Search Results (4,670)

To address the poor adaptability and rigid initiation modes of the loitering munition fuze in complex environments and the inadequacy of single fuzzy control against strong interference, this paper proposes a dual-loop adaptive reconfiguration control method. The architecture integrates the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm with fuzzy logic. The inner loop uses TD3 to dynamically optimize fuzzy scaling factors based on real-time interference and state deviations. Concurrently, the outer loop utilizes a Fuze Readiness Index (FRI) and a finite state machine to manage real-time multi-modal mission switching (e.g., proximity, delay, and airburst) and reverse safety-state conversions. Co-simulations under non-stationary composite interference show that the proposed method reduces the burst height RMSE by 82.4% and 61.6% compared with the fixed-threshold and standard fuzzy baselines under the considered non-stationary composite interference setting, respectively. The false alarm rate (FAR) is reduced to 0.15%, and the reconfiguration response time under sudden interference is shortened to 12 ms. Even under extreme conditions, such as 400 ms sensor signal loss, the relative error remains within 5%. These simulation results demonstrate the potential of the proposed architecture to improve precision, responsiveness, and robustness under dynamic interference conditions and show good robustness to intermittent observation loss within the simulated operating envelope. Full article

The sponge city pilot policy (SCP) is a green infrastructure initiative that integrates ecological stormwater management, land-use planning, and urban sustainability goals. This study employs the super-efficiency slack-based measure (SBM) model to evaluate the green total factor productivity (GFP) of 278 prefecture-level and above cities in China from 2010 to 2022. It then applies a difference-in-differences (DID) model to identify the causal effect of the SCP on urban GFP while further examining transmission mechanisms and heterogeneous policy effects. The empirical findings show that: (1) the SCP significantly enhances urban GFP, with pilot cities exhibiting an average increase of approximately 6.08% relative to non-pilot cities, indicating broader medium- to long-term ecological–economic co-benefits beyond the policy’s immediate hydrological objectives; (2) the policy effect is more pronounced in cities with stronger economic foundations, larger urban scales, greater environmental governance pressure, weaker resource dependence, and more favorable locational conditions; and (3) the SCP promotes industrial structure transformation (IST) and green technological innovation (GTI), which jointly mediate the relationship between ecological infrastructure and green productivity. Drawing on ecological modernization theory and structural change theory, this study explains how ecological infrastructure, as a techno-structural reform mechanism, can internalize environmental externalities, stimulate innovation, and facilitate sustainable urban transformation. These findings provide evidence that green infrastructure policies can generate both ecological and economic co-benefits, offering useful insights for climate-resilient and sustainable urban planning. Full article

Methane (CH₄) is a major component of natural gas and a potent greenhouse gas. Increasing atmospheric methane concentrations are attributed to emissive anthropogenic activities by an average of 13 ppb per yr since 2020 and are linked to a changing global climate. Mitigating CH₄ emissions from oil and gas production sites has recently become a target to reduce overall greenhouse gas emissions; however, monitoring the efficacy of mitigation strategies depends on accurate quantification of CH₄ emissions at the facility-level. Near-field quantification of methane (CH₄) emissions from oil and gas (O&G) facilities remains challenging due to the effects of atmospheric variability and sensor configuration on atmospheric dispersion models. This study evaluates the performance of two atmospheric dispersion models, the Gaussian plume (GP) and backward Lagrangian stochastic (bLS), by comparing calculated CH₄ emissions to controlled single-point emissions between 0.4 and 5.2 kg CH₄ h⁻¹. Emissions were calculated by both models using 121 individual sets of measurements comprising five-minute averaged downwind methane mixing ratios and matching meteorological data. The comparison shows that the bLS approach achieved a higher proportion of emission estimates within a factor of two (FAC2) of the known emission rates compared to the GP approach. The emissions calculated by the bLS model also had a lower multiplicative error and reduced bias relative to GP. Other error-based metrics further confirmed the bLS model performed better, as it yielded lower RMSE and MAE than GP. Statistical analysis of the emission data shows that the lateral and vertical alignment of the source and the sensor plays a critical role in emission estimations, as measurements made closer to the plume centerline and at a distance between 40 and 80 m downwind yielded the best FAC2 agreement. High wind meander degraded the ability of both approaches to generate representative emissions, particularly with the GP approach, as it violates the modeling approach’s assumption of steady-state emissions. Data suggest emissions calculated by the bLS model are comprehensively in better agreement, but the computational demands of the modeling approach and integration into fenceline systems limit real-time applicability. While these results provide insight into model performance under controlled near-field conditions, their applicability to more complex or heterogeneous oil and gas production environments (e.g., the regions Marcellus or Unita Basins) remains limited and uncertain. Full article

