Search Results (94)

The Maowusu Desert is still suffering from serious ecological and environmental security issues such as wind erosion and desertification, influenced by both natural and human factors. The amendment of aeolian sandy soil with soft rock material presents an effective erosion control strategy, leveraging the complementary structural and compositional properties of both materials to enhance soil stability and rehabilitate degraded environments. However, there are few studies that investigate the effect of soil surface electrochemical properties and particle interaction forces on the structural stability of compound soils with soft rock and sandy soil. This decade-long field study quantified the electrochemical properties and interparticle forces and their synergistic effects on structural stability across five soft rock-to-aeolian sandy soil blend volume ratios (0:1, 1:5, 1:2, 1:1, 1:0) within the 0–30 cm soil profile. The results showed that the soil organic matter (SOM), specific surface area (SSA), and cation exchange capacity (CEC) significantly increased with the incorporation of soft rock material. For five different proportions, with the addition of soft rock and the extension of planting years, the content of SOM increased from 5.65 g·kg⁻¹ to 11.36 g·kg⁻¹, the CEC varied from 4.68 cmol kg⁻¹ to 17.91 cmol kg⁻¹, while the σ₀ importantly decreased from 1.8 to 0.47 c m⁻² (p < 0.05). For the interaction force at 2.4 nm between soil particles, the absolute value of van der Waals attractive force increased from 0.10 atm to 0.38 atm, and the net force decreased from 0.09 atm to −0.30 atm after the incorporation ratios of soft rock from 0:1 to 1:1. There was a significant negative correlation between the resultant net force between the particles of compound soil and the SSA and CEC. These results indicate that the addition of soft rock material positively improves the surface electrochemical properties and internal forces between aeolian sandy soil particles, further enhancing its structural stability. This study establishes a foundational theoretical framework for advancing our mechanistic understanding of aeolian sand stabilization and ecosystem rehabilitation in the Mu Us Desert. Full article

This paper investigates a controversial phenomenon: the supposed generation of thrust from a symmetric system consisting of two contra-rotating gyroscopes whose spin axes form equal and opposite polar angles with respect to the axis connecting their supports. An elementary mechanical model demonstrates that, for this configuration of gyroscopes, an internal moment arises within the system. This torque, although internally generated, is well known for playing a significant role in satellite attitude control using control moment gyroscopes (CMGs). The mechanical analysis considers the system of gyroscopes mounted on a platform or cart, which is supported at its front and rear ends. In this context, it was found that the resulting dynamic interaction causes unequal reaction forces at the support points, which do not obey the length-ratio rule predicted by static analysis. Such behavior can lead to misinterpretation of the net external thrust, despite the system being closed and momentum-conserving. In this context, the present paper clearly shows that no net force is allowed to develop. Full article

This study presents a global aerosol climatology derived from six years (October 2018–October 2024) of the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observations, using a U-Net Convolutional Neural Network (CNN) machine learning algorithm for Cloud–Aerosol Discrimination (CAD). Despite ICESat-2’s design primarily as an altimetry mission with a single-wavelength, low-power, high-repetition-rate laser, ICESat-2 effectively captures global aerosol distribution patterns and can provide valuable insights to bridge the observational gap between the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) missions to support future spaceborne lidar mission design. The machine learning approach outperforms traditional thresholding methods, particularly in complex conditions of cloud embedded in aerosol, owing to a finer spatiotemporal resolution. Our results show that annually, between 60°S and 60°N, 78.4%, 17.0%, and 4.5% of aerosols are located within the 0–2 km, 2–4 km, and 4–6 km altitude ranges, respectively. Regional analyses cover the Arabian Sea (ARS), Arabian Peninsula (ARP), South Asia (SAS), East Asia (EAS), Southeast Asia (SEA), the Americas, and tropical oceans. Vertical aerosol structures reveal strong trans-Atlantic dust transport from the Sahara in summer and biomass burning smoke transport from the Savanna during dry seasons. Marine aerosol belts are most prominent in the tropics, contrasting with earlier reports of the Southern Ocean maxima. This work highlights the importance of vertical aerosol distributions needed for more accurate quantification of the aerosol–cloud interaction influence on radiative forcing for improving global climate models. Full article

