Search Results (1,963)

In maritime navigation, precise and stable ship course control is critical for operational efficiency and maritime safety, yet it is severely challenged by unpredictable marine disturbances (e.g., waves, wind, and currents) that consist of slowly varying and stochastic components. Traditional control methods, though effective under specific operating conditions, exhibit limited adaptability to the nonlinear, time-varying characteristics of marine systems and inherent dependence on accurate ship mathematical models, which easily leads to suboptimal performance and elevated navigation risks, especially under sudden and intense disturbances. To address these limitations, this study proposes a novel control strategy, namely, model-free control integrated with super-twisting sliding mode control (MFSTSMC) with a linear extended state observer (LESO), for enhanced ship course control. Derived from the ultra-local model, the proposed method integrates the simplicity and practicality of model-free control, the real-time disturbance estimation and compensation capability of LESO, and the strong robustness of STSMC. The Lyapunov stability theory is rigorously employed to prove the stability of the entire control system, ensuring that the steady-state error converges to zero. Comparative analyses are conducted on an ocean ship verification platform, with strictly unified parameters for fairness. The comparative results evaluate the proposed method under three typical scenarios: course-keeping (small ±10° and large ±70° maneuvers), course tracking (low/high-frequency sinusoidal trajectories and high-frequency 20° abrupt change trajectory), and resistance to sudden escalating disturbances. The results demonstrate that the proposed MFSTSMC with LESO significantly outperforms existing controllers in terms of tracking accuracy, response speed, stability, and disturbance rejection capability. Its superior performance originates from the synergistic effect of real-time disturbance compensation and robust sliding mode compensation, which effectively mitigates the impact of model deviations and complex marine disturbances. This study provides valuable insights for the development of advanced marine navigation control strategies, and the proposed method exhibits promising engineering application prospects for ocean ship navigation in complex dynamic marine environments. Full article

Whether energy-supply crises accelerate decarbonisation or reinforce fossil-fuel dependence remains an open empirical question, particularly in the Middle East and North Africa (MENA). This study examines the 2011 collapse of Egyptian natural gas exports to Jordan, caused by repeated attacks on the Arab Gas Pipeline, as a sudden and largely exogenous energy-security shock. Using harmonised annual electricity-generation data from Ember for six MENA and Mediterranean countries from 2000 to 2022, a panel difference-in-differences framework estimated by two-way fixed effects assesses how Jordan’s renewable electricity share evolved relative to a comparison group. The evidence indicates a delayed rather than immediate response. Event-study estimates show little change between 2012 and 2016, followed by a marked divergence reaching approximately 16 percentage points by 2022. The full-period average difference is 4.22 percentage points (95% CI −2.93 to 11.37), while the later divergence persists across leave-one-country-out specifications and when renewable generation is normalised by pre-crisis system size. Fuel concentration changed little, because Jordan replaced a gas-and-oil generation mix with a gas-and-renewables mix, a shift consistent with a compositional improvement in energy security through reduced fossil-fuel import exposure rather than greater diversification. Energy crises may, therefore, open opportunities for renewable transitions, but their realisation appears contingent on institutional capacity. Full article

To address the challenges of rapid voltage fluctuations and operational economy in new power systems with high wind power integration under sandstorm weather, this paper proposes a multi-timescale cooperative voltage control strategy for new power systems. On the second-level timescale, a discrete state-space model of wind turbines and reactive power devices is established considering sudden wind speed changes. Model predictive control (MPC) is then used to rapidly calculate the optimal reactive power references for wind turbines, static var generator (SVG), and on-load tap changer (OLTC), thereby effectively ensuring rapid stabilization of the grid-connection point voltage. On the minute-level timescale, a two-stage topology reconfiguration method is adopted. A feasible radial network is first generated through a sequential switch opening strategy, followed by iterative optimization via a switch exchange strategy. This approach rapidly identifies the optimal switch configuration to minimize network losses and improve operational economy. Simulation results demonstrate the effectiveness of the proposed strategy in voltage regulation and loss reduction, highlighting its capability to enhance the robustness of new power systems under sandstorm weather. Full article

