Learning Visual Question Answering by Bootstrapping Hard Attention

Attention mechanisms in biological perception are thought to select subsets of perceptual information for more sophisticated processing which would be prohibitive to perform on all sensory inputs. In computer vision, however, there has been relatively little exploration of hard attention, where some information is selectively ignored, in spite of the success of soft attention, where information is re-weighted and aggregated, but never filtered out. Here, we introduce a new approach for hard attention and find it achieves very competitive performance on a recently-released visual question answering datasets, equalling and in some cases surpassing similar soft attention architectures while entirely ignoring some features. Even though the hard attention mechanism is thought to be non-differentiable, we found that the feature magnitudes correlate with semantic relevance, and provide a useful signal for our mechanism's attentional selection criterion. Because hard attention selects important features of the input information, it can also be more efficient than analogous soft attention mechanisms. This is especially important for recent approaches that use non-local pairwise operations, whereby computational and memory costs are quadratic in the size of the set of features.Comment: ECCV 201

Localization and Interaction Effects in Strongly Underdoped La2-xSrxCuO4

The in-plane magnetoresistance (MR) in La2-xSrxCuO4 films with 0.03 < x < 0.05 has been studied in the temperature range 1.6 K to 100 K, and in magnetic fields up to 14 T, parallel and perpendicular to the CuO2 planes. The behavior of the MR is consistent with a predominant influence of interaction effects at high temperatures, switching gradually to a regime dominated by spin scattering at low T. Weak localization effects are absent. A positive orbital MR appears close to the boundary between the antiferromagnetic and the spin-glass phase, suggesting the onset of Maki-Thompson superconducting fluctuations deep inside the insulating phase.Comment: 4 pages, 3 figures, to appear in Phys. Rev. Letter

R23. Demographics and Outcomes of Patients Hospitalized for COVID-19

Corresponding author (University of Mississippi Medical Center): Jonathan T. Newbaker, [email protected]://egrove.olemiss.edu/pharm_annual_posters/1022/thumbnail.jp

Two types of all-optical magnetization switching mechanisms using femtosecond laser pulses

Magnetization manipulation in the absence of an external magnetic field is a topic of great interest, since many novel physical phenomena need to be understood and promising new applications can be imagined. Cutting-edge experiments have shown the capability to switch the magnetization of magnetic thin films using ultrashort polarized laser pulses. In 2007, it was first observed that the magnetization switching for GdFeCo alloy thin films was helicity-dependent and later helicity-independent switching was also demonstrated on the same material. Recently, all-optical switching has also been discovered for a much larger variety of magnetic materials (ferrimagnetic, ferromagnetic films and granular nanostructures), where the theoretical models explaining the switching in GdFeCo films do not appear to apply, thus questioning the uniqueness of the microscopic origin of all-optical switching. Here, we show that two different all-optical switching mechanisms can be distinguished; a "single pulse" switching and a "cumulative" switching process whose rich microscopic origin is discussed. We demonstrate that the latter is a two-step mechanism; a heat-driven demagnetization followed by a helicity-dependent remagnetization. This is achieved by an all-electrical and time-dependent investigation of the all-optical switching in ferrimagnetic and ferromagnetic Hall crosses via the anomalous Hall effect, enabling to probe the all-optical switching on different timescales.Comment: 1 page, LaTeX; classified reference number

Room temperature spin relaxation in GaAs/AlGaAs multiple quantum wells

We have explored the dependence of electron spin relaxation in undoped GaAs/AlGaAs quantum wells on well width (confinement energy) at 300 K. For wide wells, the relaxation rate tends to the intrinsic bulk value due to the D'yakonov-Perel (DP) mechanism with momentum scattering by phonons. In narrower wells, there is a strong dependence of relaxation rate on well width, as expected for the DP mechanism, but also considerable variation between samples from different sources, which we attribute to differences in sample interface morphology. (C) 1998 American Institute of Physics. [S0003-6951(98)02541-8].</p

Estimating turbulence kinetic energy dissipation rates in numerically simulated stratocumulus cloud-top and convective boundary layer flow: Evaluation of different methods.

We perform analysis of direct numerical simulation (DNS) data of two flow cases: stratocumulus cloud-top (SCT) and convective boundary layer (CBL). We test different methods for turbulence kinetic energy dissipation rate (EDR) retrieval. Among others we investigate performance of a new, iterative method, proposed recently in Wacławczyk et al. (2017), where an analytical model for energy spectra in the dissipative range is needed. We argue, the new method has some advantages over the standard spectral retrieval techniques. To apply it, only the information on the signals’ cut-off wavelength is needed and it is not necessary to define the fitting range in the inertial part of the spectrum. With this, the new method could be a basis of a general algorithm for EDR retrieval, applicable to a wide range of different atmospheric data (e.g. from commercial aircrafts). Moreover, we investigate how the presence of anisotropy due to shear, buoyancy and external intermittency in the flow affects the EDR retrieval based on the classical K41 for isotropic turbulence (Kolmogorov, 1941). © 2019 International Symposium on Turbulence and Shear Flow Phenomena, TSFP. All rights reserved