Anisotropic electrical resistivity of LaFeAsO: evidence for electronic nematicity

Single crystals of LaFeAsO were successfully grown out of KI flux. Temperature dependent electrical resistivity was measured with current flow along the basal plane, \rho_perpend(T), as well as with current flow along the crystallographic c-axis, \rho_parallel(T), the latter one utilizing electron beam lithography and argon ion beam milling. The anisotropy ratio was found to lie between \rho_parallel/\rho_perpend = 20 - 200. The measurement of \rho_perpend(T) was performed with current flow along the tetragonal [1 0 0] direction and along the [1 1 0] direction and revealed a clear in-plane anisotropy already at T \leq 175 K. This is significantly above the orthorhombic distortion at T_0 = 147 K and indicates the formation of an electron nematic phase. Magnetic susceptibility and electrical resistivity give evidence for a change of the magnetic structure of the iron atoms from antiferromagnetic to ferromagnetic arrangement along the c-axis at T^\ast = 11 K.Comment: 10 pages, 6 figures, minor change

Rapidité de la vitesse d'altération des minéraux du sol en conditions ferrallitiques : méthode des minéraux-test

Les minéraux des sols sont soumis à des dissolutions et reprécipitations en fonction des conditions de milieu, et en particulier de l'activité biologique. Pour déterminer la cinétique des réactions mises en jeu dans le recyclage des éléments chimiques, des sachets de minéraux test contenant séparément de la gibbsite, deux types de kaolinite et un verre siliceux, ont été introduits dans les horizons supérieurs d'un sol ferrallitique de forêt amazonienne. Au bout de 6 mois, toutes les phases implantées ont été altérées, et d'autres minéraux, oxy-hydroxydes de fer et de titane, sont apparus. La réactivité des minéraux secondaires avec les conditions de milieu est donc rapide à l'échelle des temps pédologiques dans les sols étudiés. (Résumé d'auteur

AB2CD: AI for Building Climate Damage Classification and Detection

We explore the implementation of deep learning techniques for precise building damage assessment in the context of natural hazards, utilizing remote sensing data. The xBD dataset, comprising diverse disaster events from across the globe, serves as the primary focus, facilitating the evaluation of deep learning models. We tackle the challenges of generalization to novel disasters and regions while accounting for the influence of low-quality and noisy labels inherent in natural hazard data. Furthermore, our investigation quantitatively establishes that the minimum satellite imagery resolution essential for effective building damage detection is 3 meters and below 1 meter for classification using symmetric and asymmetric resolution perturbation analyses. To achieve robust and accurate evaluations of building damage detection and classification, we evaluated different deep learning models with residual, squeeze and excitation, and dual path network backbones, as well as ensemble techniques. Overall, the U-Net Siamese network ensemble with F-1 score of 0.812 performed the best against the xView2 challenge benchmark. Additionally, we evaluate a Universal model trained on all hazards against a flood expert model and investigate generalization gaps across events, and out of distribution from field data in the Ahr Valley. Our research findings showcase the potential and limitations of advanced AI solutions in enhancing the impact assessment of climate change-induced extreme weather events, such as floods and hurricanes. These insights have implications for disaster impact assessment in the face of escalating climate challenges.Comment: 9 pages, 4 figure

Thermoacoustic effects in supercritical fluids near the critical point: Resonance, piston effect, and acoustic emission and reflection

We present a general theory of thermoacoustic phenomena in supercritical fluids near the critical point in a one-dimensional cell. We take into account the effects of the heat conduction in the boundary walls and the bulk viscosity near the critical point. We introduce a coefficient $Z(\omega)$ characterizing reflection of sound with frequency $\omega$ at the boundary. As applications, we examine the acoustic eigenmodes in the cell, the response to time-dependent perturbations, sound emission and reflection at the boundary. Resonance and rapid adiabatic changes are noteworthy. In these processes, the role of the thermal diffusion layers is enhanced near the critical point because of the strong critical divergence of the thermal expansion.Comment: 15 pages, 7 figure

A practical multirobot localization system

We present a fast and precise vision-based software intended for multiple robot localization. The core component of the software is a novel and efficient algorithm for black and white pattern detection. The method is robust to variable lighting conditions, achieves sub-pixel precision and its computational complexity is independent of the processed image size. With off-the-shelf computational equipment and low-cost cameras, the core algorithm is able to process hundreds of images per second while tracking hundreds of objects with a millimeter precision. In addition, we present the method's mathematical model, which allows to estimate the expected localization precision, area of coverage, and processing speed from the camera's intrinsic parameters and hardware's processing capacity. The correctness of the presented model and performance of the algorithm in real-world conditions is verified in several experiments. Apart from the method description, we also make its source code public at \emph{http://purl.org/robotics/whycon}; so, it can be used as an enabling technology for various mobile robotic problems

