Search Results (577)

With the increasing attention to China’s ecological environment protection and the prominence of lake water environment problems, the impact of soil erosion on lake ecosystems has become an important research topic for regional sustainable development. Based on the CiteSpace bibliometric method, this study systematically analyzed 225 research articles on the impact of soil erosion on the water environment of lakes in China in the core collection of Web of Science from 1998 to 2025, aiming to reveal the research hotspots, evolution trends and regional differences in this field. The results show that China occupies a dominant position in this field (209 papers), and the Chinese Academy of Sciences is the core research institution (93 papers). The research hotspots show obvious policy-driven characteristics, which are divided into slow start periods (1998–2007), accelerated growth periods (2008–2015), explosive growth periods (2016–2020) and stable development periods (2021–2025). A keyword cluster analysis identified nine main research directions, including sedimentation effect (#0 cluster), soil loss (#2 cluster) and nitrogen and phosphorus migration (#11 cluster) in the Three Gorges Reservoir area. The study found that the synergistic effects of climate change and human activities (such as land use change) are becoming a new research paradigm, and the Yangtze River Basin, the Loess Plateau and the Yunnan–Guizhou Plateau constitute the three core research areas (accounting for 72.3% of the total literature). Future research should focus on a multi-scale coupling mechanism, a climate resilience assessment and an ecological engineering effectiveness verification to support the precise implementation of lake protection policies in China. This study provides a scientific basis for the comprehensive management of the soil erosion–lake water environment system, and also contributes a Chinese perspective to the sustainable development goals (SDG6 and SDG15) of similar regions in the world. Full article

The process of social globalization and urbanization has developed rapidly in China, and the tension between economic development and the eco-environment is becoming increasingly tense, posing a major challenge to the sustainable development strategy of the Shandong Peninsula Urban Agglomeration (SPUA). Coordination development between economic development and habitat quality has become essential for preserving ecological stability and advancing long-term regional sustainability. This study constructed the optimal regression model to measure GDP density using night-time lighting data and economic statistical data and calculated habitat quality at the grid scale with the InVEST model. The spatiotemporal dynamics and driving factors of the coupling coordination between economy and habitat quality (EHCCD) were revealed using the coupling coordination degree model and the Geo-detector model. The results show that (1) between 2000 and 2020, the spatial pattern of GDP density has evolved from a single-core to a multi-core networked development. (2) The habitat quality of the SPUA exhibited a spatial pattern high in the east and low in the west, showing a downward trend. (3) The synergistic effect between GDP density and habitat quality was strengthened continuously, showing an overall strengthening tendency. (4) Driving factors’ influence on the EHCCD showed evident differences; socio-economic factors such as built-up area especially had greater explanatory power for the EHCCD; the interaction factors had shifted from socio-economic dominance to synergistic dominance of natural and human factors. This study not only overcomes the limitations imposed by administrative boundaries on assessing inter-regional coupling coordination but also provides fundamental data support for cross-regional cooperation, thereby advancing the sustainable development goal of the SPUA. Full article

With the increase in energy density of power batteries, the risk of thermal runaway significantly increases under extreme working conditions. Therefore, this article proposes a biomimetic liquid cooling plate design based on the fractal structure of fir needle leaf veins, combined with Murray’s mass transfer law, which has significantly improved the heat dissipation performance under extreme working conditions. A multi-field coupling model of electrochemistry fluid heat transfer was established using ANSYS 2022 Fluent, and the synergistic mechanism of environmental temperature, coolant parameters, and heating power was systematically analyzed. Research has found that compared to traditional serpentine channels, leaf vein biomimetic structures can reduce the maximum temperature of batteries by 11.78 °C at a flow rate of 4 m/s and 5000 W/m³. Further analysis reveals that there is a critical flow rate threshold of 2.5 m/s for cooling efficiency (beyond which the effectiveness of temperature reduction decreases by 86%), as well as a thermal saturation temperature of 28 °C (with a sudden increase in temperature rise slope by 284%). Under low-load conditions of 2600 W/m ³, the system exhibits a thermal hysteresis plateau of 40.29 °C. To predict the battery temperature in advance and actively intervene in cooling the battery pack, based on the experimental data and thermodynamic laws of the biomimetic liquid cooling system mentioned above, this study further constructed a support vector machine (SVM) prediction model to achieve real-time and accurate prediction of the highest temperature of the battery pack (validation set average relative error 1.57%), providing new ideas for intelligent optimization of biomimetic liquid cooling systems. Full article

