Search Results (1,166)

Ultrasonic-assisted laser-directed energy deposition (UA-DED) is a promising combined technology for manufacturing high-value thin-walled Inconel 718 components in aerospace. Nevertheless, the optimal ultrasonic frequency—a key parameter for achieving desirable performance in thin-walled Inconel 718 alloys—remains to be determined. In this study, we systematically investigated the influence of ultrasonic frequency (12–20 kHz) on the microstructure and mechanical properties of thin-walled Inconel 718 fabricated by UA-DED. The results revealed that an ultrasonic frequency of 20 kHz was optimal and can yield significant improvements in the microstructures of the as-deposited sample coordinate planes, manifested by the complete suppression of large pores, three-dimensional refinement of the γ matrix grains, alleviation of Nb and Mo segregation, the reduction of fragmented Laves particles, a decrease in residual macroscopic stresses, and homogeneous distributions of γ′/γ″ phases and γ-grain orientation. Meanwhile, the application of a 20 kHz ultrasonic frequency endows the manufactured thin-walled 718 parts with superior mechanical properties, including a tensile strength of 899 MPa in the laser scanning direction and 877 MPa in the build direction, along with the corresponding elongations of 34.8% and 38.9%. This work demonstrates the potential of modulating ultrasonic frequency to tailor microstructures and produce high-performance thin-walled Inconel 718 aerospace components. Full article

This study aims to examine the relationships among environmental sensitivity, eco-anxiety, and sustainable consumption behavior, thereby revealing how these variables interact within the framework of sustainability psychology. Conducted with a sample of 406 university students in Türkiye, the research employed a quantitative and cross-sectional design, and the proposed relationships were tested using structural equation modeling (SEM). The findings indicate that environmental sensitivity significantly predicts sustainable consumption behavior both directly and indirectly through eco-anxiety. Eco-anxiety was found to play a partial mediating role in the relationship between environmental sensitivity and sustainable consumption. In addition, the moderating effect of gender was investigated, and no significant differences were observed between women and men regarding the structural paths of the model. Overall, the results demonstrate that sustainable consumption behaviors are shaped not only by cognitive processes but also by emotional mechanisms, suggesting that eco-anxiety, as a motivational emotional response, may strengthen sustainable behavior. This study contributes to the environmental psychology literature by theoretically and empirically highlighting the decisive role of emotional processes in shaping sustainable behavior. The findings also provide important practical implications for sustainability policies, environmental education, and communication strategies. Full article

Litchi (Litchi chinensis Sonn.) is a pillar of the tropical agricultural economy in southern China, yet its production faces increasing instability due to climate change. Traditional agronomic models often fail to capture the complex, non-linear interactions between meteorological drivers and yield formation in perennial fruit trees. To address this challenge, the study constructed a yield prediction framework using an optimized Random Forest (RF) model integrated with interpretable machine learning (SHAP), based on a comprehensive dataset from 17 major production regions in Hainan Province (2000–2022). The model demonstrated robust predictive capability at the provincial scale (R² = 0.564, RMSE = 2.1 t/ha) and high consistency across regions (R² ranging from 0.51 to 0.94). Feature importance analysis revealed that heat accumulation (specifically growing degree days above 20 °C) is the dominant driver, explaining over 85% of yield variability. Crucially, scenario simulations uncovered asymmetric climate risks across phenological stages: while moderate warming generally enhances yield by promoting vegetative growth and ripening, it acts as a stressor during the Fruit Development stage, where temperatures exceeding 26 °C trigger yield decline. Furthermore, the yield penalty for drought during Flowering (−8.09%) far outweighed the marginal benefits of surplus rainfall, identifying this window as critically sensitive to water deficits. These findings underscore the necessity of phenology-aligned adaptation strategies—specifically, securing irrigation during flowering and deploying cooling interventions during fruit development—providing a data-driven basis for climate-smart management in tropical agriculture. Full article

