Search Results (2,926)

In this study, we aimed to address the lack of systematic research on key collision dynamics parameters (elastic restitution coefficient) in the full mechanization of rapeseed operations, which hinders the development of precision agriculture. In this present work, the restitution coefficient of rapeseed was systematically investigated, and a predictive model (R² = 0.959) was also established by using Box–Behnken design response surface methodology (BBD-RSM). The results show that the collision restitution coefficient varies in the range of 0.539–0.649, with the key influencing factors ranked as follows: moisture content (M_c) > material layer thickness (L) > drop height (H). The EDEM simulation methodology was adopted to validate the experimental results, and the results show that there is a minimal relative error (−1% < δ < 1%) between the measured and simulated rebound heights, indicating that the established model shows a reliable prediction performance. Moreover, by comprehensively analyzing stress, strain, and energy during the collision process between rapeseed and Q235 steel, it can be concluded that the process can be divided into five stages—free fall, collision compression, collision recovery, rebound oscillation, and rebound stabilization. The maximum stress (1.19 × 10⁻² MPa) and strain (6.43 × 10⁻⁶ mm) were observed at the beginning of the collision recovery stage, which can provide some theoretical and practical basis for optimizing and designing rapeseed machines, thus achieving the goals of precise control, harvest loss reduction, and increased yields. Full article

Tea cultivation faces significant threats from red spider mite (RSM: Oligonychus coffeae) infestations, which reduce yields and economic viability in major tea-producing regions. Current automated detection methods rely on supervised deep learning models requiring extensive labeled data, limiting scalability for smallholder farmers. This article proposes AIM-Net (AI-based Infestation Mapping Network) by evaluating SwAV (Swapping Assignments between Views), a self-supervised learning framework, for classifying RSM infestation severity (Mild, Moderate, Severe) using a geo-referenced, field-acquired dataset of RSM infested tea-leaves, Cam-RSM. The methodology combines SwAV pre-training on unlabeled data with fine-tuning on labeled subsets, employing multi-crop augmentation and online clustering to learn discriminative features without full supervision. Comparative analysis against a fully supervised ResNet-50 baseline utilized 5-fold cross-validation, assessing accuracy, F1-scores, and computational efficiency. Results demonstrate SwAV’s superiority, achieving 98.7% overall accuracy (vs. 92.1% for ResNet-50) and macro-average F1-scores of 98.3% across classes, with a 62% reduction in labeled data requirements. The model showed particular strength in Mild_RSM-class detection (F1-score: 98.5%) and computational efficiency, enabling deployment on edge devices. Statistical validation confirmed significant improvements (p < 0.001) over baseline approaches. These findings establish self-supervised learning as a transformative tool for precision pest management, offering resource-efficient solutions for early infestation detection while maintaining high accuracy. Full article

Carbon deposits on the crown of engine pistons can markedly reduce combustion efficiency and shorten service life. Conventional cleaning techniques often fail to simultaneously ensure a high carbon removal efficiency and maintain optimal surface integrity. To enable efficient and precise carbon removal, this study proposes the application of hybrid laser cleaning—combining continuous-wave (CW) and pulsed lasers—to piston carbon deposit removal, and employs response surface methodology (RSM) for multi-objective process optimization. Using the N52B30 engine piston as the experimental substrate, this study systematically investigates the combined effects of key process parameters—including CW laser power, pulsed laser power, cleaning speed, and pulse repetition frequency—on surface roughness (Sa) and carbon residue rate (RC). Plackett–Burman design was employed to identify significant factors, the method of the steepest ascent was utilized to approximate the optimal region, and a quadratic regression model was constructed using Box–Behnken response surface methodology. The results reveal that the Y-direction cleaning speed and pulsed laser power exert the most pronounced influence on surface roughness (F-values of 112.58 and 34.85, respectively), whereas CW laser power has the strongest effect on the carbon residue rate (F-value of 57.74). The optimized process parameters are as follows: CW laser power set at 625.8 W, pulsed laser power at 250.08 W, Y-direction cleaning speed of 15.00 mm/s, and pulse repetition frequency of 31.54 kHz. Under these conditions, the surface roughness (Sa) is reduced to 0.947 μm, and the carbon residue rate (RC) is lowered to 3.67%, thereby satisfying the service performance requirements for engine pistons. This study offers technical insights into the precise control of the hybrid laser cleaning process and its practical application in engine maintenance and the remanufacturing of end-of-life components. Full article

