Search Results (3,284)

This study investigates the feasibility of landfill expansion using the limit equilibrium and finite element methods. A 15.5 m high reinforced fill structure (RFS) was analyzed to assess how fill type, consolidation rate, geometric configuration, waste strength, compaction and the inclusion of banquettes affect horizontal displacement, differential settlement, reinforcement strain and facing behavior. The baseline configuration demonstrated acceptable settlement, reinforcement strain, and gabion performance but exceeded allowable horizontal displacement limits. The scenarios including increasing consolidation rate and substitution with sand backfill further aggravated displacements, whereas banquettes significantly reduced lateral movement and settlement, demonstrating their effectiveness in stabilizing slopes. Enhancing the industrial waste properties decreased displacements substantially improving overall stability. Geometric modifications, such as widening the reinforced zone, enhanced displacement control, while higher compaction achieved the best global performance, albeit with increased gabion compressibility. Extending geogrid length provided only marginal improvements beyond a certain threshold. Overall, banquettes, enhanced waste properties, and improved compaction were identified as the most effective strategies for stable efficient landfill expansion, emphasizing the importance of displacement control and reinforcement–facing interaction. Full article

With accelerating urbanization, subway stations, as high-energy-consumption sectors, face significant challenges in maintaining power supply stability and ensuring power quality. This paper proposed a novel voltage compensation solution utilizing superconducting magnetic energy storage (SMES) to suppress voltage fluctuations in the traction system of a large subway station with multiple lines, which was caused by frequent acceleration and regenerative braking of multiple subway trains. Using the MATLAB/Simulink platform, a model of the traction power system with SMES for a large subway station with multiple lines was constructed. Appropriate control methods and hierarchical control strategies were used to suppress voltage fluctuations in both single-line and multi-line configurations at subway stations. The technical advantages of SMES in rapid response and efficient charging/discharging were explored. Overall, results show SMES with the novel control strategies can effectively suppress voltage fluctuations on both single- and triple-line configurations, validating the feasibility in mitigating voltage fluctuations and enhancing regenerative braking energy utilization. Full article

Eutrophication of freshwater bodies is primarily caused by excessive nitrogen and phosphorus, resulting in significant environmental challenges, including harmful algal blooms and hypoxia. This review examines the potential for natural and modified zeolites to act as adsorbents and regulate nutrient concentrations in eutrophic freshwater ecosystems, excluding applications for wastewater or industrial water effluents. Natural zeolites are effective adsorbents of ammonium, whereas modified zeolites (with aluminum, iron, calcium, and many others) have been noted to have enhanced phosphate adsorption and a higher overall nutrient removal efficiency. The application of modified zeolites for controlling eutrophication in freshwater bodies has proven to have high efficiency in adsorbing nitrogen and phosphorus, resulting in reduced nutrient release from sediments and improved water quality in shallow lakes and reservoirs. This review describes the adsorption mechanisms and modification methods, with an appreciation for the multifunctional role of zeolites in nutrient immobilization and capping sediments. Finally, it presents the potential to use zeolite-based materials in eutrophic freshwater restoration through sustainable circular economy approaches. Zeolite materials present ample environmental applications for cost-effective and targeted mitigation approaches to freshwater eutrophication. Full article

Feed and water scarcity are major challenges for the sustainability of livestock production, particularly in semi-arid regions with structural limitations in resource availability. In this context, the valorization of agro-industrial by-products contributes to circular agriculture, reduces waste, and promotes more efficient resource use, in line with the United Nations Sustainable Development Goals. This study evaluated the inclusion of partial mixed tomato residue (PMR) silage in sheep diets and its effects on productive performance, total water intake, and meat quality. Eighteen ewe lambs were assigned to two groups: control (concentrate and deferred pasture) and PMR (tomato residue silage and deferred pasture). The PMR silage had a pH of 3.97 and was mainly characterized by lactic and acetic acids, with minor amounts of propionic and butyric acids. The butyric acid concentration (8.9 g kg⁻¹ DM) slightly exceeded the recommended threshold (0.5% DM), suggesting some clostridial activity but remaining below levels associated with severe deterioration. Animals fed PMR silage showed a 36% higher dry matter intake (p = 0.001), with greater intake of total digestible nutrients and fiber. This translated into a 54% higher average daily gain (p = 0.02) and an 11% greater final body weight compared with the control group (p = 0.02). Dietary water intake was also higher in the PMR group, reducing direct water consumption from drinkers by 38% (p < 0.001). Meat quality parameters were unaffected by the diet. Pesticide residue screening by LC-MS/MS revealed no detectable levels of abamectin, cymoxanil, chlorothalonil, difenoconazole, or mancozeb in silage. In meat samples, only chlorothalonil was tested and it was not detected. However, the use of PMR silage increased direct energy demand due to transport and compaction, while feeding costs per unit of weight gain were reduced. Overall, PMR silage proved to be a safe, fermentatively stable, and effective feeding alternative that enhances performance, reduces direct water intake, and maintains meat quality, representing a viable strategy for small ruminant production in water-limited regions. Full article