As ecologically sensitive interfaces shaped by the interplay of land and sea, coastal zones demand close attention. Uncovering the spatiotemporal evolution of ecosystem service value (ESV) and the intricate interrelations among ecosystem service (ES) functions is imperative for the informed governance of human–land interactions and for fostering sustainable regional development. This study analyzes the spatiotemporal evolution of ESV based on the modified equivalent factor table, combining the Geo-information Tupu, Markov transfer model, and standard deviation ellipse. Additionally, we introduce an ecosystem service tradeoff degree (ESTD) to assess the tradeoffs and synergies among various ESs, and we utilize GeoDetector to elucidate the driving forces behind the spatial disparities in ESV. Our findings reveal that (1) Although the land use composite index in the Liaoning coastal economic belt (LCEB) increased, the pace of land use transformation demonstrated a trend toward stabilization over the study duration. (2) Between 2000 to2020, ESV initially declined but subsequently experienced an upward rebound, resulting in a net gain of approximately 48 billion yuan. Spatial analysis indicated continuous enlargement of the standard deviation ellipse, with its centroid consistently located within Yingkou City and a gradual directional shift toward the southwest. (3) The dominant relationship among ESs showed synergy, with notable tradeoffs between hydrological regulation and other services. (4) Topography and climate factors were the primary drivers of spatial heterogeneity of ESV in the LCEB. The research provides spatial decision support for optimizing the ecological security pattern of the coastal zone. Full article

Ocean forecasting is critical for various applications and is essential for understanding air–sea interactions, which contribute to mitigating the impacts of extreme events. While data-driven forecasting models have demonstrated considerable potential and speed, they often primarily focus on spatial variations while neglecting temporal dynamics. This paper presents the TSformer, a novel non-autoregressive spatio-temporal transformer designed for medium-range ocean eddy-resolving forecasting, enabling forecasts of up to 30 days in advance. We introduce an innovative hierarchical U-Net encoder–decoder architecture based on 3D Swin Transformer blocks, which extends the scope of local attention computation from spatial to spatio-temporal contexts to reduce accumulation errors. The TSformer is trained on 28 years of homogeneous, high-dimensional 3D ocean reanalysis datasets, supplemented by three 2D remote sensing datasets for surface forcing. Based on the near-real-time operational forecast results from 2023, comparative performance assessments against in situ profiles and satellite observation data indicate that the TSformer exhibits forecast performance comparable to leading numerical ocean forecasting models while being orders of magnitude faster. Unlike autoregressive models, the TSformer maintains 3D consistency in physical motion, ensuring long-term coherence and stability. Furthermore, the TSformer model, which incorporates surface auxiliary observational data, effectively simulates the vertical cooling and mixing effects induced by Super Typhoon Saola. Full article

A Kuznets-like curve for unemployment suggests that unemployment initially rises with early economic development due to sectoral shifts but decreases as economies mature, diversify, and adapt. This explains how gross national income (GNI) per capita influences or mediates the effect of globalization on unemployment. This study investigates the impact of the interaction between GNI per capita and economic globalization on unemployment rates in 158 countries from 1991 to 2019 using the spatial Durbin model (SDM) and a weight matrix based on cultural, political, social, language, and historical backgrounds and trade pacts (CPSLHT) for better estimates. The results indicate that the direct and indirect effects of gross domestic product (GDP) on unemployment are negative and significant in the short and long term. Population growth positively and significantly impacts unemployment, while female labor force participation shows negative and significant indirect effects. The net migration effect is negative but insignificant in the overall model and becomes significant in the decomposed globalization models. The direct and indirect effects of inflation were consistently negative and significant. Trade openness exerts a significant indirect negative effect on unemployment, while the interaction between GNI per capita and economic globalization, especially through trade and foreign direct investment, also reduces unemployment. Persistent unemployment and spatial spillover effects highlight the importance of regional cooperation. Controlling population growth, enhancing GDP growth, permitting mild inflation, promoting female workforce participation, and adopting effective migration policies can reduce global unemployment. Full article