Due to the increasing environmental concerns and the growing generation of electronic waste and plastic, sustainable waste management solutions are essential for the construction industry. This study explores the potential of using electronic waste toner powder (WTP) and recycled low-density polyethylene (LDPE), either individually or in combination as modifiers for asphalt binder to enhance pavement performance and reduce environmental impact. The analysis focused on three key components: (1) binder development and testing; (2) performance evaluation through Marshall stability, indirect tensile strength, and Dynamic Shear Rheometer (DSR) testing for rutting resistance; and (3) sustainability assessment in terms of carbon footprint reduction. The results revealed that the formulation of 25% WTP and 8% LDPE processed at 160 °C achieved the best mechanical performance and lowest carbon index, enhancing Marshall stability by 32% and rutting resistance by 41%. Additionally, this formulation reduced the carbon footprint by 27% compared to conventional asphalt. The study demonstrated that the combination of WTP and LDPE significantly improves the sustainability and performance of asphalt pavements, offering mechanical, environmental, and economic benefits. By providing a quantitative assessment of waste-modified asphalt, this study uniquely demonstrates the combined use of WTP and LDPE in asphalt, offering a novel dual-waste valorization approach that enhances pavement performance while promoting circular economy practices. Full article

Background: Precision medicine refers to the formulation of personalized drug regimens according to the individual characteristics of patients to achieve optimal efficacy and minimize adverse reactions. Additive manufacturing (AM), also known as three-dimensional (3D) printing, has emerged as an optimal solution for precision drug delivery, enabling customizable and the fabrication of multifunctional structures with precise control over morphology and release behavior in pharmaceutics. However, the influence of 3D printing parameters on the printed tablets, especially regarding in vitro and in vivo performance, remains poorly understood, limiting the optimization of manufacturing processes for controlled-release profiles. Objective: To establish the fabrication process of 3D-printed controlled-release tablets via comprehensively understanding the printing parameters using fused deposition modeling (FDM) combined with hot-melt extrusion (HME) technologies. HPMC-AS/HPC-EF was used as the drug delivery matrix and carbamazepine (CBZ) was used as a model drug to investigate the in vitro drug delivery performance of the printed tablets. Methodology: Thermogravimetric analysis (TGA) was employed to assess the thermal compatibility of CBZ with HPMC-AS/HPC-EF excipients up to 230 °C, surpassing typical processing temperatures (160–200 °C). The formation of stable amorphous solid dispersions (ASDs) was validated using differential scanning calorimetry (DSC), hot-stage polarized light microscopy (PLM), and powder X-ray diffraction (PXRD). A 15-group full factorial design was then used to evaluate the effects of the fan speed (20–100%), platform temperature (40–80 °C), and printing speed (20–100 mm/s) on the tablet properties. Response surface modeling (RSM) with inverse square-root transformation was applied to analyze the dissolution kinetics, specifically t_50% (time for 50% drug release) and Q_4h (drug released at 4 h). Results: TGA confirmed the thermal compatibility of CBZ with HPMC-AS/HPC-EF, enabling stable ASD formation validated by DSC, PLM, and PXRD. The full factorial design revealed that printing speed was the dominant parameter governing dissolution behavior, with high speeds accelerating release and low speeds prolonging release through porosity-modulated diffusion control. RSM quadratic models showed optimal fits for t_50% (R² = 0.9936) and Q_4h (R² = 0.9019), highlighting the predictability of release kinetics via process parameter tuning. This work demonstrates the adaptability of polymer composite AM for tailoring drug release profiles, balancing mechanical integrity, release kinetics, and manufacturing scalability to advance multifunctional 3D-printed drug delivery devices in pharmaceutics. Full article