This paper presents a serious game designed to support the teaching of PID controllers. The game couples a visually clear Unity scene with a physics-accurate digital model of a drone with a single degree of freedom (called a one-axis drone) and helps prepare students to meet the demands of Industry 4.0 and 5.0. An analytics back-end logs system error at 10 Hz and interaction metrics, enabling instructors to diagnose common tuning issues from a plot and to provide actionable hints to students. The design process that led to choosing the one-axis drone and turbulence application via “turbulence balls” is explained, after which the implementation is described. The proposed solution is evaluated in a within-subjects study performed with 21 students from mixed technical backgrounds across two short, unsupervised tinkering sessions of up to 10 min framed by four quizzes of both general and theoretical content. Three questions shaped the analysis: (i) whether error traces can be visualized by instructors to generate actionable hints for students; (ii) whether brief, unsupervised play sessions yield measurable gains in knowledge or stability; and (iii) whether efficiency of tuning improves without measurable changes in tune performance. Results show that analysis of plotted error values exposes recognizable issues with PID tunes that map to concrete hints provided by the instructor. When it comes to unsupervised play sessions, no systematic pre/post improvement in quiz scores or normalized area under absolute error was observed. However, it required significantly less effort from students in the second session to reach the same tune performance, indicating improved tuning efficiency. Overall, the proposed serious game with the digital twin-inspired one-axis drone and custom analytics back-end has emerged as a practical, safe, and low-cost auxiliary tool for teaching PID controllers, helping bridge the gap between theory and practice. Full article

This study focuses on the design and optimization of a cooling layer system integrated into a thin-thickness mold insert to enhance heat transfer efficiency, control mold temperature, and improve the quality of composite products during injection molding. The Taguchi method with an L25 (5⁴) orthogonal array was employed to investigate four key parameters: insert thickness, cooling layer thickness, water flow rate, and coolant temperature. Among 25 experimental combinations, five representative cases were selected for detailed analysis. The results indicate that the optimal configuration (0.5 mm insert, 10 mm cooling layer, 3.5 L/min flow rate, and 80 °C coolant temperature) successfully maintained a high and stable mold temperature, with a cavity temperature difference of only 3.6 °C at steady state and a simulation–experiment deviation ranging from 2.4% to 7.2%. This condition not only improved melt flowability and surface quality but also reduced defects such as weld lines, warpage, and shrinkage. In parallel, displacement measurements on PA6 and glass fiber-reinforced PA6 (PA6 + GF) composites revealed that increasing the fiber content from 0% to 30% reduced output displacement by more than 19% compared to neat PA6, highlighting the reinforcing effect of glass fibers and the relationship between temperature distribution and mechanical displacement behavior. The findings confirm that integrating a cooling layer into a thin-thickness mold, combined with Taguchi-based optimization, provides an effective approach to enhance through-thickness heat transfer, reduce deformation, and ensure the overall quality of composite injection-molded products in industrial applications. Full article

The niche situation can reflect the advantages and disadvantages of biological individuals in the ecosystem environment as well as the overall operational status of the ecosystem. However, higher-order niche systems generally exhibit complex nonlinearities and parameter uncertainties, making it difficult for traditional Type-1 fuzzy control to accurately handle their inherent fuzziness and environmental disturbances in complex environments. To address this, this paper introduces the backstepping control method based on Type-2 T-S fuzzy control, incorporating the niche situation function as the consequent of the T-S backstepping fuzzy control. The stability analysis of the system is completed by constructing a Lyapunov function, and the adaptive law for the parameters of the niche situation function is derived. This design reflects the tendency of biological individuals to always develop in a direction beneficial to themselves, highlighting the bio-inspired intelligent characteristics of the proposed method. The results of case simulations show that the Type-2 backstepping T-S fuzzy control has significantly superior comprehensive performance in dealing with the complexity and uncertainty of high-order niche situation systems compared with the traditional Type-1 control and Type-2 T-S adaptive fuzzy control. These results not only verify the adaptive and self-development capabilities of biological individuals, as well as their efficiency in environmental utilization, but also endow this control method with a solid practical foundation. Full article

