Search Results (363)

This paper studies spacecraft control under communication congestion, multi-source uncertainties, and input constraints. To reduce communication load, a static event-triggered mechanism is used so that transmissions occur only when necessary. Unknown nonlinearities are estimated online by a radial basis function neural network (RBFNN). To address sensor outliers and external disturbances, an event-triggered stubborn composite disturbance observer (ESCDO) is proposed, and sufficient conditions are derived to ensure its globally uniformly bounded stability. Based on this, an MPC-based composite anti-disturbance controller is designed to satisfy input constraints, and conditions are provided to guarantee the uniform bounded stability of the closed loop. Numerical simulations are conducted to demonstrate the effectiveness of the proposed approach. Full article

In the context of global climate change, frequent summer heavy rainfall events act as significant disturbances to the ecosystem functions of shallow lakes. This study examined the response of phytoplankton community structure and dynamics to heavy rainfall in Lake Changhu, a shallow eutrophic lake, through monthly monitoring during the summer months (June–August) of 2020–2022. The results revealed that heavy rainfall induced substantial water level fluctuations and shifts in key environmental parameters. Marked interannual variations were observed in the phytoplankton community, with the highest species richness in summer 2021 and lowest in 2022. While Chlorophyta dominated in species composition, Cyanobacteria overwhelmingly dominated in abundance, with key taxa including Dolichospermum flos-aquae L., Pseudanabaena limnetica L., Oscillatoria princeps V., Microcystis wesenbergii K., and Merismopedia minima B. Both phytoplankton abundance and biomass peaked in summer 2021. Community diversity indices were consistently lower in June compared to July–August, indicating higher environmental stress and a more simplified community structure during the initial rainfall period. A comprehensive water quality evaluation suggested that Lake Changhu was in a lightly to moderately polluted state. Correlation and redundancy analyses (RDA) identified rainfall, water temperature, and nutrient concentrations as the primary environmental drivers shaping phytoplankton community succession. These findings systematically elucidate the mechanistic responses of phytoplankton to heavy rainfall disturbances, offering a scientific foundation for ecological resilience assessment and adaptive management of shallow lakes under climate change. Full article

Environmental DNA (eDNA) has become a promising tool for phytoplankton surveys. However, the accuracy of eDNA-based detection is related to primer selection across diverse environments, and optimal primer pairs selection on phytoplankton community in human impacted ecosystems is still lacking. The aim of this study is to evaluate how primer selection shapes phytoplankton community profiles by eDNA biomonitoring diverse anthropogenically disturbed aquatic systems (rivers, reservoirs, and seas). Four primer pairs targeting the 18S rRNA (V9-1 and V9-2), chloroplast rbcL, and ITS regions, were explored and our results revealed that primer choice critically governed the accuracy of phytoplankton profiling. Significant variations in annotated phytoplankton eDNA sequences in different groups of primer pairs were observed, where the primers 18SV9-1 and rbcL demonstrated superior specificity, amplifying >90% of phytoplankton OTUs. 18S-targeted primers detected the highest species richness, while the ITS primer showed the lowest. Alpha diversity was highest and most consistent for 18S primers. Beta diversity ordination (nMDS/Bray–Curtis) further highlighted primer-dependent community structuring in which 18S primers effectively clustered reservoir and marine samples separately, whereas primer rbcL discriminated habitat-specific signatures across three ecosystems. The primer ITS failed to distinguish among different habitats. Overall, our data demonstrated the critical role of primer optimization in eDNA-based phytoplankton studies, and could provide methodological guidelines for the design of effective monitoring protocols in rapidly urbanizing aquatic systems. Full article

This paper presents a Prescribed Performance Control (PPC) approach for robotic systems experiencing communication delay and disturbances. Under input and feedback delays, a state feedback controller is designed to maintain the output tracking error within prescribed performance specifications. Additionally, a super-twisting algorithm-based sliding-mode observer is proposed to estimate and compensate for external disturbance in the robotic system. Based on the Lyapunov method, appropriate controller parameters and observer gains are selected to ensure the accuracy of output tracking and disturbance estimation. Finally, the effectiveness of the proposed approach is validated through simulations on a nonlinear robotic system. The proposed method remains effective in the simultaneous presence of state measurement delay, control input delay, and disturbance. Full article

