Minimum lattice thermal conductivity of InSbTe by surface Brillouin scattering.

Phase-change materials are chalcogenide alloys used for nonvolatile memory applications due to their rapid and reversible structural transformation. is a promising candidate that exhibits transitions dependent on thermal conductivity. The minimum lattice thermal conductivity of amorphous is investigated by surface acoustic propagation.

nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer.

Single-cell segmentation is typically a crucial task of image-based cellular analysis. We present nucleAIzer, a deep-learning approach aiming toward a truly general method for localizing 2D cell nuclei across a diverse range of assays and light microscopy modalities. We outperform the 739 methods submitted to the 2018 Data Science Bowl on images representing a variety of realistic conditions, some of which were not represented in the training data.

Test-time augmentation for deep learning-based cell segmentation on microscopy images.

Recent advancements in deep learning have revolutionized the way microscopy images of cells are processed. Deep learning network architectures have a large number of parameters, thus, in order to reach high accuracy, they require a massive amount of annotated data. A common way of improving accuracy builds on the artificial increase of the training set by using different augmentation techniques.

Optimized determination of elastic constants of crystals and their uncertainties from surface Brillouin scattering.

Surface Brillouin scattering of light allows the angular-dependent velocities of Rayleigh surface acoustic waves (SAW), pseudo-SAW and longitudinal lateral waves (L) on the surface of an opaque crystal to be measured, and the elastic constants thereby determined. Closed form expressions exist for the surface wave velocities in high symmetry directions on crystallographic symmetry planes, and these have been exploited in the past for obtaining the values of the elastic constants. This paper describes a procedure for obtaining an optimized set of elastic constants from SAW, pseudo-SAW and L velocities measured in arbitrary directions in the (001) and (110) surfaces of cubic crystals.