A deep learning method for reflective boundary estimation.

Environment estimation is a challenging task in reverberant settings such as the underwater and indoor acoustic domains. The locations of reflective boundaries, for example, can be estimated using acoustic echoes and leveraged for subsequent, more accurate localization and mapping. Current boundary estimation methods are constrained to high signal-to-noise ratios or are customized to specific environments.

Machine-learning based detection of marine mammal vocalizations in snapping-shrimp dominated ambient noise.

Passive acoustics is an effective method for monitoring marine mammals, facilitating both detection and population estimation. In warm tropical waters, this technique encounters challenges due to the high persistent level of ambient impulsive noise originating from the snapping shrimp present throughout this region. This study presents the development and application of a neural-network based detector for marine-mammal vocalizations in long term acoustic data recorded by us at ten locations in Singapore waters.

In vitro and in silico analysis unravelled clinically desirable attributes of Bacillus altitudinis L-asparaginase.

Aims: To identify a marine L-asparaginase with clinically desirable attributes and characterize the shortlisted candidate through in silico tools.

Methods And Results: Marine bacterial strains (number = 105) isolated from marine crabs were evaluated through a stepwise strategy incorporating the crucial attributes for therapeutic safety. The results demonstrated the potential of eight bacterial species for extracellular L-asparaginase production.

Depth-dependence of the underwater noise emission from melting glacier ice.

Submarine-melting of ice at the glacier-ocean interface accounts for a large portion of the ice-loss at tidewater glaciers and produces sound via bubble-release. The sound production is dominant in the sub-surface region near the glacier-ocean interface. This depth-dependence of the sound is studied by melting ice blocks in a glacial bay at various depths up to 20 m and recording their acoustics over a large frequency range.

A dolphin-inspired compact sonar for underwater acoustic imaging.

Underwater imaging sonars are widely used for oceanic exploration but are bulky and expensive for some applications. The sonar system of dolphins, which uses sound pulses called clicks to investigate their environment, offers superior shape discrimination capability compared to human-derived imaging sonars of similar size and frequency. In order to gain better understanding of dolphin sonar imaging, we train a dolphin to acoustically interrogate certain objects and match them visually.