Search Results (61,381)

Soil stabilizers using conventional cement and lime binders incur high environmental costs owing to CO₂ emissions associated with their excavation, production, and processing. This has motivated research on low-carbon, waste-derived alternatives. The review shows that: biochar increases unconfined compressive strength (UCS) by 15–40% with a 2–5% dosage through pore filling and particle binding; nanocellulose promotes soil cohesion by 25–60% through fibrous network development and tensile bridging; recycled PET powder at 5–10% increases shear strength by 20–35% promoting mechanical interlocking, increasing stiffness, crack resistance and durability. Biochar provides direct carbon sequestration with a carbon transfer capacity of up to 2.5 tons CO₂-eq/ton. Recycled PET introduces waste valorization, with the potential to divert millions of tons of annual PET waste, while nanocellulose provides indirect carbon savings by avoiding emissions from cement and lime replacement. This review’s objectives are as follows: providing a comprehensive comparison of biochar, nanocellulose, and PET powder as promising non-cement composite stabilizers; identifying optimal dosage ranges and stabilization mechanisms for each material across different soil types; and outlining knowledge gaps and future research directions in sustainable geotechnical practices. The review assessed the individual and synergistic effects of the additives on critical geotechnical properties, including unconfined compressive strength (UCS), California bearing ratio (CBR), resilient resistance, swelling resistance, and the durability of the treated soil. Findings provide actionable guidance for practitioners seeking to reduce construction carbon footprints while maintaining geotechnical performance standards. Research gaps were identified, and future directions for integrating high-performance, low-carbon soil composites into sustainable construction solutions are proposed. Full article

Harmonic reducers exhibit non-stationary and phase-dependent degradation behavior during long-term service, challenging the ability of classical stochastic degradation models to accurately assess reliability. To address phase-dependent differences in degradation behavior, this paper proposes a reliability assessment model based on a two-phase hybrid stochastic degradation process. In the proposed framework, the Wiener process is employed to characterize early-phase gradual degradation dominated by stochastic fluctuations, while the Inverse Gaussian process is used to describe later-phase monotonically accelerated degradation driven by cumulative damage. The framework allows for sample-level variability in transition times to more realistically capture individual degradation behavior. The Schwarz Information Criterion is also adopted to detect change points. Maximum likelihood estimation is performed for model parameter inference, and analytical expressions for the reliability function, cumulative distribution function, and probability density function are derived. Numerical results indicate that a change point exists for each tested product and that the proposed model achieves the best goodness of fit among the considered candidates, demonstrating its superiority in capturing phase-dependent characteristics of harmonic reducer degradation. In terms of reliability assessment bias, the proposed model (0.06%) significantly outperforms the Wiener degradation model (32%) and the IG degradation model (9.9%). These results further confirm that, under an identical failure threshold, the proposed approach yields more accurate and realistic reliability assessment outcomes. Full article

Food waste filtrate (FW) and landfill leachate (LL) are high-strength organic wastewaters with complex compositions that pose significant challenges for conventional biological treatment. Anaerobic co-digestion is considered an effective strategy to improve process stability and methane recovery through substrate complementarity. In this study, an internal circulation (IC) anaerobic reactor was used to evaluate the co-digestion performance of FW and LL at different volumetric mixing ratios (3:7, 5:5, and 7:3). Methane production, COD removal, pH, volatile fatty acids (VFA), alkalinity, extracellular polymeric substances (EPS), enzyme activities, sludge morphology, and sludge structural and spectroscopic characteristics were analyzed to evaluate process performance and explore stability-related responses under different mixing ratios. The results showed that the 5:5 mixing ratio achieved the best overall performance. Under this condition, methane content remained at 78.79–81.60%, the volumetric methane production rate reached 893.38–1080.43 L CH₄/(m³·d), and methane yield was 0.219–0.265 L CH₄/g COD. COD removal efficiency was maintained at 86.93–88.35%. Meanwhile, the reactor operated within a relatively stable window, with pH of 6.98–7.80, VFA of 485.6–521.6 mg/L, alkalinity of 2000–3100 mg CaCO₃/L, and a VFA/TA ratio of 0.167–0.261. Compared with the other ratios, the 5:5 condition was associated with higher EPS levels, more favorable enzyme activity patterns, and a more compact sludge structure. Overall, FW-LL co-digestion exhibited clear ratio dependence, and the 5:5 mixing ratio provided the best balance between methane production, organic matter removal, and process stability. These findings offer quantitative support for substrate-ratio optimization and stable operation of anaerobic treatment systems for high-strength organic wastewaters. Full article