Siltation around the harbour entrance poses significant challenges to the navigational safety and operational stability of coastal ports. Previous research has predominantly focused on sedimentation mechanisms in sandy coastal environments, while studies on silt-muddy coasts remain scarce. This paper investigates the causes of siltation around the entrance of Binhai Port in Jiangsu Province, China, utilising field observation data and a two-dimensional tidal current numerical model, with emphasis on hydrodynamic variations and sediment dynamics. Observations reveal that tidal currents induce sediment deposition in the outer harbour entrance area, whereas pronounced scouring occurs near breakwater heads. During extreme weather events, such as Typhoons Lekima (2019) and Muifa (2022), combined wind–wave interactions markedly intensified sediment transport and accumulation, particularly amplifying siltation at the entrance, with deposition thicknesses reaching 0.5 m and 1.0 m, respectively. The study elucidates erosion–deposition patterns under combined tidal, wave, and wind forces, identifying two critical mechanisms: (1) net sediment transport directionality driven by tidal asymmetry, and (2) a lagged dynamic sedimentary response during sediment migration. Notably, the entrance zone, functioning as a critical conduit for water– sediment exchange, exhibits the highest siltation levels, forming a key bottleneck for navigational capacity. The insights gleaned from this study are instrumental in understanding the morphodynamic processes triggered by artificial structures in silt-muddy coastal systems, thereby providing a valuable reference point for the sustainable planning and management of ports. Full article

Evapotranspiration (ET) is vital for global water balance, energy cycle, and biological processes, representing a key component of Earth systems interactions. However, how human activities affect regional ET is still unknown. This study identified a decadal decrease in ET before 2000, followed by an increase over southeastern China in observations. Simulations from the coupled model intercomparison project phase 6 (CMIP6) models well reproduced the observed decadal ET change, with a lag of 10 years, which may be due to the spatial and temporal simplification of aerosol forcing data in CMIP6. Attribution analysis reveals that the change in anthropogenic aerosol emissions was the primary driver of the ET change, while the contribution of greenhouse gas was negligible. The Penman–Monteith framework identified that the net surface radiation contributed 77% of the ET trend change in the anthropogenic aerosol-only experiment. The increase and reduction in anthropogenic aerosol emissions reduce and increase the shortwave radiation reaching the Earth’s surface, respectively, resulting in the different trends of energy sources for ET. Our findings underscore the critical role of aerosols in shaping surface energy balance and influencing regional hydrological cycles. Full article

This study, based on existing research on the dynamic response of transmission tower–line systems under wind and rain loads, proposes a method for predicting these responses using the TimesNet deep learning surrogate model. Initially, a numerical model of the tower–line system is developed to generate dynamic response time series data under the influence of wind velocity and rainfall forces. Wind velocity and precipitation intensity are used as inputs for the surrogate model, with the tower’s maximum displacement and the highest tension in the line serving as the corresponding outputs. Afterward, the fast Fourier transform (FFT) is used to transform the original one-dimensional input signals into their corresponding two-dimensional representations. Feature extraction is then performed using an Inception module with 2D convolutional kernels of varying sizes. Finally, based on the amplitude-weighted information obtained through the FFT, the two-dimensional tensors are transformed back into one-dimensional output signals. The experimental results show that the proposed surrogate model provides highly accurate dynamic response predictions, even under complex conditions involving the interaction between transmission towers and lines, as well as the combined effects of wind and rainfall. Full article

The semi-humid evergreen broadleaved forest (SEBF) is the zonal vegetation type of western subtropical regions in China. Under human and natural disturbance, the area of SEBFs is severely shrinking, with remaining fragments scattered across mountains of the Central Yunnan Plateau. To explore the mechanisms of community assembly and species maintenance in the severely fragmented SEBFs, we selected three sites—Jinguangsi Provincial Nature Reserve, Huafoshan Scenic Area, and Qiongzhusi Forest Park—across the range of this vegetation type, and sampled a total of 42 plots of forest dominated by Castanopsis orthacantha Franch., the most widely distributed community type of SEBFs. We compared the species richness and composition of the communities of different age classes, employed the net relatedness index to characterize the phylogenetic structure of communities, and used Mantel tests and partial Mantel tests to quantify the impacts of spatial distance, age class, and habitat factors (including climate, topography, and soil) on species turnover across different spatial scales (i.e., intra- and inter-site) for trees, shrubs, and herbs, respectively. The results indicated the following: (1) In the young stage, the C. orthacantha communities exhibited a species richness statistically lower than those in middle-aged and mature communities. Notably, the difference in species richness among age classes was merely significant for shrub and herb species. Moreover, the phylogenetic structure changed towards over-dispersion with increasing community age. (2) The age class of the community played a pivotal role in determining taxonomic β diversity in the tree layer, while climate and soil factors significantly influenced β diversity in the shrub and herb layers of the communities. (3) Environmental filtering emerged as the predominant force shaping community assembly at the intra-site scale, whereas spatial distance was the primary determinant at the inter-site scale. Meanwhile, dispersal limitation versus biological interaction seemed to dominate the community dynamics of the C. orthacantha communities in the early versus middle and old ages, respectively. Our results highlight the variability in community assembly processes across different spatial and temporal scales, providing insights into the priority of the conservation and restoration of severely degraded zonal SEBFs. Expanding research to broader scales and other SEBF types, as well as considering the impacts of climate change and human activities, would provide further insights into understanding the mechanisms of community assembly and effective conservation strategies. Full article

