Search Results (840)

Organic–inorganic compound fertilizer application technology is a key technology for chemical fertilizer efficiency improvement, and stable grain yield increase. However, current agricultural machinery is unable to achieve uniform application of both organic and inorganic fertilisers. This study has compared two modeling methods and optimally selected the EDEM-Fluent coupled method. It aims to investigate the mechanism by which four factors—namely inorganic fertilizer drop location (Polar angle: −80° to 80°, polar radius: 60 mm to 180 mm), organic fertilizer flow rate (875–3500 g·s⁻¹), inorganic fertilizer proportion (10–50%), and fertilizer spreading disc rotational speed (300–700 r·min⁻¹)—influence inorganic fertilizer uniformity. A Box–Behnken test was designed with the pole angle and pole diameter of the drop location, organic fertiliser flow rate, spreading disc rotational speed, and coefficient of variation in the uniformity of the inorganic fertilisers as indexes. The Box–Behnken test divided the fertiliser drop location into left and right parts and established a mathematical model of fertiliser drop location, rotational speed, and organic fertiliser flow rate. Finally, the predictive performance of the model was verified in the field by testing four scenarios: low speed–low flow rate, low speed–high flow rate, high speed–low flow rate, and high speed–high flow rate. The root mean square error (RMSE) between the EDEM-Fluent coupled test and the bench test is 1.53, which is better than the RMSE (2.55) between the EDEM test and the bench test. Before optimization, the coefficients of variationof inorganic fertilizer (ICV) under four operating conditions were 28.93%, 32.43%, 38.17%, and 29.32% respectively. After optimization, the corresponding values were 19.34%, 23.78%, 21.45%, and 23.10% respectively. Compared with the pre-optimization results, the organic fertilizer coefficient of variation (OCV) remained stable, while the inorganic fertilizer coefficient of variation (ICV) decreased by an average of 10.29%. This study greatly improved the uniformity of inorganic fertiliser in the organic–inorganic spreader and provides a basis for subsequent intelligent spreaders. Full article

Background: Anemoside B4 (AB4), the major bioactive saponin from Pulsatilla chinensis, exhibits anti-inflammatory, anti-tumor, anti-apoptotic, and analgesic properties. However, its clinical translation for ulcerative colitis (UC) is constrained by poor epithelial permeability and low oral bioavailability. Objective: This study’s objective was to engineer and optimize thermosensitive rectal in situ gels (ISGs) of AB4, incorporating suitable absorption enhancers to improve mucosal permeation, bioavailability, and therapeutic efficacy against UC. Methods: Screening of effective permeation enhancers was conducted using Caco-2 cell monolayers and Franz diffusion cells. Critical formulation variables such as poloxamer 407 (P407), poloxamer 188 (P188), and hydroxypropyl methyl cellulose (HPMC) were optimized, employing single-factor experiments coupled with the Box–Behnken design response surface methodology (BBD-RSM). Comprehensive characterization encompassed in vitro release kinetics, in vivo pharmacokinetics, rectal tissue tolerability, rectal retention time, and pharmacodynamic efficacy in a UC model. Results: We used 2.5% hydroxypropyl-β-cyclodextrin (HP-β-CD) and 1.0% sodium caprate (SC) as the appropriate absorption enhancers, and the amounts of P407, P188, and HPMC were 17.41%, 4.07%, and 0.44%, respectively, to yield the corresponding in situ gels HP-β-CD-AB4-ISG and SC-AB4-ISG. The gel characterization, such as gelation temperature, gelation time, pH, gelation strength, etc., was in accordance with requirements. The ISGs did not stimulate or damage rectal tissue and remained in the rectum for a prolonged period. More importantly, an improvement in bioavailability and alleviation of UC were noted. Conclusion: Absorption enhancer-assisted, poloxamer-based thermosensitive rectal ISGs provide a safe, convenient, and effective platform for targeted delivery of AB4 to the colorectum. This strategy addresses key limitations of oral dosing and warrants further clinical development for UC and related colorectal inflammatory diseases. Full article