Electric–hydrogen hybrid microgrids integrating distributed renewables with electrolysers can efficiently convert dispersed renewables into hydrogen, meeting local electricity demands. However, intermittent and uncertain renewables together with sudden load changes can cause severe bus voltage fluctuations and degrade power quality, especially in off-grid microgrids. Furthermore, the electrolyser’s auxiliary units require stable AC power supply even during fault events, which most likely occur at AC–DC converters. To ensure stability during renewable/load fluctuations and converter faults, this paper proposes a fault-resilient coordinated voltage control scheme by combining PI with piecewise active disturbance rejection control to mitigate DC bus voltage fluctuations during transient disturbances and regulates AC-side fuel cells via control switching to stabilise AC voltage after the complete disconnection converter fault. The scheme is tested using a simulated kW-scale electric–hydrogen hybrid microgrid in various operating scenarios and compared with conventional methods that combine PI with PI or linear active disturbance rejection control. The simulation results show that the proposed control scheme improves DC bus voltage stability by 14% during transient renewable/load fluctuations via the incorporation of PADRC and enhance system resilience against AC–DC converter faults through the synergy of batteries and fuel cells, which construct the voltage (and frequency) of DC and AC buses, respectively. Full article

Concept drift can degrade encrypted-traffic classifiers deployed at the network edge as applications, protocols, and usage patterns evolve. This paper formulates federated continual learning under asynchronous real- and virtual drift and proposes DriftGuard, a framework combining a two-level per-node detector, selective adapter-based adaptation with Fisher importance masking and class-balanced replay, and drift-aware server aggregation. Level 1 detects distributional changes in learned representations, while Level 2 monitors supervised prediction errors to provide evidence consistent with decision-relevant drift before selective adaptation is activated. We further derive a convergence bound under stated assumptions that explicitly incorporates environmental variation, detection delay, and false alarms. DriftGuard is evaluated in a controlled simulation using reproducible synthetic traffic-like features under sudden, gradual, virtual-only, and recurring drift. Across five independent runs, results are reported with standard deviations, 95% confidence intervals, and paired statistical comparisons. DriftGuard maintains competitive classification accuracy while limiting forgetting of stable classes, with its clearest advantage observed under gradual asynchronous drift. Results also show that immediate adaptation using ground-truth drift states does not necessarily improve performance under the evaluated adaptation policy. The findings provide controlled methodological validation rather than evidence of production-scale deployment performance. Full article

Predicting emergencies caused by uncontrolled and sometimes sudden changes in methane concentration within working and adjacent zones of coal mines remains a critical and challenging task, the solution for which can greatly enhance mining safety. This study presents a hybrid machine-learning model trained on real and synthetic data for accurate methane concentration forecasting and risk-level classification. The authors propose an ensemble method comprising staged data preprocessing, generation of physically meaningful features, and weighted ensembles for both regression and classification. The system is augmented with expert rules to correct forecasts and a built-in anomaly detection mechanism based on residual analysis. Experimental evaluation confirmed the model’s high performance: for regression, the coefficient of determination reached 0.984–0.997; the classifier achieved a recall of 92.8% for the rare “Accident” class under severe data imbalance (10:1). The ensemble approach reduced error variance by 40–60% compared to baseline models. The results indicate the feasibility of pilot application for dynamic early warning, which can substantially reduce coal mine accident risks. Full article

Microwave-driven thermochemical cycles can split water for hydrogen production at temperatures far below those of conventional solar thermochemical routes, yet the responsible physical mechanisms remain unclear and numerical models for the coupled solar-microwave hybrid system are still scarce. Building on previous experimental work, we developed a coupled numerical model that integrates impedance matching, non-thermal enhancement, two-stage Arrhenius kinetics, and energy conservation to systematically investigate the interplay between microwave power, temperature evolution, and reaction progress. The model predictions agree well with experimental data in terms of temperature evolution trends, power threshold ranges, and reaction timescales. The results indicate that, within the present modeling framework, the effective microwave absorption efficiency increases from 1.2% at low temperatures to approximately 14% near 85 °C, with the non-thermal enhancement factor contributing as an empirical parameter. Under pure microwave mode, the required power threshold for reaction initiation is approximately 120 W; the solar-microwave synergistic mode reduces this threshold to about 70 W, a 42% reduction. At an input power of 100 W, the energy conversion efficiency reaches a maximum of 42%. Analysis of the sudden temperature change identifies 85 °C as the critical triggering temperature: below it, the system remains in a low-absorption cold state, while once crossed, a positive feedback mechanism rapidly propels the system into the high-temperature reaction regime. This study provides a numerical modeling framework for describing the coupled solar-microwave thermal behavior of the system and for guiding the optimization of its operational parameters. Since the available measurements cannot independently separate the thermal and non-thermal contributions, the non-thermal enhancement remains an empirically introduced factor rather than an experimentally established physical effect. Full article

