Search Results (4,412)

The integration of a real-time image processing system using multiple webcams with a variable rate spraying system mounted on the back of an unmanned tractor presents an effective solution to the labor shortage in agriculture. This research aims to design and fabricate a low-cost, variable-rate, remote-controlled sprayer specifically for use in sugarcane fields. The primary method involves the modification of a 15-horsepower tractor, which will be equipped with a remote-control system to manage both the driving and steering functions. A foldable remote-controlled spraying arm is installed at the rear of the unmanned tractor. The system operates by using a webcam mounted on the spraying arm to capture high-angle images above the sugarcane canopy. These images are recorded and processed, and the data is relayed to the spraying control system. As a result, chemicals can be sprayed on the sugarcane accurately and efficiently based on the insights gained from image processing. Tests were conducted at various nozzle heights of 0.25 m, 0.5 m, and 0.75 m. The average system efficiency was found to be 85.30% at a pressure of 1 bar, with a chemical spraying rate of 36 L per hour and a working capacity of 0.975 hectares per hour. The energy consumption recorded was 0.161 kWh, while fuel consumption was measured at 6.807 L per hour. In conclusion, the development of the remote-controlled variable rate sprayer mounted on an unmanned tractor enables immediate and precise chemical application through remote control. This results in high-precision spraying and uniform distribution, ultimately leading to cost savings, particularly by allowing for adjustments in nozzle height from a minimum of 0.25 m to a maximum of 0.75 m from the target. Full article

The complex system of high-entropy materials makes it challenging to reveal the specific function of each site for oxygen evolution reaction (OER). Here, with nickel foam (NF) as the substrate, FeCoNiCrMo/NF is designed to be prepared by metal–organic frameworks (MOF) as a precursor under an argon atmosphere. XRD analysis confirms that it retains a partial MOF crystal structure (characteristic peak at 2θ = 11.8°) with amorphous carbon (peaks at 22° and 48°). SEM-EDS mapping and XPS demonstrate uniform distribution of Fe, Co, Ni, Cr, and Mo with a molar ratio of 27:24:30:11:9. Electrochemical test results show that FeCoNiCrMo/NF has excellent OER characteristics compared with other reference prepared samples. FeCoNiCrMo/NF has an overpotential of 285 mV at 100 mA cm⁻² and performs continuously for 100 h without significant decline. The OER mechanism of FeCoNiCrMo/NF further reveal that Co and Ni are true active sites, and the dissolution of Cr and Mo promote the conversion of active sites into MOOH following the lattice oxygen mechanism (LOM). The precipitation–dissolution equilibrium of Fe also plays an important role in the OER process. The study of different reaction sites in complex systems points the way to designing efficient and robust catalysts. Full article

The dispersion behavior of ceramic particles in aluminum alloys during rapid solidification critically affects the resulting microstructure and mechanical performance. In this study, we investigated the nucleation and growth of Al₃(Sc,Zr) on TiB₂ surfaces in a 2TiB₂/Al–8Ni–0.6Sc–0.1Zr alloy, fabricated via wedge-shaped copper mold casting and laser surface remelting. Thermodynamic calculations were employed to optimize alloy composition, ensuring sufficient nucleation driving force under rapid solidification conditions. The results show that the formation of Al₃(Sc,Zr)/TiB₂ composite interfaces is highly dependent on cooling rate and plays a pivotal role in promoting uniform TiB₂ dispersion. At an optimal cooling rate (~1200 °C/s), Al₃(Sc,Zr) nucleates heterogeneously on TiB₂, forming core–shell structures and enhancing particle engulfment into the α-Al matrix. Orientation relationship analysis reveals a preferred (111)α-Al//(0001)TiB₂ alignment in Sc/Zr-containing samples. A classical nucleation model quantitatively explains the observed trends and reveals the critical cooling-rate window for composite interface formation. This work provides a mechanistic foundation for designing high-performance aluminum-based composites with uniformly dispersed reinforcements for additive manufacturing applications. Full article

