Search Results (2,163)

Executing multi-UAV cooperative pursuit in complex public domains requires balancing interception efficiency with flight safety under strict micro-platform constraints. Existing planners often struggle with high computational overhead or lack kinodynamic adaptability in heterogeneous environments. To address this, we propose AC2F, a lightweight Adaptive Coarse-to-Fine hybrid framework featuring a bidirectional state-switching mechanism. The framework utilizes the Apollonius circle for efficient global guidance during the coarse phase, dynamically transitioning to a Dynamic Window Approach (DWA) upon detecting path oscillations or entering terminal capture zones. To ensure robustness, a dual-layer parameter paradigm integrates offline Bayesian optimization for globally optimal baselines with online real-time weight adaptation based on target distance. Extensive simulations show that AC2F effectively escapes local minima, such as urban-style U-shaped traps. Real-world suburban validation confirms an 86% capture rate with minimal computational overhead, demonstrating AC2F’s suitability for public domain protection and civil security. Full article

In national park sections adjacent to large cities, protected wildlife habitats often intersect with roads, tourism, agriculture, forestry, and other community-use spaces. This overlap complicates the joint prioritization of multi-species conservation and potential human-wildlife conflict governance. Using species trace-point data from the Fourth National Giant Panda Survey, we developed 30 m MaxEnt distribution models for 12 mammal species in the Chengdu section of the Giant Panda National Park and integrated protected-species’ conservation priority with potential wild-boar-related conflict pressure. Test AUC values ranged from 0.702 to 0.897, and elevation was the dominant predictor for 11 species. The Top 15% weighted conservation priority area, based on protection status and rarity, covered 350.1 km². Potential wild boar conflict pressure was defined as wild boar suitability multiplied by human exposure, and the Top 15% risk area covered 348.3 km². Overlaying the two layers identified 61.6 km² of high-conservation-high-conflict areas. Functional-zone statistics showed that the core conservation zone concentrated higher multi-species conservation value, whereas the general control zone carried stronger potential wild boar conflict pressure. This framework provides a spatial basis for coordinating protected mammal monitoring, crop-damage warning, and community co-management. Full article

Cement clinker production is a thermal- and emissions-intensive process requiring high-temperature heat for drying, calcination, and sintering. This review provides a process-based assessment of refuse-derived fuel (RDF), solid recovered fuel (SRF), tire-derived fuel (TDF), and biomass as partial substitutes for coal and petcoke in modern dry-process cement kilns. The study synthesized the evidence from plant-scale trials, pilot and laboratory experiments, process modeling, computational fluid dynamics, emissions studies, life-cycle assessment (LCA), techno-economic analysis (TEA), and regional case studies to evaluate alternative fuels across fuel properties, kiln-zone suitability, process stability, clinker quality, emissions performance, and environmental outcomes. The review shows that stable co-processing generally requires fuels with net calorific values above 14 MJ kg⁻¹ and moisture contents below 15%, although TDF can provide 26–33 MJ kg⁻¹ and sustain high-energy kiln duty when sulfur, zinc, and steel residues are controlled. RDF, SRF, and biomass require pre-processing, homogenization, calibrated dosing, and continuous fuel-quality monitoring to limit incomplete burnout, deposit formation, volatile circulation, and clinker-quality variation. LCA studies show that 20% RDF thermal substitution can reduce global warming potential by about 3.3–4.2%, increasing to approximately 6.7% when avoided landfill methane credits are included. Modern abatement systems can maintain particulate matter at about 10–30 mg Nm⁻³ and PCDD/F below 0.1 ng TEQ Nm⁻³ under stable operation. The review concludes that alternative fuels are quality-dependent co-processing options whose mitigation role is complementary to clinker-factor reduction, energy-efficiency improvement, low-clinker binders, electrified heating, oxy-fuel calcination, and carbon capture. Full article