The high salt content in saline–alkali soil has a significant impact on plant nutrient absorption and water transport, severely inhibiting crop growth. Through esterification reactions, silicic acid is grafted onto humic acid to form an organic silicon fertilizer (OSiF). The unique Si-O-C bond in the material endows this new type of organic silicon-based fertilizer with the ability to effectively alleviate the harm of high-salt soil to plants. In this study, a soil column experiment was designed to systematically evaluate and compare the effects of organic silicon fertilizers with different organic silicon contents (0%, 5%, and 10%) and traditional compound fertilizers on soil water characteristics, salt ion concentration, pH value, and electrical conductivity. The results showed that the addition of an appropriate amount of organic silicon fertilizer could significantly reduce the activity of salt ions in the soil solution. Experimental data indicated that the 5% and 10% organic silicon fertilizers had the most significant effect on the consumption of major salt ions such as sodium and chloride ions. X-ray photoelectron spectroscopy (XPS) analysis revealed that the reaction of Si-O-C bonds in the soil with Lewis bases led to a shift in the valence state of the 1S electrons of silicon atoms, providing a theoretical basis for the mechanism by which silicon fertilizers alleviate high-salt stress. Full article

Coconut coir, a key substrate in soilless cultivation, presents challenges for accurate moisture detection because of its complex internal structure, which limits the understanding of water infiltration and redistribution. This study employed RGB image recognition techniques combined with machine learning algorithms to systematically investigate the effects of initial moisture content (10%, 20%, and 30%), coarse-to-fine coir volume ratio (1:0, 1:1, and 0:1), and emitter discharge rate (1.0, 1.5, and 2.0 L h⁻¹) on wetting front morphology, water transport dynamics, and moisture variation within coir substrates. Morphological features of the wetting front were extracted from images and incorporated into three machine learning models—Support Vector Regression (SVR), Random Forest (RF), and Polynomial Regression—to construct a predictive framework for coir moisture estimation. The results showed that the SVR model achieved the best predictive performance in coarse coir substrates (R² = 0.89, RMSE = 3.37%), whereas Polynomial Regression performed best in mixed substrates (R² = 0.861, RMSE = 4.34%). All models exhibited lower accuracy in fine coir, particularly at high moisture levels. Under the same irrigation volume, increasing the initial moisture content enhanced both the water transport rate and the wetting front extent, with the aspect ratio (AR) decreasing from approximately 2.0 to 1.3, indicating a morphological transition of the wetting front from a “thumb-shaped” to a “hemispherical” pattern. Coarse particles facilitated vertical infiltration, while fine particles exhibited stronger water retention. By integrating RGB image recognition with machine learning approaches, this study achieved reliable prediction of coir moisture content and proposed an optimal management strategy using mixed substrates with an initial moisture content of 20–30% to balance infiltration efficiency and water-holding capacity while minimizing percolation risk. These findings provide a robust technical pathway for precise water management in coir-based cultivation systems. Full article

Long-term wind speed changes over the Yangtze River waterway have critical implications for inland shipping efficiency, emission dispersion, and renewable energy potential. This study utilizes a high-resolution 5 km gridded reanalysis dataset spanning 1979–2018 to conduct a comprehensive spatiotemporal analysis of surface wind climatology, variability, and trends along China’s primary inland waterway. A pivotal regime shift was identified around 2000, marking a transition from terrestrial stilling to a recovery phase characterized by wind speed intensification. Multiple change-point detection algorithms consistently identify 2000 as a pivotal turning point, marking a transition from the late 20th century “terrestrial stilling” to a recovery phase characterized by wind speed intensification. Post-2000 trends reveal pronounced spatial heterogeneity: the upstream section exhibits sustained strengthening (+0.02 m/s per decade, p = 0.03), the midstream shows weak or non-significant trends with localized afternoon stilling in complex terrain (−0.08 m/s per decade), while the downstream coastal zone demonstrates robust intensification exceeding +0.10 m/s per decade during spring–autumn daytime hours. Three distinct wind regimes emerge along the 3000 km corridor: a high-energy maritime-influenced downstream sector (annual means > 3.9 m/s, diurnal peaks > 6.0 m/s) dominated by sea breeze circulation, a transitional midstream zone (2.3–2.7 m/s) exhibiting bimodal spatial structure and unique summer-afternoon thermal enhancement, and a topographically suppressed upstream region (<2.0 m/s) punctuated by pronounced channeling effects through the Three Gorges constriction. Critically, the observed recovery contradicts widespread basin greening (97.9% of points showing significant positive NDVI trends), which theoretically should enhance surface roughness and suppress wind speeds. Correlation analysis reveals that wind variability is systematically controlled by large-scale atmospheric circulation patterns, including the Northern Hemisphere Polar Vortex (r ≈ 0.35), Western Pacific Subtropical High (r ≈ 0.38), and East Asian monsoon systems (r > 0.60), with distinct seasonal phase-locking between baroclinic spring dynamics and monsoon-thermal summer forcing. These findings establish a comprehensive, fine-scale climatological baseline essential for optimizing pollutant dispersion modeling, and evaluating wind-assisted propulsion feasibility to support shipping decarbonization goals along the Yangtze Waterway. Full article