Forecasting USD/CNY exchange rate volatility is of substantial practical significance for the management of cross-border capital flows and the formulation of monetary policies. In recent years, multiple external shocks arising from China–US geopolitical tensions and sharp fluctuations in the international crude oil market have become increasingly intertwined. Traditional forecasting models are often unable to capture such sudden risk signals in a timely manner, while a single model is also insufficiently adaptable to multi-scale volatility structures. To address these challenges, this paper develops a deep-learning-based dynamic forecasting framework that integrates a China–US geopolitical risk feature system (CUGRI) with international oil price shock signals. Specifically, CUGRI is constructed from news texts published by 15 authoritative Chinese and US media outlets, combining a finance-specific language model with a geopolitical-domain sentiment lexicon to build a five-dimensional daily risk quantification feature system. At the modeling level, this paper proposes a GRU-BiLSTM-Transformer dynamic fusion model, which adaptively assigns fusion weights according to the recent forecasting performance of each sub-model. All empirical analyses are implemented under the Python programming environment with the PyTorch deep learning framework. Using nearly ten years of daily data, this paper conducts out-of-sample forecasting tests. The empirical results show that the proposed dynamic fusion model achieves an out-of-sample $R^2$ of 0.342, while reducing RMSE and MAE by 4.01% and 3.72%, respectively, relative to the best-performing baseline model. CUGRI exhibits significant incremental predictive value, with forecasting gains substantially higher during periods of elevated geopolitical risk than under normal conditions. Oil price shocks provide complementary predictive information, and the dynamic weighting mechanism further improves the accuracy of combined forecasts. In practice, the findings are relevant to cross-border firms and financial institutions when tracking changes in geopolitical and energy-market risks and adjusting foreign-exchange hedging strategies. For monetary and regulatory authorities, the model helps identify periods when external shocks may amplify USD/CNY volatility and supports exchange-rate risk surveillance and macro-financial stability analysis. Full article

This study presents a five-state functional model for assessing the reliability of electric vehicle charging infrastructure from the perspective of charging-service capability. The model distinguishes full functionality, three levels of degradation, and the loss of the basic charging function. State changes are described using a time-homogeneous continuous-time Markov process that includes progressive degradation, sudden functional loss, and restoration to state S0. On this basis, MTTF, MTTR, and MTBF are reinterpreted in relation to first attainment, restoration trajectories, and complete functional cycles. The reference calculations determine stationary state probabilities, annual residence times, and the effectiveness of restoration before reaching S4. The results show that a low stationary probability of S4 may still correspond to a meaningful annual period of service unavailability, while most functional cycles end with restoration from intermediate states. The proposed framework provides a reproducible basis for analysing EV charging infrastructure and can be applied using transition intensities estimated from operator records. Full article

Externally bonded carbon fiber-reinforced polymer (CFRP) systems are used to improve the flexural performance of reinforced concrete members. However, premature debonding, particularly intermediate crack-induced (IC) debonding, limits CFRP utilization and may lead to sudden failure. This study experimentally and numerically investigates the effectiveness of CFRP patch anchors with different anchorage configurations in improving the flexural behavior and failure mode of CFRP-strengthened reinforced concrete slabs. Nine reinforced concrete slabs were tested under four-point bending, including one reference slab, two slabs strengthened with longitudinal CFRP strips without anchorage, and six slabs strengthened with CFRP strips and transverse patch anchors. The experimental results showed that CFRP increased the ultimate load by about 30–61% compared with the reference slab. The unanchored specimens failed mainly by IC debonding. In contrast, the patch-anchored specimens showed better strain distribution, delayed debonding, and a shift toward CFRP rupture. The numerical results showed good agreement with the experimental results, with ultimate-load prediction errors below 7%. Changing the patch area did not significantly increase the ultimate load, with about 0.8% difference between the mean capacities of the anchored groups, while end anchors alone were insufficient to prevent debonding. CFRP patch anchors effectively delayed premature debonding and improved CFRP utilization. Full article

