Search Results (9,442)

Grasshopper outbreaks threaten forage production and rangeland sustainability, yet long-term evidence linking routinely monitored outbreak conditions to pest-management responses remains limited. We analyzed 12 years (2008–2019) of county-level monitoring and management records from 14 purposively selected units in Inner Mongolia, China, spanning five grasshopper-occurrence subregions. Rangeland outbreaks there are dominated by Oedaleus decorus together with Calliptamus italicus, Gomphocerus sibiricus, Myrmeleotettix palpalis, Bryodema spp., and Chorthippus spp. The records included affected and severely affected grassland areas, biological- and chemical-control areas, and operational inputs comprising personnel, equipment, and pesticide quantities. We evaluated long-term change in control composition and associations linking outbreak pressure to treatment scale and resource mobilization. Biological-control share increased markedly over time, with an average linear change of 6.53 percentage points per year, although the trajectory was nonlinear and the increase was concentrated before approximately 2014. Fixed-effects models showed that a 1-SD increase in outbreak extent was associated with a 5.14-percentage-point increase in total control intensity. The corresponding association with biological-control share was positive but too imprecisely estimated to be informative. Conditional severity was positively associated with all six operational resource indicators in the primary models, while only pesticide input remained supported after adjustment for total control intensity. These results indicate that long-term control composition, annual treatment scale, and operational mobilization represent distinct but related dimensions of grassland grasshopper management. With only 14 county-level clusters, the analysis characterizes this purposively selected monitoring sample rather than the whole of Inner Mongolia, and it does not establish treatment efficacy, causal decision rules, or forecasting performance. Full article

Rural clean heating in China is moving away from large-scale infrastructure retrofits towards long-term operation and optimization. How environmental performance changes over time and among different townships remains insufficiently understood. This study examines 36 townships in Qingdao using multisource data from 2017 to 2024. A composite environmental performance index (CEPI) was constructed from heating-season concentrations of PM₂.₅, PM₁₀, NO₂, and SO₂, together with building-sector CO₂ emission intensity. CRITIC–TOPSIS, spatial autocorrelation analysis, and an XGBoost–SHAP framework with township-grouped cross-validation were applied to characterize spatiotemporal changes and nonlinear associations with explanatory factors. The results show that: (1) CEPI rose from 0.385 in 2017 to 0.816 in 2024, and all 36 townships improved. SO₂ concentrations fell the most, and the reductions in CO₂ emission intensity were smaller. Sensitivity analyses supported the robustness of the evaluation. (2) Environmental performance exhibited persistent positive spatial autocorrelation, with relatively stable high-value clusters in northern areas and low-value clusters in central areas. (3) XGBoost achieved a mean R² of 0.793 in five-fold grouped cross-validation and outperformed the linear benchmark. SHAP analysis revealed nonlinear statistical associations between CEPI and climatic conditions, population concentration, and residential energy use, rather than causal effects attributable to the clean-heating policy. Heating-season surface solar radiation accounted for 42.32% of total SHAP importance, while climatic variables jointly accounted for 67.5%, reflecting their predictive importance rather than independent causal effects. Strong conditional interactions were observed between precipitation and solar radiation and between population density and residential electricity-use density. These findings indicate that long-term clean-heating management should move beyond city-level averages and incorporate township-scale spatial clustering, meteorological conditions, and energy-use characteristics into monitoring and regional diagnosis to support more targeted environmental management and the environmental sustainability of rural clean heating. Full article

Fresh-food distribution with electric vehicles requires coordinated routing and fleet decisions under perishability, time window, and battery constraints. Simplified energy consumption models and limited consideration of fleet heterogeneity can overlook the effects of changing payloads on these decisions. This study formulates an optimization model integrating load-dependent electricity consumption, heterogeneous vehicle capacities, battery swapping, product spoilage, and soft time windows. A particle swarm optimization-guided adaptive multi-operator genetic algorithm (PSO-AMOGA) is developed, with an outer PSO procedure optimizing the selection probabilities of crossover and mutation operators. Numerical experiments show that PSO-guided operator selection improves solution quality and yields lower total costs than fixed-probability operator selection, while fleet-composition decisions require balancing vehicle-deployment costs, energy consumption, and battery-swapping requirements. Sensitivity analyses further highlight the importance of jointly optimizing vehicle assignment, routing, and battery-swapping decisions according to demand characteristics, product perishability, and delivery requirements. These findings support sustainable fresh-food distribution by informing the joint management of energy consumption, product spoilage, and operating costs through coordinated vehicle assignment, routing, and battery-swapping decisions. Full article