A simple visual navigation system for an UAV

We present a simple and robust monocular camera-based navigation system for an autonomous quadcopter. The method does not require any additional infrastructure like radio beacons, artificial landmarks or GPS and can be easily combined with other navigation methods and algorithms. Its computational complexity is independent of the environment size and it works even when sensing only one landmark at a time, allowing its operation in landmark poor environments. We also describe an FPGA based embedded realization of the method’s most computationally demanding phase

Effects of Frontal Transcranial Direct Current Stimulation on Emotional State and Processing in Healthy Humans

The prefrontal cortex is involved in mood and emotional processing. In patients suffering from depression, the left dorsolateral prefrontal cortex (DLPFC) is hypoactive, while activity of the right DLPFC is enhanced. Counterbalancing these pathological excitability alterations by repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS) improves mood in these patients. In healthy subjects, however, rTMS of the same areas has no major effect, and the effects of tDCS are mixed. We aimed to evaluate the effects of prefrontal tDCS on emotion and emotion-related cognitive processing in healthy humans. In a first study, we administered excitability-enhancing anodal, excitability-diminishing cathodal, and placebo tDCS to the left DLPFC, combined with antagonistic stimulation of the right frontopolar cortex, and tested acute emotional changes by an adjective checklist. Subjective emotions were not influenced by tDCS. Emotional face identification, however, which was explored in a second experiment, was subtly improved by a tDCS-driven excitability modulation of the prefrontal cortex, markedly by anodal tDCS of the left DLPFC for positive emotional content. We conclude that tDCS of the prefrontal cortex improves emotion processing in healthy subjects, but does not influence subjective emotional state

Relations between teachers' goal orientations, their instructional practices and student motivation

Relations between teachers’ goal orientations, their instructional practices as expressed in perceived class- room goal structures and students’ goal orientations were analyzed, focusing also on potential moderators. Results of a questionnaire study with 46 Mathematics teachers and their 930 students supported the as-sumption that teachers’ goal orientations affect their instructional practices and students’ goal orientations. These effects were, in part, moderated by teacher beliefs (implicit theories, self-efficacy beliefs). Overall, the results provided strong support for the notion that the mechanisms underlying these effects are based on the functionality of certain instructional practices for the attainment of teachers’ goals

Minimal Surfaces, Screw Dislocations and Twist Grain Boundaries

Large twist-angle grain boundaries in layered structures are often described by Scherk's first surface whereas small twist-angle grain boundaries are usually described in terms of an array of screw dislocations. We show that there is no essential distinction between these two descriptions and that, in particular, their comparative energetics depends crucially on the core structure of their screw-dislocation topological defects.Comment: 10 pages, harvmac, 1 included postscript figure, final versio

Gaussian approximation for finitely extensible bead-spring chains with hydrodynamic interaction

The Gaussian Approximation, proposed originally by Ottinger [J. Chem. Phys., 90 (1) : 463-473, 1989] to account for the influence of fluctuations in hydrodynamic interactions in Rouse chains, is adapted here to derive a new mean-field approximation for the FENE spring force. This "FENE-PG" force law approximately accounts for spring-force fluctuations, which are neglected in the widely used FENE-P approximation. The Gaussian Approximation for hydrodynamic interactions is combined with the FENE-P and FENE-PG spring force approximations to obtain approximate models for finitely-extensible bead-spring chains with hydrodynamic interactions. The closed set of ODE's governing the evolution of the second-moments of the configurational probability distribution in the approximate models are used to generate predictions of rheological properties in steady and unsteady shear and uniaxial extensional flows, which are found to be in good agreement with the exact results obtained with Brownian dynamics simulations. In particular, predictions of coil-stretch hysteresis are in quantitative agreement with simulations' results. Additional simplifying diagonalization-of-normal-modes assumptions are found to lead to considerable savings in computation time, without significant loss in accuracy.Comment: 26 pages, 17 figures, 2 tables, 75 numbered equations, 1 appendix with 10 numbered equations Submitted to J. Chem. Phys. on 6 February 200