Deep-learning-based phase control method for tiled aperture coherent beam combining systems

We incorporate deep learning (DL) into tiled aperture coherent beam combining (CBC) systems for the first time, to the best of our knowledge. By using a well-trained convolutional neural network DL model, which has been constructed at a non-focal-plane to avoid the data collision problem, the relative phase of each beamlet could be accurately estimated, and then the phase error in the CBC system could be compensated directly by a servo phase control system. The feasibility and extensibility of the phase control method have been demonstrated by simulating the coherent combining of different hexagonal arrays. This DL-based phase control method offers a new way of eliminating dynamic phase noise in tiled aperture CBC systems, and it could provide a valuable reference on alleviating the long-standing problem that the phase control bandwidth decreases as the number of array elements increases.

Shaping sustainability of seafood from capture fisheries integrating the perspectives of supply chain stakeholders through combining systems analysis tools

Seafood from capture fisheries can be assessed in many ways and for different purposes, with sometimes divergent views on what characterizes “sustainable use”. Here we use two systems analysis tools—Ecological Risk Assessment for Effects of Fishing (ERAEF) and Life Cycle Assessment (LCA)—over the historical development of the Australian Patagonian toothfish fishery at Heard and McDonald Islands since the start in 1997. We find that ecological risks have been systematically identified in the management process using ERAEF, and with time have been mitigated, resulting in a lower risk fishery from an ecological impact perspective. LCA inventory data from the industry shows that fuel use per kilo has increased over the history of the fishery. Our results suggest that LCA and ERAEF may provide contrasting and complementary perspectives on sustainability and reveal trade-offs when used in combination. Incorporation of LCA perspectives in assessing impacts of fishing may facilitate refinement of ecosystem-based fisheries management, such as improved integration of the different perspectives of supply chain stakeholders.

Macro-Social Marketing Research

Macro-social marketing is the use of social marketing – up, mid and downstream – to affect holistic systemic change (Kennedy 2016). Presently, fragmented views within macro-social marketing threaten to divide the field. Much of this fragmentation is due to a confusion between systems thinking and systems theory, the basis for macro-social marketing. This article presents an explanation of the key facets of systems literature, a macro-social marketing philosophy and a macro-social marketing methodology to show the benefits of combining systems thinking and systems theory, thus alleviating conflict within the field.