Repeated mining of shallow-buried close-distance coal seams can disturb the fractured strata remaining in the goaf of the upper coal seam. Under gully terrain, mining disturbance is coupled with surface-relief effects, which may reactivate the overburden structure and induce dynamic strata-pressure behavior. In particular, when the working face advances across gullies, the change in surface slope alters the spatial distribution of roof load, while lower-seam extraction further disturbs the fractured rock mass formed by upper-seam mining, increasing the risk of severe strata-pressure behavior and support-crushing accidents. Taking the cross-ditch mining of the 2⁻² and 3⁻¹ coal seams in Anshan Coal Mine as the research object, this study integrates field geological investigation, theoretical calculation, physical similarity simulation, and field engineering verification to analyze overburden structural evolution, key-stratum breaking characteristics, and support-load variation under gully terrain. The results show that gully landforms generate obvious nonuniform loading above the working face. During upslope advance, the roof load gradually increases from the goaf side to the solid-coal side, causing tensile stress concentration at the fixed end of the key stratum and accelerating rock-stratum failure. A cantilever rock-beam mechanical model subjected to parabolic nonuniform loading was established, and the maximum breaking interval of the key stratum was calculated as 24.09 m. With increasing gully slope angle, the load gradient intensifies, the rock-beam breaking interval decreases, and the risk of overburden instability increases. Physical similarity simulation indicates that, when the 2⁻² coal seam working face passes through the 45° steep-slope section, the fractured overburden is more likely to form a stepped rock-beam structure, accompanied by slope rotation, stepped surface subsidence, and a sharp increase in support pressure. Under the 30° gentle-slope condition, The lateral confinement effect is stronger, roof movement is more gradual, and support-pressure fluctuation is reduced. During subsequent extraction of the lower 3⁻¹ coal seam, repeated mining disturbance reactivates the overlying goaf structure, and the upper stepped rock beam and lower hinged rock beam couple to form a double composite structure. When the fracture lines of the upper and lower key strata are staggered, the instability load of the upper structure is mainly buffered by caved gangue and interburden strata. The calculated support resistance in the asynchronous breaking stage is 8248.04 kN, which agrees well with the field-measured value of 8273 kN. When the fracture lines tend to coincide and synchronous breaking occurs, the unstable load of the upper key block is transferred downward and superimposed on the structural load of the lower key block, increasing the required support resistance to 15,165.55 kN, far exceeding the rated working resistance of the ZY9200/15/29 hydraulic support. Sensitivity analysis indicates that gully slope angle is the dominant factor affecting support resistance. As the slope angle increases from 30° to 60°, the support resistance increases from 13,228.65 kN to 18,278.43 kN, and the normalized support-resistance index increases from 0.872 to 1.205. Therefore, synchronous breaking of double key strata is the main mechanical cause of sudden support-load increase and support-crushing risk during cross-ditch mining of shallow-buried close-distance coal seams. The results can provide a basis for hydraulic support selection, roof weakening, weighting-interval control, and dynamic strata-pressure prevention under similar conditions. Full article

Background/Objectives: Pregnancy is associated with profound hormonal, hemodynamic, and metabolic changes that may affect the auditory and vestibular systems. However, evidence regarding pregnancy-related audiological disturbances remains limited due to the low incidence of these conditions and the scarcity of dedicated studies. The study aimed to identify the most commonly reported audiological changes occurring during pregnancy and the postpartum period with an emphasis on sudden sensorineural hearing loss (SSNHL), its risk factors, clinical presentation, and treatment methods. Methods: A literature search was conducted in PubMed, Embase, Web of Science, and Google Scholar from database inception to November 2025 using combinations of the keywords “pregnancy”, “hearing loss”, and “audiological changes”. The review is based on twenty-four original articles that met the preselected criteria. Results: Current evidence does not support pregnancy as an independent risk factor for SSNHL; the prevalence in obstetric patients is lower than in the control groups. Most cases occur during the third trimester or the postpartum period. Pre-pregnancy obesity and elevated blood pressure were identified as potential risk factors. Higher income levels and rural residency are associated with an increased incidence of SSNHL, whereas gestational diabetes, pre-eclampsia, and pregnancy-related weight gain showed no consistent association with SSNHL. Audiometric studies demonstrated mild, predominantly low-frequency, hearing threshold elevations that were generally transient and resolved after delivery. Tinnitus, nausea, aural fullness, dizziness, and vertigo were the most common ear-related complaints. Most of these disorders resolve spontaneously, but some studies suggest steroid treatment should be introduced. Intratympanic corticosteroid therapy was the most frequently investigated treatment for SSNHL and was associated with favorable hearing outcomes in most reported cases. Limited evidence suggests that Dextran 40 may improve hearing outcomes when used as an adjunctive therapy. Conclusions: Potentially transient cochleovestibular impairment during pregnancy and the postpartum period should not be underestimated and requires further evaluation. Pregnancy-related physiological adaptations may contribute to transient auditory and vestibular disturbances, particularly during late pregnancy and the postpartum period. Although current evidence does not indicate an increased risk of SSNHL during pregnancy, prompt recognition and management remain important to prevent long-term hearing impairment. Further high-quality studies are required to clarify the underlying mechanisms and establish evidence-based treatment recommendations for pregnant patients with SSNHL. Full article