Temporal knowledge graphs built from public cyber threat intelligence (CTI) reports reflect report composition and analysis conditions as well as the reported techniques. Interpreting temporal changes therefore requires examining sensitivity to these factors. To this end, we constructed annual graphs for 2002–2023 from 1474 reports, linking techniques identified in the same report and applying report-level time allocation. We compared the observed weighted ratio W with the excess ratio R, the positive part of W minus the composition-preserving randomization mean μ. Nine descriptors and constant, linear, and piecewise-constant models summarized graph-level changes. The top 74 reports accounted for 92.72% of summed per-report combination counts. One case showed an increase in W while R became zero; another had 12 positive years both before and after exclusion, with only 11 years in common. Under the unified positive criterion and 9600 randomized samples per year, the full corpus retained only the piecewise-constant model across five replicate bundles, whereas top-15 or top-74 exclusion retained only the constant model. Random removal of 74 reports retained only the piecewise-constant model in 95/100 subsets sampled from all reports and 85/100 sampled from reports generating combinations. Top-74 exclusion produced greater score movement toward the constant model than any sampled subset. Candidate sets also depended on the positive criterion and relation selection rules. We derived reporting items covering supporting reports, W, μ, R, condition-specific year sets, and candidate sets. Interpreting these patterns as attack-behavior changes requires source-event and operational evidence. Full article

Infrared imaging techniques are capable of providing reliable visual information across varying lighting conditions, particularly in environments with low or no illumination. However, traditional infrared image generation methods still face limitations in scene adaptability, image quality, and efficiency. To address this, this paper proposes VTOI-GAN, a lightweight method based on an Enhanced Pix2Pix model. Firstly, a residual dense Unet generator with multiscale feature fusion is constructed to enhance the extraction and reconstruction of image features. Secondly, a dual discriminator incorporating the Sobel operator is designed to fully exploit the high-frequency information in infrared images. Finally, a composite loss function is designed by combining adversarial loss, $L_1$ loss, edge loss, and shallow feature loss to effectively constrain the texture and grayscale information of the infrared images generated. Compared to Pix2Pix, the infrared images generated by VTOI-GAN on the M3FD low-light dataset exhibit improvements of 11.32% in PSNR, 15.53% in SSIM, 35.17% in LPIPS and 23.33% in FID. The experimental results demonstrate that the VTOI-GAN can generate infrared images with higher fidelity, and they are visually closer to real infrared images in terms of similarity metrics. Full article

Magnetite–geopolymer composites have primarily been investigated as adsorbents, whereas their use as enzyme carriers offers a catalytic route for phenol removal. Here, a magnetic allophane–kaolin geopolymer biofunctionalized with tangerine peel extract was developed as a support for covalent horseradish peroxidase (HRP) immobilization. This study combines this material platform with an integrated assessment of phenol and halogenated phenol removal, operational stability, water matrix effects, and post-treatment phytotoxicity. This study evaluates the obtained T-M-AK-G-HRP as a recoverable biocatalyst and assesses the contribution of biofunctionalization by comparing it with pristine and non-biofunctionalized magnetic geopolymer supports. At an initial phenol concentration of 10 mg/L, immobilized HRP (0.7 U/mL, n(H₂O₂)/n(phenol) = 1:1) achieved complete removal within 1 h, whereas the support showed no measurable phenol adsorption under the tested conditions. Removal efficiencies of 72–95% were obtained in spiked real-water matrices after 2 h. At 25 mg/L, removal efficiencies for phenol and derivatives ranged from 80.2% to 96.6% after 1 h. The biocatalyst was magnetically recovered for repeated use, achieving 56.6% phenol removal in the fourth treatment cycle. Treatment also reduced phytotoxicity in the Allium cepa assay. These findings extend magnetic geopolymer applications from pollutant adsorption to enzyme-mediated treatment and identify biofunctionalization as a strategy for improving biocatalyst reusability. Full article