Electrocatalytic H₂O₂ production via the two-electron oxygen reduction reaction (ORR) is a highly sustainable alternative to industrial methods. To further optimize non-noble catalysts, we report an interfacial engineering strategy to stabilize the metastable P6₃/mmc-La₂O₃ phase on SrTiO₃. This symmetry evolution from the low-symmetry $\mathrm{P}\stackrel{\mathrm{-}}{3}\mathrm{m}1$ (trigonal) to the high-symmetry P6₃/mmc (hexagonal) space group yields a composite with >95% H₂O₂ selectivity. Mechanistic studies demonstrate that the symmetry-regulated interface optimizes *OOH conversion and suppresses O–O bond cleavage. This work offers a robust design principle for high-performance, noble-metal-free H₂O₂ electrosynthesis. Full article

Beef production is widely recognized as a significant contributor to global greenhouse gas emissions, making robust and transparent environmental assessments essential for advancing sustainability within supply chains. This study applies a comprehensive cradle-to-grave Life Cycle Assessment (LCA) to evaluate the environmental performance of beef destined for export, following ISO 14040, ISO 14044 and ISO 14067 standards and the Product Category Rules for meat of mammals. Sixteen impact categories were quantified for 1 kg of vacuum-packed beef using detailed primary data from a pasture-based production system and a representative processing facility. The total climate change impact was 3.27 × 10¹ kg CO₂eq, with enteric methane and feed production jointly responsible for over 70% of overall impacts. Slaughtering and distribution were associated mainly with fossil energy use and ozone depletion, while soil carbon sequestration partially compensated biogenic emissions. The results were consistent with international benchmarks, highlighting the environmental advantages of pasture-based systems, low fertilizer use, and stable land management. Key hotspots were identified in animal growth, feed efficiency, and manure management, with logistics also contributing notably. Overall, the study provides a high-resolution environmental baseline that can support Environmental Product Declarations and guide targeted mitigation strategies across beef supply chains. While the results are derived from a specific pasture-based production system, the study is positioned as a case-study-based application of a high-resolution LCA framework, illustrating how detailed inventories can support environmental benchmarking and hotspot identification without implying statistical representativeness of all beef production systems. Full article

Cooperation plays a central role in the sustainability of agricultural value chains. This study analyzes cacao and dairy producer organizations in the Department of Caquetá, Colombia, with three objectives: to characterize their current organizational status, to understand legal representatives’ perceptions of the role of cooperation in strengthening their organizations, and to examine the structure of cooperation networks across different stages of the value chains. A qualitative approach was adopted, based on structured interviews, participatory network-mapping workshops, and secondary data analysis. The results show that cacao organizations exhibit higher levels of institutional consolidation than dairy organizations. Representatives’ perceptions indicate that in cacao, cooperation is primarily oriented toward administrative and strategic strengthening, whereas in dairy it is concentrated on production, budgeting, and marketing. Network analysis reveals a predominance of linking-type cooperation, characterized by vertical relationships with external actors, which enhances access to resources but also generates dependency. Overall, network structure and the prevailing types of cooperation influence organizational autonomy and collective performance in Amazonian contexts. Full article

