Search Results (8,153)

Ensuring physical layer security for low-altitude economic networking (LAENet) is critical due to the broadcast nature of wireless channels. In dense urban environments, multi-antenna LAENet systems are often impaired by the keyhole effect, which induces rank deficiency and poses significant security challenges. This paper investigates the secrecy performance of a multiple-input multiple-output multiple-antenna eavesdropper (MIMOME) system in LAENet with keyhole channels. Depending on the availability of channel state information (CSI) at the transmitter, three wiretap scenarios are considered: (i) broadcasting, (ii) passive eavesdropping, and (iii) spoofing. For each scenario, the optimal precoder is designed to maximize the secrecy transmission rate. Based on these designs, we derive closed-form expressions for the secrecy outage probability (SOP) and average secrecy rate (ASR). To provide insights into the effect of keyholes on secrecy diversity order and array gain under this severe rank-deficiency structure, we also obtain asymptotic expressions for SOP and ASR in the high signal-to-noise ratio (SNR) regime using the Mellin transform. Numerical results validate the analytical expressions and illustrate the influence of key parameters on secrecy performance. These findings provide meaningful guidance for the secure design of future LAENet deployments. Full article

This paper investigates the application of cooperative relaying systems with non-orthogonal multiple access (NOMA) in low-altitude intelligent networking-enabled medical Internet of Things (IoT) and analyzes their transmission performance. First, to enhance the communication quality of remote base stations, we deploy a relaying unmanned aerial vehicle (UAV). A two-slot NOMA cooperative transmission mechanism is proposed accordingly. Next, for the NOMA-enhanced UAV-relayed smart healthcare system under Rician fading channels, an exact closed-form expression for the achievable rate is derived using the incomplete Gamma function. Then, to improve computational efficiency, a low-complexity approximation method based on Gauss–Chebyshev quadrature is designed, overcoming the high complexity of the exact expression. Finally, the simulation results validate a close match between the proposed approximation and the exact values (average approximation error below 6.17%), and demonstrate superior achievable rate performance compared to three state-of-the-art schemes. Full article

Uncrewed aerial systems (UASs) have diverse applications in natural environments, yet their deployment can inadvertently disturb wildlife. This PRISMA-guided systematic review synthesised 39 studies (2015–2025) encompassing birds, mammals, and marine taxa to identify UAS operational drivers of disturbance. We applied a Factors–Responses–Consequences (F–R–C) framework linking UAS operational characteristics, observed wildlife responses, and ecological consequences. Three patterns emerged: (i) Factors: Contextual and operational conditions such as flight altitude, noise, and approach direction interact with species-specific sensitivities to shape disturbance potential. (ii) Responses: Physiological measures (e.g., elevated heart rates) often reveal hidden stress not evident from behaviour alone. (iii) Consequences: Short-term effects may accumulate into long-term impacts on health, reproduction, and habitat use. These findings highlight the need for species- and context-specific flight envelopes rather than solely uniform altitude limits. By structuring existing evidence within the F–R–C framework, this synthesis provides a transferable foundation for UAS mission planning, drone development, operational decision-making, ethical practice, and environmental impact assessment in conservation and wildlife-management contexts. As all screening and data extraction were conducted by a single reviewer, the findings should be interpreted with appropriate caution pending independent validation. Full article

This paper presents a vision-based framework for detecting humans and estimating head surface temperature from aerial thermal imagery acquired by Unmanned Aerial Systems (UAS). A comparative evaluation of recent object detection architectures was conducted to identify the most stable and reliable model for thermal human detection under varying flight altitudes. The selected framework integrates two head localization strategies, namely, segmentation-based mask slicing and pose-assisted keypoint localization, to extract head regions and compute per-pixel temperature values from radiometric metadata. The results show that cross-domain inference using pre-trained YOLOv11 models achieves reliable human detection across controlled outdoor environments. Between the two pipelines, the pose-assisted method produced temperature estimates closer to the expected human physiological range (36–38 ${}^{\circ }$C), whereas the segmentation-based approach exhibited higher values attributable to mask boundary contamination and solar surface heating. In the absence of ground-truth validation from medical-grade sensors, these findings are characterized as relative comparisons rather than absolute accuracy claims. This study establishes a methodological foundation for future UAS-based thermal assessment systems and identifies critical calibration and validation requirements for field deployment. Full article