As a key sustainable green-mining technology, ultra-high-water backfill mining is widely used to control surface subsidence and sustain extraction of constrained coal seams. Focusing on the Hengjian coal mine in the Handan mining area, this study uses physical modeling and industrial tests to clarify surface subsidence under different filling rates and identify the rock layers that hydraulic supports must control at various equivalent mining heights. A method is proposed to improve the filling rate by optimizing the thickness of the hydraulic support canopy through topological analysis. Results show that, compared with a filling rate of 85%, a 90% filling rate reduces subsidence of the basic roof, key layer, and surface by 51%, 57%, and 63%, respectively, while the industrial practice results have verified that the filling rate can significantly control surface subsidence. The equivalent mining height thresholds for instability of the immediate roof and high basic roof at the 2515 working face are 0.44 m and 1.26 m. Reducing the trailing beam thickness by 10 cm can theoretically raise the filling rate of the 2515 working face by about 2%, offering guidance for similar mines. Full article

Pleurotus pulmonarius is a high-value, commercially cultivated edible fungus whose primordium formation is a critical phase for yield and commercial value. To better understand the developmental processes of P. pulmonarius, samples from four key developmental stages were collected and subjected to transcriptome analysis. A total of 6530 DEGs were identified, including 50 transcription factors from 10 families. Among these, the PpZCP11 gene, encoding a Zn₂Cys₆ transcription factor, was found to be specifically highly expressed during the primordium stage. We cloned PpZCP11 gene and confirmed its nuclear localization. The OE-PpZCP11 strains produced abundant primordia, while primordium formation in the RNAi-PpZCP11 strains was severely suppressed. Moreover, RNA-seq and yeast-one-hybrid analysis suggested that PpZCP11 may regulate cell wall synthesis. These findings indicate that the PpZCP11 transcription factor acts as a positive regulator of primordium formation by regulating the expression of cell wall-related genes. This study provides a theoretical reference for elucidating the molecular mechanism underlying primordium formation in P. pulmonarius. Full article

The Chaijiagou Mo deposit (0.11 Mt Mo @ 0.07%) is located along the northern margin of the North China Craton. This study integrates ore geology, S–Pb–He–Ar–H–O isotopes, and fluid inclusion (FI) analyses to constrain the sources of ore-forming fluids and metals, as well as mineralization mechanisms. Three principal inclusion types were identified: liquid-rich, vapor-rich, and saline FIs. Microthermometry documents a progressive decline in homogenization temperatures and salinities from early to late mineralization stages: Stage 1 (360–450 °C; 5.3–11.3 and 35.4–51.5 wt.% NaCl equation), Stages 2.1–2.2 (320–380 °C and 260–340 °C; 5.4–11.8 and 33.8–44.5 wt.% NaCl equation), and Stage 4 (140–200 °C; 0.4–3.9 wt.% NaCl equation). Noble gas and stable isotope data reveal that the ore-forming fluids were initially dominated by crustally derived magmatic–hydrothermal components with a minor mantle contribution, subsequently experiencing significant meteoric water input. S–Pb isotopic compositions demonstrate a genetic relationship between mineralization and the ore-bearing granite porphyry, indicating a magmatic origin for both sulfur and lead. Fluid–rock interactions and fluid boiling were the dominant controls on molybdenite and chalcopyrite deposition during Stage 2, whereas mixing with meteoric waters triggered galena and sphalerite precipitation in Stage 3. Full article