The persistent challenge of fracture-driven interference (FDI) during large-scale hydraulic fracturing in the southern Sichuan Basin has severely compromised shale gas productivity, while the existing research has inadequately addressed both FDI risk reductions and the optimization of reservoir stimulation. To bridge this gap, this study developed a mechanistic model of the competitive multi-cluster fracture propagation under non-uniform perforation conditions and established a perforation-based design methodology for the mitigation of horizontal well interference. The results demonstrate that spindle-shaped perforations enhance the uniformity of fracture propagation by 20.3% and 35.1% compared to that under uniform and trapezoidal perforations, respectively, with the perforation quantity (48) and diameter (10 mm) identified as the dominant control parameters for balancing multi-cluster growth. Through a systematic evaluation of the fracture communication mechanisms, three distinct inter-well types of FDI were identified: Type I (natural fracture–stress anisotropy synergy), Type II (natural-fracture-dominated), and Type III (stress-anisotropy-dominated). To mitigate these, customized perforation schemes coupled with geometry-optimized fracture layouts were developed. The surveillance data for the offset well show that the pressure interference decreased from 14.95 MPa and 6.23 MPa before its application to 0.7 MPa and 0 MPa, achieving an approximately 95.3% reduction in the pressure interference in the application wells. The expansion morphology of the inter-well fractures confirmed effective fluid redistribution across clusters and containment of the overextension of planar fractures, demonstrating this methodology’s dual capability to enhance the effectiveness of stimulation while resolving FDI challenges in deep shale reservoirs, thereby advancing both productivity and operational sustainability in complex fracturing operations. Full article

As a new functional graded lattice structure construction strategy, the relative density gradient strategy has a promising future due to its ease of realization in various lattice structures. This paper proposes a BCC lattice structure combining two different lattice single cells. Based on this, the single cells of different structures are assigned different relative density gradients, resulting in 18 combined gradient lattice structures. Based on proving the experimental feasibility of numerical simulation, the mechanical properties and energy absorption characteristics of the combined gradient lattice structure are investigated by numerical simulation. When applied to composite lattice structures, the proposed wave-like gradient design significantly improves mechanical properties. Among the various gradient strategies examined, several have achieved mechanical performance close to that of uniform lattice structures. To some extent, this approach mitigates the common drawback of gradient lattice structures—where the relative density of the weakest layer is consistently lower than the interlayer relative density of uniform lattice structures—resulting in varying degrees of mechanical performance degradation compared to their uniform counterparts. The proposed linearly enhanced gradient strategy (Strategy-LE) possesses higher SEA and CLE values when the lattice structure is subjected to compressive loading, with an improvement of 6.36% in SEA and 61.6% in CLE over the uniform structure. Through the relative density gradient design, the adaptability of the BCC lattice structure in actual complex application scenarios is greatly enhanced, and the energy-absorbing properties of the lattice structure are greatly improved. Full article

Though the pursuit of sustainable desalination processes with high water recovery has intensified the research interest in membrane distillation (MD), the influence of module connection configuration on performance stability remains poorly explored. The current study provided a comprehensive multiparameter assessment of hollow fibre membrane modules connected in parallel and series in direct contact membrane distillation (DCMD) for the first time. The configurations were evaluated under varying process parameters such as temperature (50–70 °C), flow rates (22.1–32.3 mL·s⁻¹), magnesium concentration as scalant (1.0–4.0 g·L⁻¹), and flow direction (co-current and counter-current), assessing their influence on temperature gradients (∆T), flux and pH stability, salt rejection, and crystallisation. Interestingly, the parallel module configuration maintained high operational stability with uniform flux and temperature differences (∆T) even at high recovery factors (>75%). On one hand, the serial configuration experienced fluctuating ∆T caused by thermal and concentration polarisation, causing an early crystallisation (abrupt drop in feed conductivity). Intensified polarisation effects with accelerated crystallisation increased the membrane risk of wetting, particularly at high recovery factors. Despite these changes, the salt rejection remained relatively high (99.9%) for both configurations across all tested conditions. The findings revealed that acidification trends caused by MgSO₄ were configuration-dependent, where the parallel setup-controlled rate of pH collapse. This study presented a novel framework connecting membrane module architecture to mass and heat transfer phenomena, providing a transformative DCMD module configuration design in water desalination. These findings not only provide the critical knowledge gaps in DCMD module configurations but also inform optimisation of MD water desalination to achieve high recovery and stable operation conditions under realistic brine composition. Full article