The objective of this study is to accurately, expeditiously, and efficiently identify the wear state of milling cutters. To this end, a state identification method is proposed that combines continuous wavelet transform and an improved MobileViT lightweight network. The methodology involves the transformation of the cutting force signal during the milling cutter cutting process into a time–frequency image by continuous wavelet transform. This is followed by the introduction of a Contextual Transformer module after layer 1 and the embedding of a Global Attention Mechanism module after layer 2 of the MobileViT network structure. These modifications are intended to enhance visual representation capability, reduce information loss, and improve the interaction between global features. The result is an improvement in the overall performance of the model. The improved MobileViT network model was shown to enhance accuracy, precision, recall, and F1 score by 1.58%, 1.23%, 1.92%, and 1.57%, respectively, in comparison with the original MobileViT. The experimental results demonstrate that the proposed model in this study exhibits a substantial advantage in terms of memory occupation and prediction accuracy in comparison to models such as VGG16, ResNet18, and Pool Former. This study proposes an efficient identification method for milling cutter wear state identification, which can identify the tool wear state in near real-time. The proposed method has potential applications in the field of industrial production. Full article

With the urgent demand for net-zero emissions, renewable energy is taking the lead and wind power is becoming increasingly important. Among the most promising sources, offshore wind energy located in deep water has gained significant attention. This review focuses on the experimental methods, simulation approaches, and wake characteristics of floating offshore wind turbines (FOWTs). The hydrodynamics and aerodynamics of FOWTs are not isolated and they interact with each other. Under the environmental load and mooring force, the floating platform has six degrees of freedom motions, which bring the changes in the relative wind speed to the turbine rotor, and furthermore, to the turbine aerodynamics. Then, the platform’s movements lead to a complex FOWT wake evolution, including wake recovery acceleration, velocity deficit fluctuations, wake deformation and wake meandering. In scale FOWT tests, it is challenging to simultaneously satisfy Reynolds number and Froude number similarity, resulting in gaps between scale model experiments and field measurements. Recently, progress has been made in scale model experiments; furthermore, a “Hardware in the loop” technique has been developed as an effective solution to the above contradiction. In numerical simulations, the coupling of hydrodynamics and aerodynamics is the concern and a typical numerical simulation of multi-body and multi-physical coupling is reviewed in this paper. Furthermore, recent advancements have been made in the analysis of wake characteristics, such as the application of instability theory and modal decomposition techniques in the study of FOWT wake evolution. These studies have revealed the formation of vortex rings and leapfrogging behavior in adjacent helical vortices, which deepens the understanding of the FOWT wake. Overall, this paper provides a comprehensive review of recent research on FOWT wake dynamics. Full article

This study explores the hydrodynamic behaviour of a fish cage in a steady current by employing a fluid–structure interaction model with one-way coupling between a fluid solver and a structural model. The fluid field around the fish cage is predicted using a computational fluid dynamics solver, while the stress and deformation of the netting are calculated using finite element structural algorithm with solid elements reflecting their real geometry. The fluid velocity and hydrodynamic pressure are calculated and mapped to the structural analysis model. The fluid–structure interaction model is validated by comparing drag force results with published experimental data at different current conditions. Instead of modelling the netting of the fish cage as porous media or using lumped mass methods, the complete structural model is built in detail. The analysis of the fluid field around the nets shows that the change in the current condition has a limited impact on the flow behaviour, but the increase in the current velocity significantly enhances the magnitude of the drag force. This study reveals a reduction in flow within and downstream of the net, consistent with prior experimental findings and established research. Mechanical analysis shows that knotted nets have better performance than knotless ones, and although fluid pressure causes some structural deformation, it remains within safe limits, preventing material failure. Full article