Wildfires significantly affect wood properties and usability, yet their impact on hardwood species remains insufficiently understood. This study presents an exploratory characterization of moderately fire-affected pedunculate oak (Quercus robur L.) wood, combining physical, mechanical, chemical, and thermal analyses to evaluate depth-related changes within outer stem zones. Samples were collected from bark and from wood originating approximately 1 cm and 1–2 cm beneath the cambial region to evaluate radial variation associated with moderate surface fire exposure. The oven-dry density of fire-affected wood reached 720 kg·m⁻³, corresponding to values marginally below the literature reference ranges reported for unaffected oak wood. Bending strength decreased to 85.56 MPa, while compressive strength remained within or marginally above the literature reference (71.16 MPa), and Brinell hardness (42.75 MPa) stayed within the typical range for oak. Chemical and elemental analyses revealed degradation of polysaccharides and carbon enrichment in surface layers. FTIR and DSC analyses suggested partial hemicellulose degradation, structural modification of cellulose, and reduced thermal reactivity in outer stem regions. Despite these changes, the higher heating value (19.09–19.56 MJ·kg⁻¹) remained within the literature reference ranges reported for oak wood. The results suggest that under moderate surface fire conditions, fire-induced changes were primarily concentrated in outer stem layers, while inner wood retained properties comparable to the literature reference values for unaffected oak wood. These findings indicate that moderately fire-affected oak wood may remain suitable for selected material or energy-related applications following appropriate quality assessment and removal of thermally altered surface zones. Full article

The research aims to develop methodologies for the detailed characterization and spatial zoning of landfills as a means of assessing their environmental impact. The principal objective is to establish an integrated framework for evaluating landfill conditions through multisource data analysis, encompassing remote sensing, field investigations, and geochemical analyses. The proposed framework incorporates several critical components: satellite and UAV-based remote sensing, multispectral vegetation assessment, geochemical soil profiling, temporal and functional zoning, and morphodynamic evaluation. Research findings indicate substantial environmental pollution in the vicinity of landfill sites, at levels that exceed the natural self-purification capacity of surrounding ecosystems. This encompasses the contamination of all principal environmental components, including groundwater, surface water, soil, vegetation, and atmosphere. The key findings demonstrate that only a comprehensive environmental impact analysis, conducted in conjunction with detailed landfill zoning, yields a thorough understanding of the associated adverse effects. Remote sensing methodologies are shown to play a pivotal role in data acquisition and ongoing monitoring. The practical contribution of this study lies in the development of methodological frameworks for detailed landfill zoning, environmental impact assessment, monitoring, damage mitigation measures, and waste management optimisation. The results obtained have the potential to improve waste management systems, inform the development of effective monitoring protocols, and underpin strategies aimed at reducing the environmental footprint of landfills. Overall, this research advances scientific and technical knowledge in the field of waste management and contributes towards efforts to mitigate environmental impact—a matter of persistent concern given rising rates of waste generation and the increasingly constrained availability of suitable landfill capacity. Full article

Identifying corrosion-prone conditions early is a major maintenance challenge in closed, hard-to-access structural zones. This paper reports an in-service validation of the first monitoring layer of a multi-sensor data fusion approach for early warning of such conditions in selected closed zones of a medical rescue aircraft. The work covers sensor selection, installation in restricted-access compartments, and analysis of data from helicopter operations. Environmental, conductance, and electrochemical channels are combined to identify persistent conditions favorable to long-term corrosion development and to assign warning levels linked to maintenance actions. The thresholds proposed here are empirical screening criteria from the 82-day campaign, not universal damage thresholds or proof of existing corrosion. PZT and eddy-current sensing are planned as follow-up diagnostic layers in the overall architecture. These technologies have been validated separately under laboratory or controlled conditions but were not installed on the flying helicopter during this initial period. Although persistent severe early-warning episodes were detected, they did not coincide with an approved maintenance-access window suitable for additional PZT/EC hardware installation. The present results therefore characterize the corrosion-prone environment and the likelihood of corrosion initiation, not the type, exact location, pit depth, mass loss, or crack initiation of actual damage. Field inspection evidence of corrosion in hidden zones supports the practical relevance of early warning, while full end-to-end validation of localization and damage-growth monitoring remains future work. Full article

This study addresses how limited field observations can be extended into a defensible irrigation–nitrogen management range for plastic-mulched drip-fertigated silage maize in the Hexi Irrigation District. The Root Zone Water Quality Model 2 (RZWQM2) was calibrated using six fertilized treatments in 2022 and independently validated using the corresponding treatments in 2023. The calibrated model was then used to compare 25 irrigation–nitrogen scenarios based on dry matter at maturity, mean 0–30 cm soil moisture at maturity, interannual stability, and proximity to the field reference treatment. RZWQM2 reproduced both variables with acceptable accuracy. For dry matter, RMSE values were 0.40 and 0.80 t·hm⁻² in 2022 and 2023, with corresponding nRMSE values of 1.61% and 3.18%, respectively. For soil moisture, based on 18 layer-specific observations per year, RMSE values were 0.0057 and 0.0064 m³·m⁻³, and nRMSE values were 3.65% and 4.14%, respectively. Dry matter reached its maximum under I1N4 in both years, but its advantage over the baseline scenario I3N3 was limited. When dry matter performance, soil-moisture deviation from the baseline scenario, interannual stability, and proximity to the baseline management level were considered jointly, I2N3, I2N4, and I3N4 were identified as priority scenarios. These scenarios corresponded to 4981.5–5535.0 m³·hm⁻² irrigation and 280–308 kg N·hm⁻² additional urea-N input. The results indicate that a slight irrigation reduction to baseline irrigation combined with baseline to moderately increased urea-N input represents a suitable local management range for plastic-mulched drip-fertigated silage maize under the tested soil–climate–management conditions. Full article

