Search Results (4,578)

The ecological environment of Qinghai Lake is fragile and exhibits a pronounced response to climate change. Its unique natural conditions render its tourism activities particularly sensitive to climatic variations. However, existing studies rarely examine the impacts of climate change on tourism activities in climate-sensitive regions of high-altitude inland lakes, such as Qinghai Lake. Therefore, this paper takes Qinghai Lake as a case study to investigate the effects of climate change on tourist perception and tourism demand, thereby providing a scientific basis for decision-making by scenic area managers. The results are as follows: (1) In recent decades, the warming and humidification trend of Qinghai Lake has been clear, and the number of comfortable days for tourism has increased significantly, which has had a direct positive effect on the experience of tourists. (2) Climate change has caused changes in the natural ecology and landscape quality of Qinghai Lake, which has indirectly affected the tourism experience as follows: the expansion of the lake has increased the willingness of tourists to travel; the inundation of Bird Island and Sand Island has reduced the willingness of tourists to travel; and the increase in the number of animals and plants along with the enrichment of biological diversity has increased the willingness of tourists to travel. (3) Different types of tourists respond to the impact of climate change to varying degrees. Among them, female tourists and tourist groups with a higher level of education respond more strongly to climate change and its impacts. Full article

Highland vernacular dwellings face multiple environmental stresses, but existing studies often examine either individual passive strategies or qualitative cultural interpretations, leaving limited evidence on how regional climate, settlement wind environments, and indoor microclimates are connected. This study investigates Tibetan vernacular dwellings in northwestern Sichuan, China, across a climatic gradient from warm–humid low altitude to dry–cool mid altitude and cold–arid high altitude. Three settlements—Zhonglu Township, Sergu Town, and Gemo Township—were examined through field surveys, settlement mapping, and measured drawings of 24 dwellings. Climate Consultant, WindNinja, GBSware CFD simulations, and Radiance daylighting analysis were integrated to assess climatic stresses, outdoor wind environments, indoor ventilation, daylighting, and envelope responses. The results show that patchy, dense, and linear settlement morphologies produce different wind-protection and ventilation performances. Building form factors decrease with altitude from 0.65 to 0.54 and 0.44, while daylighting compliance remains below 10% in all cases. The findings demonstrate the value of multi-scale simulation for diagnosing climate-responsive strategies in vernacular dwellings and provide evidence for highland settlement conservation and climate-responsive building renewal. Full article

The Qinghai–Tibet Plateau presents extreme environmental challenges, including hypobaric hypoxia and nutritional scarcity, to which indigenous yaks (Bos grunniens) are remarkably adapted, whereas introduced Holstein cattle (Bos taurus) often exhibit severe maladaptation. This study compared the gut microbiota of grazing yaks (n = 20) and feedlot Holstein cattle (n = 20) under high-altitude conditions using 16S rRNA gene amplicon sequencing (for community composition) and shotgun metagenomic sequencing (for direct functional profiling of CAZy, COG, and KEGG pathways), combined with in vitro fermentation, digestive enzyme assays, and serum immune- and growth-related indicators. Results: The yak gut microbiota was dominated by Proteobacteria (35 ± 4%) and Actinobacteria (15 ± 2%), whereas Holstein cattle were dominated by Firmicutes (40 ± 4%) and Bacteroidetes (25 ± 3%). At the species level, NR-based metagenomic annotation suggested that Acinetobacter-related taxa, putatively assigned as Acinetobacter pseudolwoffii and A. lwoffii, were abundant in yaks. Functional profiling revealed that the yak microbiota was enriched in CAZy families CE1, GT2, and GT4, whereas the feedlot Holstein cattle microbiota showed enrichment of several KEGG orthologs related to multidrug efflux and carbohydrate transport, including dinF/mepA/vmrA and susC/susD. In vitro fermentation using enriched culturable fecal bacterial consortia showed higher dry matter digestibility and digestive enzyme activities in yak-derived consortia than in Holstein-derived consortia. For serum immune indicators, IgG was significantly higher in feedlot Holstein cattle, whereas IgA and IgM did not differ significantly between groups. Yaks showed higher serum levels of TNF-α, IL-6, TGF-β1, IL-4, IL-10, and IL-13, but lower IL-1β. Conclusions: These findings indicate that divergent gut microbiota configurations are associated with contrasting physiological profiles (e.g., digestive and immune functions) in grazing yaks and introduced feedlot Holstein cattle under the same high-altitude environment. However, due to the confounding effects of diet and management system, causal relationships cannot be inferred from this comparative study. Full article

