Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.

Background: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and interpretations vary widely between users. The digitization of auscultation acquisition and interpretation is a particularly promising strategy for diagnosing and monitoring infectious diseases such as Coronavirus-19 disease (COVID-19) where automated analyses could help decentralise care and better inform decision-making in telemedicine.

Size does matter: crocodile mothers react more to the voice of smaller offspring.

Parental care is widespread in Archosaurs (birds, crocodilians, dinosaurs and pterosaurs), and this group provides a useful model for the evolution of parent-offspring interactions. While offspring signalling has been well-studied in birds, the modulation of parental care in crocodilians remains an open question. Here we show that acoustic communication has a key role in the dynamics of crocodilian' mother-offspring relationships.

Video-rate optical low-coherence reflectometry based on a linear smart detector array.

A low-coherence reflectometer based on a conventional Michelson interferometer and a novel silicon detector chip that allows parallel heterodyne detection is presented. Cross-sectional images of 64x256 pixels covering an area of 1.92 mm x 1.

Optical coherence topography based on a two-dimensional smart detector array.

A low-coherence reflectometer based on a conventional Michelson interferometer and a novel silicon detector chip with a two-dimensional array of pixels that allows parallel heterodyne detection is presented. We demonstrate acquisition of three-dimensional images with more than 100,000 voxels per scan at a sensitivity of -58 dB and a rate of 6 Hz.

Numerical parametric lens for shifting, magnification, and complete aberration compensation in digital holographic microscopy.

The concept of numerical parametric lenses (NPL) is introduced to achieve wavefront reconstruction in digital holography. It is shown that operations usually performed by optical components and described in ray geometrical optics, such as image shifting, magnification, and especially complete aberration compensation (phase aberrations and image distortion), can be mimicked by numerical computation of a NPL. Furthermore, we demonstrate that automatic one-dimensional or two-dimensional fitting procedures allow adjustment of the NPL parameters as expressed in terms of standard or Zernike polynomial coefficients.