Search Results (855)

The Earth’s climate is an open nonlinear system, sustained far from thermodynamic equilibrium by solar radiation and energy and matter exchange among its four major subsystems: atmosphere, ocean, land, and cryosphere. Among these four subsystems, the ocean significantly influences and sustains Earth’s climate over decadal to millennial timescales. Although modern numerical models increasingly capture intricate dynamical details, the fundamental concepts of large-scale ocean variability are less frequently explored. This study revisits ocean circulation through the lens of self-organization theory and synergetics. The key synergetic concepts of mode competition, order parameters, and the slaving principle are interpreted within the framework of general ocean circulation and the Atlantic Meridional Overturning Circulation (AMOC). The Brusselator, a simplified model of a nonlinear dynamical system initially developed in chemical kinetics, serves as a conceptual analog for ocean circulation energy conversion. Despite its high abstraction, this proxy model effectively captures essential bifurcation behaviors, such as Hopf bifurcation transitions and limit-cycle behaviors. This clarifies feedback regulation, instability, and potential regime transitions in the AMOC. The synthesis in this study is intended for an interdisciplinary readership and highlights the broader applicability of synergetic principles to the complex Earth climate system maintained far from equilibrium. Full article

Wind power has experienced rapid development due to its renewable advantages. To address the performance degradation of wind turbines caused by icing in alpine regions, this study integrates field testing and numerical simulation to analyze three key aspects for a 1.5 MW turbine: the underlying mechanism of icing impact, the effect of a de-icing coating on performance during ice-free operation, and the coating’s efficacy under active icing conditions. Results show that ice accretion causes a 25% power loss, induces severe flow separation and vortex shedding, and shifts the separation point forward to 15% chord length. Under ice-free conditions at an average wind speed of 8.3 m/s, the de-icing coating introduces a negligible power deviation of only 0.4%. In extreme cold, ice thickness on the coated blade section was measured at just 4.86 cm. The research demonstrates that de-icing the outer 10 m blade tip section substantially improves performance and confirms that the coating has a minimal aerodynamic footprint during normal operation while providing effective ice mitigation. These findings offer a scientific foundation for optimizing de-icing techniques and support the broader application of such coatings for wind turbines in cold climates. Full article

Disease resistance breeding is an important direction for the genetic improvement of Chinese cabbage. The traditional elite variety ‘Yutian Baojian’ Chinese cabbage is highly regarded for its tall cylindrical head with a pointed tip, tightly twisted wrapper leaves, and sweet taste. However, long-term cultivation has led to a significant decline in its resistance to clubroot caused by Plasmodiophora brassicae. To restore clubroot resistance while maintaining its desirable horticultural traits, this study used the clubroot-susceptible ‘Yutian Baojian’ as the recurrent parent and the resistant donor ‘Shaocai’, which carries the CRd resistance gene, to develop backcross populations. Using marker-assisted selection (MAS), plants were comprehensively screened based on foreground selection with markers tightly linked to the CRd gene, background selection with 73 genome-wide polymorphic markers, and phenotypic evaluation of horticultural traits, including plant height, plant spread, head shape, and soluble solids content. In the BC₁ population, three individuals showing high genetic similarity were selected. From the BC₂ population, four elite individuals were obtained, exhibiting 99.32% genetic similarity, stable clubroot resistance, and typical horticultural characteristics. Furthermore, three homozygous resistant inbred lines (BC₂S₂) with the ‘Yutian Baojian’ phenotype were developed. These results enrich the clubroot-resistant germplasm resources of Chinese cabbage and provide an effective MAS-based strategy for the precise improvement and germplasm innovation of local cultivars. Full article