The use of extremely high frequency (EHF) bands for satellite and terrestrial communications has increased because of the large available bandwidth and the potential for high data rates. At the same time, signal propagation in this range is strongly affected by atmospheric absorption and phase dispersion, both of which vary with altitude and weather conditions. Accurate Earth-to-space link-budget estimation therefore requires a propagation model that accounts not only for local attenuation but also for the refracted path through the atmosphere. In this work, Earth-to-space cumulative attenuation is analyzed by combining the real and imaginary parts of atmospheric refractivity along the propagation path. The real part determines the ray geometry, while the imaginary part determines the accumulated loss. The model is evaluated for clear-sky, fog, and rain conditions and for different transmission elevation angles. The results show the strong dependence of cumulative attenuation on frequency, weather conditions, and path geometry across EHF satellite communication bands. Full article

With the rapid growth of the low-altitude economy, the number of unmanned aerial vehicles (UAVs) has grown rapidly. It is challenging to plan substantial UAV trajectories in complex urban low-altitude airspace, considering the airspace capacity, inter-vehicle safety, and communication reliability. To deal with this challenge, we propose a dual-scale grid-based trajectory planning approach that separates the global routing and local refinement. Specifically, we discretize the three-dimensional airspace into coarse macro-grids for capacity-constrained routing and high-quality communication-aided fine micro-grids for collision-free trajectory refinement. Both consider an altitude-dependent energy model. To handle the complex dual-scale grid trajectory planning of UAVs, we propose a priority-driven dual-grid Theta* with adaptive relaxation (DGTAR) to balance the global planning efficiency and local obstacle avoidance accuracy. First, we design a priority-driven capacity allocation mechanism to enforce safe separation among UAVs. Then, a combined planner is proposed, which integrates a Theta*-enhanced global search with a sampling-based refinement algorithm, invoking on-demand boundary relaxation to ensure the feasibility. Simulation results reveal that the proposed method DGTAR achieves reductions in many aspects compared with benchmark mechanisms, while maintaining a high planning success rate in congested scenarios. Full article

Multi-UAV missions for remote sensing and environmental monitoring under extreme conditions require task allocation and path optimisation to efficiently distribute goals across vehicles. These methods must also be executed reliably inside an autonomous robotics framework. Several methods for the multiple travelling salesman problem (mTSP) show robust offline routeing efficiency. However, system-level validation under realistic operational conditions including waypoint management and inter-UAV separation remains limited. This research transforms the previously proposed Distance Efficient Clustering Kmeans Genetic Algorithm (DECK_GA) from an offline model into a deployment-focused multi-UAV remote sensing framework implemented in ROS2, Aerostack2, and Gazebo. A uniform waypoint management interface integrates planning, Rviz visualisation, and autonomous execution. The system combines Dynamic Centroid Kmeans (DCKmeans) for spatially coherent waypoint allocation with a Distance Efficient Genetic Algorithm (DEGA) for individual UAV route optimisation. The evaluation is conducted in a high-fidelity Antarctic environment where waypoints represent survey desired objectives in moss regions, and altitude is managed using terrain-referenced control involving two to five UAVs and 30 to 120 waypoints. The framework was evaluated against two baselines under identical mission configurations, with 10 trial runs for each: a Traditional GA Divide & Conquer planner and a Classical Kmeans DEGA planner, which utilises the same route optimisation method and differentiates the outcomes of the allocation stage. DECK_GA showed reduced mean planned and executed distances compared to the Traditional GA Divide & Conquer baseline across all configurations, achieving planned distance reductions ranging from 15.99% to 75.36%. Additionally, it produced shorter path than Classical Kmeans DEGA in 14 out of 16 configurations. The average minimum inter-UAV separation was greater than the Traditional GA Divide & Conquer baseline in 15 of the 16 configurations and higher than Classical Kmeans DEGA in 14 of the 16, which demonstrates that the DCKmeans allocation improves spatial separation. This research focuses on the framework for planning to execution instead of the introduction of a new optimisation method, as DECK_GA was proposed in previous research and is now incorporated and tested within an autonomy framework. This evaluation is simulation only. Real world flying, hardware in the loop testing, wind, communication latency, and location error prediction tend to be future developments. Full article