Secondary hypereutectic Al-Si alloys are attractive for sustainable manufacturing, yet their application is often limited by low strength and electrical conductivity due to impurity-induced microstructural defects. Achieving a balance between mechanical and conductive performance remains a significant challenge. In this work, nickel-coated carbon nanotubes (Ni-CNTs) were introduced into secondary Al-20Si alloys to tailor the microstructure and enhance properties through interfacial engineering. Composites containing 0 to 0.4 wt.% Ni-CNTs were fabricated by conventional casting and systematically characterized. The addition of 0.1 wt.% Ni-CNTs resulted in the best combination of properties, with a tensile strength of 170.13 MPa and electrical conductivity of 27.60% IACS. These improvements stem from refined α-Al dendrites, uniform eutectic Si distribution, and strong interfacial bonding. Strengthening was achieved through grain refinement, Orowan looping, dislocation generation from thermal mismatch, and the formation of reinforcing interfacial phases such as AlNi₃C₀.₉ and Al₄SiC₄. At higher Ni-CNT contents, property degradation occurred due to agglomeration and phase coarsening. This study presents an effective and scalable strategy for achieving strength–conductivity synergy in secondary aluminum alloys via nanoscale interfacial design, offering guidance for the development of multifunctional lightweight materials. Full article

The development of gas sensors with high sensitivity and low operating temperatures is essential for practical applications in environmental monitoring and industrial safety. SnO₂-based gas sensors, despite their widespread use, often suffer from high working temperatures and limited sensitivity to H₂ gas, which presents significant challenges for their performance and application. This study addresses these issues by introducing a novel SnO₂-based sensor featuring a three-dimensional (3D) nanostructure, designed to enhance sensitivity and allow for room-temperature operation. This work lies in the use of a 3D anodic aluminum oxide (AAO) template to deposit SnO₂ nanoparticles through ultrasonic spray pyrolysis, followed by modification with platinum (Pt) nanoparticles to further enhance the sensor’s response. The as-prepared sensors were extensively characterized, and their H₂ sensing performance was evaluated. The results show that the 3D nanostructure provides a uniform and dense distribution of SnO₂ nanoparticles, which significantly improves the sensor’s sensitivity and repeatability, especially in H₂ detection at room temperature. This work demonstrates the potential of utilizing 3D nanostructures to overcome the traditional limitations of SnO₂-based sensors. Full article

Background/Objectives: This study aimed to determine whether postpartum mothers exhibit a uniform trajectory of postpartum emotional status (PES) changes or if distinct subgroups with differing trajectories of PES exist. Additionally, it investigated whether intensified tactile stimulation of the infant through Shantala massage influences maternal PES. Method: A quasi-experimental design with a matched control group was employed. Eighty women following their first physiological delivery volunteered to participate. The intervention involved applying intensified tactile stimulation to the infant via Shantala massage over a 12-week postpartum period. Maternal PES, divided into negative and positive emotional domains, was assessed using four standardized questionnaires. Results: Two opposing trajectories of PES change were identified: adverse and favorable. Intensified tactile stimulation was associated with improvement in maternal emotional status along both trajectories. Conclusions: PES changes do not follow a uniform course across all women; notably, those with a favorable trajectory often begin with more severe symptoms. Overlooking this distinction in diagnosis, prevention, and treatment may result in suboptimal care. The factors influencing PES trajectories remain unidentified but may affect clinical intervention outcomes. The Shantala massage intervention appears to slow the progression of emotional disorders in women with adverse PES changes and accelerate recovery in those with favorable changes. Implementation of this approach in clinical settings is recommended. Full article