Efficient task allocation and coordination are critical for heterogeneous multi-agent systems operating in dynamic field environments. This paper presents a closed-loop framework that integrates Large Language Models (LLMs) with graph-based optimisation to enable end-to-end task decomposition, allocation, and adaptive execution. High-level task scripts are initially parsed by an LLM into structured execution flows, which are transformed into Directed Acyclic Graphs (DAGs) capturing action-level dependencies. A Genetic Algorithm (GA) then optimises agent-to-task assignments by minimising makespan under capability and battery constraints. To ensure robustness, the framework incorporates an LLM-driven recovery module that enables localised replanning under execution failures without interrupting unaffected agents. System-level experiments in a high-fidelity agroforestry simulation demonstrate a 37% increase ($p<0.001$) in harvesting productivity and a 19% reduction in human idle time compared to manual baselines. Under mid-execution failures, the system maintains significantly higher performance, with replanning latencies averaging 24 s. The framework scales to large fleets (up to 1000 agents) and effectively enhances human–robot collaboration through structured, dependency-aware coordination. Full article

Surface ozone monitoring remains challenging due to sparse ground networks and limited satellite boundary-layer sensitivity. This study evaluates, for the first time, China’s Environmental Trace Gases Monitoring Instrument II (EMI-II) for estimating surface ozone over the Beijing–Tianjin–Hebei (BTH) region. EMI-II total ozone columns (TOCs) are retrieved using the differential optical absorption spectroscopy (DOAS) algorithm and validated against the TROPOspheric Monitoring Instrument (TROPOMI) (R = 0.96), Geostationary Environment Monitoring Spectrometer (GEMS) (R = 0.97), and the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) ground measurements (R > 0.92, bias < 4%). TOCs are then combined with ERA5 meteorology, satellite NO₂/HCHO, and surface observations within machine learning models, achieving cross-validated R² of 0.94 and RMSE of 12.05 μg/m³ for surface ozone estimation. EMI-II estimates show strong agreement with independent observations (R = 0.91, RMSE = 10.83 μg/m³) and reproduce seasonal gradients, with summer concentrations (131 μg/m³) more than double winter levels (61 μg/m³). Estimation skill is regime-dependent: performance comparable to TROPOMI occurs under strong photochemical activity, while reduced sensitivity occurs under weak radiation and stable boundary layers—consistent with averaging kernel diagnostics. This first comprehensive validation demonstrates that EMI-II, despite vertical sensitivity limitations, provides meaningful surface ozone constraints under favorable atmospheric conditions. The framework is potentially applicable to other regions and sensors under similar conditions, providing a case study for integrating national satellite products into multi-source surface ozone estimation. Full article

This study evaluated the performance, carcass yield, and meat quality of slow-growing chickens fed diets containing different levels of replacement of crude protein from soybean meal with crude protein from cottonseed meal (CSM), with and without supplementation of 2% lysine. A total of 600 male chickens of the Red Colonial heavy strain were used and evaluated from 8 to 56 and to 77 days of age. In Experiment 1, chickens were fed diets with 0, 15, 30, and 45% replacement of soybean meal protein by CSM protein; in Experiment 2, the same replacement levels were associated with supplementation of 2% lysine based on the protein content of CSM. The 15% replacement level promoted higher live weight and average weight gain at 56 and 77 days. Feed conversion ratio at 56 and 77 days indicated that replacing soybean meal protein with CSM protein, with the addition of 2% lysine relative to the protein value, resulted in improved values for this variable. It is concluded that replacing up to 15% of soybean meal protein with cottonseed meal protein, with or without supplementation of 2% lysine, does not compromise productive parameters, carcass yield, or meat quality in slow-growing chickens. Full article