Centrifugal irrigation pumps in Southern Xinjiang face severe performance degradation due to high fine-sediment loads in canal water. This study combines Eulerian multiphase simulations with experimental validation to investigate the coupled effects of sediment size (0.05~0.8 mm) and concentration (5~20%) on hydraulic performance. Numerical models incorporating Realizable k–ε turbulence closure and discrete phase tracking reveal two critical thresholds: (1) particle sizes ≥ 0.4 mm trigger a phase transition from localized disturbance to global flow disorder, expanding low-pressure zones by 37% at equivalent concentrations; (2) concentrations exceeding 13% accelerate nonlinear pressure decay through collective particle interactions. Velocity field analysis demonstrates size-dependent attenuation mechanisms: fine sediments (≤0.2 mm) cause gradual dissipation via micro-scale drag, while coarse sediments (≥0.6 mm) induce “cliff-like” velocity drops through inertial impact-blockade chains. Experimental wear tests confirm simulation accuracy in predicting erosion hotspots at impeller inlets/outlets. The identified synergistic thresholds provide critical guidelines for anti-wear design in sediment-laden irrigation systems. Full article

The seismic bearing capacity of water-saturated composite foundations adjacent to slopes is critical for engineering safety, yet it is significantly influenced by complex factors such as earthquakes and heavy rainfall. This paper establishes a failure mechanism model that involves both reinforced and non-reinforced zones, comprehensively considering the synergistic effects of seismic force, pore water pressure and group pile replacement rate, and thus addressing the issue that existing models struggle to account for the coupling effects of multiple factors. Based on the principle of virtual work, a general solution for ultimate bearing capacity is derived, and the optimal solution is obtained using the MATLAB R2023a exhaustive method. Findings reveal that pile group support substantially enhances bearing capacity: the improvement becomes more pronounced with higher soil strength parameters (φ, c) and replacement ratios. When the seismic acceleration coefficient increases from 0 to 0.3, the bearing capacity of the unreinforced foundation decreases by approximately 61.6% (from 134.71 kPa to 51.83 kPa), while group pile support can increase the bearing capacity by 433.2%. Notably, when soil strength is inherently high, the marginal benefit of pile group reinforcement diminishes. A case study in Fuzhou validates through numerical simulation that pile groups improve foundation stability by altering energy dissipation distribution, with the discrepancy between theoretical calculations and simulation results within 10%. The research results can directly guide the design of saturated composite foundations near slopes in earthquake-prone areas (such as Fujian and Guangdong) and enhance the seismic safety reserve by optimizing the replacement rate of group piles (recommended to be 0.2~0.3). Full article

With the advancement of oil and gas exploration and development technologies into deeper and ultra-deep reservoirs, complex geological conditions here render them highly susceptible to severe lost circulation. However, conventional bridging plugging methods struggle with large-sized lost circulation channels, while chemical gel plugging faces challenges such as low success rates and insufficient pressure-bearing capacity. To address this, a novel leak plugging method combining bridging and gel plugging is proposed herein. From structural stability and mechanical properties perspectives, the enhancing effect of nanomaterials on the gel system is revealed, and the synergistic mechanism of gel-bridging coupled plugging is elucidated. For the experimental setup, orthogonal experiments determined a base formulation with controllable gelation time: 10 wt% main agent, 2 wt% crosslinking agent, and a 1:3 pH regulator ratio. Introducing 1.0 wt% nanosilica enhanced gel properties, achieving 30 N strength at 120 °C aging. An optimized walnut shell bridging agent constructed the supporting skeleton, yielding a coupled plugging formulation with up to 8 MPa pressure for a 7 mm fracture. Lost circulation volume is controlled at 163 mL, outperforming single plugging methods. Research results demonstrate gel-bridging coupled plugging’s advantages for large fractures, providing new technical insights for severe lost circulation field construction. Full article