Vertical axis wind turbines (VAWTs) have significant potential for renewable energy generation, yet their operational efficiency is often limited by reduced aerodynamic performance and difficulties during start-up. This study investigates the effect of passive flow control and material selection on the performance of H-Darrieus VAWT blades, with the aim of identifying design solutions that enhance start-up dynamics and overall efficiency. Two-dimensional numerical simulations were conducted using the Dynamic Mesh method with six degrees of freedom (6DOF) in ANSYS 19.2 Fluent, enabling a time-resolved assessment of rotor behavior under constant wind velocities. Two blade configurations were analyzed: a baseline NACA0012 geometry and a modified profile with inclined cavities on the extrados. In addition, the influence of blade material was examined by comparing 3D-printed resin blades with lighter 3D-printed polycarbonate blades. The results demonstrate that cavity-modified blades provide superior performance compared to the baseline, showing faster acceleration, higher tip speed ratios, and improved power coefficients, particularly at higher wind velocities. Furthermore, polycarbonate blades achieved more efficient energy conversion than resin blades, highlighting the importance of material properties in turbine optimization. These findings confirm that combining passive flow control strategies with advanced lightweight materials can significantly improve the aerodynamic and dynamic performance of VAWTs, offering valuable insights for future experimental validation and prototype development. Full article

Joint connections are critical to the overall performance of prefabricated structures. This paper proposes a novel reverse-rotation locking sleeve connection method, designed to ensure the safety of joint engineering while optimizing construction processes, improving operational efficiency, and endowing the joints with excellent seismic energy dissipation performance. To evaluate the performance of this connection method, quasi-static tests under displacement-controlled lateral loading were designed and conducted on three reinforced concrete column specimens (Specimen A: conventional reinforcement–cast-in-place monolithic; Specimen B: conventional reinforcement–reverse-rotation locking sleeve connected; Specimen C: enhanced reinforcement–reverse-rotation locking sleeve connected). The failure modes, hysteretic characteristics, skeleton curves, ductility, energy dissipation capacity, load-bearing capacity, and stiffness degradation patterns of the specimens were systematically examined. The results indicate that Specimen B exhibited the most severe damage extent, while Specimen A demonstrated the best integrity; in contrast, Specimen B showed significant and rapid degradation in energy dissipation capacity during the intermediate-to-late stages of testing; the hysteretic curves of Specimens B and C were full in shape, without obvious yield plateaus; the skeleton curves of all specimens exhibited S-shaped characteristics, and the peak loads of Specimens A and C corresponded to a lateral displacement of 21 mm, while that of Specimen B corresponded to a lateral displacement of 28 mm; compared to the cast-in-place monolithic Specimen A, the reverse-rotation locking sleeve–connected Specimens B and C showed increases in ultimate load under positive cyclic loading by 18.7% and 5.5%, respectively, and under negative cyclic loading by 40.8% and 2.0%, respectively; the ductility coefficients of all three specimens met the code requirement, being greater than 3.0 (Specimen A: 5.13; Specimen B: 3.56; Specimen C: 5.66), with Specimen C exhibiting a 10.3% improvement over Specimen A, indicating that the reverse-rotation locking sleeve–connected specimens possess favorable ductile performance; analysis revealed that the equivalent viscous damping coefficient of Specimen C was approximately 0.06 higher than that of Specimen A, meaning Specimen C had superior energy dissipation capacity compared to Specimen A, confirming that the reverse-rotation locking sleeve connection can effectively absorb seismic energy and enhance the seismic and energy dissipation characteristics of the specimens. The load-bearing capacity degradation coefficients of all specimens fluctuated between 0.83 and 1.01, showing an initial stable phase followed by a gradual declining trend; the stiffness degradation coefficients exhibited rapid initial decline, followed by a deceleration in the attenuation rate, and eventual stabilization. This indicates that the reverse-rotation locking sleeve-connected specimens can maintain relatively stable strength levels and favorable seismic performance during the plastic deformation stage. Full article