Poverty reduction, which is central to the UN Sustainable Development Goals, drives strategies like poverty alleviation relocation. China’s poverty alleviation relocation program represents a systematic government project to achieve national modernization. However, a holistic perspective of examining the process of reconstructing the social space of resettlement areas in poverty alleviation relocation is relatively limited. Drawing on spatial production theory, this study examines the mechanisms of spatial reconstruction in the Mu’en Di Resettlement Area in China from a holistic perspective, focusing on institutional, material, and spiritual spaces. This study primarily employs field-based ethnography, supplemented by a text analysis of policy documents. The findings reveal that the reconstruction of social space in resettlement areas constitutes a dynamic arena of interactions among state planning, market regulation, and migrant adaptation. This study offers insights for the practice of spatial reconstruction for impoverished migrants and emphasizes the importance of empowering migrants as active agents in this process. Full article

In the context of climate change, the hydrological processes and water resource system vulnerabilities in inland river basins of arid regions are intensifying. Understanding their evolutionary patterns and driving mechanisms is crucial for sustainable water resource management, agricultural development, and the protection of ecological security. This study focuses on the Kaidu River Basin, systematically analyzing the temporal and spatial variations in hydrological cycle elements in the basin from 1998 to 2023 based on multi-source precipitation data, the SWAT hydrological model, and the glacier degree-day model. The study also identifies the main driving factors using a geographic detector. The results show that the SWAT model performs well (calibration period R² and NSE ≥ 0.75, validation period R² and NSE of 0.75 and 0.70, respectively), indicating reliable simulation results. The surface water resources and the contribution of glacier meltwater to runoff in the basin both show a fluctuating downward trend, while potential evapotranspiration increases. The contribution of glacier meltwater during the ablation season decreased from 69.86% in 2014–2016 to 45.01% in 2017–2021. The hydrological processes exhibit a spatial pattern of “mountain areas generating runoff, non-mountain areas consuming water”. The geographic detector results indicate that precipitation is the decisive factor for the spatial differentiation of hydrological processes (influence degree q = 56.9%), with temperature, potential evapotranspiration, and altitude playing important synergistic roles. Moreover, the explanatory power of multi-factor interactions is much greater than that of individual factors. The findings of this study provide a scientific basis for the optimized allocation of watershed water resources, efficient agricultural irrigation, and the sustainable development of oasis ecosystems under changing environmental conditions, thereby supporting the goals of water security and sustainable development in inland river basins of arid regions. Full article

The northeastern margin of the Qinghai–Tibet Plateau is an ecologically fragile region that faces severe habitat fragmentation, which directly threatens regional biodiversity conservation and ecological security. To address this challenge, this study constructed a hierarchical “source-corridor-node” ecological network for the Gannan Tibetan Autonomous Prefecture by integrating Morphological Spatial Pattern Analysis (MSPA), the Minimum Cumulative Resistance (MCR) model, landscape connectivity assessment, and gravity modeling. The key results are as follows: (1) The Gannan Yellow River Water Source Replenishment Area contains 11 core ecological source regions, which are predominantly located in the southeastern regions of Diebu County and Zhouqu County, covering a total area of 4237.81 km²; (2) Ecological resistance analysis identifies high-resistance zones concentrated in anthropogenically active river valleys and urban belts (e.g., Hezuo urban area, Awanzang Town, and the G213 corridor). Low-resistance zones are predominantly situated in protected ecological enclaves (e.g., Zhagana Geopark and Gahai Wetland Reserve); (3) A total of 55 ecological corridors were identified, with a total length of 4355.77 km. Among these, 26 were classified as key ecological corridors, primarily distributed in Diebu and Zhouqu counties in the eastern part of Gannan Prefecture. These areas feature relatively concentrated ecological sources, and the key corridors play a critical role in connecting isolated ecological patches and maintaining regional ecological connectivity. (4) Across the entire territory of Gannan Prefecture, a total of 81 first-level ecological nodes and 53 second-level ecological nodes were delineated. As the core hub of the regional ecological network in Gannan Prefecture, Diebu County encompasses 60 First-level and 41 Second-level ecological nodes, respectively. The hierarchical “source-corridor-node” ecological network constructed in this study effectively enhances the overall landscape connectivity of the area. This progressive analytical framework—integrating source identification, corridor extraction, and node diagnosis—provides a scientific basis for biodiversity conservation, territorial ecological restoration, and sustainable development in high-altitude ecologically fragile zones. Full article