Urban ecosystems are structurally and functionally distinct from their natural counterparts, with anthropogenic management potentially altering fundamental ecological processes such as seasonal community dynamics and impairing their sustainability. However, the mechanisms through which management filters plant diversity across seasons remain poorly understood. This study tested the hypothesis that management acts as an abiotic filter, dampening seasonal community variations and increasing biotic homogenization in urban green spaces. In this respect, through an intensive, multi-seasonal case study comparing two Mediterranean urban green spaces under contrasting management regimes, we analysed plant communities across 120 plots over four seasons. Results reveal a contingency cascade under management: while the species composition remains relatively stable (+26% variability, p < 0.001), the demographic success becomes more contingent (+41%, p < 0.001), and the ecological dominance becomes highly stochastic (+90%, p < 0.001). This hierarchy demonstrates that management primarily randomizes which species achieve dominance, in terms of biomass and cover, from a pool of disturbance-tolerant generalists. A 260% increase in alien and cosmopolitan species and persistent niche pre-emption dominance–diversity patterns also indicate biotic homogenization driven by management filters (mowing, trampling, irrigation, and fertilization) that favors species resistant to mechanical stresses and induces a breakdown of deterministic community assembly. These processes create spatially and temporally variable assemblages of functionally similar species, explaining both high structural variability and persistent functional redundancy. Conversely, seasonally structured, niche-based assemblies with clear dominance–diversity progressions are observed in the unmanaged area. Overall, findings demonstrate that an intensive management homogenizes urban plant communities by overriding natural seasonal filters and increasing stochasticity. The study provides a mechanistic basis for sustainable urban green space management, indicating that reduced intervention can help preserve the seasonal dynamics crucial for sustaining biodiversity and ecosystem functioning. Full article

Deep-sea polymetallic nodule provinces harbor rich benthic microbial communities that underpin biogeochemical cycles and sustain abyssal ecosystem functions. Recent studies have begun to map their abundance, diversity and community structure, emphasizing the role of environmental gradients and spatial heterogeneity. Yet the spatiotemporal dynamics and assembly mechanisms of these microbes remain largely unresolved. Mining-induced sediment plumes further complicate the picture: they modify microbial biomass, activity and composition, but the trajectories of community succession and the functional consequences of disturbance are still unclear. Thresholds used to gauge plume impacts also differ markedly among studies, hampering consistent risk assessments. In summary, a stark contrast exists between the limited in situ observational data, the widely varying impact thresholds reported across studies, and the pressing need for unified standards in environmental impact assessments for deep-sea mining. It recommends future work that integrates multi-omics, time-series in situ monitoring, cross-regional comparisons and standardized evaluation frameworks to refine microbial indicators and ecological thresholds for deep-sea mining impact assessments. Full article

This study addresses a critical challenge in global conservation: understanding how rare species contribute to ecosystem structure and resilience. The ecological role of the endangered black-and-white snub-nosed monkey in China’s temperate mountain forests was examined, with the hypothesis that its tree-shaking behavior alters forest structure and microclimates to enhance ecosystem health. To assess long-term impacts, current monkey-inhabited forests were compared with historical sites abandoned over decades, by analyzing tree gaps, forest structure, and environmental conditions. Monkeys’ canopy-disturbing actions were also directly observed. Findings revealed monkey activity created more canopy gaps (38.3% in current habitats vs. 29.9~33.5% in abandoned sites) and altered microclimate conditions, which boosted plant diversity and optimized the community’s vertical and age structures. Current forests supported nearly twice as many tree species, 2.5 times as many shrub species, and threefold more herb species than areas abandoned for 40 years. Even 20 years after monkeys disappeared, abandoned sites retained higher diversity and gaps, showing lasting ecological benefits. These results confirm the monkey’s vital role as a resilience promoter, demonstrating how rare species can shape healthier ecosystems. This highlights the need to prioritize protecting such species, as their survival not only preserves biodiversity but also sustains ecosystem functions crucial for human well-being. Full article

