Average Lattice Symmetry and Nanoscale Structural Correlations in Magnetoresistive Manganites

We report x-ray scattering studies of nanoscale structural correlations in the paramagnetic phases of the perovskite manganites La$_{0.75}$(Ca$_{0.45}$Sr$_{0.55}$)$_{0.25}$MnO$_3$, La$_{0.625}$Sr$_{0.375}$MnO$_3$, and Nd$_{0.45}$Sr$_{0.55}$MnO$_3$. We find that these correlations are present in the orthorhombic $O$ phase in La$_{0.75}$(Ca$_{0.45}$Sr$_{0.55}$)$_{0.25}$MnO$_3$, but they disappear abruptly at the orthorhombic-to-rhombohedral transition in this compound. The orthorhombic phase exhibits increased electrical resistivity and reduced ferromagnetic coupling, in agreement with the association of the nanoscale correlations with insulating regions. In contrast, the correlations were not detected in the two other compounds, which exhibit rhombohedral and tetragonal phases. Based on these results, as well as on previously published work, we propose that the local structure of the paramagnetic phase correlates strongly with the average lattice symmetry, and that the nanoscale correlations are an important factor distinguishing the insulating and the metallic phases in these compounds.Comment: a note on recent experimental work, and a new reference adde

Pulsar-wind nebulae and magnetar outflows: observations at radio, X-ray, and gamma-ray wavelengths

We review observations of several classes of neutron-star-powered outflows: pulsar-wind nebulae (PWNe) inside shell supernova remnants (SNRs), PWNe interacting directly with interstellar medium (ISM), and magnetar-powered outflows. We describe radio, X-ray, and gamma-ray observations of PWNe, focusing first on integrated spectral-energy distributions (SEDs) and global spectral properties. High-resolution X-ray imaging of PWNe shows a bewildering array of morphologies, with jets, trails, and other structures. Several of the 23 so far identified magnetars show evidence for continuous or sporadic emission of material, sometimes associated with giant flares, and a few possible "magnetar-wind nebulae" have been recently identified.Comment: 61 pages, 44 figures (reduced in quality for size reasons). Published in Space Science Reviews, "Jets and Winds in Pulsar Wind Nebulae, Gamma-ray Bursts and Blazars: Physics of Extreme Energy Release

Air-exposure behavior: a restricted or a common conduct among intertidal hermit crabs?

A new behavior related to shell care was recently reported for the intertidal hermit crab Clibanarius erythropus (Latreille, 1818) in the Gulf of Cádiz (southwestern Europe). It also has been observed in other species of the diogenid genera Clibanarius Dana, 1952, and Calcinus Dana, 1951, however, it has not been described as an active behavior. In the present study, intertidal hermit crabs from different species and localities were sampled to assess if air-exposure is a shell cleaning behavior restricted to some species of intertidal hermit crabs or if it is a more generalized behavior among species inhabiting intertidal habitats. The results revealed that air-exposure is an active behavior in species of Clibanarius and Calcinus, since we observed it also in Clibanarius albidigitus Nobili, 1901, and Calcinus obscurus Stimpson, 1859, from the Pacific coast of Costa Rica, although not in other intertidal species studied by us. We found interspecific differences in tolerance to physical stress of emerged hermit crabs. This air-exposure tolerance can be interpreted as a physiological adaptation to desiccation stress and is also related to the shell type they inhabit. Also, we provide additional features and details of the air-exposure behavior, combining observations of the first description in 2015 with our new field observations.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Ciencias del Mar y Limnología (CIMAR)UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Biologí

Dust in Supernovae and Supernova Remnants II: Processing and survival

Observations have recently shown that supernovae are efficient dust factories, as predicted for a long time by theoretical models. The rapid evolution of their stellar progenitors combined with their efficiency in precipitating refractory elements from the gas phase into dust grains make supernovae the major potential suppliers of dust in the early Universe, where more conventional sources like Asymptotic Giant Branch (AGB) stars did not have time to evolve. However, dust yields inferred from observations of young supernovae or derived from models do not reflect the net amount of supernova-condensed dust able to be expelled from the remnants and reach the interstellar medium. The cavity where the dust is formed and initially resides is crossed by the high velocity reverse shock which is generated by the pressure of the circumstellar material shocked by the expanding supernova blast wave. Depending on grain composition and initial size, processing by the reverse shock may lead to substantial dust erosion and even complete destruction. The goal of this review is to present the state of the art about processing and survival of dust inside supernova remnants, in terms of theoretical modelling and comparison to observations

Weakly supervised power line detection algorithm using a recursive noisy label update with refined broken line segments

Detection of power lines in aerial images is an important problem to prevent accidents of unmanned aerial vehicles operating at low altitudes in the electrical industry. Recently, pixel-level power line detection using deep learning has been studied but production of the pixel-level annotations for massive dataset is difficult. In this study, we propose a power line detection algorithm using weakly supervised learning method to reduce the labeling cost for dataset generation. The algorithm is divided into two stages. First, an approximately localized mask was generated based on a convolutional neural network which was trained with only patch-level labels. Second, recursive training of segmentation network with refined broken line segments was executed. A refinement algorithm, line segment connecting (LSC) is a power-line-specialized refinement module that connects broken lines by approximating the segments as partially straight. In proposed algorithm, predicted image at each recursive step was updated as a label of the next training and the label was developed by itself with LSC. The comprehensive experimental results of our algorithm showed state-of-art F1-score of 94.3% in weakly supervised learning approaches on public dataset. This result suggests that the proposed algorithm is useful for low labeling cost with high performance in line detection application. © 2020 Elsevier Ltd1