The skull of a juvenile Chelonia mydas from the beaches of Saint Kitts and Nevis is described using high-resolution photographs and multi-angle radiographs to document the main cranial structures. Standard veterinary anatomical terminology was used, and osteometric measurements were obtained and compared with published data on adult individuals. The investigated juvenile green turtle skull comprises three main regions: the neurocranium, splanchnocranium, and mandible. Noteworthy features include a paired premaxilla at the snout tip, a prominent L-shaped maxilla forming much of the upper jaw, and a robust parietal bone at the skull’s apex. Additional observations include the presence of a lacrimal foramen and a distinct crest on the exoccipital bone. As the study is constrained by reliance on a single juvenile specimen, the findings should be interpreted as preliminary rather than as strong indicators of the population. Morphometric data suggest the juvenile skull reaches about 40% of adult size. Measurements show somewhat greater growth in the posterior region than in the anterior region, which might imply later development or changes in the feeding structures of the skull. Overall cranial proportions remain consistent during growth. Because the metrical study relies on a single juvenile specimen, findings should be interpreted as preliminary rather than as strong indicators of the population. These results, combined, may serve as an entry point for future taxonomic, evolutionary, and clinical research, as comprehensive anatomical knowledge of both local and migratory species, such as Chelonia mydas, is essential for conservation initiatives, veterinary diagnostics, and the study of adaptive morphological changes in isolated island ecosystems. Full article

As a representative large shallow freshwater lake in China, Lake Taihu has suffered from persistent cyanobacterial blooms for a long time. Although intensive restoration actions have been carried out and caused visible improvements, the long-term evolution path and inner driving mechanisms of its ecosystem are still not fully made clear. Based on long-term monitoring data during 2011 to 2024, this study aims to characterize temporal dynamics of the aquatic environment, find out key drivers that shape community succession, and offer a scientific foundation for effective lake management. A series of data about hydrometeorological factors, physicochemical water quality indexes, and biological community data was analyzed by using the Mann–Kendall trend test, Pettitt change-point test, Redundancy Analysis, and correlation heatmaps. The results show that the Taihu ecosystem has experienced a notable regime shift in the past 14 years. First, nitrogenous nutrients reacted quickly to external emission reductions, showing a notable monotonic decline; in comparison, Total Phosphorus and Cyanobacterial Density followed a non-linear “U-shaped” path, with a notable shift happening in 2020, which marks the change from a “deterioration phase” to a “recovery phase.” Second, correlation analysis has confirmed that the lake is mainly phosphorus-limited, and a clear “decoupling” between nitrogen levels and algal outbreaks has taken place. Third, the “10-year Fishing Ban” (initiated in 2020), together with sustained phosphorus control, reduced the competitive exclusion of phytoplankton by cyanobacteria, promoting the recent rebound in biodiversity. This study points out that Lake Taihu has passed a tipping point of ecological restoration, shifting from a turbid “algae-dominated state” to a stable state with higher biodiversity. Future management strategies should put first the mitigation of internal phosphorus loading and adaptive management against extreme climatic events. Full article

As wind power penetration increases, understanding its potential to exercise unilateral market power is critical. This dynamic is particularly relevant in systems like the Colombian wholesale electricity market, which is characterized by a strong dependence on reservoir-based hydropower and a concentrated oligopolistic structure. However, evaluating the threshold where a renewable generator transitions from a price-taker to a price-setter remains challenging. This article explores this strategic transition and its market implications. By isolating a wind agent’s actions against a competitive hydro-thermal fringe using a discretized bi-level approach, we analyze how physical capacity withholding strategies might evolve under varying wind availability and system stress. The findings suggest that wind market power operates across three dynamic regimes: (i) a defensive “Price-Support” strategy during low demand, where capacity may be withheld to prevent price collapses; (ii) a “Scarcity Creation” tipping point during peak demand (observed around a 20% wind availability factor), which appears to incentivize fractional withholding to force expensive thermal dispatch; and iii) a return to “Volume Maximization” when abundant wind renders manipulation economically suboptimal. Ultimately, these results indicate that renewable market power is highly transient and conditional on meteorological profiles, suggesting that regulators could benefit from shifting toward predictive, weather-driven market surveillance. Full article