This study investigates an integrated solar-driven single-effect H₂O–LiBr absorption chiller powered by low-grade thermal energy. A detailed thermodynamic model, comprising a solar collector, a thermal storage tank, and an absorption cycle, was developed using the Engineering Equation Solver (EES) software V10.561. A comprehensive parametric analysis and multi-objective optimization were then conducted to enhance both the energy and exergy performance of the system. The Response Surface Methodology (RSM), based on the Box–Behnken Design, was employed to develop regression models validated through analysis of variance (ANOVA). The generator temperature (78–86 °C), evaporator temperature (2.5–6.5 °C), and absorber/condenser temperature (30–40 °C) were selected as key variables. According to the results, the single-objective analyses revealed maximum values of COP = 0.8065, cooling capacity = 20.72 kW, and exergy efficiency = 39.29%. Subsequently, the multi-objective RSM optimization produced a balanced global optimum with COP = 0.797, cooling capacity = 20.68 kW, and exergy efficiency = 36.93%, achieved under optimal operating conditions of 78 °C generator temperature, 6.5 °C evaporator temperature, and 30 °C absorber/condenser temperature. The obtained results confirm the significance of the proposed low-grade solar absorption chiller, demonstrating comparable or superior performance to recent studies (e.g., COP ≈ 0.75–0.80 and ≈35–37%). This agreement validates the RSM-based optimization approach and confirms the system’s suitability for sustainable cooling applications in low-temperature solar environments. Full article

To enhance the effectiveness and precision of design and to produce more low-carbon and high-performance Engineered Cementitious Composites (ECCs), novel hybrid fiber-reinforced high-ductility cementitious composites developed by incorporating a combination of ultra-high-molecular-weight polyethylene fibers (UHMWPE) and basalt fibers (BFs) into the cementitious matrix. Building upon the Box–Behnken design model from Response Surface Methodology (RSM), this study investigates the effects of different water-to-binder ratios and fiber contents on the mechanical properties of hybrid fiber-reinforced ECC. Analysis of variance (ANOVA) was used to validate the regression models. Furthermore, multi-objective optimization of the ECC mix proportion was achieved by employing the NSGA-II algorithm in conjunction with the TOPSIS comprehensive evaluation method. The results indicate that UHMWPE and BFs exhibited a significant positive hybrid effect. The order of factor significance was as follows: The content of ultra-high-molecular-weight polyethylene is greater than that of basalt fiber, and the content of basalt fiber is greater than that of the water–binder ratio. The results of variance analysis show that the regression model has high fitting accuracy. Furthermore, the algorithmic optimization yielded an optimal mix proportion: a water-to-binder ratio of 0.21, UHMWPE fiber content of 1.51%, and BF content of 0.85%. This study provides a valuable reference for the multi-objective optimization design of ECC mix proportions targeting diverse strength and toughness requirements. Full article

Background: Glioma remains an intractable and highly aggressive brain tumor, mainly due to the daunting obstacle presented by the blood–brain barrier (BBB). To overcome this challenge and enhance therapeutic efficacy, a dual-drug delivery system was engineered. This system co-encapsulated curcumin, a nutraceutical with multitargeted anticancer potential, with atorvastatin calcium, a repurposed anticancer agent, within lipidic nanocapsules (LNCs). Methods: LNCs were prepared via the phase inversion temperature method and optimized using a Box–Behnken design. The optimized LNCs were subsequently functionalized with folic acid (FA) to enable active targeting. FA-LNCs were characterized using XPS, TEM, in vitro release, and MTT cytotoxicity assays. Atorvastatin and curcumin were radiolabeled separately with iodine-131 to evaluate the in vivo pharmacokinetics in a glioma-bearing mouse model. Results: The optimized LNCs and FA-LNCs displayed a mean particle size of 97.98 ± 2.27 nm and 181.60 ± 2.83 nm, a polydispersity index of 0.32 ± 0.07 and 0.40 ± 0.02, and a zeta potential of −15.85 ± 1.35 mV and −11.90 ± 2.80, respectively. XPS and FTIR analyses verified FA conjugation. Both LNCs and FA-LNCs enhanced the in vitro cytotoxicity compared to free drugs; however, the most pronounced effect of FA functionalization was observed in vivo. Most significantly, FA-LNCs achieved markedly greater glioma accumulation than non-functionalized LNCs, with AUC values 2.0-fold higher for atorvastatin and 2.6-fold higher for curcumin. When compared to the free drug solutions, this efficiency was even more pronounced, with atorvastatin and curcumin showing enhancements of 8.2 and 12.4 times, respectively. Conclusions: FA-LNCs markedly improved glioma targeting efficiency and reduced systemic clearance, which underscores the therapeutic potential of integrating nutraceuticals with repurposed agents to achieve effective glioma therapy. Full article