Asymptotic solutions are derived to model the development of atmospheric internal gravity waves generated by latent heating in a two-dimensional configuration involving a vertically-sheared background flow. The mathematical model comprises nonlinear partial differential equations derived from the conservation laws of fluid dynamics under the anelastic approximation where the background density and temperature vary with altitude. The latent heating is represented by a horizontally-periodic but vertically-localized nonhomogeneous forcing term in the energy conservation equation. This generates gravity waves that are considered as perturbations to the background flow and are expressed as perturbation series, with the leading-order contributions being the solutions of linearized equations. Taking into account the nonlinear terms at the next order gives expressions for the effects of the waves on the background mean flow. Due to the vertical shear, there is a critical level where momentum and energy are transferred from the wave modes to the mean flow. The asymptotic solutions show that the wave–mean-flow interaction is nonlocal and occurs over the range of altitudes from the thermal forcing level up the critical level. This is in contrast to what occurs in the case of waves forced by an oscillatory lower boundary, where the interaction is typically localized around the critical level. It is found that the wave drag is negative above the thermal forcing level, making the mean flow velocity more negative, but it becomes positive as the waves approach the critical level, indicating wave absorption in this region. There is wave transmission through the critical level, as well as absorption, and the extent of transmission depends on the depth of the latent heating profile. The mean potential temperature is reduced above the thermal forcing level and enhanced at the critical level, a situation that could ultimately lead to the development of convective instabilities. Full article

This study evaluates GNSS water-vapor tomography across the Lisbon metropolitan area and explores how increasing network density with low-cost receivers improves three-dimensional humidity fields for meteorological applications. Three configurations were tested for December 2022, a month characterized by several rainfall events, including a severe urban-impacting one: (i) a hybrid setup combining permanent and low-cost stations (TOMO_PL), (ii) a dense network of only low-cost stations (TOMO_L), (iii) a sparse arrangement using only permanent stations (TOMO_P). Tomographic water vapor density fields were compared with independent references from the Weather Research and Forecasting (WRF) model, ERA 5 reanalysis, and radiosonde data. All products show the expected exponential decline in water vapor with increasing altitude. Tomography consistently underestimates moisture in the lowest 2.0 to 2.5 km and tends to overestimate it at higher levels, with a weaker correlation above mid-tropospheric heights. Vertical RMSE remains below 2 g m⁻³ for all solutions, but TOMO_P performs the worst due to weak and uneven spatial geometry. Time–height analysis reveals that densified setups capture the changing moisture in the lower atmosphere, including increased near-surface humidity during December 11–13, when rainfall exceeded 120 mm in 24 h, although mid-level intrusions and dry layers observed by radiosondes are not captured. Mean PWV patterns show realistically low points over the Sintra mountain range and align best with TOMO_PL (spatial RMSE 0.6 g m⁻³, bias 0.4 g m⁻³, correlation 0.9), while TOMO_P creates artifacts that mimic mesoscale gradients. Categorized skill analysis shows the highest accuracy under high-moisture conditions and limited ability to detect dry conditions, with TOMO_PL showing the best overall performance against both ERA5 and WRF. Overall, low-cost densification significantly enhances boundary-layer humidity and PWV retrievals, supporting their use for urban heavy-rain monitoring and, with error-aware integration, for short-term forecasting. Full article

