Noncontacting Benchtop Measurements of the Elastic Properties of Shales

We evaluated a laser-based noncontacting method to measure the elastic anisotropy of horizontal shale cores. Whereas conventional transducer data contained an ambiguity between phase and group velocity measurements, small laser source and receiver footprints on typical core samples ensured group velocity information in our laboratory measurements. With a single dense acquisition of group velocity versus group angle on a horizontal core, we estimated the elastic constants C11, C33, and C55 directly from ultrasonic waveforms, and C13 from a least-squares fit of modeled to measured group velocities. The observed significant P-wave velocity and attenuation anisotropy in these dry shales were almost surely exaggerated by delamination of clay platelets and microfracturing, but provided an illustration of the new laboratory measurement technique. Although challenges lay ahead to measure preserved shales at in situ conditions in the lab, we evaluated the fundamental advantages of the proposed method over conventional transducer measurements

Theory and Laboratory Experiments of Elastic Wave Scattering by Dry Planar Fractures

Remote sensing of fractures with elastic waves is important in fields ranging from seismology to nondestructive testing. In many geophysical applications, fractures control the flow of fluids such as water, hydrocarbons or magma. While previous analytic descriptions of scattering mostly deal with very large or very small fractures (compared to the dominant wavelength), we present an analytic solution for the scattering of elastic waves from a fracture of arbitrary size. Based on the linear slip model for a dry fracture, we derive the scattering amplitude in the frequency domain under the Born approximation for all combinations of incident and scattered wave modes. Our analytic results match laser-based ultrasonic laboratory measurements of a single fracture in clear plastic, allowing us to quantify the compliance of a fracture

Word order preference in sign influences speech in hearing bimodal bilinguals but not vice versa: Evidence from behavior and eye-gaze

We investigated cross-modal influences between speech and sign in hearing bimodal bilin- guals, proficient in a spoken and a sign language, and its consequences on visual attention during message preparation using eye-tracking. We focused on spatial expressions in which sign languages, unlike spoken languages, have a modality-driven preference to mention grounds (big objects) prior to figures (smaller objects). We compared hearing bimodal bilin- guals’ spatial expressions and visual attention in Dutch and Dutch Sign Language (N = 18) to those of their hearing non-signing (N = 20) and deaf signing peers (N = 18). In speech, hear- ing bimodal bilinguals expressed more ground-first descriptions and fixated grounds more than hearing non-signers, showing influence from sign. In sign, they used as many ground-first descriptions as deaf signers and fixated grounds equally often, demonstrating no influence from speech. Cross-linguistic influence of word order preference and visual attention in hearing bimodal bilinguals appears to be one-directional modulated by modality-driven difference

Using SVD for improved interferometric Green’s function recovery.

Seismic interferometry is a technique used to estimate the Green’s function (GF) between two receiver locations, as if there were a source at one of the locations. By crosscorrelating the recorded seismic signals at the two locations we generate a crosscorrelogram. Stacking the crosscorrelogram over sources generates an estimate of the inter-receiver GF. However, in most applications, the requirements to recover the exact GF are not satisfied and stacking the crosscorrelograms yields a poor estimate of the GF. For these non-ideal cases, we enhance the real events in the virtual shot gathers by applying Singular Value Decomposition (SVD) to the crosscorelograms before stacking. The SVD approach preserves energy that is stationary in the crosscorrelogram, thus enhancing energy from sources in stationary positions, which interfere constructively, and attenuating energy from non-stationary sources that interfere distructively. We apply this method to virtual gathers containing the virtual refraction artifact and find that using SVD enhances physical arrivals. We also find that SVD is quite robust in recovering physical arrivals from noisy data when these arrivals are obscured by or even lost in the noise in the standard seismic interferometry technique

Artificial neural networks for 3D cell shape recognition from confocal images

We present a dual-stage neural network architecture for analyzing fine shape details from microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification for diagnostic and theragnostic use.Comment: 17 pages, 8 figure