A multi-objective optimal trajectory planning method is proposed for manipulators in this paper to enhance motion efficiency and to reduce component wear while ensuring motion smoothness. The trajectory is initially interpolated in the joint space by using quintic non-uniform B-splines with virtual points, achieving the C⁴ continuity of joint motion and satisfying dynamic, kinematic, geometric, synchronization, and boundary constraints. The interpolation reformulates the trajectory planning problem into an optimization problem, where the time intervals between desired adjacent waypoints serve as variables. Travelling time and the integral of the squared jerk along the entire trajectories comprise the multi-objective functions. A constrained multi-objective dream optimization algorithm is designed to solve the time–jerk optimal trajectory planning problem and generate Pareto solutions for optimized trajectories. Simulations conducted on 6-DOF manipulators validate the effectiveness and superiority of the proposed method in comparison with existing typical trajectory planning methods. Full article

As the core equipment for efficient wastewater treatment, the internal structure of microporous aeration bioreactors directly determines the mass transfer efficiency and treatment performance. Based on Computational Fluid Dynamics (CFD) technology, this study explores the optimization mechanism of a Spherical Grid-Structured on the internal flow field of the reactor through a 3D numerical simulation system, aiming to improve the aeration efficiency and resource utilization. This study used a combination of experimental and numerical simulations to compare and analyze different configurations of the Spherical Grid-Structure. The simulation results show that the optimal equilibrium of the flow field inside the reactor is achieved when the diameter of the grid sphere is 2980 mm: the average flow velocity is increased by 22%, the uniformity of the pressure distribution is improved by 25%, and the peak turbulent kinetic energy is increased by 30%. Based on the Kalman vortex street theory, the periodic vortex induced by the grid structure refines the bubble size to 50–80 microns, improves the oxygen transfer efficiency by 20%, increases the spatial distribution uniformity of bubbles by 35%, and significantly reduces the dead zone volume from 28% to 16.8%, which is a decrease of 40%. This study reveals the quantitative relationship between the structural parameters of the grid and the flow field characteristics through a pure numerical simulation, which provides a theoretical basis and quantifiable optimization scheme for the structural design of the microporous aeration bioreactor, which is of great significance in promoting the development of low-energy and high-efficiency wastewater treatment technology. Full article

Understanding vehicle emissions is essential for developing effective carbon reduction strategies in the transport sector. Conventional emission models often assume homogeneity and linearity, overlooking real-world asymmetries that arise from variations in vehicle design and powertrain configurations. This study explores how machine learning and explainable AI techniques can effectively capture both symmetric and asymmetric emission patterns across different vehicle types, thereby contributing to more sustainable transport planning. Addressing a key gap in the existing literature, the study poses the following question: how do structural and behavioral factors contribute to asymmetric emission responses in internal combustion engine vehicles compared to new energy vehicles? Utilizing a large-scale Spanish vehicle registration dataset, the analysis classifies vehicles by powertrain type and applies five supervised learning algorithms to predict CO₂ emissions. SHapley Additive exPlanations (SHAPs) are employed to identify nonlinear and threshold-based relationships between emissions and vehicle characteristics such as fuel consumption, weight, and height. Among the models tested, the Random Forest algorithm achieves the highest predictive accuracy. The findings reveal critical asymmetries in emission behavior, particularly among hybrid vehicles, which challenge the assumption of uniform policy applicability. This study provides both methodological innovation and practical insights for symmetry-aware emission modeling, offering support for more targeted eco-design and policy decisions that align with long-term sustainability goals. Full article