To address the issues of hydrogen embrittlement, creep, and fatigue that commonly occur in the welds of hydrogen production reactor operating under hydrogen exposure, high temperature and high pressure, this study proposes adding Si and Mo as reinforcing elements to the welding materials to enhance weld performance. Given the varying performance requirements of different weld layers in the stacked weld, a gradient performance optimization method for the stacked weld of hydrogen production reactors based on the response surface methodology (RSM)–genetic algorithm (GA) is proposed. Using tensile strength, the hydrogen embrittlement sensitivity index, fatigue strain strength, creep rate and weld performance evaluation indices, a high-precision regression model for Si and Mo contents and weld performance indices was established through RSM and analysis of variance (ANOVA). A multi-objective optimization mathematical model for gradient improvement of the stacked weld was also established. This model was solved using a GA to obtain the optimal element content combination added to the welding wire and the optimal weld thickness for each weld layer. Finally, submerged arc welding experiments of the stacked weld were conducted according to the optimization results. The results show that the tensile strength of the base layer, filling layer and cover layer of the stacked weld increased by 5.60%, 6.16% and 4.53%, respectively. Hydrogen embrittlement resistance increased by 70.56%, 52.40% and 45.16%, respectively. The fatigue and creep resistance were also improved. The experimental results validate the feasibility and accuracy of the proposed optimization method. Full article

In recent years, recovering precious and base metals such as silver and copper from end-of-life products has become a fundamental factor in the sustainable development of many countries. This not only supports environmental goals but is also a profitable economic activity. Therefore, in this study, we investigate the recovery of silver and copper from an end-of-life photovoltaic panel powder using an alternative leaching system containing sulfuric acid and ferric sulfate instead of nitric acid-based leaching systems, which are susceptible to producing hazardous gases such as NO_x. To obtain this goal, a series of experiments were designed with the Central Composite Design (CCD) approach using Response Surface Methodology (RSM) to evaluate the effect of reagent concentrations on the leaching rate. The leaching results showed that high recovery rates of silver (>85%) and copper (>96%) were achieved at room temperature using a solution containing only 0.2 M sulfuric acid and 0.15 M ferric sulfate. Analysis of variance was applied to the leaching data for silver and copper recovery, resulting in two statistical models that predict the leaching efficiency based on reagent concentrations. Results indicate that the models are statistically significant due to their high R² (0.9988 and 0.9911 for Ag and Cu, respectively) and the low p-value of 0.0043 and 0.0003 for Ag and Cu, respectively. The models were optimized to maximize the dissolution of silver and copper using Design Expert software. Full article

The olive oil industry generates by-products like olive leaves and pomace, which are rich in bioactive compounds, especially polyphenols. This study applied a circular economy approach to valorize these residues using green ultrasound-assisted extraction (UAE) with GRAS solvents. Key parameters (solvent composition, ultrasound amplitude, and specific energy) were optimized via Response Surface Methodology (RSM) to enhance polyphenol recovery and yield. Ethanol concentration proved to be the most influential factor. Optimal conditions for olive pomace were 100% ethanol, 46 μm amplitude, and 25 J∙mL⁻¹ specific energy, while olive leaves required 72% ethanol with similar ultrasound settings. Under these conditions, extracts were prepared and analyzed using HPLC-ESI-QTOF-MS and DPPH assays. The optimized UAE process achieved yields of 15–20% in less than 5 min and under mild conditions. Optimal extracts showed high oleuropein content (6 mg/g in leaves, 5 mg/g in pomace), lower hydroxytyrosol levels, and minimal oxidized derivatives, suggesting reduced degradation compared to conventional methods. These findings demonstrate UAE’s effectiveness in recovering valuable phenolics from olive by-products, supporting sustainable and efficient resource use. Full article