The growing affordability, autonomy, and swarming of small unmanned aerial vehicles (UAVs) turn low-altitude defense from single-shot interception into a multi-node cooperative decision problem, in which the loss of sensing, coordination, or engagement nodes breaks the closed loops linking them. This study formulates their recovery as the dynamic reconfiguration of cooperative counter-UAV task chains. Given a pre-disturbance plan and a set of failed defending nodes, reconfiguration is modeled as a constrained bi-objective optimization balancing recovered engagement effectiveness against the change to the baseline plan and is solved by Multi-Agent Heuristic Evolution (MAHE), an automated heuristic design framework whose evolution, coordinator, repair, and reflection agents—driven by a large language model—evolve scoring heuristics for a fixed reconfiguration solver. Across instances of varying scale and under light-to-heavy node loss conditions, MAHE outperforms both a single-agent heuristic design counterpart and a range of hand-crafted solvers: on ten held-out test instances spanning 8–320 targets it attains the highest overall normalized hypervolume (0.947, versus 0.935 for the single-agent counterpart and 0.30–0.45 for the hand-crafted solvers) and the best mean rank (1.43 of six methods, $p<{10}^{-5}$); the hand-crafted solvers lose most of their solution quality as the problem grows, whereas MAHE preserves it and sustains high recovery at a nearly constant reconfiguration cost. An ablation confirms that its agents contribute complementary gains. These simulation results indicate that automatically generated, reconfiguration-specific heuristics offer a scalable algorithmic foundation for dynamic, heterogeneous, and constraint-intensive counter-UAV task-chain reconfiguration. Full article

Engine high-altitude simulation tests require establishing a stable low test-chamber pressure across a wide range of operating conditions. Existing studies focus predominantly on the local starting mechanisms—namely, shock-wave swallowing, aerodynamic choking, and boundary-layer separation—of individual ejector or diffuser components, with limited investigation of the coupling among shock evolution, chamber pressure response, starting hysteresis, and diffuser starting thresholds during continuous ejection pressure regulation. To address this gap, a two-dimensional axisymmetric Reynolds-averaged Navier–Stokes model with the standard k-ε turbulence model is employed, encompassing the test chamber, engine nozzle, supersonic diffuser, and annular ejector of a large-scale active-ejection test stand (where an annular ejector actively evacuates the test chamber to simulate high-altitude backpressure). The formation, migration, and stabilization of the shock system are revealed under increasing ejection pressure. Hysteresis characteristics are elucidated by comparing pressure-increasing and pressure-decreasing paths. The non-monotonic relationship between chamber pressure and ejector total pressure ratio under zero-secondary-flow conditions is established. The mechanism governing diffuser starting threshold variation under coupled engine gas and ejection flows is identified. Quantitatively, the ejector starting pressure ratio is found to be approximately 16.78 with a hysteresis width of ~13.6% between the starting and unstarting thresholds, and the diffuser starting threshold scales linearly with the ejector total pressure ratio (R² = 0.976). The results reveal the coupling among shock evolution, hysteresis, chamber pressure response, and diffuser starting thresholds and clarify the dual influence of ejection pressure on both chamber pressure regulation and diffuser starting thresholds. These findings provide a theoretical basis for parameter matching and operational control of high-altitude simulation facilities. Full article

To overcome the limitations imposed by the natural ionosphere on high-frequency (HF) communication systems, the generation of artificial electron clouds through space-based release of ionizable materials offers a controllable means of constructing localized plasma environments. However, a systematic mapping between release parameters and radio wave propagation characteristics is still lacking, which restricts engineering applications. This paper establishes a full-chain simulation framework that links release parameters, cloud morphology, and propagation characteristics by combining a two-fluid hydrodynamic model with ray tracing. Results show that as release altitude rises from 150 km to 210 km, the cloud undergoes pronounced stretching along the magnetic field (the cloud scale grows from 17.28 km to over 80 km), resulting in a broader signal shadow zone (expands from 116 km to 170 km) and a marked increase in multipath delay spread. Increasing mass from 4 kg to 12 kg raises peak electron density from 7.416 × 10¹² to 2.154 × 10¹³ m⁻³ and widens the shadow zone from 144 km to 174 km. Raising the ionization rate from 20% to 80% broadens the enhancement zone but reduces the shadow zone. Higher altitudes favor broad shielding, larger masses enhance scattering strength and duration, while higher ionization rates accelerate cloud evolution for rapid response and lower rates provide stable coverage. These findings can provide theoretical guidance for the precise design of artificial electron clouds tailored to different application requirements. Full article