The reconstruction of land spatial planning and the increasing severity of carbon emissions pose significant challenges to carbon peak and carbon neutrality strategies. To establish low-carbon and sustainable agricultural spatial planning while achieving dual carbon strategy goals, it is essential to accurately analyze the mechanisms of agricultural spatial transfer and their carbon emission effects, as well as the key factors influencing carbon emissions from agricultural spatial transfer. Therefore, this study, based on land use remote sensing data from 2000 to 2020, proposes a carbon emission accounting system for agricultural space transfer. The carbon emission total from agricultural space transfer in the Harbin-Changchun urban agglomeration over the 20-year period is calculated using the carbon emission coefficient method. Additionally, the spatiotemporal patterns and influencing factors are analyzed using the standard deviation ellipse method and the geographical detector model. The results indicate that: (1) The agricultural space in the Harbin-Changchun urban agglomeration has increased, with a reduction in living space and an expansion of production space. Among land type conversions, the conversion between cultivated land and forest land has been the most intense. (2) The conversion of agricultural space to grassland and built-up land has been the primary source of net carbon emissions. The carbon emission center has shown a migration path characterized by “eastward movement and southward progression,” with a high-north to low-south distribution pattern. Significant carbon emission differences were observed at different spatial scales. (3) Natural environmental factors dominate the carbon emissions from agricultural space transfer, while socioeconomic and policy factors act as driving forces. Elevation is the primary factor influencing carbon emissions from agricultural space transfer. Interactions between factors generally exhibit nonlinear enhancement, with the interaction between elevation, annual precipitation, and industrial structure showing a strong explanatory power. Notably, the interactions between elevation, average annual precipitation, and industrial structure demonstrate significant explanatory power. These findings highlight the necessity for government action to balance agricultural spatial use with ecological protection and economic development, thereby providing scientific references for optimizing future land spatial structures and formulating regional carbon balance policies. Full article

Vegetation plays an important role in absorbing carbon dioxide and accelerating the achievement of carbon neutrality. As the ecological barrier of North China, the Taihang Mountains are pivotal to the ecological construction project of China. Nevertheless, the dynamic development of the vegetation carbon sink in the region and the impact factors on the sink have not been systematically evaluated. This study employed a comprehensive approach, utilising remote sensing technology and meteorological and topographic data, in conjunction with the net ecosystem productivity (NEP) estimation model to reveal the characteristics of vegetation carbon sinks in the Taihang Mountain, and then revealed the dynamics evolution of the NEP and the inter-annual trend by using Theil–Sen Median slope estimation, the Mann–Kendall test, and the coefficient of dissociation and analysed the driving roles of the influencing factors by using the parameter optimal geographic detector. Our findings suggest that the NEP in the Taihang Mountain area has a clear growth trend in time, the average value of NEP in the Taihang Mountain area is 289 gC-m⁻²-a⁻¹ from 2000 to 2022, and the spatial distribution shows the characteristics of high in the northeast and low in the middle and west, with a gradual increase from the northeast to the southwest; the areas with high fluctuation of NEP are mainly distributed in the areas around some cities that are susceptible to the interference of natural or anthropogenic factors. The vegetation carbon sinks in the Taihang Mountains are influenced by a variety of natural factors, among which the explanatory power of each natural factor is as follows: DEM (0.174) > temperature (0.148) > precipitation (0.026) > slope (0.017) > slope direction (0.003). The natural factor DEM had the strongest explanatory power for NEP changes, and the two-by-two effects of the natural factors on vegetation carbon sinks were all significantly stronger than the effects of a single factor, in which the interaction between DEM and precipitation had the strongest explanatory power; distinguishing from climate change factors, the contribution of anthropogenic activities to NEP changes in more than 90% of the area of the Taihang Mountainous Region was more than 60%, and the driving force of anthropogenic factors on NEP changes in the Taihang Mountainous Region was significantly stronger than that of natural climate change. The contribution of anthropogenic factors to NEP changes in the Taihang Mountains was significantly stronger than that of natural climate change. The results of this study can not only provide a reference for carbon reduction and sink increase and ecological restoration projects in the Taihang Mountains but also benefit the research paradigm of vegetation carbon sequestration in other regions. Full article