The underground urban rail transit (URT) is usually vulnerable to waterlogging caused by rainstorms, and floods run into the URT systems mainly via stations. Because of the increasing rainstorms due to global warming, assessing and improving the waterlogging resilience of URT stations is essential for preventing flooding disasters in URT. Here, an entropy weight–TOPSIS method is proposed to assess the waterlogging resilience of metro stations in Changsha, China. Firstly, 20 assessment indicators were selected from stability, resistance, and recovery of the system, respectively. Then, the entropy weight method was used to determine the objective weight of each indicator, and the TOPSIS method was applied to calculate the resilience index of metro stations. The results indicate that among the 137 metro stations, there are 26 low-resilience ones, 64 medium-resilience ones, and 47 high-resilience ones. The waterlogging resilience of metro stations shows a decreasing trend from the urban periphery to the urban center, and the low-resilience stations are predominantly located in the eastern low-altitude flat areas of Changsha. Finally, the countermeasures are proposed to improve the resilience of metro stations. Full article

Accurate measurement of atmospheric temperature profiles in the mesopause region is crucial for understanding the atmospheric dynamics and climate processes. To address this challenge, a sodium Doppler lidar based on the resonance fluorescence scattering mechanism was recently developed to precisely detect atmospheric temperatures in the mesopause region in Qingdao (36.1°N, 120.1°E), China. For the first time, high-resolution observations of atmospheric temperature in the mesopause region (80–105 km) were achieved by the self-developed Na Doppler lidar in Qingdao under the complex atmospheric conditions of the mid-latitude coastal zone. A systematic cross-validation between the self-developed lidar and SABER satellite observations was conducted, and the temperature bias between the two detection methods in the mesopause region and its altitude-dependent characteristics were quantitatively assessed. The temperature profiles measured by lidar exhibited good agreement when compared with the satellite data yielding estimations of RMSE and mean absolute deviation of 9.2 K and 7.3 K, respectively, from 80 km to 100 km altitudes. A correlation analysis conducted between the lidar temperature data and satellite data showed that the closer the satellite passed over Qingdao, the better the correlation demonstrated by the data. The correlation coefficient of the closer comparison data can reach 0.86, which means that the self-developed lidar system in Qingdao has a good ability to detect temperature profiles in the middle and upper atmosphere. The nocturnal evolution details and short-period fluctuations of the temperature field in the mesopause region over Qingdao were observed, revealing the local temperature structural characteristics under the complex atmospheric conditions at the land–sea interface in the Qingdao area. Full article

Fatigue failure in scaffolding components poses significant risks to worker safety, particularly in high-altitude construction environments. This study investigates the fatigue behavior of scaffolding stirrups, a critical structural element prone to premature failure. The objective is to analyze the fatigue damage mechanisms in stirrups through a combined experimental and numerical approach. Mechanical characterization and micro-hardness testing were conducted to assess the material properties of the stirrup, while finite element modeling (FEM) was employed to simulate its performance under cyclic loading. The Johnson–Cook material model was utilized to compare experimental hysteresis curves with FEM results, validating the numerical approach. Additionally, the Extended Finite Element Method (XFEM) was applied to model crack initiation and propagation. Results reveal that material hardening and fatigue crack growth are the primary causes of stirrup failure, with distinct fatigue zones and crack paths identified. The study quantifies the relationship between crack growth stages and stirrup bending, providing insights into the failure process. These findings contribute to improving the safety and lifespan of scaffolding systems by identifying key factors influencing stirrup durability. Full article