With the rapid growth of autonomous vehicle technologies, effective path-tracking control has become a critical component in ensuring safety and efficiency in complex traffic scenarios. When a high-level decision-making agent generates a collision-free path, a robust low-level controller is required to precisely follow this trajectory. However, connected autonomous vehicles (CAV) are inherently affected by communication delays and computation delays, which significantly degrade the performance of conventional controllers such as PID or other more advanced controllers like disturbance observers (DOB). While DOB-based designs have shown effectiveness in rejecting disturbances under nominal conditions, their performance deteriorates considerably in the presence of unknown time delays. To address this challenge, this paper proposes a delay-tolerant communication disturbance observer (CDOB) framework for path-tracking control in delayed systems. The proposed CDOB compensates for the adverse effects of time delays, maintaining accurate trajectory tracking even under uncertain and varying delay conditions. It is shown through a simulation study that the proposed control architecture maintains close alignment with the reference trajectory across various scenarios, including single-lane change, double-lane change, and Elastic Band-generated collision avoidance paths under various time delays. Simulation results further demonstrate that the proposed method outperforms conventional approaches in both tracking accuracy and delay robustness, making it well-suited for connected autonomous driving applications. Full article

Northern hardwood forests of the Lake Superior region face a series of novel disturbance pressures including canopy dieback. Previous studies have linked regional sugar-maple (Acer saccharum) canopy dieback to introduced earthworms, which may have coinciding impacts on the ground-layer plant community. Dieback–earthworm interactions may lead to important longer-term changes in forest structure and function, but these relationships but have not been characterized. We sampled ground-layer plant communities in five national forest units in Michigan, Wisconsin, and Minnesota in 2010, and again just over a decade later in 2021. Non-metric multidimensional scaling ordination and indicator species analysis were used to assess relationships among ground-layer community composition and structure, functional traits, and environmental gradients including forest-floor condition and A. saccharum canopy dieback. Increases in dieback and earthworm disturbance in the decade between inventories were accompanied by a marked divergence in observed ground-layer plant community structure between national forests. Ordinations of 2021 data indicated a strengthening relationship between forest-floor condition and earthworm abundance. Our results suggest that earthworm impacts and A. saccharum dieback are driving changes in the ground layer on broad geographic and temporal scales, with short- and long-term implications for plant-community structure and function, and higher trophic levels. Full article

In recent years, the availability of automated change detection algorithms in Google Earth Engine has permitted the cloud-based processing of large quantities of satellite imagery. Models such as the Continuous Change Detection and Classification (CCDC), CCDC-Spectral Mixture Analysis (CCDC-SMA), and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) allow users to exploit decades of Earth Observations (EOs), leveraging the Landsat archive and data from other sensors to detect disturbances in forest ecosystems. Despite the wide adoption of these methods, robust documentation, and a growing community of users, little research has systematically detailed their tuning process in mangrove environments. This work aims to identify the best practices for applying these models to monitor changes within mangrove forest cover, which has been declining gradually in Belize the last several decades. Partnering directly with the Belizean Forest Department, our team developed a replicable, efficient methodology to annually update the country’s mangrove extent, employing EO-based change detection. We ran a series of model variations in both CCDC-SMA and LandTrendr to identify the parameterizations best suited to identifying change in Belizean mangroves. Applying the best performing model run to the starting 2017 mangrove extent, we estimated a total loss of 540 hectares in mangrove coverage by 2024. Overall accuracy across thirty variations in model runs of LandTrendr and CCDC-SMA ranged from 0.67 to 0.75. While CCDC-SMA generally detected more disturbances and had higher precision for true changes, LandTrendr runs tended to have higher recall. Our results suggest LandTrendr offered more flexibility in balancing precision and recall for true changes compared to CCDC-SMA, due to its greater variety of adjustable parameters. Full article

Alzheimer’s disease (AD) is a complex neurodegenerative disorder where age, genetic factors and sleep disturbance significantly influence disease risk. Recent genome-wide association studies identified a C/T missense variant (rs141749679) in the sortilin (SORT1) gene linked to heightened AD risk, revealing SORT1’s role as a key player in the disease’s pathophysiology. This type I membrane glycoprotein is implicated in amyloid β (Aβ) accumulation and associated lipid dysregulation, particularly through its interaction with apolipoprotein E (ApoE). SORT1 facilitates the uptake of ApoE-bound polyunsaturated fatty acids (PUFAs), conversion to endocannabinoids (eCBs), and the regulation of anti-inflammatory pathways via peroxisome proliferator-activated receptors (PPARs). Notably, this neuroprotective signaling is contingent on the APOE allele, exhibiting functionality in presence of ApoE3 but disrupted with ApoE4. Additionally, the brain-type fatty acid binding protein, FABP7, mediates this signaling cascade, emphasizing its role in neuron-glia communication. FABP7 is known to regulate sleep across species and binds PUFAs and eCBs. Therefore, dysfunction of the ApoE-SORT1-FABP7 axis may underlie the neuroprotective loss observed in AD, linking sleep disruption and lipid homeostasis to disease progression. This perspective aims to elucidate the intricate neural-glial mechanisms governing the ApoE-SORT1-FABP7 interaction and their implications for targeting therapeutic interventions in Alzheimer’s disease. Full article