To identify efficient cellulose-degrading microbes suitable for the animal intestinal environment and to address the low utilization of crude fiber in feed, eight cellulolytic strains were isolated from the ileum of Yangzhou geese. Among them, strain A2 showed the highest cellulolytic activity (D/d = 1.48) via the CMC (carboxymethyl cellulose) agar transparent zone method. Based on whole-genome-based identification, strain A2 was identified as Bacillus subtilis. Whole-genome sequencing revealed a circular chromosome of 4.02 Mb with a GC content of 43.72%, containing 4083 protein-coding sequences, of which 7.40% were involved in carbohydrate transport and metabolism. CAZyme annotation identified 167 carbohydrate-active enzyme genes, including 64 glycoside hydrolase genes, along with 60 hemicellulase and 3 lignin-degrading enzyme genes, forming a complete lignocellulose-degrading system. The cellulase from A2 exhibited optimal activity at 55 °C and pH 7.0, with good stability at 50–65 °C and pH 5–7, and was significantly inhibited by Cu²⁺, Mn²⁺, and Zn²⁺. Notably, its degradation efficiency toward microcrystalline cellulose reached 197% of that toward CMC. In conclusion, B. subtilis A2, with its excellent enzymatic properties and robust genetic foundation, is a promising candidate for developing feed enzymes and enhancing lignocellulose utilization. Full article

Small Mediterranean islands relying on the sun–sea–sand (3S) tourism model face growing climate risks that threaten their tourism-dependent economies. This study evaluates climate suitability for 3S tourism on the Island of Vis by integrating the Climate Index for Tourism (CIT) with land- use and land-cover (LU/LC) spatial analysis. The integration is operationalized by overlaying CIT-derived seasonal suitability windows with LU/LC-based spatial vulnerability maps, enabling identification of micro-zones where natural buffers (forest cover and elevation) can offset thermal discomfort during peak heat stress periods. Observed data reveals declining ideal 3S conditions from July to October, with the island already exceeding 50 days per year of Physiologically Equivalent Temperature (PET) above 35.1 °C, increasing by 0.7 days per year. Regional climate models tend to exhibit a cold bias over small Adriatic islands, largely related to their limited spatial horizontal resolution (12.5 km grid spacing). However, they robustly reproduce the direction of recent and projected warming trends. Future projections indicate that the annual number of strong heat stress days with PET above 35.1 °C increase from approximately one per year in the reference period to six under RCP4.5 and nine under RCP8.5, with both scenarios reducing ideal peak-summer conditions while extending favorable periods into transitional seasons. Spatial analysis shows that coastal zones have higher sealed surfaces and less forest cover, reducing natural shade and cooling capacity, while the island interior offers higher elevations, forest buffers, hiking trails, and a UNESCO Global Geopark. Drawing on social–ecological resilience theory, we conceptualize the island’s tourism system as an adaptive unit whose long-term viability depends on spatially diversified resource use and temporally extended seasonality. The integrated analytical framework identifies not only when conditions deteriorate but where alternative tourism resources exist, enabling more targeted adaptation planning and supporting diversification toward outdoor tourism forms. The novelty of this study lies in the systematic spatial integration of bioclimatic suitability assessments (CIT and PET) with LU/LC analysis at the micro-island scale. Such an approach moves beyond temporally focused climate–tourism indices to produce actionable, location-specific adaptation strategies. Full article