The green husk of Juglans regia L. is rich in bioactive phytochemicals and exhibits various biological activities. This study aimed to investigate the skin anti-aging potential of the green husk of J. regia by determining the optimal extraction conditions using a Box–Behnken Design (BBD), targeting elastase inhibition, and by correlating variations in phenolic compounds identified through metabolomic analyses with changes in the extraction conditions. Ultrasonic-assisted extraction was employed along with natural deep eutectic solvents (NADES). Three levels of three independent variables (NADES/H₂O ratio, temperature, and extraction time) were incorporated into the BBD. Phenolic compounds were determined semi-quantitatively using liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-q-TOF/MS), while elastase inhibition was evaluated by spectroscopic methods. Quadratic response surface models were proposed based on the BBD model adequacy test using multiple regression analysis. It was determined that the optimum conditions for maximizing phenolic content and elastase inhibition were 99.79% ethanol, 51.30 °C temperature, and 49.58 min, in which case the desirability score was 1. Metabolomic analysis identified 41 phenolic compounds across 27 ontological groups, with 24 compounds showing a semi-quantitative increase. Consequently, the waste green husk of J. regia demonstrated enhanced anti-aging potential due to the higher content and diversity of phenolic compounds. Full article

Background/Objectives: Despite the advantages of polycaprolactone (PCL) for drug delivery, it still lacks effective approaches to enhance its encapsulation of drugs. Blending PCL with less hydrophobic polymers can tailor physicochemical properties to overcome these limitations. This study, for the first time, integrates two beneficial approaches—polymer blending and Box–Behnken design (BBD) optimisation—to develop PCL-based blend nanoparticles (NPs) with enhanced encapsulation efficiency (EE), controlled particle size, and improved stability through surface charge modulation. Methods: Drug-loaded blend NPs were developed using a double emulsion method, with different polymer ratios. A BBD model was employed to investigate the influential factors that control the size, charge, and EE. Results: Blending PCL with a less hydrophobic polymer significantly improved EE, achieving 60.96% under optimal conditions. The BBD model successfully predicted conditions for obtaining NPs with optimum size, negative charge, and enhanced drug encapsulation. The drug amount was identified as the most influential factor for EE, while polymer amounts significantly impacted size and charge. Conclusions: Careful control of polymer ratios, drug amount, and surfactant levels was shown to significantly influence particle size, surface charge, and EE, with the balanced 50:50 PCL:PLGA blend achieving optimal physicochemical performance. Using the BBD, the study identified the predicted optimal formulation consisting of 162 mg polymer blend, 8.37 mg drug, and 8% surfactant, which is expected to yield NPs with a size of 283.06 nm, zeta potential of −31.54 mV, and EE of 70%. The application of BBD allowed systematic evaluation of the factors and their interactions, providing robust predictive models. Full article

Electrocoagulation (EC) employing aluminum–aluminum (Al–Al) electrodes was investigated for hospital wastewater treatment, targeting the removal of turbidity, soluble chemical oxygen demand (sCOD), and total dissolved solids (TDS). A hybrid modeling framework integrating response surface methodology (RSM) and artificial neural networks (ANN) was developed to enhance predictive reliability and identify energy-efficient operating conditions. A Box–Behnken design with 15 experimental runs evaluated the effects of pH, current density, and electrolysis time. Multi-response optimization determined the overall optimal conditions at pH 7.0, current density 20 mA/cm², and electrolysis time 75 min, achieving 94.5% turbidity, 69.8% sCOD, and 19.1% TDS removal with a low energy consumption of 0.34 kWh/m³. The hybrid RSM–ANN model exhibited high predictive accuracy (R² > 97%), outperforming standalone RSM models, with ANN more effectively capturing nonlinear relationships, particularly for TDS. The results confirm that EC with Al–Al electrodes represent a technically promising and energy-efficient approach for decentralized hospital wastewater treatment, and that the hybrid modeling framework provides a reliable optimization and prediction tool to support process scale-up and sustainable water reuse. Full article