Spring vegetation phenology is highly sensitive to climate change; however, climate drivers and their threshold responses at the urban scale remain insufficiently and systematically quantified. Focusing on 31 provincial capitals and municipalities in mainland China, this study integrated MODIS MCD12Q2-derived start-of-season (SOS) for spring green-up and TerraClimate climate data (2001–2023) at a 500 m grid resolution. SOS trends were characterized using the Mann–Kendall test and the Theil–Sen slope estimator. Building on these trend metrics, we developed an XGBoost–SHAP framework using the interannual rate of temperature change (tem_slope) and the interannual rate of precipitation change (pre_slope) as input features, to quantify the nonlinear contributions of climate-change rates to SOS trends and to identify key thresholds. Results indicate that the multi-year mean SOS across China’s provincial capitals and municipalities is primarily distributed between approximately DOY 74 and 138, exhibiting a clear spatial pattern of earlier green-up in the south, later green-up in the north, and delayed green-up on plateaus, with pronounced shifts in distribution centers and dispersion among climatic zones and cities. At the city level, the mean SOS trend shows an overall advancing rate of 0.81 d·year⁻¹ (i.e., the average of city-mean Sen slopes across the 31 cities). Pixel-level trend analyses show that advancing and delaying trends commonly coexist within most cities; among pixels with significant or marginally significant SOS trends identified by the Mann–Kendall test (MK p < 0.10) across all cities, advancing and delaying SOS pixels account for 75.02% and 24.98%, respectively. At the city scale, the proportions of advancing versus delaying pixels vary markedly among cities, forming directional structures characterized by advance-dominant, delay-dominant, or bidirectional coexistence patterns. SHAP dependence relationships further reveal that the effects of tem_slope and pre_slope on SOS trends are generally nonlinear and piecewise, with substantial heterogeneity across climate zones and cities. The identified tipping points and associated sensitive ranges collectively delineate spatially differentiated climate-sensitive intervals, which define the nonlinear response boundaries of spring SOS to sustained warming and precipitation changes. This study provides quantitative evidence for regional differences in urban spring phenological responses to climate change across major Chinese cities and offers a methodological reference for identifying actionable climate thresholds in urban greening design and climate-adaptive management. Full article

Concrete structures often develop penetrating cracks due to the initiation and propagation of local cracks during service, which may lead to the fracture and failure of the entire structure. The propagation modes and laws of cracks in structural members are closely related to the safety of the overall structure. Conducting research on crack propagation and predicting crack propagation paths for cracked structures can provide technical support for the safety design and reinforcement of structures. Based on the basic framework of the extended finite element method (XFEM), this paper develops a user-defined element (UEL) for ABAQUS using the level set method, and simulates in a two-dimensional space the crack propagation in concrete beam bending tests with the self-developed UEL and the built-in XFEM module of the software. The solution results of the self-developed UEL are consistent in trend with those of the XFEM module, yet the cracks simulated by the XFEM module can only propagate along element boundaries and cannot cross elements, and the accuracy of its results is highly dependent on mesh size. The crack tip simulated by the self-developed UEL can stay inside the element, and the simulated crack propagation paths show a higher degree of agreement with the experimental results. The correctness of the UEL is verified through comparative analysis with the results of the four-point bending tests of concrete beams and the XFEM module of the software. The UEL developed in this paper can effectively predict the crack propagation paths of concrete beams and reveal the multi-crack propagation laws of concrete beams. Full article

The objective of this study was to use plant models, Allium cepa and Lepidium sativum, to assess the genotoxic effects of the urban particulate matter (PM) collected in a Northern Italian town. Aqueous extracts of different particle sizes (PM_10–3, PM_3–0.5, PM_0.5) were tested alongside the organic extracts through the standard Ames test. The organic particulate matter extracts were subjected to mutagenicity testing in the Salmonella typhimurium strains TA98 and TA100 (without and with metabolic activation), whereas the aqueous extracts were evaluated for genotoxicity in the emerging seedlings of L. sativum and in the root tips of A. cepa bulbs using the comet test to detect the primary DNA damage. Furthermore, the micronuclei frequency was assessed in the bulbs of A. cepa. As expected, the organic extracts of PM_3–0.5 and PM_0.5 induced point mutations in bacteria. The aqueous extracts of the finest fractions caused a significant increase in genotoxic damage in both plant models. These findings indicate that the two plant models (L. sativum seeds and A. cepa bulbs) are able to detect the genotoxicity of aqueous extracts of air pollutants, with many potential advantages as screening-level tools to complement Ames testing for an easier assessment of urban air quality in terms of DNA toxicity. Full article

