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Dissolved oxygen (DO) is an important aspect of water quality in aquaculture. To prevent oxygen deficiency, aeration is used to improve DO and increase yields in aquaculture farms. However, the experimental quantification of standard oxygen transfer rate (SOTR) of aerators is highly case dependent and varies under different aerator operational conditions. Hence, using SOTR for modeling, simulation, and aerator design purposes tends to be unreliable. This work validates an existing theoretical oxygen transfer model of an economical fine-pore diffuser using a bench-scale aeration system. Modifications were made to the model to account for physical conditions and to relate the model to SOTR. Aeration tests were conducted using various airflow rates and diffuser depths for three water volumes (137 L, 160 L, 192 L). As a parameter to the model, bubble diameters were determined for each experiment using an automated image processing tool developed for this study. The percentage error between the theoretical and experimental oxygen transfer coefficients range from 12.87% to 19.99% and are well within the 95% confidence interval of both respective results. The oxygen transfer coefficient and rate increased with diffuser submergence and airflow rate. However, standard aeration efficiency decreased exponentially with increasing airflow rates. The use of this model provides an approximate estimate of oxygen transfer rates in different conditions, which can be used to optimally design aerators and strategically create cost-saving practices for both intensive and extensive aquaculture applications. [ABSTRACT FROM AUTHOR]

The article offers information on research related to the semantic processing of words and objects conducted by Barry J. Devereux and colleagues. Topics include input modality and semantic representations, functional magnetic resonance imaging to study neural processing, and activity in parts of the brain including the left posterior middle temporal gyrus, the left angular gyrus, and the left interparietal sulcus.

Light Detection and Ranging (LiDAR), a comparatively new technology in the field of underwater surveying, has principally been used for taking precise measurement of undersea structures in the oil and gas industry. Typically, the LiDAR is deployed on a remotely operated vehicle (ROV), which will "land" on the seafloor in order to generate a 3D point cloud of its environment from a stationary position. To explore the potential of subsea LiDAR on a moving platform in an environmental context, we deployed an underwater LiDAR system simultaneously with a multibeam echosounder (MBES), surveying Kingston Reef off the coast of Rottnest Island, Western Australia. This paper compares and summarises the relative accuracy and characteristics of underwater LiDAR and multibeam sonar and investigates synergies between sonar and LiDAR technology for the purpose of benthic habitat mapping and underwater simultaneous localisation and mapping (SLAM) for Autonomous Underwater Vehicles (AUVs). We found that LiDAR reflectivity and multibeam backscatter are complementary technologies for habitat mapping, which can combine to discriminate between habitats that could not be mapped with either one alone. For robot navigation, SLAM can be effectively applied with either technology, however, when a Global Navigation Satellite System (GNSS) is available, SLAM does not significantly improve the self-consistency of multibeam data, but it does for LiDAR. [ABSTRACT FROM AUTHOR]