slightly stronger suppression of the superconducting fluctuations, compared to the case when the fields are applied individually.Comment: 4 pages, 1 figure, to be published in Phys. Rev.

Autocalibration with the Minimum Number of Cameras with Known Pixel Shape

In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforcing simple constraints on the camera parameters. In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint. Given a projective reconstruction of a rigid scene, we address the problem of the autocalibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. We propose an algorithm that only requires 5 cameras (the theoretical minimum), thus halving the number of cameras required by previous algorithms based on the same constraint. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisting in the set of planes intersecting six given lines of 3D space in points of a conic. We show that the set of solutions of the Euclidean upgrading problem for three cameras with known pixel shape can be parameterized in a computationally efficient way. This parameterization is then used to solve autocalibration from five or more cameras, reducing the three-dimensional search space to a two-dimensional one. We provide experiments with real images showing the good performance of the technique.Comment: 19 pages, 14 figures, 7 tables, J. Math. Imaging Vi

The in-plane paraconductivity in La_{2-x}Sr_xCuO_4 thin film superconductors at high reduced-temperatures: Independence of the normal-state pseudogap

The in-plane resistivity has been measured in $La_{2-x}Sr_xCuO_4$ (LSxCO) superconducting thin films of underdoped ($x=0.10,0.12$), optimally-doped ($x=0.15$) and overdoped ($x=0.20,0.25$) compositions. These films were grown on (100)SrTiO$_3$ substrates, and have about 150 nm thickness. The in-plane conductivity induced by superconducting fluctuations above the superconducting transition (the so-called in-plane paraconductivity, $\Delta\sigma_{ab}$) was extracted from these data in the reduced-temperature range 10^{-2}\lsim\epsilon\equiv\ln(T/\Tc)\lsim1. Such a $\Delta\sigma_{ab}(\epsilon)$ was then analyzed in terms of the mean-field--like Gaussian-Ginzburg-Landau (GGL) approach extended to the high-$\epsilon$ region by means of the introduction of a total-energy cutoff, which takes into account both the kinetic energy and the quantum localization energy of each fluctuating mode. Our results strongly suggest that at all temperatures above Tc, including the high reduced-temperature region, the doping mainly affects in LSxCO thin films the normal-state properties and that its influence on the superconducting fluctuations is relatively moderate: Even in the high-$\epsilon$ region, the in-plane paraconductivity is found to be independent of the opening of a pseudogap in the normal state of the underdoped films.Comment: 35 pages including 10 figures and 1 tabl