Al₂O₃ single beads were deposited on a Ti-6Al-4V (Ti64) substrate by laser-directed energy deposition (DED-LB) to establish baseline process conditions for ceramic protective layers and future Ti64/Al₂O₃ functionally graded materials (FGMs). These ceramic-containing surface layers are applicable to titanium components requiring improved oxidation, wear, and thermal resistance in aerospace, automotive, and high-temperature structural applications. Laser power (300–700 W) and scan speed (300–700 mm/min) were varied, and bead geometry was quantified from cross-sectional observations; energy density and dilution ratio were calculated. Melt pool depth increased with higher power and lower speed, indicating increased heat input and substrate melting. Crack formation in the melt zone was more sensitive to laser power than to scan speed. In contrast, bead height showed a non-monotonic response to energy density, which may be associated with possible coupled effects such as recoil pressure-driven melt pool disturbance, powder scattering, and insufficient powder melting at high scan speeds. Dilution-based optimization identified 300 W laser power and 400 mm/min scan speed, with a powder feed rate of 3 g/min, as the most suitable condition within the investigated process window, giving the lowest practical dilution ratio of approximately 40.27%. SEM–EDS and XRD analyses were conducted to examine the interfacial microstructure and phase characteristics under the selected condition. Overall, this study provides fundamental process guidelines and mechanistic insight into bead formation, dilution behavior, and interface formation, supporting the future application of DED-LB-based ceramic protective or graded layers on Ti64 surfaces. Full article

(1) Background: The rapid spatial expansion of the ruderal weed Chenopodium hybridum L. poses a potential challenge to agricultural production and regional ecosystems in China. However, the spatial evolution characteristics of its potential geographic distribution remain unclear under the compound scenarios of global warming and intensified human activities. (2) Methods: Utilizing an optimized MaxEnt model (regularization multiplier (RM) = 0.5, feature combination (FC) = LQ), this study integrated bioclimatic, topographic, soil, and Human Footprint (Hfp) data to predict the potential suitable habitats of C. hybridum in China under current conditions and four future Shared Socioeconomic Pathways (SSPs) emission scenarios (SSP126, SSP245, SSP370, and SSP585) for the 2050s and 2070s. Additionally, spatial turnover rate and centroid migration analyses were incorporated to elucidate its spatiotemporal dynamics. (3) Results: The results indicate that the optimized model exhibited robust predictive performance (Area Under the Curve (AUC) = 0.928). The Human Footprint (Hfp) was the environmental factor most prominently associated with the macro-spatial distribution of C. hybridum, with a relative contribution of 58.4%—significantly higher than any single natural geographic factor. Currently, potential suitable habitats are primarily concentrated in North, Central, and Southwest China, totaling approximately 205.59 × 10⁴ km². Under future climate scenarios, the highly suitable core habitats exhibit a consistent contraction trend, whereas the marginal suitable habitats shift spatially toward the arid inland regions of the northwest and the high-altitude areas of the southwest. By the 2070s under the higher-emission scenario (SSP585), the spatial turnover rate reaches a peak value (16.23%), and the distributional centroids of the potential suitable habitats exhibit localized directional shifts. (4) Conclusions: The spatial expansion trajectory of C. hybridum exhibits a high degree of spatial congruence with human activity corridors, reflecting a distinct macro-ecological niche spatial response characterized by shifts toward higher latitudes and elevations. It must be emphasized that the projections of this study reflect potential habitat suitability rather than definitive future actual distributions. The three-tier spatial management framework proposed herein—encompassing transport regulation, ecological management in core areas, and early warning in marginal zones—can serve as a scientific basis for the early monitoring and spatial management of this species under climate change. Full article

High-pressure liquid CO₂ jets possess the characteristics of low-temperature cooling and dry, residue-free impact, which makes this technology particularly suitable for removing hydroxyl-terminated polybutadiene (HTPB) propellant from decommissioned solid rocket motors. However, existing studies lack multi-objective optimization of impact efficiency and CO₂ consumption, which limits their engineering applications and further promotion. In this study, a high-accuracy quadratic Response Surface Methodology (RSM) relating process parameters to damaged volume was established using a Box–Behnken design (BBD) combined with three-dimensional topography scanning. A theoretical model for CO₂ consumption was developed based on the Homogeneous Equilibrium Model (HEM). On this basis, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used to obtain the Pareto-optimal set for maximizing propellant damaged volume and minimizing CO₂ consumption. The results indicate that nozzle diameter has the most significant effect on damaged volume and exhibits a strong interaction with jet pressure. The knee-point solution gives a jet pressure of 15.35 MPa, a stand-off distance of 5 mm, and a nozzle diameter of 1.8 mm. Compared with the initial condition, this compromise condition increases the damaged volume by 72% while increasing CO₂ consumption by only 4.9%. Furthermore, the temperature in the impact zone was reduced to a minimum of −92.4 °C, with no thermal accumulation observed. These findings reveal the influence of liquid CO₂ jet process parameters on impact efficiency and CO₂ consumption, providing a theoretical basis and parameter references for its engineering application in the safe removal of propellants from decommissioned solid rocket motors. Full article