The study of Leymus chinensis seed cleaning has been hindered by the lack of accurate discrete-element contact parameters for seed–straw interactions, thereby limiting, to some extent, the optimization of cleaning equipment. To address this issue, the present study analyzed a mixture of L. chinensis seeds and straw, and determined their fundamental physical and contact parameters via laboratory experiments. The Hertz–Mindlin (no slip) discrete element simulation model was employed to calibrate the parameters of the seed–straw mixture. A Plackett–Burman test was used to identify key factors significantly affecting the repose angle, including the seed–seed static friction coefficient and the seed–straw static and dynamic friction coefficients. These factors’ optimal ranges were further refined using steepest ascent experiments. A Box–Behnken design was used to optimize contact parameters, resulting in the following values: a seed–seed static friction coefficient of 0.709, a seed–straw static friction coefficient of 0.281, and a seed–straw dynamic friction coefficient of 0.085. Validation experiments demonstrated an error of less than 2.14%, confirming the reliability of the calibrated parameters. This study offers a theoretical foundation for discrete element simulations in L. chinensis seed cleaning applications. Full article

This study presents a newly developed program that seamlessly converts G-code into formats compatible with Abaqus, enabling precise finite element simulations for FDM 3D printing. The tool operates on a two-pronged framework: a mathematical model incorporating key print parameters (layer thickness, extrusion temperature, print speed, and raster width) and a shape generator managing geometric parameters (fill density, pattern, and raster orientation). Initially, a predefined virtual section, based on predetermined dimensions, enhanced the correlation between experimental results and simulations. Subsequently, a corrected virtual section, derived from the mathematical model using the Box–Behnken methodology, improves accuracy, achieving a virtual thickness error of 1.06% and a width error of 8%. The model is validated through tensile testing of ASTM D638 specimens at 0°, 45°, and 90° orientations, using adaptive C3D4 mesh elements (0.35–0.6 mm). Results demonstrate that the corrected cross-section significantly improved simulation accuracy, reaching correlations above 95% in the elastic zone and 90% in the elastoplastic zone across all orientations. By optimizing the workflow from design to manufacturing, this program offers substantial benefits for the aerospace, medical, and automotive sectors, enhancing both the efficiency of the printing process and the reliability of simulations. Full article

A phosphogypsum flotation tailings-derived zeolite (PGTZ) was synthesized from the tailings produced during the reverse flotation of phosphogypsum through alkaline fusion and hydrothermal treatment. The response surface methodology (RSM) utilizing a three-level Box–Behnken design (BBD) was used to assess the adsorption of MB by PGTZ. Polynomial regression models were developed to analyze the effects of process parameters on adsorption capacity (q_e). The maximum MB adsorption occurred under the following optimized conditions: PGTZ dosage = 5.31 g·L⁻¹; initial MB concentration = 294.59 mg·L⁻¹; pH = 7.42; and adsorption time = 187.89 min. Additionally, adsorption isotherm and kinetic models were fitted to the experimental data to determine model parameters. The Langmuir isotherm model and pseudo-second-order kinetic model incorporating intraparticle diffusion were able to effectively predict MB adsorption onto PGTZ. Thermodynamic analyses indicated that the adsorption process was spontaneous, with strong chemical interactions between MB and PGTZ. Full article

In response to the poor soil loosening effect of the previous bionic four-bar deep loosening mechanism, this study optimized the bionic motion trajectory according to agronomic requirements, established a trajectory synthesis optimization model of the Stephenson III six-bar mechanism, and solved it using an improved differential evolution algorithm to design a six-bar deep loosening mechanism achieving the optimized trajectory. Based on the Box–Behnken experiment, a regression model of the mechanism’s process parameters and performance indicators was established, and multiple indicators were integrated into a single objective via a satisfaction function. The optimal process parameters obtained were: entry angle 99.61°, shovel distance 185 mm, forward speed 0.29 $\mathrm{m}/\mathrm{s}$, and input speed $5\pi$ rad/s. A comparative simulation using the Discrete Element Method (DEM) showed that, compared to the bionic four-bar mechanism, the six-bar mechanism reduces resistance by 9.91%, increases soil-breaking capacity by 4.23%, reduces shallow disturbance by 14.43%, increases deep disturbance by 29.54%, and improves overall disturbance effect by 42.71%, verifying the effectiveness of agronomic-driven bionic trajectory optimization. Indoor soil tank experiments measured an average resistance of 258.83 N, with a relative error of 8.67% compared to the simulation result (281.32 N). The experiments and simulations were consistent in soil-breaking layer range, soil layer disturbance range, and soil discharge state, validating the model and the six-bar deep loosening mechanism. Full article