This study examined the potential value of operational records from the Driving Record Analysis System (eTAS) as supplementary information for future service life evaluations of 119 ambulances in South Korea.An international literature review was combined with regional and correlation analyses of 102 ambulances from seven metropolitan and provincial fire headquarters. Nine machine learning models predicting Idling Time were evaluated using 70 ambulances (52 training and 18 testing), excluding 32 Jeonnam ambulances because required operational variables could not be fully extracted. Idling Time differed by approximately six-fold among vehicles with similar Driving Distance. Total Operating Time was strongly correlated with Idling Time (r = 0.93), whereas Driving Distance showed a weaker association. Ridge Regression achieved a Test R² of 0.883, compared with 0.726 for XGBoost. Excluding Total Operating Time reduced the respective Test R² values to 0.654 and 0.533. However, because Idling Time is a component of Total Operating Time, the observed associations and predictive performance may partly reflect this compositional relationship rather than independent effects. The findings suggest that Driving Distance alone cannot fully characterize ambulance utilization and provide preliminary operational evidence for future evaluation frameworks. Relationships with mechanical deterioration, remaining service life, and replacement outcomes require further validation. Full article

The long-term condition monitoring of bonded insulated rail joints (BIRJs) is complicated by operational variability, environmental effects, and changes in the measurement chain. This study presents a methodology for environmentally informed long-term monitoring based on repeated passages of Siemens Vectron locomotives at $160\pm 5\mathrm{km}{\mathrm{h}}^{-1}$, multi-position Macro Fiber Composite sensing, time- and frequency-domain descriptors including variational mode decomposition (VMD), sensor-response ratios, and numerical modal sensitivity analysis. Physical interpretation was restricted to a quality-controlled post-repair spring–summer dataset. Two short-duration high-temperature episodes coincided with consistent changes in the aligned passage waveforms, peak amplitude, and prominence at all sensing positions. The centre frequencies of the dominant low-frequency VMD components remained comparatively stable, whereas component energies exhibited stronger temporal and spatial variability. Ratios between the inner and outer sensors on the same rail revealed a systematic redistribution of the measured response with changing environmental conditions. Numerical sensitivity analysis showed that different frequency regions are preferentially sensitive to ballast-bed and rail-pad stiffness. The results demonstrate that environmentally related variability is measurable in the operational response and must be characterized before structural changes are interpreted as degradation. The proposed framework provides a basis for year-round monitoring and for extension to other critical railway assets. Full article

Egypt’s New Delta mega-project represents the largest horizontal agricultural expansion in modern Egyptian history, creating an urgent need for cost-effective land-cover and crop monitoring systems capable of operating under hyper-arid conditions. This study evaluates the operational feasibility of machine learning (ML)-based land-cover and crop classification using multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) imagery in the El-Daba Development Corridor, Egypt, a hyper-arid component of newly irrigated desert land. Sentinel-1 Ground Range Detected (GRD) data (vertical-vertical (VV) and vertical-horizontal (VH) polarizations) acquired from January to December 2025 were processed within Google Earth Engine (GEE). Monthly composite images were generated to capture phenological development, from which backscatter features, polarization ratios and differences, statistical descriptors, the Radar Vegetation Index (RVI), and Gray-Level Co-occurrence Matrix (GLCM) texture features were extracted. K-Means clustering (K = 10) provided an initial stratification of the feature space, while Random Forest (RF) classification was trained on 840 samples (70%) and validated on 358 independent samples (30%). Temporal backscatter analysis revealed distinct phenological signatures: wheat and sugar beet peaked in March (VV = −7 dB), maize reached maximum backscatter in July (VH = −12 dB, RVI = 0.70), and perennial crops maintained stable signatures year-round. Feature importance analysis identified VH in July (8.7%), VV in March (7.9%), and RVI in July (7.2%) as the most discriminative variables, confirming that combining observations from multiple phenological periods substantially enhances crop separability. The RF classifier achieved 90.5% overall accuracy with a Kappa coefficient of 0.895, with per-class accuracies ranging from 77.8% (vegetables) to 100% (non-agricultural classes). Optimal discrimination windows were identified as February-March for winter cereals, June-July for summer maize, and January/May-June for potato. These results demonstrate that SAR-only land-cover and crop mapping can deliver operationally useful accuracy in hyper-arid environments where optical imagery is constrained, providing a scalable foundation for agricultural monitoring in Egypt’s desert reclamation frontiers and comparable arid systems globally. Full article