Based on an extended Theory of Planned Behavior (ETPB), this study investigated how perceived social sustainability shaped individuals’ intentions to use fitness facilities. Specifically, it examined the moderating role of social sustainability in the relationships between key TPB determinants and fitness facility use intention. Survey data were collected from 195 adults living in metropolitan areas and were analyzed using partial least squares structural equation modeling (PLS-SEM). The results revealed that perceived social sustainability exerted a dual moderating influence on intention formation by strengthening the effect of subjective norm while attenuating the effect of perceived behavioral control on use intention. Higher levels of perceived social sustainability (SS) strengthened the relationship between subjective norm (SN) and fitness facility use intention with a medium effect size, while attenuating the relationship between perceived behavioral control (PBC) and use intention with a small effect size. In contrast, no significant moderating effect was observed in the relationship between attitude and use intention. These findings suggest that value-oriented considerations related to social responsibility and community well-being enhanced socially driven motivations while reducing the relative influence of control-based factors. By demonstrating the conditional effects of perceived social sustainability within the TPB framework, this study extended existing research on health-related behavioral intentions. The findings further highlight the importance of incorporating community-oriented and socially responsible practices into fitness facility management to foster sustainable user engagement. Full article

To investigate concrete drying shrinkage in high-altitude environments, moisture evaporation and shrinkage rates were examined under combined curing regimes of four temperatures (40 °C, 20 °C, 0 °C, −10 °C) and three relative humidities (RH40%, RH60%, RH80%). Curing temperature and humidity primarily regulate shrinkage deformation by altering the internal moisture evaporation rate. Both evaporation and shrinkage rates exhibited a rapid initial increase, followed by deceleration, and finally stabilization with increasing age. A strong positive correlation was observed between these two parameters. The high-temperature and low-humidity condition (40 °C, RH40%) induced the most severe shrinkage. Four machine learning algorithms (XGBoost, RF, ANN, and KNN) were used to construct prediction models. After hyperparameter optimization and cross-validation, the RF models exhibited superior generalization and robustness (test set R² > 0.94). The model accurately captures the complex non-linear relationship between environmental parameters and shrinkage. SHAP analysis on the optimal models identified the moisture evaporation rate as the primary driving factor. The analysis quantified the non-linear contributions of temperature and age, alongside the inhibitory effect of humidity. The study verified the consistency between data-driven models and physical mechanisms. This study elucidates the shrinkage mechanism under extreme conditions. It provides a reliable reference for crack control and life prediction in high-altitude engineering. Full article

Climate variability is a major driver of belowground microbial assembly, yet its effects on rhizosphere microbiomes in perennial crops remain insufficiently resolved. We investigated how macroclimatic oscillations associated with the El Niño–Southern Oscillation (ENSO) influence bacterial communities in the rhizosphere of Coffea arabica. Using 16S rRNA amplicon sequencing across five sampling campaigns covering El Niño, La Niña, and Neutral phases in the Colombian Andes, together with multivariate and variance-partitioning analyses, we quantified the relative contributions of climatic and edaphic factors to rhizosphere community structure. PERMANOVA across three dissimilarity metrics showed that the ENSO explained 11–17% of β-diversity, exceeding the contribution of intra-annual seasonality (6–12%). Ordination analyses indicated moderate compositional differentiation with considerable overlap among ENSO groups, consistent with gradual community turnover under contrasting hydroclimatic conditions. Rainfall and soil pH emerged as the main edaphic correlates of community composition, although their independent effects were no longer significant after accounting for the ENSO phase and season. Despite these shifts, the rhizosphere remained dominated by Acidobacteriota, Actinobacteriota, and Proteobacteria, and a prevalence-defined core microbiome (genera detected in ≥85% of samples) was maintained across climatic phases and seasons. These results indicate that, within the explained fraction of variation, macroclimatic variability contributed more to rhizosphere bacterial turnover than local edaphic heterogeneity, while a conserved prevalence-defined bacterial core may contribute to taxonomic stability in climate-sensitive coffee systems. Full article