This study addresses the challenges encountered in mechanized agricultural fields, particularly the soil disruption associated with conventional horizontal rotary straw cleaning equipment. To mitigate the inefficiency of straw cleaning observed in the current vertical rotary apparatus, this study introduces a vertical rotary fixed-angle straw cleaning device. The essential conditions for establishing the cutter tooth angle were identified through theoretical analysis. Analyzing the kinematics of the cutter tooth to direct the movement of the straw, we determined that the deflection angle of the cutter tooth group (DA) is a critical parameter for enhancing the effectiveness of straw cleaning. A multiphase interaction model encompassing soil, straw, and machinery components was developed utilizing a coupled simulation approach with RecurDyn and EDEM software. The Box–Behnken response surface methodology was employed to systematically investigate the interaction effects of three critical parameters on both the straw cleaning rate and the soil disturbance rate: operation speed (OS), rotation speed of the straw cleaning rotary table (RS), and the DA. For optimization experiments where the OS is set to 2.4 m/s, RS is 400 r/min, and DA is 48°, the straw cleaning rate reaches 94.1% and the soil disturbance rate is 27.2%. This device can efficiently create a localized clean seeding belt for no-till planters without significantly damaging the soil structure, providing an innovative solution for the development of low-disturbance, high-efficiency conservation tillage equipment. Full article

To solve the problems of large root damage and incomplete seedling blocks (SBs) in rice machine transplanting, this study numerically optimized the root blanket-cutting device for rice blanket seedling cutting and throwing transplanters based on the discrete element method (DEM) and multi-body dynamics (MBD) coupling method. A longitudinal sliding cutter (LSC)–substrate–root interaction model was established. Based on the simulation tests of Center Composite Design and response surface analysis, the sliding angle and cutter shaft speed of the LSCs arranged at the circumferential angles (CAs) of 0°, 30°, and 60° were optimized. The simulation results indicated that the LSC arrangement CA significantly affected the cutting performance, with the optimal configuration achieved at a CA of 60°. Under the optimal parameters (sliding angle of 57°, cutter shaft speed of 65.3 r/min), the average deviation between the simulated and physical tests was less than 11%, and the reliability of the parameters was verified. A seedling needle–substrate–root interaction model was established. The Box–Behnken Design method was applied to conduct simulation tests and response surface optimization, focusing on the picking angle, needle width, and rotary gearbox speed. The simulation results showed that the picking angle was the key influencing factor. Under the optimal parameters (picking angle of 20°, seedling needle width of 15 mm, rotary gearbox speed of 209 r/min), the average deviation between the simulated and physical tests was less than 10%, which met the design requirements. This study provides a new solution for reducing root injury, improving SB integrity, and reducing energy consumption in rice transplanting, and provides theoretical and technical references for optimizing transplanting machinery structure and selecting working parameters. Full article

Conventional ridging and mulching machines struggle to perform effectively in yellow sand substrates due to their loose texture, high collapsibility, and strong fluidity, which compromise ridge stability and operational quality. To address these challenges, this study proposes the development of an integrated rotary tillage, ridging, and film-mulching machine specifically designed to meet the agronomic requirements of tomato cultivation in greenhouse environments with yellow sand substrate. Based on theoretical analysis and parameter calculations, a soil transportation model was established, and the key structural parameters—such as blade arrangement and helical shaft geometry—were determined. A discrete element method (DEM) simulation was employed to construct a contact model for the yellow sand–slag mixed substrate. A combination of single-factor experiments and Box–Behnken response surface methodology was used to investigate the effects of forward speed, shaft rotational speed, and tillage depth on ridge stability and operational performance. The simulation results indicated that a forward speed of 0.82 m·s⁻¹, shaft speed of 260 rpm, and tillage depth of 150 mm yielded the highest ridge stability, with an average of 95.7%. Field trials demonstrated that the ridge top width, base width, height, and spacing were 598.6 mm, 802.3 mm, 202.4 mm, and 1002.8 mm, respectively, with an average ridge stability of 94.3%, differing by only 1.4 percentage points from the simulated results. However, a quantitative traction/energy comparison with conventional equipment was not collected in this study, and we report this as a limitation. The energy consumption is estimated based on power usage and effective field capacity (EFC) under similar operating conditions. Soil firmness reached 152.1 kPa, fully satisfying the agronomic requirements for tomato cultivation. The proposed machine significantly improves operational adaptability and ridge stability in yellow sand substrate conditions, providing robust equipment support for efficient greenhouse farming. Full article