Soil salinity severely limits tomato growth by impairing photosynthesis and redox balance. Carbon dots (CDs) have emerged as promising nanomaterials to promote growth and enhance stress tolerance. In this study, we synthesized and characterized CDs derived from Pleurotus eryngii stipe bases (PbCDs), with rich hydrophilic groups including carboxyl groups and secondary amines. The particles were uniform, with an average diameter of 4.17 nm, and exhibited blue fluorescence. Importantly, PbCDs significantly promoted tomato growth under control and salt conditions. Under salt conditions, PbCD-treated plants showed enhanced shoot and root growth, larger leaf area, and growth comparable to control plants without stress. Interestingly, PbCD treatment of the plants enhanced cell expansion under control conditions and promoted cell division under salt conditions. In addition, PbCD-treated plants had higher chlorophyll content, net photosynthetic rate, and maximum quantum efficiency of PSII, which alleviated the inhibition caused by salinity. Furthermore, PbCDs also reduced oxidative damage by lowering O₂^•−, and H₂O₂ levels, while activating antioxidant enzymes (superoxide dismutase, catalase, peroxidase, and ascorbate peroxidase) under salt stress. Overall, PbCDs promoted tomato growth and conferred salt tolerance through coordinated regulation of the cell cycle, photosynthesis, and antioxidant defenses, supporting their potential as sustainable nanomaterials for crop improvement in saline soils. Full article

In complex 3D maneuvering tasks (e.g., post-disaster rescue, urban operations, and infrastructure inspection), the trajectories that quadrotors need to track are often complex—containing both gentle flight phases and highly maneuverable trajectory segments. Under such trajectory tracking tasks with the composite characteristics of “gentle-high maneuvering”, quadrotors face challenges of limited onboard computing resources and short endurance, requiring a balance between trajectory tracking accuracy, computational efficiency, and energy consumption. To address this problem, this paper proposes a lightweight trajectory tracking control method based on hierarchical decision-making and dual-threshold adaptive switching. Inspired by the biological “prediction–reflection” mechanism, this method designs a dual-threshold collaborative early warning switching architecture of “prediction layer–confirmation layer”: The prediction layer dynamically assesses potential risks based on trajectory curvature and jerk, while the confirmation layer confirms in real time the stability risks through an attitude-angular velocity composite index. Only when both exceed the thresholds, it switches from low-energy-consuming Euler angle control to high-precision geometric control. Simulation experiments show that in four typical trajectories (straight-line rapid turn, high-speed S-shaped, anti-interference composite, and narrow space figure-eight), compared with pure geometric control, this method reduces position error by 19.5%, decreases energy consumption by 45.9%, and shortens CPU time by 28%. This study not only optimizes device performance by improving trajectory tracking accuracy while reducing onboard computational load, but also reduces energy consumption to extend UAV endurance, and simultaneously enhances anti-disturbance capability, thereby improving its operational capability to respond to emergencies in complex environments. Overall, this study provides a feasible solution for the efficient and safe flight of resource-constrained onboard platforms in multi-scenario complex environments in the future and has broad application and expansion potential. Full article

This study proposes a compensation method for operating region variations in in-wheel PMSMs, which are widely used in small mobility applications such as e-scooters and e-bikes. As motor temperature increases during operation, electrical parameters such as inductance vary, leading to unstable control. To address this, a Single-Layer Backpropagation Neural Network (SLBPNN) is used to estimate inductance variations in real-time. The proposed algorithm adjusts the motor’s operating point to maintain stable performance under thermal stress. Simulation results using MATLAB 2024b confirm the model’s effectiveness by estimating inductance from voltage, current, speed, and position inputs. Experimental validation further demonstrates that the proposed method compensates for the shift in the operating region due to temperature changes, improving the overall motor efficiency. Full article

With the continuous increase in the penetration of single-phase microgrids in low-voltage distribution networks (LVDNs), the phase asymmetry of source–load distribution has made the problem of three-phase imbalance increasingly prominent. To address this issue, this paper proposes an active–reactive power coordinated optimization model for distribution network–microgrid clusters considering three-phase imbalance mitigation. The model is formulated within a master–slave game framework: in the upper level, the distribution network acts as the leader, formulating time-of-use prices for active and reactive power based on day-ahead forecast data with the objective of minimizing operating costs. These price signals guide the flexible loads and photovoltaic (PV) inverters of the lower-level microgrids to participate in mitigating three-phase imbalance. In the lower level, each microgrid responds as the follower, minimizing its own operating cost by determining internal scheduling strategies and power exchange schemes with the distribution network. Finally, the resulting leader–follower game problem is transformed into a unified constrained model through strong duality theory and formulated as a mixed-integer second-order cone programming (MISOCP) problem, which is efficiently solved using the commercial solver Gurobi. Simulation results demonstrate that the proposed model fully exploits the reactive power compensation potential of PV inverters, significantly reducing the degree of three-phase imbalance. The maximum three-phase voltage unbalance factor decreases from 3.98% to 1.43%, corresponding to an overall reduction of 25.87%. The proposed coordinated optimization model achieves three-phase imbalance mitigation by leveraging existing resources without the need for additional control equipment, thereby enhancing power quality in the distribution network while ensuring economic efficiency of system operation. Full article

