Coral reefs consist of diverse benthic habitats that influence seawater CO2 chemistry variability on multiple spatial and temporal scales. Understanding the present-day seawater CO2 chemistry variability across both habitat-specific and reef-wide scales is critical to accurately predict the effects of future environmental change. Here, we utilize autonomous sensors and discrete seawater samples across diverse habitats at multiple scales ranging from habitat-specific (inner lagoon, patch reefs and seagrass beds; 0.02–0.72km2) to reef-wide scales at Dongsha Atoll (250km2) and Taiping Island (20km2) to characterize seawater chemistry. Across all habitats, daily mean pH ranged from 7.79–8.60 with mean diel variability ranging from 0.19–0.91. Spatially, pH variability ranged from 0.08 (patch reef) to 1.29 (inner lagoon). Biogeochemical modification of seawater chemistry was dominated by organic carbon cycling at individual habitat scales, whereas inorganic carbon cycling dominated at the scale of Dongsha Atoll. The largest alkalinity depletion (net calcification) was associated with patch reef habitats, whereas the highest alkalinity repletion was associated with a semi-enclosed lagoon. Under two climate change scenarios (linear dissolved inorganic carbon increase derived from historical observations and the CMIP6 SSP5-8.5 pathway), pH and/or aragonite saturation state (ΩAr) observations across all habitats in this study are projected to be below proposed thresholds for net reef accretion (pH < 7.7: inner lagoon 10–13
Noctiluca scintillans is a globally distributed harmful algal bloom (HAB) species known for potentially causing fish mortality and economic losses to fisheries. N. scintillans tends to accumulate near the sea surface, making it particularly susceptible to transport by ocean currents, however, direct evidence of long-distance dispersal has remained limited. Year-round monitoring in Kumamoto revealed that the Indonesian (Jakarta-type, K2) genotype occurs predominantly during the autumn high-abundance period, coinciding with smaller cell sizes that match Jakarta population. To evaluate the plausibility of long-distance transport, we conducted Lagrangian particle-tracking simulation using OSCAR surface currents. The results showed a plausible physical ocean connectivity between Indonesia and Japan within 600 days, with consistent patterns across different particle-release numbers indicating that arrival probabilities remained low but spatially robust. Recognizing that OSCAR provides a 0.25° satellite-derived representation of basin-scale surface circulation that does not explicitly resolve mesoscale eddies, we interpret these trajectories as possible connectivity pathways rather than literal particle tracks. Together, our genetic, morphological, and particle-tracking simulation results indicate that N. scintillans populations in Yatsushiro Bay likely consist of both regional and foreign genetic contributors, highlighting the potential for long-range connectivity under contemporary circulation patterns.
This work presents a novel methodology for preview repetitive control (PRC) in nonlinear Markovian jump systems (MJS) with partially unknown transition probabilities, utilizing Takagi–Sugeno (T-S) fuzzy modeling. The study addresses the challenge by constructing an augmented error model (AEM) for T-S fuzzy MJS in the presence of time-varying uncertainties, thereby transforming the original fuzzy PRC problem into a stability analysis task for the AEM. Two distinct fuzzy PRC schemes are then developed based on the system’s state and output information of the T-S fuzzy MJS, incorporating previewed reference signals for enhanced performance. Sufficient stability conditions for the AEM and controller design criteria are rigorously derived through Lyapunov stability theory combined with linear matrix inequality (LMI) techniques. The effectiveness of the proposed control strategies is validated through two illustrative simulation examples, demonstrating their practical applicability and performance advantages.
Copper indium gallium selenide (CIGS) thin-film solar cells are a leading technology for next-generation photovoltaics due to their high absorption coefficients and tunable electronic properties. However, achieving optimal device performance via scalable methods like magnetron sputtering is critically dependent on precise stoichiometric control of the quaternary absorber layer, which remains a significant challenge. We fabricated CIGS thin films by sputtering from two distinct targets, one slightly Cu-poor and one Cu-rich, followed by a rapid thermal selenization process. We found that annealing at 500 °C for 30 minutes is optimal for producing highly crystalline films with minimal secondary phases. Devices fabricated using the Cu-poor target achieved a power conversion efficiency of 4.6
This research delves into the event-triggered (E-T) control for uncertain nonlinear cyber–physical systems with quantization, modeled through the Takagi–Sugeno fuzzy model (TSFM) framework over a finite-time (F-T) interval. The main objective is to refine the E-T control strategy to guarantee that the closed-loop T–S fuzzy cyber–physical system (TSFCPS) achieves finite-time boundedness (FTB) and meets the predetermined mixed H_∞ and passive performance indices. An E-T control strategy is employed to alleviate the network communication load and optimize network resource utilization. To further reduce data exchange across networks, data quantization is also integrated with the E-T scheme. In addition, the impact of random cyber-attacks, which may alter the transmitted data during network communication, on the TSFCPS is considered. By resorting to Lyapunov stability theory along with analytical techniques, the sufficient conditions within the framework of linear matrix inequalities (LMIs) are established to ensure FTB of the closed-loop uncertain TSFCPS while satisfying the mixed H_∞ and passivity performance constraints. Finally, we simulate a practical system to verify the performance of the proposed control approach.