Precise, spatially explicit sub-provincial GDP estimates are essential for regional planning, especially in mountainous areas where official economic data remain spatially coarse and unevenly distributed. This study develops a multisource county-level GDP spatialization framework for Sichuan Province, China, integrating corrected NPP/VIIRS nighttime-light (NTL) data with Points of Interest (POIs), land-use structure indicators (proportion of farmland (PFL); proportion of construction land (PCL)), elevation, precipitation, accessibility and population density within a unified indicator system. Two regression approaches—Ordinary Least Squares (OLS) as a global benchmark and Geographically Weighted Regression (GWR) as the spatially adaptive primary model—are calibrated on county-level cross-sectional data for 2020 (n = 183) and evaluated using R², adjusted R², AICc and residual spatial diagnostics. The multisource GWR model achieves R² = 0.882 (adjusted R² = 0.872, AICc = 5712.26), substantially outperforming both the global OLS benchmark (R² = 0.801) and NTL-only GWR baseline (R² = 0.662), confirming that spatial nonstationarity is an intrinsic feature of the GDP–proxy relationship and that integrating complementary geospatial proxies is the primary pathway to improved estimation accuracy in topographically heterogeneous regions. The GWR-based GDP surface exhibits a pronounced basin–plateau contrast: high-value clusters concentrate along the Chengdu Plain and adjacent city corridors, while extensive low-value zones prevail across the western highlands (global Moran’s I = 0.33, Z = 14.26, p < 0.001). Spatially varying GWR coefficients reveal that elevation and precipitation constrain GDP most strongly in high-altitude counties, construction land exerts a consistently positive but spatially graded effect, and the influences of accessibility and population density are context-dependent and locally differentiated. These findings support differentiated territorial development policies: plateau counties require accessibility-first strategies; hill counties benefit from targeted small-city industrialization; and basin cores need managed growth to balance agglomeration advantages against congestion pressures. The framework relies exclusively on globally or nationally available data and is portable to other mountainous regions, though cross-regional validation and extension to multi-year panels using geographically weighted panel regression remain important directions for future work. Full article

Silage serves as a cornerstone for the advancement of the livestock industry and a critical method for biomass preservation and utilization. This study investigated the impact of geographical and environmental factors—including longitude, latitude, temperature, relative humidity, precipitation, altitude, and sunshine duration—on fermentation parameters and bacterial communities in natural forage silage. Fresh samples of Saccharum arundinaceum and Leucaena leucocephala were collected from Changjiang, Haikou, Wanning, Danzhou, Qiongzhong and Sanya in Hainan Province, China. After 60 days of anaerobic fermentation, fermentation parameters and bacterial communities were analyzed. Results showed that fermentation parameters of the same plant exhibited significant variations across different regions. For instance, Leucaena leucocephala silage from Haikou showed the lowest pH value (4.32), while that from Danzhou recorded the highest pH value (5.63). In Saccharum arundinaceum silages, the prevalent genera in HGH (Saccharum arundinaceum silage from Haikou) were Weissella (49.85%) and Leuconostoc (20.42%), while the bacterial community of DGH (Saccharum arundinaceum silage from Danzhou) was dominated by Klebsiella (62.69%). These results revealed significant variations in fermentation characteristics and microbial community structure of the same plant species across different geographical regions. The Mantel-test network heatmap analysis demonstrated that longitude, latitude, altitude, precipitation, and relative humidity were identified as influential factors shaping silage microbial communities, with latitude being the most important geographical factor influencing silage microbiota. In conclusion, these findings highlight the critical need for region-specific adaptation of silage production strategies, particularly in response to latitudinal variations, to accommodate local environmental conditions, even when processing identical plant species. Full article

Using high-resolution field data from the Yunnan Provincial Grassland Pest Survey and an optimized MaxEnt model, we compared the climate-driven habitat dynamics of two invasive Asteraceae weeds (Chromolaena odorata, Ageratina adenophora) and a native weed (Cirsium japonicum). We assessed whether invasive and native weeds differ in environmental responses, future range dynamics, and management strategies, and three novel patterns were revealed. First, the invasive Chromolaena odorata exhibits a sustained positive response to mean annual temperature (contribution 67.6%), while the native Cirsium japonicum shows a strictly unimodal response with a narrow optimum (0–10 °C, contribution 46.4%) and high-temperature sensitivity, projecting over 50% habitat loss by the 2050s under high emissions. Second, the invasive Ageratina adenophora displays a southern contraction versus northern expansion pattern under high emissions (current highly suitable area ~9.12 × 10⁴ km²), suggesting that extreme warming may enable it to breach high-altitude barriers. Third, all three species show unimodal responses to human disturbance with species-specific optima. Overall, the invasive species, leveraging broad ecological amplitudes and strong adaptability, are poised for continued expansion of their potential suitable habitat, while the native species, constrained by a narrow niche and limited dispersal capacity, faces systemic habitat loss. These findings provide a mechanistic basis for differentiating management strategies between invasive and native problematic weeds in Yunnan grasslands. Full article