Fog is a near-surface weather phenomenon with low visibility that significantly threatens transportation safety. Understanding the spatiotemporal evolution and formation mechanisms of fog is essential for improving fog forecasting and warning services to reduce related casualties and economic losses. This study examines consecutive dense fog events with long duration and high intensity that occurred along the Ma-Zhao Expressway in northeastern Yunnan from 24 to 30 October 2022. Yunnan is a typical low-latitude plateau region in southwestern China with complex terrain and diverse climates, leading to particularly complicated fog formation processes. Correlation analysis indicates that thermal and vapor factors show stronger correlations with visibility, with correlation coefficients reaching 0.68 for vertical temperature difference and −0.63 for surface relative humidity, both significant at the 99% confidence level. These values are notably higher than those of dynamic factors such as near-surface wind speed, which yields a correlation coefficient of 0.47. The results confirm the dominant role of thermal and vapor conditions in the formation and maintenance of these dense fog events, together with favorable conditions including near-surface air saturation, weak dynamic processes, and a temperature inversion in the lower troposphere. Standardized anomaly analysis reveals obvious atmospheric anomalies during the fog episodes. A strong southerly wind anomaly appears in the lower troposphere, driven by a cyclone over the Philippines and an anomalous anticyclone east of Yunnan. This southerly transport delivers warm and moist air toward the Ma-Zhao Expressway, accompanied by a positive temperature anomaly of 1.7, standard deviations near 700 hPa and a positive specific humidity anomaly of more than 2 standard deviations in the lower troposphere. These conditions favor the development of temperature inversions and atmospheric saturation, further promoting the occurrence and persistence of consecutive dense fog events. This study clarifies the key effects of thermal and vapor conditions as well as low-level southerly wind anomalies on dense fog over the Yunnan low-latitude plateau. These conclusions deepen the understanding of fog formation mechanisms in complex plateau terrain and provide a scientific reference for fog forecasting and early warning along mountain expressways in similar low-latitude plateau regions. Full article

Ultra-high-performance concrete (UHPC) is widely used due to its strength, toughness, and durability. Shrinkage issues are the primary cause of concrete cracking and one of the main factors limiting the widespread application of UHPC in structural engineering. The shrinkage properties of UHPC vary depending on curing conditions. Research indicates that after thermal curing, the pore structure of UHPC is optimized, resulting in a significant reduction in shrinkage values. Based on the superposition principle, temperature creep coefficients and humidity creep coefficients are introduced to correct the temperature and humidity in the test environment to a constant temperature (20 °C) and humidity (75% relative humidity). The B3 coefficient of variation method was used to compare five different creep prediction models. The CEB-FIP2010 model was selected as the benchmark creep model, and curing condition coefficients were incorporated into the model to establish a comprehensive creep calculation model considering curing conditions. After 550 days of steam curing, the shrinkage strain of the UHPC specimens was approximately 28.9% of that of the uncured specimens. The additional creep deformation caused by temperature and humidity in the uncured and steam-cured specimens accounted for approximately 10% and 20% of the total creep deformation over 550 days, respectively. The strain development rates for both tensile and compressive strains in steam-cured specimens were lower than those in uncured specimens. A ten-year long-term creep simulation of UHPC precast joint beams was conducted using the finite element software Midas-Fea, and the comparison results validated the reliability of the comprehensive creep model. Full article

This paper examines economic and institutional convergence between EU Core, EU New, and Western Balkan countries over the period 2004–2023 using a comprehensive panel dataset and multiple convergence frameworks. Evidence of absolute β-convergence is found, although at a slow pace, while conditional specifications show that structural and institutional factors explain growth differences; institutional quality appears to affect growth primarily through direct effects rather than through significant interaction-based β-convergence. A Principal Component Analysis-based Institutional Index (PC1) explains 90% of the variance in institutional quality, highlighting its role in shaping cross-country growth differentials rather than directly influencing convergence speed. Group-specific models reveal heterogeneous convergence paths across European regions. EU Core economies exhibit relatively stable convergence patterns, reflecting their proximity to steady-state income levels. In contrast, EU New and Cohesion Economies do not display statistically significant β-convergence, suggesting that catch-up processes are uneven and not uniformly driven by initial income differences. Western Balkan economies show weak and limited convergence patterns, reflecting persistent structural and institutional constraints. Robustness tests (FE/RE, Hausman, VIF, Breusch–Pagan, residual diagnostics) confirm the validity of the results. Findings suggest an important role of institutional quality in supporting long-term growth and the accession process of the Western Balkans. Policy implications highlight the importance of governance reforms, human capital development, and EU integration mechanisms in accelerating convergence. Full article