Biological nitrogen removal from wastewater with limited organic carbon is challenging, and carbon supplementation increases treatment inputs. We assessed whether an aerobically pre-acclimated microbial consortium could improve nitrogen removal in sequencing batch biofilm reactors treating real domestic wastewater with a low carbon-to-nitrogen ratio. Two reactors with matched carriers, seed sludge, and operating conditions ran for 80 days at ambient temperature without external carbon addition; the bioaugmented reactor received consortium additions during the first 40 days. Influent chemical oxygen demand/total nitrogen averaged 2.14 ± 1.09. During stable operation, total nitrogen removal reached 83.3–88.6% in the bioaugmented reactor versus 69.1–75.9% in the control. The bioaugmented reactor also showed greater ammonium removal and lower effluent nitrate concentrations, whereas chemical oxygen demand removal was similar. Cycle-resolved nitrogen profiles and apparent simultaneous nitrification and denitrification efficiency were consistent with closer coupling of nitrogen transformations. Microbial community profiles, nitrogen-cycling gene abundances, and dissolved organic matter fluorescence indicated accompanying changes in microbial composition, functional potential, and organic-matter characteristics. These findings support consortium addition as a promising approach for improving nitrogen removal from real low-carbon wastewater without external carbon supplementation. Its performance in replicated and larger-scale systems warrants further evaluation. Full article

The Canfranc International Railway Station (Huesca, Spain) opened in 1928 and was listed as a monument in 2002. In 2023 it was converted into a hotel, while the wider railway site was restructured. The aim of this study is to develop and apply an evidence-based attribute-coding framework to document which heritage attributes of a large railway complex are preserved, transformed or replaced by adaptive reuse. The framework is applied through a historical–architectural case study that combines fieldwork campaigns (2010–2023), archival sources and planning documents. Significant attributes are identified in five dimensions (urban configuration, composition, functional organisation, construction and material systems, and landscape character) and coded at both building and precinct scales. In the historic passenger building, the façade composition, the reinforced-concrete structure, the roof and the circulation layout remain legible. The thermal envelope and services, by contrast, were transformed by upgrades designed to EnerPHit criteria. Change is greater in the precinct, where former track fields were replaced by public space, roads and a new operational station, which reduces the legibility of the railway yard. The main contribution is an evidence-linked coding matrix that records change in large station complexes in a consistent way. It supports comparison between cases and may serve as a preparatory layer for stakeholder-weighted multi-criteria assessment. Energy performance, social perception and economic outcomes are not evaluated. Full article

Accurate monitoring of composition-related changes in concentrated pharmaceutical streams is relevant to process control and quality assessment. Here, we experimentally demonstrate a non-functionalized fiber taper-based Mach–Zehnder interferometer (MZI) as a bulk refractive-index sensor using paracetamol solutions as a controlled model system. The sensing mechanism is based on changes in the bulk refractive index of the surrounding medium, which are correlated with paracetamol concentration in controlled aqueous samples prepared using either a paracetamol standard or commercial tablets. Wavelength tracking of the MZI transmission spectra over 0–12.5 mg/mL paracetamol, corresponding to a refractive-index range of 1.333–1.335 RIU, yielded a sensitivity of 233 pm/(mg/mL) and 1497.3 nm/RIU, with a limit of detection (LOD) of 1.08 mg/mL. An intensity-based interrogation provided an average absolute sensitivity of 5.73 × 10⁻⁶ W/(mg/mL), a practical resolution of 44.2 mg/L, and an improved LOD of 75.6 mg/L. Additionally, an MZI configuration in reflection, evaluated using reagent-grade paracetamol standard solutions, yielded a wavelength sensitivity of 318 pm/(mg/mL), while phase tracking of reflected spectra yielded a sensitivity of −97.4 mrad/(mg/mL). These results demonstrate the versatility, linearity, repeatability, temporal stability, and low-maintenance operation of the MZI for bulk refractive-index monitoring, confirming its performance under controlled model system conditions. Full article