Digital transformation enhances the processes and efficiency of enterprise green innovation through technological empowerment, while the ESG framework guides the direction and value of such innovation via institutional norms. However, existing studies often examine digital transformation and ESG in isolation, resulting in insufficient exploration of their synergistic effects. Based on data from manufacturing high-tech enterprises, this study employs necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (FsQCA) to systematically examine the synergistic effects of digital transformation and ESG on enterprise green innovation. The key findings are as follows: (1) While no single factor constitutes a necessary condition for high green innovation, the elements of social governance and digital management demonstrate universal applicability in enabling enterprises to achieve high levels of green innovation. (2) The dual-core-driven configuration achieves green innovation through the synergy between social governance and digital management, with its specific pathways varying according to the coordinated combinations of auxiliary factors. This delineates three distinct types, including compliance-oriented, environmentally empowered, and comprehensively balanced pathways. (3) The digitally driven configuration establishes an endogenous linkage between technological innovation and green development through the deep coupling of digital technology R&D and application. (4) The low green innovation configuration exhibits insufficient efficacy due to either isolated single elements or the absence of digital management, resulting in suboptimal green innovation performance. This study empirically demonstrates that the effective advancement of green innovation fundamentally relies on the endogenous dynamics of social governance, the technological underpinnings of digital management, and the systemic synergy among key elements, offering significant strategic implications for enterprises to develop differentiated green innovation approaches. Full article

Low-salinity waterflooding (LSWF) enhances oil recovery at low cost in carbonate reservoirs, but its effectiveness requires the precise control of injected water chemistry and interaction with reservoir minerals. This study specifically investigates carbonated low-salinity waterflooding (CLSWF), where dissolved ${\mathrm{CO}}_2$ modulates geochemical processes. This study develops an integrated transport model coupling geochemical surface complexation modeling (SCM) with multiphase compositional dynamics to quantify wettability alteration during CLSWF. The framework combines PHREEQC-based equilibrium calculations of the Total Bond Product (TBP)—a wettability indicator derived from oil–calcite ionic bridging—with Corey-type relative permeability interpolation, resolved via COMSOL Multiphysics. Core flooding simulations, compared with experimental data from calcite systems at 100 ${}^{\circ }\mathrm{C}$ and 220 bar, reveal that magnesium ([${\mathrm{Mg}}^{2+}$]) and sulfate ([${\mathrm{SO}}_4^{2-}$]) concentrations modulate the TBP, reducing oil–rock adhesion under controlled low-salinity conditions. Parametric analysis demonstrates that acidic crude oils (TAN higher than 1 $\mathrm{m}$$\mathrm{g}$ KOH/$\mathrm{g}$) exhibit TBP values approximately $2.5 \mathrm{times}$ higher than those of sweet crudes, due to carboxylate–calcite bridging, while pH elevation (higher than 7.5) amplifies wettability shifts by promoting deprotonated ${\mathrm{-COO}}^{-}$ interactions. The model further identifies synergistic effects between ([${\mathrm{Mg}}^{2+}$]) (ranging from 50 to 200 mmol/kgw) and ([${\mathrm{SO}}_4^{2-}$]) (higher than 500 mmol/kgw), which reduce (${\mathrm{Ca}}^{2+}$)-mediated oil adhesion through competitive mineral surface binding. By correlating TBP with fractional flow dynamics, this framework could support the optimization of injection strategies in carbonate reservoirs, suggesting that ion-specific adjustments are more effective than bulk salinity reduction. Full article

In the field of cognitive workload assessment for aerospace training, existing methods exhibit significant limitations in unimodal feature extraction and in leveraging complementary synergy among multimodal signals, while current fusion paradigms struggle to effectively capture nonlinear dynamic coupling characteristics across modalities. This study proposes DST-Net (Cross-Modal Downsampling Transformer Network), which synergistically integrates pilots’ multimodal physiological signals (electromyography, electrooculography, electrodermal activity) with flight dynamics data through an Anti-Aliasing and Average Pooling LSTM (AAL-LSTM) data fusion strategy combined with cross-modal attention mechanisms. Evaluation on the “CogPilot” dataset for flight task difficulty prediction demonstrates that AAL-LSTM achieves substantial performance improvements over existing approaches (AUC = 0.97, F1 Score = 94.55). Given the dataset’s frequent sensor data missingness, the study further enhances simulated flight experiments. By incorporating eye-tracking features via cross-modal attention mechanisms, the upgraded DST-Net framework achieves even higher performance (AUC = 0.998, F1 Score = 97.95) and reduces the root mean square error (RMSE) of cumulative flight error prediction to 1750. These advancements provide critical support for safety-critical aviation training systems. Full article