Chaotic systems have demonstrated significant potential in the field of image encryption due to their extreme sensitivity to initial conditions, inherent unpredictability, and pseudo-random behavior. However, existing chaos-based encryption schemes still face several limitations, including narrow chaotic regions, discontinuous chaotic ranges, uneven trajectory distributions, and fixed pixel processing sequences. These issues substantially hinder the security and efficiency of such algorithms. To address these challenges, this paper proposes a novel hyperchaotic map, termed the two-dimensional cross-coupled chaotic map (2D-CFCM), derived from a newly designed 2D cross-coupled chaotic system. The proposed 2D-CFCM exhibits enhanced randomness, greater sensitivity to initial values, a broader chaotic region, and a more uniform trajectory distribution, thereby offering stronger security guarantees for image encryption applications. Based on the 2D-CFCM, an innovative image encryption method was further developed, incorporating efficient scrambling and forward and reverse random multidirectional diffusion operations with symmetrical properties. Through simulation tests on images of varying sizes and resolutions, including color images, the results demonstrate the strong security performance of the proposed method. This method has several remarkable features, including an extremely large key space (greater than $2^{912}$), extremely high key sensitivity, nearly ideal entropy value (greater than 7.997), extremely low pixel correlation (less than 0.04), and excellent resistance to differential attacks (with the average values of NPCR and UACI being $99.6050\%$ and $33.4643\%$, respectively). Compared to existing encryption algorithms, the proposed method provides significantly enhanced security. Full article

Under conservation tillage in the Huang-Huai-Hai wheat–maize rotation area, the ridge-clearing no-till seeder for strip tillage mitigates the adverse impacts of surface residues on seeding quality by clearing stubble specifically within the seed rows, demonstrating significant potential for application and promotion. However, the inadequate understanding of the seeder’s operational performance and governing mechanisms under varying field conditions hinders its high-quality and efficient implementation. To address this issue, this study selected the stubble height, forward speed, and stubble knife rotational speed (PTO speed) as experimental factors. Employing a three-factor quasi-level orthogonal experimental design, coupled with response surface regression analysis, this research systematically elucidated the interaction mechanisms among these factors concerning the seeding depth consistency and seed spacing uniformity of the seeder. An optimized parameter-matching model was subsequently derived through equation system solving. Field trials demonstrated that a lower forward speed improved the seed spacing uniformity and seeding depth consistency, whereas high speeds increased the missing rates and spacing deviations. An appropriate stubble height enhanced the seed spacing accuracy, but an excessive height compromised depth precision. Higher PTO speeds reduced multiple indices but impaired depth accuracy. Response surface analysis based on the regression models demonstrated that the peak value of the seed spacing qualification index occurred within the forward speed range of 8–9 km/h and the stubble height range of 280–330 mm, with the stubble height being the dominant factor. Similarly, the peak value of the seeding depth qualification index occurred within the stubble height range of 300–350 mm and the forward speed range of 7.5–9 km/h, with the forward speed as the primary factor. Validation confirmed that combining stubble heights of 300−330 mm, forward speeds of 8−9 km/h, and PTO speeds of 540 r/min optimized both metrics. This research reveals nonlinear coupling relationships between operational parameters and seeding quality metrics, establishes a stubble–speed dynamic matching model, and provides a theoretical foundation for the intelligent control of seeders in conservation tillage systems. Full article

In this paper, a joint Matching Field Processing (MFP) Algorithm based on horizontal uniform circular array (UCA) is proposed for three-dimensional position of underwater wrecked targets. Firstly, a Marine search and rescue position model based on Minimum Variance Distortionless Response (MVDR) and matching field quadratic joint Algorithm was proposed. Secondly, an MVDR beamforming method based on pre-Kalman filtering is designed to refine the real-time DOA estimation of the desired signal and the interference source, and the sound source azimuth is determined for prepositioning. The antenna array weights are dynamically adjusted according to the filtered DOA information. Finally, the Adaptive Matching Field Algorithm (AMFP) used the DOA information to calculate the range and depth of the lost target, and obtained the range and depth estimates. Thus, the 3D position of the lost underwater target is jointly estimated. This method alleviates the angle ambiguity problem and does not require a computationally intensive 2D spectral search. The simulation results show that the proposed method can better realise underwater three-dimensional positioning under certain signal-to-noise ratio conditions. When there is no error in the sensor coordinates, the positioning error is smaller than that of the baseline method as the SNR increases. When the SNR is 0 dB, with the increase in the sensor coordinate error, the target location error increases but is smaller than the error amplitude of the benchmark Algorithm. The experimental results verify the robustness of the proposed framework in the hierarchical ocean environment, which provides a practical basis for the deployment of rapid response underwater positioning systems in maritime search and rescue scenarios. Full article