The power system’s dynamic frequency stability is affected by common-mode ultra-low-frequency oscillation and differential-mode low-frequency oscillation. Traditional frequency control based on generators is facing the problem of capacity reduction. It is urgent to explore new regulation resources such as photovoltaics. To address this issue, this paper proposes a distributed active support method based on photovoltaic systems via state–disturbance observation and dynamic surface consensus control. A three-layer distributed control framework is constructed to suppress low-frequency oscillations and ultra-low-frequency oscillations. To solve the high-order problem of the regional grid model and to obtain its unmeasurable variables, a regional observer estimating both system states and external disturbances is designed. Furthermore, a distributed dynamic frequency stability control method is proposed for wide-area photovoltaic clusters based on the dynamic surface control theory. In addition, the stability of the proposed distributed active support method has been proven. Moreover, a parameter tuning algorithm is proposed based on improved chaos game theory. Finally, simulation results demonstrate that, even under a 0–2.5 s time-varying communication delay, the proposed method can restrict the frequency deviation and the inter-area frequency difference index to 0.17 Hz and 0.014, respectively. Moreover, under weak communication conditions, the controller can also maintain dynamic frequency stability. Compared with centralized control and decentralized control, the proposed method reduces the frequency deviation by 26.1% and 17.1%, respectively, and shortens the settling time by 76.3% and 42.9%, respectively. The proposed method can effectively maintain dynamic frequency stability using photovoltaics, demonstrating excellent application potential in renewable-rich power systems. Full article

This article investigates the zonotope-based state estimation for boost converter system with Markov jump process. DC-DC boost converters are pivotal in modern power electronics, enabling renewable energy integration, electric vehicle charging, and microgrid operations by elevating low input voltages from sources like photovoltaics to stable high outputs. However, their nonlinear dynamics and sensitivity to uncertainties/disturbances degrade control precision, driving research into robust state estimation. To address these challenges, the boost converter is modeled as a Markov jump system to characterize stochastic switching, with time delays, disturbances, and noises integrated for a generalized discrete-time model. An adaptive event-triggered mechanism is adopted to administrate the data transmission to conserve communication resources. A zonotopic set-membership estimation design is proposed, which involves designing an observer for the augmented system to ensure $H_{\infty }$ performance and developing an algorithm to construct zonotopes that enclose all system states. Finally, numerical simulations are performed to verify the effectiveness of the proposed approach. Full article

Our study addresses how large-scale hydrological alterations shape zooplankton biodiversity in floodplain ecosystems, which are highly sensitive to changes in river connectivity. Following the operation of the Gabčíkovo hydroelectric power plant in the Danube inland delta, we examined the long-term responses of crustacean zooplankton communities, as these organisms are key indicators of hydromorphological disturbance. Based on previous evidence that river regulation often reduces habitat heterogeneity, we hypothesized that hydrological alterations in the Danube riverscape would promote increasing taxonomic and functional homogenization within sites, while simultaneously enhancing differentiation between sites over the past three decades. A total of 121 planktonic crustacean species were recorded across six monitored sites between 1991 and 2020, comprising 49 copepods and 72 cladocerans. Communities showed rising species richness, especially during the first decade of the hydropower plant’s operation. While overall richness increased, dam-induced hydromorphological changes triggered habitat-specific community shifts. In the main channel and adjacent parapotamal arm, taxonomic and functional homogenization occurred, dominated by resilient tychoplanktonic species with a gathering or secondary filter-feeding strategy. In contrast, isolated side arms experienced gradual eutrophication, favoring euplanktonic and primary filter-feeding taxa. The observed taxonomic and functional convergence within both habitat groups reflects the loss of connectivity and the cessation of artificial flooding. Full article