Search-and-rescue (SAR) missions following earthquakes and other disasters require aerial video perception systems that do more than detect objects in isolated frames. Operators must maintain the identities of access points, vehicles, responders, hazards, and other mission-relevant targets despite UAV ego-motion, dust, debris, occlusion, scale variation, and abrupt scene transitions. This paper presents E’CHIT (Edge-Oriented Colour Histogram Instance-Guided Tracking), a deployment-oriented, operator-centric UAV tracking framework for real-world disaster-response applications. Its primary scientific contribution is an identity-stabilised, detector-assisted tracking methodology. YOLOv8-seg proposals trained on D’RespNeT initialise and refresh tracks; a Custom-RE3 recurrent module propagates target states through short detector dropouts; and a lightweight EOMC verifier, based on edge orientation, mean colour, and shape consistency, determines whether tracks should be accepted, refreshed, or reacquired. A scene-cut watchdog that combines luminance mean absolute difference (MAD) with HSV histogram divergence prevents stale identities from carrying over after hard edits or sudden feed changes. Custom-RE3 is the continuation module implemented and evaluated in this study. The surrounding E’CHIT wrapper follows an initialise–reseed–verify–reset cycle and is tracker-adaptable at the software-interface level: another compatible SOT or MOT continuation module can be integrated through adapter modifications, state and bounding-box conversion, and method-specific retuning, followed by independent validation. All reported quantitative results therefore apply to the Custom-RE3 implementation. D’RespNeT, the optional reinforcement learning (RL) warm start, the HUD, and the deployment stack support this central tracking contribution. D’RespNeT provides 28 polygon-annotated SAR classes. An author-developed PPO/SAC script is used only during offline detector training. In the reported runs, it produces different early optimisation trajectories for selected difficult or under-represented classes, while the default supervised schedule remains the strongest final global mAP reference. No RL policy runs during deployment; the detector architecture, parameter count, and inference graph remain unchanged. Evaluation on D’RespNeT and authentic disaster-response UAV footage shows that E’CHIT increases Success@IoU ≥ 0.5 from 0.62 to 0.79, reduces identity switches by approximately 71%, and maintains real-time 1080p performance, achieving 164–330 FPS for single-target tracking and 24–100+ FPS for end-to-end multi-target operation on an RTX-class GPU using FP16. The VOT2014, NT-VOT211, and VOTS2024 figures reproduce historical result spaces reported in the literature and include a clearly labelled, non-official E’CHIT operating-point marker solely for context. This marker was not produced using the corresponding official datasets, toolkits, reset rules, or submission routes; it is excluded from the primary quantitative claims and must not be interpreted as a leaderboard rank or a protocol-identical comparison. Overall, the system demonstrates how identity-stable UAV tracks can provide actionable operator cues for target monitoring, entry-point assessment, and UAV–UGV/ground-team coordination in cluttered disaster scenes. Full article