Exploring the coordinated development of the tourism economy and ecological environment in China’s border areas is of great significance for promoting high-quality tourism development and ecological barrier construction in these regions. This study constructed an evaluation index system for the tourism economy and ecological environment in China’s border provinces and employed the comprehensive index method as well as coupling coordination, interactive coercion, and obstacle degree models to analyze the basic indices, coupling coordination relationship, interactive coercion relationship, and major obstacle factors of the tourism economy and ecological environment from 2009 to 2019. The results show the following. (1) The tourism economy index increased rapidly, presenting a distribution pattern of “high in the southwest, second in the northeast, and low in the northwest”; the ecological environment index fluctuated but rose, showing a distribution pattern of “single-pole leading and convergence among multiple provinces”, with Xizang maintaining a relatively good level. (2) The coupling coordination degree between the tourism economy and ecological environment steadily improved, with Liaoning, Yunnan, Xizang, and Guangxi achieving relatively good coordination levels. (3) The relationship between the tourism economy and ecological environment exhibited an evolutionary process of “stress first, then coordination”, characterized by spatial heterogeneity; therefore, each province should optimize the interactive coercion relationship according to local conditions. (4) Ecological environment state, tourism economic efficiency, and tourism economic scale are the main obstacle factors affecting the coordination between tourism and ecology. Regarding specific indicators, most provinces share common characteristics in their obstacle factors, while Liaoning and Xizang display unique particularities. Full article

In this study, we determined the distribution profile of different mineral fertilizers applied by a DJI Agras T50 remotely piloted aircraft (RPA) under different flight heights and speeds. The experiment was conducted in a randomized block design in a 3 × 3 × 3 factorial scheme, involving three fertilizers (urea, potassium chloride, and single superphosphate), three flight heights (4, 6, and 8 m), and three flight speeds (16, 18, and 20 km h⁻¹). The methodology included laboratory characterization of the physical properties of the fertilizers and the determination of the transverse distribution profile under field conditions. The data were processed using Adulanço software version 4.0 and subjected to statistical analyses (p-value < 0.05). The results indicated that flight height stood out as the main factor, increasing the total and effective swath widths; however, it reduced deposition per unit area and increased the relative error as height increased. The combination of 20 km h⁻¹ with flight heights of 4 and 6 m maximized deposition within the effective swath and provided theoretical operational capacities greater than 8 ha h⁻¹, regardless of the fertilizers. Correlation analysis indicated an operational trade-off, showing that fertilizers with different physical properties respond differently to flight height and flight speed. Full article

Despite the growing adoption of Ti6Al4V-ELI made by Laser Powder Bed Fusion (LPBF) in tribologically demanding applications, the influence of hybrid nanoparticle additives on its lubrication behavior under starved contact conditions remains insufficiently explored. The tribological performance of Ti6Al4V was investigated under starved boundary-to-mixed lubrication conditions using engine oil modified with Ag-doped TiO₂ nanoparticles. Double-scan LPBF-fabricated discs were tested in a ball-on-disc configuration against AISI 52100 bearing steel using a TRB³ tribometer. Nanolubricants were prepared by dispersing TiO₂ and Ag–TiO₂ nanopowders with different Ag⁺/Ti⁴⁺ ratios (0.5%, 1.5%, and 2.5%) in SAE 10W-40 engine oil at a constant nanoparticle concentration of 0.05 wt%. Comprehensive physicochemical characterization of the nanopowders and nanolubricants was performed through structural, chemical, optical, morphological, rheological, and stability analyses. Tribological experiments were conducted following a full-factorial design combining three normal loads (5–15 N), three sliding speeds (0.10–0.20 m·s⁻¹), and four lubricant formulations. The steady-state coefficient of friction ranged between 0.281 and 0.359, while the specific wear rate varied from 2.81 × 10⁻⁴ to 4.83 × 10⁻⁴ mm³·N⁻¹·m⁻¹. The contact temperature rise remained relatively moderate, within the interval of 1.9–9.4 °C. Among the investigated formulations, the lubricant containing 1.5% Ag–TiO₂ exhibited the lowest friction coefficient, whereas the formulation with the highest Ag content showed improved stability of tribological performance across the investigated operating domain. These results indicate that Ag-modified TiO₂ nanoparticles are consistent with the formation of protective tribofilms and contribute to the stabilization of friction, wear, and thermal behavior under starved lubrication conditions. ANOVA confirmed that sliding speed and the load–lubricant interaction are the dominant factors governing friction and wear, while normal load controls the thermal response. These findings support the use of Ag–TiO₂ nanolubricants as a viable strategy for stabilizing interfacial behavior in LPBF-fabricated titanium components operating under starved lubrication conditions. Full article