Assessing habitat quality and quantifying human disturbance are fundamental prerequisites for ecological conservation. However, existing studies predominantly focus on single dimensions. There is an urgent need to integrate habitat quality and human disturbance, and quantify their spatially coupled coordination relationships to address the disconnect between them in current research. As a critical ecological reserve in southeastern China, Fujian Province faces threats of ecological degradation. This study employed the InVEST model to evaluate habitat quality in Fujian from 1980 to 2020, utilized a human disturbance index to quantify spatiotemporal patterns of anthropogenic activities, analyzed their changes using landscape indices, and applied coupling coordination analysis to examine their interrelationships. Machine learning and geographically weighted regression were further integrated to identify driving factors of coupling coordination patterns. The results showed that: (1) Habitat quality remained relatively high while human disturbance levels stayed low throughout 1980–2020, though both showed gradual deterioration over time, particularly during 2010–2020, with riverine and coastal eastern regions exhibiting the lowest habitat quality and highest disturbance levels. (2) Coupling coordination relationships predominantly exhibited synergy, with moderate imbalance zones concentrated in the eastern coastal areas. Temporally, regions with lower imbalance expanded significantly during 2010–2020. (3) Landscape metric analysis revealed declining dominance of high-quality habitat/low-disturbance/synergistic zones, contrasted by increased fragmentation of low-quality habitat/high-disturbance/imbalanced zones. (4) Socioeconomic factors exerted stronger influence on coupling coordination patterns than natural environmental variables, proximity to urban areas, road density, and nighttime light indices. Each driver displayed spatially variable positive/negative effects. The results enhance our understanding of human–nature sustainable development dynamics, urban expansion–ecological conservation trade-offs, and provide methodological insights for regional ecological management and achieving sustainable development goals. Full article

Ecological drought in terrestrial systems is a vegetation-functional degradation phenomenon triggered by the long-term imbalance between ecosystem water supply and demand. This process involves nonlinear coupling of multiple climatic factors, ultimately forming a compound ecological stress mechanism characterized by spatiotemporal heterogeneity. Based on meteorological and remote sensing datasets from 1982 to 2022, this study identified the spatial distribution and temporal variability of ecological drought in China, elucidated the dynamic evolution and return periods of typical drought events, unveiled the scale-dependent effects of climatic factors under both univariate dominance and multivariate coupling, as well as deciphered the response mechanisms of ecological drought to meteorological drought. The results demonstrated that (1) terrestrial ecological drought in China exhibited a pronounced intensification trend during the study period, with the standardized ecological water deficit index (SEWDI) reaching its minimum value of −1.21 in February 2020. Notably, the Alpine Vegetation Region (AVR) displayed the most significant deterioration in ecological drought severity (−0.032/10a). (2) A seasonal abrupt change in SEWDI was detected in January 2003 (probability: 99.42%), while the trend component revealed two mutation points in January 2003 (probability: 96.35%) and November 2017 (probability: 43.67%). (3) The drought event with the maximum severity (6.28) occurred from September 2019 to April 2020, exhibiting a return period exceeding the 10-year return level. (4) The mean values of gridded trend eigenvalues ranged from −1.06 in winter to 0.19 in summer; 87.01% of the area exhibited aggravated ecological drought in winter, with the peak period (88.51%) occurring in January. (5) Evapotranspiration (ET) was identified as the dominant univariate driver, contributing a percentage of significant power (POSP) of 18.75%. Under multivariate driving factors, the synergistic effects of ET, soil moisture (SM), and air humidity (AH) exhibited the strongest explanatory power (POSP = 19.21%). (6) The response of ecological drought to meteorological drought exhibited regional asynchrony, with the maximum correlation coefficient averaging 0.48 and lag times spanning 1–6 months. Through systematic analysis of ecological drought dynamics and driving mechanisms, a dynamic assessment framework was constructed. These outcomes strengthen the scientific basis for regional drought risk early-warning systems and spatially tailored adaptive management strategies. Full article

Urban lifeline Natech events are coupled systems composed of multiple risks and entities with complex dynamic transmission chains. Predicting risk evolution probabilities is the core task for achieving the safety management of urban lifeline Natech events. First, the risk evolution mechanism is analyzed, where urban lifeline Natech events exhibit spatial evolution characteristics, which involves dissecting the parallel and synergistic effects of risk evolution in spatial dimensions. Next, based on fitting marginal probability distribution functions for natural hazard and urban lifeline risk evolution, a Multi-dimensional Copula (MdC) function for the joint probability distribution of urban lifeline Natech event risk evolution is constructed. Building upon the MdC function, a Markov Chain Monte Carlo (MCMC) model for predicting risk evolution probabilities of urban lifeline Natech events is developed using the Metropolis–Hastings (M-H) algorithm and Gibbs sampling. Finally, taking the 2021 Zhengzhou ‘7·20’ catastrophic rainstorm as a case study, joint probability distribution functions for risk evolution under Rainfall-Wind speed scenarios are fitted for traffic, electric, communication, water supply, and drainage systems (including different risk transmission chains). Numerical simulations of joint probability distributions for risk evolution are conducted, and visualizations of joint probability predictions for risk evolution are generated. Full article

