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Acoustic propagation measurements were collected in a seagrass meadow in a shallow lagoon for periods of over 65 h in winter and 93 h in summer. A bottom-deployed sound source transmitted chirps (0.1–100 kHz) every 10 min that were received on a four-receiver horizontal hydrophone array. Oceanographic probes measured various environmental parameters. Daytime broadband acoustic attenuation was 2.4 dB greater in summer than winter, and the median received acoustic energy levels were 8.4 dB lower in summer compared to winter. These differences were attributed in part to seasonal changes in photosynthesis bubble production and above-ground seagrass biomass.

 

Microbial ecology research requires sampling strategies that accurately represent the microbial community under study. These communities must typically be transported from the collection location to the laboratory and then stored until they can be processed. However, there is a lack of consensus on how best to preserve microbial communities during transport and storage. Here, we evaluated dimethyl sulfoxide, ethylenediamine tetraacetic acid, saturated salt (DESS) solution as a broadly applicable preservative for microbial ecology experiments. We stored fungus gardens grown by the ant Trachymyrmex septentrionalis in DESS, 15% glycerol, and phosphate buffered saline (PBS) to test their impact on the fungus garden microbial community. Variation in microbial community structure due to differences in preservative type was minimal when compared to variation between ant colonies. Additionally, DESS preserved the structure of a defined mock community more faithfully than either 15% glycerol or PBS. DESS is inexpensive, easy to transport, and effective in preserving microbial community structure. We therefore conclude that DESS is a valuable preservative for use in microbial ecology research. 

A classic reachability problem for safety of dynamic systems is to compute the set of initial states from which the state trajectory is guaranteed to stay inside a given constraint set over a given time horizon. In this paper, we leverage existing theory of reachability analysis and risk measures to devise a risk-sensitive reachability approach for safety of stochastic dynamic systems under non-adversarial disturbances over a finite time horizon. Specifically, we first introduce the notion of a risk-sensitive safe set as a set of initial states from which the risk of large constraint violations can be reduced to a required level via a control policy, where risk is quantified using the Conditional Value-at-Risk (CVaR) measure. Second, we show how the computation of a risk-sensitive safe set can be reduced to the solution to a Markov Decision Process (MDP), where cost is assessed according to CVaR. Third, leveraging this reduction, we devise a tractable algorithm to approximate a risk-sensitive safe set, and provide theoretical arguments about its correctness. Finally, we present a realistic example inspired from stormwater catchment design to demonstrate the utility of risk-sensitive reachability analysis. In particular, our approach allows a practitioner to tune the level of risk sensitivity from worst-case (which is typical for Hamilton-Jacobi reachability analysis) to risk-neutral (which is the case for stochastic reachability analysis).