About 16% of typhoons making landfall in China strike Hainan Island, where near-surface extreme winds in dense urban areas exhibit a strong spatiotemporal heterogeneity that is difficult to capture with current observations and mesoscale models. Focusing on Haikou during Super Typhoon Yagi (2024)—the strongest autumn typhoon to hit China since 1949—we developed a multiscale ERA5–WRF–PALM framework to conduct 30 m resolution large-eddy simulations. PALM results are in reasonable agreement with most of the five automatic weather stations, while performance is weaker at the most sheltered park site. Mean near-surface wind speeds increased by 20–50% relative to normal conditions, showing a coastal–urban gradient: maps of weighted cumulative exposure to strong winds (≥Beaufort force 8) show much longer and more intense events along open coasts than within built-up urban cores. Urban morphology exerted nonlinear effects: wind speeds followed a U-shaped relation with both the open-space ratio and mean building height, with suppression zones at ~0.5–0.7 openness and ~20–40 m height, while clusters of super-tall buildings induced Venturi-like acceleration of 2–3 m s⁻¹. Spatiotemporal analysis revealed banded swaths of high winds, with open areas and islands sustaining longer, broader extremes, and dense street grids experiencing shorter, localized events. Methodologically, this study provides a rare, systematically evaluated application of a multiscale ERA5–WRF–PALM framework to a real typhoon case at 30 m resolution in a tropical coastal city. These findings clarify typhoon–city interactions, quantify morphological regulation of extreme winds, and support risk assessment, urban planning, and wind-resilient design in coastal megacities. Full article

Heavy metals are among the most hazardous pollutants to human health and can be particularly harmful when inhaled or ingested. Therefore, the concentrations of heavy metals in fruits and vegetables grown in regions with high levels of heavy metal pollution should be carefully examined. This study investigated the variation in aluminum (Al), nickel (Ni), and zinc (Zn) concentrations by species and organ in tomatoes, peppers, eggplants, cucumbers, and corn grown near the industrial zone in Düzce, a heavily polluted city in Europe. We determined bioconcentration factors (BCFs) and translocation factors (TFs) in plant organs and assessed the health risk through the Target Hazard Quotient (THQ) and Hazard Index (HI). The results show that Al pollution in the region significantly exceeded the World Health Organization (WHO) and European Union (EU) limit values, and accumulated in all plant organs, including fruits. Furthermore, high levels of metals were translocated from the soil into the organs of peppers and tomatoes. The HI indicated a potential non-carcinogenic health risk (HI > 1) from the consumption of tomatoes, cucumbers, and peppers, primarily driven by Ni. Based on these results, it is recommended that local authorities address Al pollution in the region, avoiding the cultivation of tomatoes and peppers and instead cultivating corn and eggplant. We also observed that Zn levels were very high in the aerial parts of the plants, reaching up to 90% compared to Ni and Al. This study underscores the need to reduce Zn absorption rates, as dietary intake can pose a significant threat to human health. Full article

To address the limitations of the standard Sparrow Search Algorithm (SSA) in complex optimization problems—such as insufficient convergence accuracy and susceptibility to local optima—this paper proposes a Composite Strategy Sparrow Search Algorithm (CSSA) for multidimensional optimization. The algorithm first employs chaotic mapping during initialization to enhance population diversity; second, it integrates coordinate axis pattern search to strengthen local exploitation capabilities; third, it applies intelligent crossover operations to promote effective information exchange among individuals; and finally, it introduces an adaptive vigilance mechanism to dynamically balance exploration and exploitation throughout the optimization process. Compared with seven state-of-the-art algorithms, CSSA demonstrates superior performance in both 30-dimensional low-dimensional and 100-dimensional high-dimensional test scenarios. It achieves optimal solutions in three real-world engineering applications: thermal management of electric vehicle battery packs, photovoltaic power system configuration, and data center cooling systems. Wilcoxon rank-sum tests further confirm the statistical significance of these improvements. Experimental results show that CSSA significantly outperforms mainstream optimization methods in terms of convergence accuracy and speed, demonstrating substantial theoretical value and practical engineering significance. Full article