Against the backdrop of accelerating global energy transition, developing high-performance energy-storage systems is crucial for achieving carbon neutrality. Traditional electrode materials are limited by a single densification storage mechanism and low conductivity, struggling to meet demands for high energy/power density and a long cycle life. Carbon/high-entropy alloy nanocomposites provide an innovative solution through multi-component synergistic effects and cross-scale structural design: the “cocktail effect” of high-entropy alloys confers excellent redox activity and structural stability, while the three-dimensional conductive network of the carbon skeleton enhances charge transfer efficiency. Together, they achieve synergistic enhancement via interfacial electron coupling, stress buffering, and dual storage mechanisms. This review systematically analyzes the charge storage/attenuation mechanisms and performance advantages of this composite material in diverse energy-storage devices (lithium-ion batteries, lithium-sulfur batteries, etc.), evaluates the characteristics and limitations of preparation techniques such as mechanical alloying and chemical vapor deposition, identifies five major challenges (including complex and costly synthesis, ambiguous interfacial interaction mechanisms, lagging theoretical research, performance-cost trade-offs, and slow industrialization processes), and prospectively proposes eight research directions (including multi-scale structural regulation and sustainable preparation technologies, etc.). Through interdisciplinary perspectives, this review aims to provide a theoretical foundation for deepening the understanding of carbon/high-entropy alloy composite energy-storage mechanisms and guiding industrial applications, thereby advancing breakthroughs in electrochemical energy-storage technology under the energy transition. Full article

Motivated by the rapid development of SERS technology, trace detection of various viruses in the sewage and body fluid environments and accurate positive and negative diagnosis of detection samples can be achieved. However, evaluating the environmental survival ability of viruses based on SERS technology remains an unexplored issue, but holds significant guiding significance for effective epidemic prevention and control as well as inactivation treatment. In this work, Au nanoarrays were fabricated on silicon substrates through a simple Ar ion sputtering route as ultra-sensitive SERS chips. With the synergistic contribution of the “lightning rod” effect and the enhanced coupling surface plasmon caused by the nanoarrays, the ultra-sensitive detection of SARS-CoV-2 S protein with a concentration of 1 pg/mL and SERS enhancement factor of 4.89 × 10⁹ can be achieved. Exploration of the environmental survival ability of the SARS-CoV-2 virus indicates that the Raman activity of SARS-CoV-2 S protein exhibited higher temperature tolerance from 0 °C to 60 °C than SARS-CoV S protein, suggesting that the SARS-CoV-2 virus has less temperature influence from increasing air temperature than the SARS-CoV virus to a certain extent, which explains the seasonal recurrence pattern and regional transmission pattern of the novel coronavirus that are different from the SARS virus. Full article

This study investigated the influence of manganese (Mn) on microstructure evolution and property optimization in Al-0.6Mg-0.58Si-0.24Fe-xMn alloys under both as-cast and hot-extruded conditions. The balance mechanisms of Mn in tensile properties and electrical conductivity of Al-Mg-Si alloy were elucidated, achieving synergistic optimization of strength-elongation-conductivity. For non-equilibrium solidified as-cast alloys, JMatPro simulations coupled with Fe-rich phase size statistics reveal an inhibitory effect of Mn on β-Al₅FeSi phase formation. Matthiessen’s rule analysis quantitatively clarifies Mn-induced resistivity variations through solid solution and phase morphology modifications. In hot-extruded alloys, TEM characterization was used to analyze the structure of Al-Fe-Mn-Si quaternary compounds and clarify their combined effects with typical Mg₂Si phases on dislocation and subgrain configurations. The as-cast Al-0.6Mg-0.58Si-0.24Fe-0.18Mn alloy demonstrate comprehensive properties with ultimate tensile strength, elongation and electrical conductivity. The contributions of dislocations, grain boundaries and precipitates to resistivity are relatively minor, so the main source of resistivity in hot-extruded alloys is still Mn. The hot-extruded alloy containing 0.18 wt.% Mn still has better properties, with a tensile strength of 176 MPa, elongation of 24% and conductivity of 48.07 %IACS. Full article