This paper develops an observer-based adaptive fuzzy fractional sliding mode control (AFFSMC) approach for trajectory tracking of a four-degree-of-freedom robotic manipulator subject to nonlinear coupling, parametric uncertainty, unmodeled friction, and external disturbances. The approach integrates three components within a single design: a fractional-order PID-type sliding surface that shapes the transient and steady-state error response through Caputo operators, a Mamdani fuzzy reaching law whose gain is scheduled online by a supervisory fuzzy system, and a radial basis function (RBF) neural network estimator that approximates the lumped uncertainty online. The control law is derived with respect to a nominal model, so that inertia, Coriolis, gravity, and friction mismatches, together with the external disturbance, are collected into one lumped uncertainty whose reduced sliding dynamics are derived explicitly. The RBF weight-adaptation law is obtained from the same composite Lyapunov function used for the sliding variable, and the analysis establishes uniform ultimate boundedness with an explicit ultimate bound that depends on the ideal-weight bound, the leakage gain, the reconstruction residual, and the damping gain. Actuator torque limits are incorporated through a saturation-aware gain bound, a conditional-integration anti-windup, and a boundedness result under saturation. Numerical studies on the four-link platform cover four uncertainty scenarios and include a comparison with computed-torque PID, sign-based fractional sliding mode, and fuzzy fractional sliding mode control without the estimator, a study of the estimator regressor, a sensitivity study of the design parameters, and a saturation study. With realistic torque limits, the tracking errors of all four joints converge to a sub-milliradian band within about one second in every scenario, with steady-state errors of 1.4–16 microradians. In the combined-uncertainty scenario, the proposed approach reduces the steady-state error by factors of 4.8, 4.1, and 15 relative to the controller without the estimator, sign-based fractional sliding mode control, and computed-torque PID, while its control-torque total variation is about 190 times lower than that of sign-based fractional sliding mode control. Full article

The cast iron foundry industry has undergone important changes in melting operations, with induction furnaces becoming a major source of molten iron. In many foundries, grey (GI) and ductile (DI) irons are produced simultaneously, including from the same base iron prepared in the same melting furnace. The response of a common base iron to the specific metallurgical treatments required for GI and DI production may differ and can be evaluated by thermal (cooling curve) analysis (TCCA). Experiments were conducted to evaluate, by TCCA, the effects of inoculation on near-eutectic DI (4.10–4.15% CE) and medium-strength GI (3.7–3.8% CE) produced from the same base iron melts, with a limited Mn content and less than 0.02% S. Based on the average values from four melts, inoculation decreased the austenite liquidus temperature by 7.2 °C in DI and 1.8 °C in GI, increased the eutectic undercooling temperature by 16 °C in DI and 2.2 °C in GI, and produced a substantially larger increase in the end-of-solidification temperature in DI. Eutectic recalescence increased by approximately 72% in both irons, while the first-derivative minimum at the end of solidification became more negative after inoculation. The results indicate that the common base iron is suitable for DI production under the specified compositional constraints for ferritic–pearlitic and pearlitic matrices. In contrast, the high degree of undercooling during solidification of the resulting GI increased susceptibility to free-carbide formation and undercooled graphite. Under the present conditions, inoculation had only a limited ability to reduce undercooling during the eutectic reaction and at the end of solidification and to promote sufficient graphitization in GI. Based on previous research on low-sulphur GI, possible improvements are recommended, including stronger inoculation, preconditioning with oxide-forming elements, a more effective inoculation technique, and/or improved graphite nucleation through an increase in the (%Mn) × (%S) factor. Full article

The features of the formation of the porous structure of a Zr(OH)_n(CO₃)_m–ZnO composite adsorbent, as well as its thermal and sorption properties with respect to CO₂, have been studied in relation to life-support systems for closed environments. It has been established that the amorphous micro-mesoporous structure of the material is formed during the synthesis of the adsorbent at the hydrothermal treatment stage as a result of the hydrolysis of zirconium hydroxycarbonate. The specific surface area and micropore volume of the material increase almost a hundredfold compared with the initial zirconium hydroxycarbonate and amount to 298 m²/g and 0.120 cm³/g, respectively. Zinc oxide acts as a stabilizing additive that mitigates the degradation of the porous structure of Zr(OH)_n(CO₃)_m and of the adsorbent as a whole upon its contact with water vapor during operation, particularly during regeneration. The material exhibited a high sorption capacity for carbon dioxide under dynamic conditions (of the order of 9–11.5 L/L at a CO₂ content in the air mixture equal to 0.4–1.0%) and stability over long-term resource testing (4600 adsorption–desorption cycles), which makes it possible to recommend it for CO₂ capture and for the air revitalization of space complexes. Full article