Using dissolved gas analysis (DGA) to diagnose faults in power transformers is essential for preventing major failures and improving the reliability of power systems. This paper proposes a diagnostic framework based on the Duval Pentagon Combined Complex (DPCC). This framework integrates the areas of Duval Pentagons 1 and 2, along with the electric arc and paper charring subregions, into one geometric structure. This results in 16 distinct defect regions. A physically consistent dataset was generated, respecting the relative proportions of the five key gases (H₂, CH₄, C₂H₆, C₂H₄, and C₂H₂) and the typical concentration ranges in ppm reported in the literature. Four machine learning (ML) classifiers were trained using this dataset: Neural Network (NN), Fine Gaussian Support Vector Machine (SVM), Weighted K-Nearest Neighbors (KNN) and Bagged Trees Ensemble. Cross-validation results indicate high performance for all analyzed models. The Wide NN classifier had an overall accuracy of 96.53%. The Fine Gaussian SVM reached 96.07%. The Bagged Trees Ensemble achieved 96.26%. The Weighted KNN had an accuracy of 95.74%. The area under the curve (AUC) values were close to 1 for most classes, confirming the regions defined by DPCC were highly separable. Compared with conventional ML-based methods relying on individual classifiers and standard geometric representations, the proposed method provides more accurate defect separation, increased robustness in transition regions, and improved stability of the diagnostic decision. The integration of the DPCC representation with a weighted probabilistic ensemble framework reduces ambiguities between classes and enables more accurate identification of defects associated with electric arcs and insulation paper carbonization. To improve the robustness of the classification in transition zones, we implemented a Weighted Probabilistic Ensemble framework, in which each model’s contribution is proportional to its validation accuracy. This strategy minimizes the impact of geometrical ambiguity on the decision and provides a more reliable defect type estimate. The proposed methodology demonstrates that combining DPCC geometric modeling with modern ML techniques allows for the development of a robust, automated diagnostic system suitable for power transformer monitoring and predictive maintenance applications. Full article

The increasing production of sewage sludge (SS) from wastewater treatment plants presents significant environmental challenges worldwide, requiring sustainable treatment strategies that enable resource recovery while minimizing environmental risks. Although composting is widely recognized as an effective method for SS stabilization, current technologies still exhibit limitations, including inefficient oxygen transfer, uneven aeration, high greenhouse gas emissions, and insufficient control of emerging contaminants. This review aims to synthesize current knowledge on SS composting with a focus on strategies for improving operation performance and reducing environmental impacts. Recent studies indicate that composting performance is strongly influenced by factors such as temperature, moisture content, aeration, carbon-to-nitrogen (C:N) ratio, and the use of suitable bulking agents. In addition to conventional approaches, alternative technologies—including co-composting, in-vessel systems, vermicomposting, and pretreatment methods—are discussed as pathways for improving system efficiency. Special attention is given to emerging innovations such as nanobubble aeration, which shows potential to enhance oxygen transfer and reduce anaerobic zones, although its application in composting remains insufficiently explored. The review highlights critical knowledge gaps related to aeration optimization, contaminant behaviour, and process integration, identifying opportunities where further scientific research can significantly advance SS composting toward more efficient and environmentally sustainable systems. Full article

Euler deconvolution is widely used to estimate the three-dimensional locations of geological sources from magnetic anomaly data. However, traditional Euler deconvolution is commonly performed on planar gridded data, whereas magnetic surveys in mountainous and hilly areas are often acquired over undulating terrain. Reducing such data to a horizontal plane before derivative calculation can introduce transformation errors, and derivative calculation by the conventional FFT-based (wavenumber-domain) method becomes less suitable under variable topographic conditions. To address these limitations, this study proposes an equivalent source method based on correlation imaging for calculating the spatial derivatives required by Euler deconvolution directly from magnetic anomaly data acquired over undulating terrain. An improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is further introduced to suppress spurious Euler solutions and retain valid source location estimates. Synthetic model experiments show that the proposed equivalent source method yields more accurate derivatives than the conventional FFT-based method under undulating terrain conditions. The improved DBSCAN algorithm effectively removes spurious solutions while preserving clustered solutions associated with geological sources. The proposed workflow was further applied to magnetic data from a coal fire zone in Shenmu, Shaanxi Province, China, to estimate the 3D locations of underground magnetic sources related to underground coal fires. The interpreted source locations are consistent with surface validation evidence, demonstrating the applicability of the proposed method for magnetic anomaly interpretation in complex topographic settings. Full article