Background: Hypoxia signaling and the circadian clock exhibit extensive molecular crosstalk, but how endogenous circadian timing influences behavioral responses during high-altitude exposure remains incompletely understood. Methods: Male C57BL/6J mice were exposed to hypobaric hypoxia equivalent to an altitude of 6000 m. Wheel-running activity was continuously monitored under 12 h light/12 h dark (LD) cycle and constant-dark conditions to evaluate locomotor activity, rhythm amplitude, circadian phase, and free-running period. After 48 h of exposure, whole-hypothalamus samples were collected across the circadian cycle for time-series RNA sequencing, rhythmicity and pathway-enrichment analyses, and qPCR validation. In a separate experiment, hypoxia was initiated at ZT2 or ZT14 to assess circadian-phase-dependent behavioral responses. Results: High-altitude exposure acutely reduced locomotor activity and rhythm amplitude and subsequently delayed behavioral circadian phase under a LD cycle, whereas the free-running period under constant darkness remained unchanged. Transcriptomic analysis revealed extensive remodeling of rhythmic gene expression in the whole hypothalamus, involving multiple signaling and metabolic pathways. Relaxin-related signaling emerged as a candidate pathway associated with hypoxia-induced temporal transcriptional remodeling, and selected core clock genes and relaxin pathway-associated genes showed altered temporal expression profiles. Furthermore, exposure initiated at ZT14 produced greater locomotor suppression than exposure initiated at ZT2. Conclusions: High-altitude exposure disrupts behavioral circadian organization and remodels hypothalamic rhythmic transcription. These findings suggest that endogenous circadian timing modulates behavioral sensitivity to hypoxic stress. Full article

The Yellow River Basin (YRB) is a key ecological barrier and socio-economic region in China, but the spatiotemporal dynamics of its ecosystem carbon sink and the non-linear effects of environmental drivers remain insufficiently understood. This study estimated Net Ecosystem Productivity (NEP) in the YRB from 2001 to 2024 using MODIS Net Primary Productivity (NPP) data and an empirical soil heterotrophic respiration model, analyzed NEP trends with the Theil–Sen estimator and Mann–Kendall test, and quantified non-linear responses to climatic, temporal, and spatial factors using a Generalized Additive Model (GAM). The YRB acted as a persistent and strengthening net carbon sink, with annual total NEP increasing significantly from 39.85 Tg C yr⁻¹ in 2001 to 176.44 Tg C yr⁻¹ in 2024, at a rate of 5.65 Tg C yr⁻¹. NEP showed a clear southeast-to-northwest decreasing gradient, and 85.6% of the basin exhibited increasing trends, particularly on the Loess Plateau. The GAM captured non-linear associations of NEP with temperature, precipitation, solar radiation, relative humidity, year, and spatial location, and achieved a moderate pooled spatial block cross-validated R² of 0.723. NEP displayed a unimodal association with temperature—with a fitted peak near 0 °C reflecting the spatial transition from cold high-altitude to warmer water-limited regions—and a saturation-type response to precipitation, highlighting the joint control of hydrothermal conditions and pervasive water limitation. The fitted spatial smooth further revealed residual spatially structured variation that may be partly associated with irrigation and land management. These findings improve the understanding of carbon-sink dynamics in the YRB and provide scientific support for climate-adaptive ecosystem management and the regional implementation of China’s “dual carbon” goals. Full article

Stratospheric airship navigation requires accurate wind field measurements at a ~20 km altitude, where low pressure and density limit the effectiveness of conventional wind sensors. To address this, we present a compact direct-detection Rayleigh Doppler wind lidar based on the molecular double-edge technique. The system utilizes a 532 nm fiber-coupled pulsed laser (0.5 W, 5 ns) and a fixed-cavity dual-channel Fabry–Perot etalon as the frequency discriminator. A liquid crystal variable retarder (LCVR) combined with a polarization beam splitter (PBS) enables non-mechanical, high-speed beam switching between two orthogonal line-of-sight (LOS) directions for horizontal wind measurement. Systematic tests are performed in controlled wind fields within Mie-dominated and Rayleigh-dominated regimes. The lidar effectively captures the sharp radial velocity profiles at wind speeds up to 7.6 m/s. Comparative experiments with a reference anemometer show that the system delivers reliable performance at 0.48 m range resolution, with measurement uncertainty below 0.34 m/s. With its compact, lightweight, and high-precision design, the developed lidar demonstrates reliable wind measurement capability under laboratory conditions, indicating its potential for future deployment on stratospheric airships. Full article

