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Considering the full dynamics of the different conversion stages from ocean waves to the electricity grid is essential to evaluate the realistic power flow in the drive train and design accurate model-based control formulations. The power take-off system for wave energy converters (WECs) is one of the essential parts of wave-to-wire (W2W) models, for which hydraulic transmissions are a robust solution and offer the flexibility to design specific drive-trains for specific energy absorption requirements of different WECs. The potential hydraulic drive train topologies can be classified into two main configuration groups (constant-pressure and variable-pressure configurations), each of which uses specific components and has a particular impact on the preceding and following stages of the drive train. The present paper describes the models for both configurations, including the main nonlinear dynamics, losses and constraints. Results from the mathematical model simulations are compared against experimental results obtained from two independent test rigs, which represent the two main configurations, and high-fidelity software. Special attention is paid to the impact of friction in the hydraulic cylinder and flow and torque losses in the hydraulic motor. Results demonstrate the effectiveness of the models in reproducing experimental results, capturing friction effects and showing similar losses.

Many shark species exhibit complex spatial ecology throughout their life histories, posing a challenge for conservation and management. Although most marine protected areas (MPAs) were originally established to protect less mobile organisms, protection of shark species from fishing and other impacts is possible if individuals exhibit high residency and site fidelity within the MPA boundaries. For this study, we used a fixed acoustic telemetry array to study the residency, habitat use, and interspecific space use among 4 shark species in Buck Island Reef National Monument (BIRNM), an MPA in St. Croix, US Virgin Islands. From June 2013 to May 2017, 11 nurse sharks Ginglymostoma cirratum, 6 lemon sharks Negaprion brevirostris, 13 Caribbean reef sharks Carcharhinus perezi, and 6 tiger sharks Galeocerdo cuvier were monitored in the array. Overall, residency was high for all species, with a mean residency index of 0.52 or higher for each species. Network analysis revealed complex inter- and intraspecific spatial associations among individuals. Community detection algorithms showed that G. cirratum and N. brevirostris frequently used the same areas in BIRNM, selecting for shallow sand and seagrass habitats near linear reefs, while G. cuvier and C. perezi had more individualized space use. C. perezi also exhibited ontogenetic shifts, developing individual territories and using deeper water with increasing body size. This work emphasizes the importance of MPA size, placement, and habitat composition when aiming to protect highly mobile species with potentially large home ranges and shifting space use throughout their life histories.

Great barracuda (Sphyraena barracuda) are a high trophic level predator that uses a wide variety of habitats globally throughout tropical and subtropical waters. Despite the important top-down pressure this species likely exerts on fish communities within its foraging territories, the specifics of spatial ecology remain relatively unknown. This study tracked 17 great barracuda throughout Buck Island Reef National Monument, a marine-protected area located in St. Croix, U.S. Virgin Islands (17.786944° N, − 64.620556° W) from July 2014 to May 2016. Broad- and fine-scale acoustic telemetry was used to examine individual variability and study population patterns in residency, site fidelity, territoriality, and complexity of spatial use within home ranges. Network analysis of broad-scale data revealed spatial and temporal differentiation among the population in location of core use areas and showed that these areas contained multiple unique receiver groups or communities, a product of spatial or temporal variation within core activity spaces. Results from the fine-scale positioning system reinforced spatial and temporal partitioning in core use areas between individuals, indicating territorial behaviors, and showed evidence for both resident and transient movements. Preliminary fine-scale analysis also suggested diel variation in location of activity spaces. Although ubiquitous throughout all shallow water habitats, detection patterns for the study population appear to be influenced by high residency, territoriality, spatial partitioning, and diel variation. Understanding the complexities of individual space use is fundamental to ecologically founded and effective area-based spatial management frameworks at community scales.

As marine protected areas expand globally, filling data gaps regarding the spatial ecology of marine species has become increasingly important. Acoustic telemetry aims to provide this vital information through generating datasets that can be used to reveal complex movement patterns. The effects of analytic method choice and study design on results must be rigorously analyzed to validate the accuracy of ecological interpretations. We assessed the role of analytic method choice on ecological conclusions derived from an acoustic telemetry array at Buck Island Reef National Monument, USVI. Core use area estimates of great barracuda Sphyraena barracuda (n = 32) generated with 3 methods were compared, and the impact of variation in detection history on the ability to interpret results was modeled. Kernel utilization densities, dynamic Brownian bridge movement models, and network analysis indicated high site fidelity paired with less frequent broad exploratory movements. The first 2 methods both identified high use areas, whereas network methods placed higher emphasis on movement corridors and links between core and peripheral use areas. Generalized linear models showed that detection history impacted home range area estimates and confounded the ability to determine ecological relationships. As marine protected areas increase in relevance, it is important that methods to evaluate their effectiveness do not miss complex spatial-temporal patterns and that areas vital to ecological processes are considered alongside areas of highest use. Including network methods in routine spatial assessments may help reveal fish movement patterns previously hidden by using conventional home range analyses.