Background: Cardiac arrhythmias in children and adolescents may present with nonspecific symptoms such as precordial pain, palpitations, and syncope. We evaluated the clinical characteristics and rhythm findings of symptomatic pediatric patients and examined cross-sectional associations between reported symptoms and selected rhythm diagnoses, with particular attention to the diagnostic and management yield of ambulatory Holter monitoring. Because symptom timing is not always captured during diagnostic monitoring, associations between reported symptoms and detected rhythm abnormalities must be distinguished from temporal symptom–rhythm correlation and causation. Methods: We conducted an observational study of 119 children and adolescents aged 1–18 years, who were evaluated at a tertiary pediatric hospital for symptoms potentially suggestive of cardiac rhythm abnormalities. Data included demographic characteristics, clinical symptoms, personal and family history, resting electrocardiography, ambulatory Holter monitoring, and exercise testing where clinically indicated. The primary analysis was cross-sectional. Because symptom timing during ambulatory monitoring was not recorded, the study was not designed to establish temporal symptom–rhythm correlation or causality. Descriptive analyses were performed for the final 119-participant cohort. Selected symptom–rhythm associations were evaluated using the contingency table methods with odds ratios (ORs), 95% confidence intervals (CIs), and Fisher’s exact tests where appropriate. Holm’s adjustment was applied to the prespecified family of reconstructed symptom–rhythm comparisons. Results were interpreted according to both statistical evidence and effect-size precision. Results: The cohort comprised 119 participants, including 75 females (63.0%) and 44 males (37.0%). The most frequently reported symptoms were precordial pain (105/119, 88.2%), palpitations (80/119, 67.2%), and syncope or lipothymia (39/119, 32.8%). A family history of sudden cardiac death was reported by 28 participants (23.5%). Forty-two participants (35.3%) had a normal resting ECG, while 77 (64.7%) underwent ambulatory Holter monitoring. Among those undergoing Holter monitoring, 65/77 (84.4%) had rhythm abnormalities detected exclusively by ambulatory monitoring and not identified on the resting ECG. Holter findings resulted in at least one documented management change in 38/77 participants (49.4%). Management categories were not mutually exclusive and included lifestyle or activity adjustment in 21 participants, initiation of antiarrhythmic therapy in 19, medication monitoring in 19, and targeted cardiac imaging, including cardiac magnetic resonance imaging, in 5. In this cross-sectional analysis, reported syncope/lipothymia was strongly associated with the presence of complete atrioventricular block (10/39 [25.6%] versus 1/80 [1.3%]; OR 27.24, 95% CI 3.34–222.29; Fisher’s exact p < 0.001; Holm’s adjusted p approximately 0.0004). The unadjusted association between syncope/lipothymia and the WPW-labelled diagnosis did not remain statistically significant after Holm’s adjustment. No statistically significant associations were identified between syncope/lipothymia and PSVT or VT. Conclusions: In this pediatric cohort, ambulatory Holter monitoring identified rhythm abnormalities not detected on resting ECG in a substantial proportion of monitored participants and resulted in documented changes in clinical management in approximately half of those monitored. Reported syncope/lipothymia was strongly associated with the presence of complete atrioventricular block in the reconstructed cross-sectional analysis. Because symptom timing during monitoring was not recorded, these findings do not establish that the detected rhythm abnormalities caused the reported symptoms or that symptoms predict future rhythm outcomes. Further studies using prospectively defined symptom–rhythm event recording and longitudinal follow-up are needed to evaluate temporal correlation and prognosis. Full article

Floodplain lake ecosystems around the world have witnessed growing environmental degradation under combined natural climatic variability and anthropogenic activities. Reconstructing their long-term ecological change is vital for lake ecosystem conservation and management. Cladoceran subfossils are used as an important proxy indicator to reconstruct ecological evolution of floodplain lake systems worldwide. The sedimentary record of Zhangdu Lake, a shallow floodplain lake in the middle and lower reaches of the Yangtze River in China, is important for reconstructing more than 150 years of environmental history and tracing the lake ecosystem’s transition from a natural flood-pulse system to a new regime driven by anthropogenic disturbances. Integration of subfossil cladoceran data with other biological proxies (diatoms and testate amoebae) and physicochemical sedimentary proxies successfully identified the period of river–lake disconnection and the associated ecological processes and succession in Lake Zhangdu. An abrupt disconnection of the lake from the Yangtze River in the early 1950s led to a sudden ecological vulnerability together with a drastic community decline. Sequential t-test Analysis of Regime Shifts (STARS) identified cladoceran community shifts in 1966 and 1999, with regime shift index (RSI) values of 1.195 and 3.29, respectively, reflecting multi-phase ecological reorganization following the 1950s disconnection. Differences among the proxies in the timing and magnitude of change and in their apparent drivers reflected group-specific habitat preferences, response thresholds, and trophic positions. This study shows that the assessment of multi-taxa paleoecological indicators can provide a strong evidence base for guiding restoration efforts in degraded floodplain lake ecosystems in China and elsewhere. Full article