Tipping points of vegetation transitions represent the thresholds beyond which ecosystems can no longer maintain their stable states. Approaching these critical points may result in declined resilience or irreversible vegetation transitions. Detecting and predicting tipping points remains notably challenging, yet it is essential for guiding the preservation and restoration of terrestrial ecosystems. In this study, lag-1 temporal autocorrelation (AC1) derived from the Kernel Normalized Difference Vegetation Index (kNDVI) was utilized as an early warning signal to monitor resilience dynamics. We developed a new tipping-point detection method by combining land-cover changes, time series segmentations and temporal–spatial filters. We revealed a widespread resilience decline in China, with the dominant transition type as shrub encroachment. Then, two machine learning models coupled with temporal cross-validation were employed to predict the probabilities of abrupt shifts in the near future. The results showed that Random Forest models (accuracy > 70%) demonstrated robustness across lead times. High probabilities of transitions in 2024 were concentrated along the 400 mm annual isohyet, mainly affected by decreased water availability, lower soil acidity and degraded vegetation functions. Our study provides an effective methodology to pinpoint hotspots of vegetation vulnerability and to support the conservation of ecosystems for a sustainable future. Full article

The last few years have been marked by intense debates about the environmental agenda. Forums all over the world are discussing effective actions that can mitigate the effects of human actions on the environment. What was once destined for the imposed policy of developed countries upon emerging ones is now a global policy. Countries, nations, and the corporate world need to adopt urgent measures to make their activities less impactful before the feared tipping point is reached. In this context, hospitals (public and private) take on a fundamental role. As major consumers of water, generators of waste, and sources of high greenhouse gas emissions, hospital ecosystems must re-evaluate their processes to ensure the efficient use of water and energy resources. Although still a recent action, the Green Health concept has been disseminated globally, contributing to the achievement of the Sustainable Development Goals. The present study analyzes the current landscape of Green Health within the Brazilian context, based on a review of scholarly literature. To this end, consultations were made to publications deposited in the period from 2003 to 2025, whose information was processed and used to generate similarity visualization maps. This exploratory study sought to provide a proof of concept by defining a baseline to assess how the term ‘Green Health’ is being appropriated by researchers in Brazil. The results indicate that even though there are some actions in Brazil directed toward Green Health practices, they are modest and lack greater integration, especially regarding research on the topic. Full article

Exercise-induced muscle damage (EIMD) has classically been attributed to localized mechanical disruption following eccentric contractions. Emerging evidence, however, indicates that EIMD represents a systems-level failure of stress integration within skeletal muscle rather than a purely mechanical lesion. Mechanical loading initiates disturbances in intracellular Ca²⁺ homeostasis, which interact with metabolic stress, redox imbalance, and immune activation to form self-reinforcing feedback loops. When compensatory capacity is exceeded, transient injury may shift toward maladaptive remodeling marked by mitochondrial dysfunction, ferroptosis, chronic inflammation, and impaired regeneration. Recent studies identify reactive oxygen species accumulation, iron-dependent lipid peroxidation, dysregulated energy sensing, and aberrant immune polarization as key molecular tipping points governing injury reversibility. Beyond their regenerative role, satellite cells act as integrators of metabolic history and epigenetic memory, linking repetitive injury to reduced muscle adaptability, age-related sarcopenia, and heightened metabolic disease risk. Here, we synthesize evidence from animal models, clinical studies, and multi-omics analyses to establish a systems biology framework for EIMD. We delineate the spatiotemporal interactions among mechanical, metabolic, oxidative, immune, and regenerative modules; identify regulatory nodes that determine adaptive repair versus pathological outcomes; and critically evaluate current nutritional, physical, pharmacological, and regenerative interventions from a mechanism-oriented perspective. Finally, we discuss how multi-omics, digital monitoring, and individualized rehabilitation may enable precision management of EIMD and advance understanding of muscle stress resilience and adaptive limits. Full article