Heat stress is a major environmental stressor in poultry production that reduces growth performance and induces oxidative stress, inflammatory responses, and lung tissue injury. This study investigated the protective effects of dietary supplementation with Ginkgo biloba extract and tea polyphenols against heat stress-induced lung injury in broilers. A total of 320 one-day-old broilers were reared under standard management conditions until 21 days of age. Subsequently, 300 birds with similar body weight were selected and randomly allocated into six groups: a thermoneutral control group, a heat stress group, a heat stress group supplemented with 300 mg/kg tea polyphenols, and three heat stress groups receiving 300 mg/kg tea polyphenols combined with 100, 300, or 600 mg/kg Ginkgo biloba extract. The analysis of the results showed that heat stress significantly reduced the average daily gain and feed intake while increasing the feed conversion ratio. It also markedly increased serum lactate dehydrogenase activity and malondialdehyde levels, while decreasing antioxidant-related indicators, indicating the occurrence of oxidative stress and inflammatory responses. Histological examination revealed lung injury characterized by alveolar wall thickening, epithelial cell shedding, and disruption of the endothelial barrier, accompanied by upregulated expression of heat shock proteins and inflammation-related signaling genes. Supplementation with tea polyphenols alone partially alleviated these changes. Notably, the combined supplementation of Ginkgo biloba extract and tea polyphenols exerted more pronounced protective effects, significantly enhancing antioxidant capacity, attenuating inflammatory responses, and maintaining pulmonary barrier integrity. Among the tested levels, the groups receiving 300 mg/kg Ginkgo biloba extract in combination with tea polyphenols showed the most evident improvements. These findings suggest that the combined use of these plant-derived extracts effectively mitigates heat stress-induced lung injury in broilers. Full article

The integration of electric mobility and energy systems has emerged as a key research domain in the transition toward sustainable energy and decarbonized transport, yet the literature is lacking systematic quantitative overviews of its scientific development. This study addresses this gap by conducting a bibliometric analysis of research activities across five domains central to electric vehicle–energy system integration: central energy management systems; renewable energy, hydrogen production, and large-scale storage; industrial applications; smart energy communities, virtual power plants, and vehicle-to-X; and urban high-power charging parks with local storage. Using publication data from Web of Science and Scopus, performance analysis and science mapping techniques were applied to examine publication dynamics, thematic structures, and intellectual linkages. Results indicate strong growth and consolidation around smart grids and decentralized flexibility solutions, particularly within energy management, renewable integration, and community-based energy systems, while industrial applications and high-power charging infrastructures remain comparatively underrepresented. The findings suggest a maturing interdisciplinary field characterized by expanding connections between mobility and energy research, alongside emerging opportunities related to industrial integration, charging infrastructure, and vehicle-to-grid deployment. The study provides a structured, multi-domain perspective on the convergence of electric mobility and energy systems, enabling a differentiated understanding of research dynamics. The study provides a structured, multi-domain perspective on the convergence of electric mobility and energy systems. The findings highlight priority areas for future research, particularly industrial integration and scalable charging infrastructure, and offer insights for policymakers and industry stakeholders. Full article

Improving environmental sustainability while maintaining economic viability is a major challenge for Mediterranean cereal production, where conventional systems are associated with high input use, elevated greenhouse gas emissions, and strong cost pressures. Although Conservation Agriculture (CA) and Precision Agriculture (PA) are widely promoted as promising solutions, evidence on their combined environmental and economic performance under real farming conditions remains limited. This study evaluated CA, PA, and their combined application (CPA) in winter cereal systems in Greece, using three years of farmer-managed field data from four representative sites. Agronomic and environmental performance and economic outcomes were assessed under actual farm sizes and a scaled 300 ha scenario. Across sites and years, no systematic yield differences were observed among CA, PA, and CPA, indicating that alternative systems can maintain yield stability under real farmer-managed conditions. Environmental performance was driven primarily by tillage intensity: CA reduced CO₂eq emissions by 212–238 kg ha⁻¹ relative to conventional tillage, while CPA achieved the largest reductions (262–332 kg ha⁻¹), accompanied by surface-layer SOM increases of 0.30–0.56% over three years. PA applied within conventional tillage resulted in only modest emission reductions (41–82 kg ha⁻¹), but consistently improved NUE, with variable-rate fertilization increasing NUE by approximately 5–7% relative to uniform application. Despite these environmental benefits, economic performance remained constrained due to high fixed machinery costs, high input prices, and low grain values resulting in negative net profits across all systems. CA reduced total costs by 3.8–11.8%, PA delivered only marginal improvements, while CPA achieved the largest cost reductions (5.0–12.6%) delivering also the most stable net profit mitigation. Carbon credit revenues increased profitability by only 2–3%. Scaling to 300 ha improved competitiveness through fixed-cost dilution, but profitability remained unattainable. Overall, integrated CA–PA systems offer substantial environmental benefits but require targeted policy support, cooperative machinery use, and service-based solutions to enable economically viable adoption in Mediterranean cereal systems. Full article