As a pivotal driver of high-quality development, new quality productivity (NQP) forms an indispensable synergistic relationship with land use efficiency (LUE) for achieving regional sustainability. Based on panel data from 29 prefecture-level cities in the Central Plains Urban Agglomeration (CPUA) from 2010 to 2023, this study integrates the entropy-weighted TOPSIS method, super-efficiency Slack-Based Measure (SBM) model, Malmquist index, and fixed-effects models to systematically explore the spatiotemporal evolution of NQP and its underlying impact mechanism on LUE. Key findings reveal: (1) The comprehensive NQP index of the CPUA increased from 0.280 to 0.828, exhibiting a “stepwise rise” trend, with a spatial pattern characterized by a “core–secondary–periphery” three-tier gradient distribution. Zhengzhou, as the core growth pole, played an innovative leading role, while peripheral cities (e.g., Handan, Hebi) remained constrained by resource-dependent economic structures, with NQP indices consistently below 0.2. (2) The average LUE in the study area increased from 0.917 to 1.031. Cities within Henan Province generally performed better than those in Hebei, Shanxi, and Anhui provinces. Total factor productivity grew at an average annual rate of 16.4%, with technological progress serving as the primary driver. (3) NQP exerts a significantly positive impact on LUE, yet with notable heterogeneity: large-scale cities enhanced intensive land use substantially through technological agglomeration and industrial upgrading; cities with scarce arable land and high economic development levels effectively leveraged NQP to boost LUE; in contrast, small cities, regions rich in arable land, and areas with low economic development have not established effective synergistic mechanisms, hindered by limited technological absorption capacity, path dependence, and factor bottlenecks. This study provides empirical support and actionable insights for optimizing land resource allocation and advancing coordinated development between NQP and LUE in similar urban agglomerations. Full article

Traditional fossil fuel consumption is the main contributor increased atmospheric PM2.5 concentration. In 2014, China designated 81 new-energy demonstration cities, aiming to replace traditional fossil fuel energy with renewable energy. This research aimed to forecast PM2.5 trends. Fractional policy shock term was introduced into grey model to simulate the temporal variability. This model was compared with several existing models to confirm its accuracy and efficacy. We also assessed the robustness characteristics of key parameter. This research found the following: (1) The new-energy demonstration policy achieved stable PM2.5 reductions in the Beijing-Tianjin-Hebei agglomeration. The policy showed strong regional linkages and marginal mitigation effects. (2) The fractional breakpoint grey model (FBGM(s,t)) outperformed existing classical forecasting models and neural networks in fitting and generalization capability. FBGM(s,t) decreased the MAPE by over 2% across all four cities. (3) Robustness analyzes confirmed that the model’s performance advantage remained stable under reasonable parameter variations. Full article

With global warming, tropical islands, as sensitive areas to climate change, exhibit new and significant temperature variation characteristics. Using the high-resolution Hainan Island Regional Reanalysis (HNR) dataset and multi-source data, this study analyzes temperature changes on Hainan Island from 1900 to 2022, focusing on spatiotemporal trends, diurnal patterns, and probability distribution shifts. The findings reveal significant periodic temperature changes: weak warming (0.02–0.08 °C/decade) from 1900 to 1949, a temperature hiatus from 1950 to 1979, and accelerated warming (0.14–0.28 °C/decade) from 1979 to 2022. Coastal plains (0.11 °C/decade) warm faster than inland mountains (0.08 °C/decade), reflecting oceanic and topographic effects. Diurnal temperature variations show topographic dependence, with a maximum range (8–9 °C) in the north during the warm season, and a southwest–northeast gradient in the cold season. Probability density function analysis indicates that the curves for transitional and cold seasons show a noticeable widening and rightward shift, reflecting the increasing frequency of extreme temperature events under the trend of temperature rise. The study also finds that the occurrence time of daily maximum temperature over coastal plains is advancing (−0.05 to −0.1 h/decade). This study fills gaps in understanding tropical island climate responses under global warming and provides new insights into temperature changes over Hainan Island. Full article