To meet the requirements of effectiveness and strength in actual engineering, based on the dynamic fracture characteristics, the dynamic propagation of orthogonal anisotropic interface cracks in piezoelectric bimaterials was analyzed. By performing Laplace transformation and Fourier transformation on the governing equations, the problem was transformed into a singular integral equation. Using the Chebyshev point method and Laplace inversion, the stress and electric displacement intensity factors at the crack tip of the orthogonal anisotropic interface were obtained. The results show that the crack length affects the dimensionless function. The longer the crack, the larger the dimensionless function. Under certain conditions, the smaller the elastic parameters, the smaller the dimensionless dynamic stress intensity factor. At the same time, the impact time also affects the dynamic crack propagation. With the passage of time, the dimensionless function first increases, then reaches a peak, and finally oscillates and converges to the static value. On this basis, the response surface method was used for analysis and prediction. The R² value of the random forest model is 0.9886, which indicates that the model has high predictive accuracy. When the optimal values of A ($d_1/a$), B ($c_{p}t/a$) and C ($c_{44}^{(2)}/c_{44}^{(1)}$) are 0.4045, 1.6797 and 1.9035 respectively, the stress intensity reaches its maximum value of 1.3375. Full article

Accurate crop yield prediction is paramount for food security amid climate volatility but struggles with complex, nonlinear, and spatially heterogeneous weather–crop interactions. This study develops a novel Spatially Heterogeneous Functional Additive Model (SH-FAM), representing a methodological innovation by uniquely integrating Multivariate Functional Principal Component Analysis (mFPCA) with data-driven climate zoning into a Generalized Additive Model (GAM) framework. The U.S. Midwest was selected as a study area for its pronounced east–west aridity and north–south thermal gradients, forming a natural laboratory for dissecting spatially heterogeneous climate–yield relationships. Unlike traditional models, SH-FAM preserves the continuous temporal structure of weather while allowing nonlinear biological thresholds to vary structurally across distinct agro-climatic zones. Extensive cross-validation shows SH-FAM reduces prediction error by 19% compared to benchmarks and substantially mitigates spatial bias during extreme events like the 2012 drought. We reveal distinct regional sensitivities to Heat and Drought Stress: water-limited western counties face immediate linear yield declines; the high-yielding core exhibits a nonlinear resilience threshold with catastrophic loss beyond a critical tipping point; northern regions show an inverted-U response where moderate warming enhances productivity. These spatially explicit response patterns enable zone-specific adaptation strategies, from drought mitigation in water-limited regions to thermal opportunity exploitation in heat-limited zones, providing actionable guidance for climate-resilient agricultural planning. Full article

Blade icing in cold climates poses significant risks to operational stability and results in substantial power generation deficits. This study establishes and validates an integrated multiscale framework, CFD-OpenFAST-Stacking, to characterize the complex aeroelastic behavior of iced wind turbines and facilitate high-fidelity power forecasting. The methodology utilizes high-fidelity CFD to quantify the aerodynamic degradation of simulated iced airfoils. These data are subsequently coupled with the OpenFAST aeroelastic platform for full-scale turbine simulations to evaluate the system’s dynamic response. A Stacking ensemble learning model is developed by synthesizing these simulation results with historical SCADA data through an innovative data-fusion approach. Numerical findings indicate that icing severely compromises aerodynamic efficiency, inducing a 17.65% reduction in the maximum lift coefficient and a 34.07% escalation in drag at the aerodynamically sensitive blade tip. Consequently, the rated power point is shifted from 10.5 m/s to 13 m/s, with performance degradation most prominent in the low-to-medium wind speed regime. Model validation demonstrates that the data-fusion technique significantly improves predictive robustness, increasing the R² from 0.75 to 0.84 while reducing the RMSE from 37.69 to 17.04. SHAP analysis further identifies generator speed and wind speed as the primary determinants of power variability. This research substantiates the efficacy of bridging physical simulations with data-driven methodologies, providing a robust theoretical framework for performance evaluation in extreme weather environments. Full article