This paper examines the effect of gas oil fraction extraction depth from fuel oil on the physicochemical and performance properties of road bitumen. The study’s novelty lies in establishing the relationship between the seven-component chemical group composition of heavy residues and their oxidation kinetics. It has been experimentally demonstrated that using feedstock with a nominal viscosity (VU80) in the range of 20–80 s (corresponding to fractions of 480–525 °C) enables the production of bitumen that simultaneously meets the requirements of ASTM D946, EN 12591, and ST RK 1373. The paper substantiates an optimal “viscosity range” for processing non-standard feedstock, ensuring increased resistance of the finished product to thermal-oxidative aging. Full article

The electrification of the automotive industry and the lightweighting of aerospace equipment demand high-efficiency centrifugal pumps for compact spaces. A novel centrifugal pump incorporates an integrated impeller-motor rotor design, achieving a more compact footprint and higher power density. However, research is scarce on the radial clearance between the rotor and casing. This study presents a comprehensive investigation of the internal flow dynamics, combining numerical simulations with experimental validation. A significant reduction in fluctuation amplitude for pump efficiency, head coefficient, and frictional loss rate occurs when the clearance ranges from 1.0 to 1.5 mm. Within clearances of 0.75 to 1.5 mm, complex vortex systems emerge in the radial clearance, inducing diverse circumferential high-speed zones. Pressure fluctuations within the radial clearance are predominantly governed by the blade passing frequency. At a clearance of 1.5 mm, the rotational harmonic amplitude at monitoring points exceeds the blade passing frequency amplitude by a factor of 1.9, while the average pressure fluctuation intensity at other points increases significantly by 36.9%. An optimal clearance of 1.25 mm achieves a balance between flow characteristics and energy consumption. This research provides practical insights for optimizing pump energy performance and operational stability. Full article

Rapid and reliable tea classification is valuable for routine product screening, yet conventional sensory or physicochemical methods are subjective or time-consuming. Electronic nose (E-nose) sensing provides a fast alternative, but performance often degrades under domain shifts caused by different tea types, commercial categories, or acquisition conditions. This study proposes MGDA-Net, a multi-granularity domain adversarial network for cross-domain tea classification using E-nose time-series signals. MGDA-Net learns local temporal dynamics via a CNN branch and global contextual dependencies via a self-attention branch, and fuses them through an adaptive gating module. A branch-level adversarial alignment strategy is introduced to reduce source–target discrepancy at both local and global feature levels. A three-stage training procedure, consisting of source pretraining, adversarial alignment, and target fine-tuning, enables knowledge transfer from a labeled green tea source-domain to two target tasks. Experiments on oolong tea commercial-category classification (6 classes) and jasmine tea retail price-level classification (8 classes) show that MGDA-Net achieves mean accuracies of 99.31 ± 0.69% and 99.38 ± 0.51% over 10 independent runs, substantially outperforming all compared baseline methods. Ablation studies, feature-space analyses, and label-efficiency experiments further confirm the contribution of each component and show that MGDA-Net maintains mean accuracies above 87% when only 40% of the target-domain labels are used for fine-tuning. These findings suggest that MGDA-Net is a promising approach for cross-domain tea classification using E-nose data. Full article