Neonatal hypoxic ischemic encephalopathy (HIE) is a common birth complication that can cause death or lifelong disabling conditions like cerebral palsy, epilepsy, and autism. It is well established that maternal infection and inflammation are significant risk factors for HIE but reasons for this increase in neurological risk to the offspring remain unknown. Inflammation or infection are associated with epigenetic changes and may contribute to the increased risk of neurodevelopmental disability in exposed offspring. Here, we analyzed and compared DNA methylation patterns in brain monocytes isolated from control, maternal immune activation (MIA), and an inflammation sensitized HIE (IS-HIE) CF-1 mouse model at postnatal day 7. We found that maternal inflammation induced significant methylation differences in neonates relative to control samples in both MIA and IS-HIE samples with no significant differences identified between the MIA and IS-HIE groups. MIA samples showed hypermethylation at loci involving craniofacial development and transcription factors important for regulating neurodevelopment and immune function. MIA samples also demonstrated significant hypermethylation at multiple mitochondrial genome CpGs. These findings suggest that maternal inflammation induces epigenetic alterations in fetal brain immune cells that are detectable in neonates. These changes may contribute to heightened neurodevelopmental risk in offspring following hypoxic injury, highlighting potential molecular pathways for future therapeutic targeting. Full article

Accurate prediction of corrosion-fatigue crack growth rate in aluminum alloys is critical for the safety assessment of aerospace structures. Conventional empirical fracture-mechanic models often struggle to capture multiphysics coupling effects, whereas purely data-driven machine-learning models may lack physical interpretability and generalize poorly beyond the training distribution. To address this challenge, this study proposes a physics-guided knowledge-based XGBoost (KBXGB) model. Based on a comprehensive dataset comprising 2786 experimental records, Permutation Feature Importance was utilized to identify 11 key features, including the stress intensity factor range, stress ratio, frequency, and environmental parameters. The KBXGB framework learns the residual between physics-based empirical models (e.g., the Paris and Walker laws) and measured experimental data, recasting the complex nonlinear mapping into a correction of the systematic deviations of the physical models, thereby achieving deep integration of domain knowledge and data-driven learning. Test results demonstrate that the KBXGB model achieves a coefficient of determination (R²) of 0.9545 and a reduced Mean Relative Error (MRE) of 1.61% on the test set, outperforming standard XGBoost and traditional regression models. Crucially, in independent extrapolation validation, the standard XGBoost model failed (R² = 0.2858) with non-physical staircase artifacts, whereas the KBXGB model maintained high predictive fidelity (R² = 0.8646) and successfully reproduced physical crack growth trends. The proposed approach effectively mitigates the “black-box” limitations of machine learning in sparse data regions, offering a high-precision and physically robust tool for corrosion fatigue-life prediction under complex service conditions. Full article

Understanding the long-term dynamics of cropland water use efficiency (WUE) and its underlying environmental drivers is essential for ensuring food and water security, particularly for regions facing intensified climate change. Here, we investigated the spatial patterns and long-term trends of gross primary productivity (GPP), evapotranspiration (ET), and WUE in cropland ecosystems across Northeast China during the past two decades as the nation’s primary commodity grain base using the time-series Breathing Earth System Simulator (BESS) products. Subsequently, the ridge regression method was used to quantitatively disentangle the relative contributions of key climatic variables to the observed WUE trends of cropland. Our results revealed a pronounced decreasing gradient in both GPP and ET along the southeast–northwest direction. A significant increase in GPP was observed over the 20-year period (p < 0.01), with 95.94% of the cropland area showing positive trends. ET showed a slight, non-significant increase (p > 0.05), though 82.77% of pixels exhibited positive trends, particularly in the northwest. Consequently, WUE showed a widespread and significant enhancement (p < 0.01), with approximately 98% of cropland pixels exhibiting increasing trends. Attribution analysis identified air temperature as the dominant environmental variable, accounting for 92.4% of the observed WUE increase, while solar radiation and precipitation contributed modestly (3.4% and 3.2%, respectively). Our findings underscore the predominant role of thermal conditions in shaping the carbon–water coupling efficiency of agroecosystems in semi-arid to semi-humid transition zones. This study provides quantitative evidence that warming climate, rather than changes in water availability or radiation, has been the primary climatic factor driving the improved cropland WUE over the past two decades. These insights have important implications for developing adaptive water management strategies to enhance agricultural climate resilience in Northeast China and similar regions worldwide. Full article