Eye movements are regulated by the ocular motor nerves (cranial nerves [CNs] III, IV, and VI), which control the six extraocular muscles of each eye. Palsies of CNs III, IV, and VI can restrict eye movements, resulting in strabismus and diplopia, and so clinical evaluations of eye movements are crucial for diagnosing CN palsies. This study aimed to develop an accurate artificial intelligence (AI) system for classifying CN III, IV, and VI palsies using nine-gaze ocular photographs. We analyzed 478 nine-gaze photographs comprising 70, 29, and 58 cases of CN III, IV, and VI palsies, respectively. The images were processed using MATLAB. For model training, each photograph of eye movements in the nine directions was numerically coded. A multinetwork model was employed to ensure precise analyses of paralytic strabismus. The AI system operates by referring data on minor abnormalities in the nine-gaze image to a network designed to detect CN IV abnormalities, which re-examines downward and lateral gazes to detect distinctions. Data on major abnormalities are directed to a different network trained to differentiate between CN III and VI abnormalities. EfficientNet-B0 was applied to reduce overfitting and improve learning efficiency in training with limited medical imaging data as the neural network architecture. The diagnostic accuracies of the proposed network for CN III, IV, and VI palsies were 99.31%, 97.7%, and 98.22%, respectively. This study has demonstrated the design of an AI model using a relatively small dataset and a multinetwork training system for analyzing nine-gaze photographs in strabismus patients with CN III, IV, and VI palsies, achieving an overall accuracy of 98.77%. Full article

In order to alleviate the constraints of global warming and sustainable development, digitalization has made significant contributions to promoting agricultural carbon reduction through resources, technology, and platforms. Under this situation, China insists on developing agricultural scale management. However, what impact will scale management in agricultural digital emission reduction have on mechanisms and pathways? Based on three rounds of follow-up surveys conducted by the Digital Countryside Research Institute of Nanjing Agricultural University in Jiangsu Province from 2022 to 2024, in this study a total of 258 valid questionnaires on the rice and wheat industry were collected. Methods such as member checking and audit trail were employed to ensure data reliability and validity. Using econometric approaches including Tobit, mediation, and moderation models, this study quantified the Scale Management Level (SML), examined the mechanism pathways of digital emission reduction in a scaled environment, further demonstrated the impact of scale management on digital emission reduction, and verified the mediating and moderating effects of internal and external scale management. We found that: (1) In scale and carbon reduction, the SBM-DEA model calculates that the scale of agricultural land in Jiangsu showed an “inverted S” trend with SML and an “inverted W” trend with the overall agricultural green production efficiency (AGPE), and the highest agricultural green production efficiency is 0.814 in the moderate scale range of 20–36.667 hm². (2) In digitalization and carbon reduction, the Tobit regression model results indicate that Network Platform Empowerment (NPE) significantly promotes carbon reduction (p < 1%), but its squared terms exhibit an inverted U-shaped relationship with agricultural green production efficiency (p < 1%), and SML is significant at the 5% level. From a local regression perspective, the strength of SML’s impact on the three core variables is: NPE > DRE > DTE. (3) Adding scale in agricultural digital emission reduction, the intermediary mechanism results showed that the significant intensity (p < 5%) of the mediating role of Agricultural Mechanization Level (AML) is NPE > DTE > DRE, and that of the Employment of Labor (EOL) is DRE > NPE > DTE. (4) Adding scale in agricultural digital emission reduction, the regulatory effect results showed that the Organized Management Level (OML) and Social Service System (SSS) significantly positively regulate the inhibitory effect of DRE and DTE on AGPE. Finally, we suggest controlling the scale of land management reasonably and developing moderate agricultural scale management according to local conditions, enhancing the digital literacy and agricultural machinery training of scale entities while encouraging the improvement of organizational level and social service innovation, and reasonably reducing labor and mechanization inputs in order to standardize the digital emission reduction effect of agriculture under the background of scale. Full article