The Dongping Lake Basin (DLB) serves as a critical water regulation and supply zone for the South-to-North Water Diversion Project in China. Understanding the coupling effects and influence mechanisms between ecosystem services is essential for regional ecological restoration and sustainable development. This study employed the Coupling Coordination Degree (CCD) model, Random Forest, and Geodetector. We analyzed the spatiotemporal characteristics and driving factors of the relationship between carbon storage and water yield in the DLB from 1990 to 2020. The results showed that: (1) Carbon storage and water yield exhibited a pronounced spatial mismatch. This was generally characterized by a pattern of high in the eastern/northeastern regions and low in the west/southwest. (2) The overall coordination between carbon storage and water yield remained at a medium-to-low level. Temporally, the CCD followed a trajectory of initial stability, abrupt decline post-2000, and subsequent low-level stagnation. Spatially, the CCD presented an agglomeration gradient of “high in the northeast and low in the southwest”. It also exhibited a significant positive correlation with rising elevation, peaking in mid-to-high altitude zones. Furthermore, the overall coupling relationship showed a continuous degradation trend, heavily concentrated in the southwestern region. (3) Land use type and topographic slope were the primary driving factors shaping the CCD pattern. However, the synergistic interaction between precipitation and soil sand content demonstrated the strongest spatial explanatory power. This underscores the necessity of adapting localized management to specific environmental conditions. This study provides scientific support for carbon sink enhancement and water resource management in lake basins, thereby mitigating potential negative impacts on human well-being. Full article

Following the 2021 Montiferru wildfire, one of the largest wildfire events in modern Italian history, assessing the suitability of olive-growing environments for high-quality extra virgin olive oil (EVOO) production is crucial for supporting sustainable agricultural restoration. This study models the spatial distribution and temporal stability of total polyphenol concentration in EVOO (cv. Bosana) across a complex Mediterranean landscape. Olive samples from georeferenced sites were collected during the 2022 (22 samples) and 2023 (37 samples) harvest seasons and processed using a standardized protocol. Spatial modeling was performed via Empirical Bayesian Kriging Regression Prediction (EBKRP), integrating seven bioclimatic and topographic covariates. Cross-validation demonstrated high predictive accuracy with negligible bias (RMSE = 53.3 and 58.8 mg kg⁻¹ for 2022 and 2023, respectively). While single-predictor correlations were weak, multi-variable analysis highlighted a strong interaction between topography and water balance driving phenolic accumulation. The mean prediction map identified regional hotspots approaching600 mg kg⁻¹ of polyphenols content in the obtained olive oils. Spatial overlay analysis successfully delineated “Stable High-Phenolic Core Areas” (>500 mg kg⁻¹ with interannual variation < 100 mg kg⁻¹), filtering out high-altitude marginal zones. This geostatistical approach provides a valuable territorial decision-making tool to support post-fire agricultural reconversion and the valorization of high-quality monovarietal EVOO terroirs. Full article

In this study, honey samples collected from the Varda Plateau (İkizdere Valley, Rize) and Yusufeli regions of northeastern Türkiye were comprehensively characterized in terms of their melissopalynological, physicochemical, elemental, and volatile properties. Ten honey samples collected from different apiaries were analyzed. Melissopalynological results identified two samples as monofloral Castanea sativa (chestnut) honeys and three samples as Myosotis-dominant honeys, while the remaining samples were classified as multifloral. The pollen spectra reflected the rich floristic diversity of the region, shaped by both forest vegetation and high-altitude herbaceous flora. Moisture and proline analyses indicated that the investigated samples were consistent with the characteristics of natural and well-matured honeys. Volatile compound analysis by HS-SPME/GC–MS revealed substantial qualitative and quantitative differences among samples, with chestnut and Myosotis honeys generally exhibiting more distinctive aroma profiles than multifloral honeys. Benzaldehyde, furfural, nonane, and linalool derivatives were among the most frequently detected volatile compounds, although their relative abundances varied considerably among samples. Elemental analysis identified potassium as the predominant mineral in all honey samples, while significant variability was observed for Fe, Zn, Mn, Ni, and Cu concentrations. Particularly, the Yusufeli samples were characterized by markedly higher Fe and Cu contents than the Varda samples, indicating a strong geographical influence on elemental composition. Multivariate analyses, including PCA, HCA, and UpSet analysis, confirmed considerable compositional heterogeneity and demonstrated that both botanical and geographical origins contribute to honey differentiation. Overall, the findings provide new insights into the chemical and botanical characteristics of chestnut, Myosotis, and multifloral honeys from the Eastern Black Sea region and highlight the value of integrated analytical and chemometric approaches for honey characterization, classification, and origin assessment. Full article