Background Information regarding the movement ecology of horse-eye jack Caranx latus throughout the Caribbean is limited despite their prevalence. Passive acoustic telemetry was used to infer movement patterns of seven adult C. latus within Buck Island Reef National Monument (BIRNM), a no-take marine protected area (MPA) northeast of St. Croix, U.S. Virgin Islands. In addition, a preliminary exploration of detections recorded outside of BIRNM was used to gain knowledge of the potential for larger scale movements. Ascertaining long-term movement patterns, including residency, mobility, and identifying core activity spaces can play a considerable role in how MPAs, like BIRNM, are adapted to meet the needs of mobile species. Results High residency index values were observed for individual C. latus within the BIRNM array (mean ± SE: 0.913 ± 0.04, range 0.75–1.0) across the 17 months monitored. Most fish were also detected on receivers located outside BIRNM. An observed to expected detection ratio revealed that despite high residency, only 9.6% of expected transmissions were detected based on the average tag transmission rate. Network analysis revealed high individual connectivity with many of the receivers inside BIRNM and a large number of core use receivers (mean: 10.7, range 6–14) within individual networks. Conclusions Most C. latus were present in BIRNM at least twice per day, but were overall detected below the expected rates, demonstrating mobility, large core activity spaces and wide use of the acoustic array inside BIRNM and greater St. Croix shelf. How residency is inferred from acoustic telemetry detections, and interpreted for species with variable mobility, has important considerations for spatial management planning and telemetry analyses. For MPA development to meet the spatial requirements of species with mixed resident–mobile spatial ecology, detailed long-term movement data are required. Assessing residency in MPAs using acoustic telemetry should be formalized and carefully interpreted based on specific species, environmental conditions, and array configuration.

Background A better understanding of sea turtle spatial ecology is critical for the continued conservation of imperiled sea turtles and their habitats. For resource managers to develop the most effective conservation strategies, it is especially important to examine how turtles use and select for habitats within their developmental foraging grounds. Here, we examine the space use and relative habitat selection of immature green turtles ( Chelonia mydas ) using acoustic telemetry within the marine protected area, Buck Island Reef National Monument (BIRNM), St. Croix, United States Virgin Islands. Results Space use by turtles was concentrated on the southern side of Buck Island, but also extended to the northeast and northwest areas of the island, as indicated by minimum convex polygons (MCPs) and 99%, 95%, and 50% kernel density estimations (KDEs). On average space use for all categories was < 3 km 2 with mean KDE area overlap ranging from 41.9 to 67.7%. Cumulative monthly MCPs and their proportions to full MCPs began to stabilize 3 to 6 detection months after release, respectively. Resource selection functions (RSFs) were implemented using a generalized linear mixed effects model with turtle ID as the random effect. After model selection, the accuracy of the top model was 77.3% and showed relative habitat selection values were highest at shallow depths, for areas in close proximity to seagrass, and in reef zones for both day and night, and within lagoon zones at night. The top model was also extended to predict across BIRNM at both day and night. Conclusion More traditional acoustic telemetry analyses in combination with RSFs provide novel insights into animal space use and relative resource selection. Here, we demonstrated immature green turtles within the BIRNM have small, specific home ranges and core use areas with temporally varying relative selection strengths across habitat types. We conclude the BIRNM marine protected area is providing sufficient protection for immature green turtles, however, habitat protection could be focused in both areas of high space use and in locations where high relative selection values were determined. Ultimately, the methodologies and results presented here may help to design strategies to expand habitat protection for immature green turtles across their greater distribution.

Resource selection functions (RSFs) have been widely applied to animal tracking data to examine relative habitat selection and to help guide management and conservation strategies. While readily used in terrestrial ecology, RSFs have yet to be extensively used within marine systems. As acoustic telemetry continues to be a pervasive approach within marine environments, incorporation of RSFs can provide new insights to help prioritize habitat protection and restoration to meet conservation goals. To overcome statistical hurdles and achieve high prediction accuracy, machine learning algorithms could be paired with RSFs to predict relative habitat selection for a species within and even outside the monitoring range of acoustic receiver arrays, making this a valuable tool for marine ecologists and resource managers. Here, we apply RSFs using machine learning to an acoustic telemetry dataset of four shark species to explore and predict species-specific habitat selection within a marine protected area. In addition, we also apply this RSF-machine learning approach to investigate predator-prey relationships by comparing and averaging tiger shark relative selection values with the relative selection values derived for eight potential prey-species. We provide methodological considerations along with a framework and flexible approach to apply RSFs with machine learning algorithms to acoustic telemetry data and suggest marine ecologists and resource managers consider adopting such tools to help guide both conservation and management strategies.

ObjectiveTo assess whether hypertension is an independent risk factor for mortality among patients hospitalised with COVID-19, and to evaluate the impact of ACE inhibitor and angiotensin receptor blocker (ARB) use on mortality in patients with a background of hypertension.MethodThis observational cohort study included all index hospitalisations with laboratory-proven COVID-19 aged ≥18 years across 21 Australian hospitals. Patients with suspected, but not laboratory-proven COVID-19, were excluded. Registry data were analysed for in-hospital mortality in patients with comorbidities including hypertension, and baseline treatment with ACE inhibitors or ARBs.Results546 consecutive patients (62.9±19.8 years old, 51.8% male) hospitalised with COVID-19 were enrolled. In the multivariable model, significant predictors of mortality were age (adjusted OR (aOR) 1.09, 95% CI 1.07 to 1.12, p<0.001), heart failure or cardiomyopathy (aOR 2.71, 95% CI 1.13 to 6.53, p=0.026), chronic kidney disease (aOR 2.33, 95% CI 1.02 to 5.32, p=0.044) and chronic obstructive pulmonary disease (aOR 2.27, 95% CI 1.06 to 4.85, p=0.035). Hypertension was the most prevalent comorbidity (49.5%) but was not independently associated with increased mortality (aOR 0.92, 95% CI 0.48 to 1.77, p=0.81). Among patients with hypertension, ACE inhibitor (aOR 1.37, 95% CI 0.61 to 3.08, p=0.61) and ARB (aOR 0.64, 95% CI 0.27 to 1.49, p=0.30) use was not associated with mortality.ConclusionsIn patients hospitalised with COVID-19, pre-existing hypertension was the most prevalent comorbidity but was not independently associated with mortality. Similarly, the baseline use of ACE inhibitors or ARBs had no independent association with in-hospital mortality.