Sweet potato is a valuable root due to its nutritional benefits, health-promoting properties, and technological applications. The peel, often discarded during food processing, can be employed in the food industry, supporting a circular economy. Purple sweet potato peel (PSPP) is rich in anthocyanins, which can be used as natural colourants and antioxidants. Optimising their extraction can enhance yield and reduce costs. The current work aimed to optimize anthocyanin and antioxidant recovery from PSPP using a Box-Behnken design and sonotrode ultrasound-assisted extraction (sonotrode-UAE). Three independent variables were analysed: extraction time (2–6 min), ethanol concentration (35–85%), and liquid-to-solid ratio (10–30 mL/g). The dependent variables included total monomeric anthocyanin content (TMAC), individual anthocyanins, and antioxidant activity. TMAC in 15 extracts ranged from 0.16 to 2.66 mg/g PSPP. Peonidin-3-caffeoyl-p-hydroxybenzoyl sophoroside-5-glucoside was the predominant anthocyanin. Among four antioxidant assays, Ferric-reducing antioxidant power (FRAP) showed the highest value. Ethanol concentration significantly influenced anthocyanin and antioxidant recovery (p < 0.05). The model demonstrated adequacy based on the coefficient of determination and variation. Optimal extraction conditions were 6 min with 60% ethanol at a 30 mL/g ratio. Predicted values were validated experimentally (coefficient of variation <10%). In conclusion, PSPP is a promising matrix for obtaining anthocyanin-rich extracts with antioxidant activity, offering potential applications in the food industry. Full article

Although corn germ meal is a rich source of dietary fiber, it contains a relatively low proportion of soluble dietary fiber (SDF) and is frequently contaminated with high levels of zearalenone (ZEN). Solid-state fermentation has the dual effects of modifying dietary fiber (DF) and degrading mycotoxins. This study optimized the solid-state fermentation process of corn germ meal using Bacillus subtilis K6 through response surface methodology (RSM) to enhance SDF yield while efficiently degrading ZEN. Results indicated that fermentation solid-to-liquid ratio and time had greater impacts on SDF yield and ZEN degradation rate than fermentation temperature. The optimal conditions were determined as temperature 36.5 °C, time 65 h, and solid-to-liquid ratio 1:0.82 (w/v). Under these conditions, the ZEN degradation rate reached 96.27 ± 0.53%, while the SDF yield increased from 9.47 ± 0.68% to 20.11 ± 1.87% (optimizing the SDF/DF ratio from 1:7 to 1:3). Scanning electron microscopy (SEM) and confocal laser scanning microscope (CLSM) revealed the structural transformation of dietary fiber from smooth to loose and porous forms. This structural modification resulted in a significant improvement in the physicochemical properties of dietary fiber, with water-holding capacity (WHC), oil-holding capacity (OHC), and water-swelling capacity (WSC) increasing by 34.8%, 16.4%, and 15.2%, respectively. Additionally, the protein and total phenolic contents increased by 23.0% and 82.61%, respectively. This research has achieved efficient detoxification and dietary fiber modification of corn germ meal, significantly enhancing the resource utilization rate of corn by-products and providing technical and theoretical support for industrial production applications. Full article

This study systematically investigated the oxidation of chitosan using the TEMPO/NaClO/NaBr catalytic system under varying experimental conditions, namely temperature, reaction time, and pH, in order to optimize the oxidation process. Response surface methodology (RSM) was employed to determine the optimal parameters for maximizing the efficiency of the reaction. The structural modifications to the chitosan following oxidation were confirmed using Fourier-transform infrared spectroscopy (FTIR), alongside additional analytical techniques, which validated the successful introduction of carbonyl and carboxyl functional groups. Solvent-cast films were prepared from both native and oxidized chitosan in order to evaluate their functional performance. The antibacterial activity of these films was assessed against Gram-negative (Salmonella) and Gram-positive (Streptococcus faecalis) bacterial strains. The oxidized chitosan films exhibited significantly enhanced antibacterial effects, particularly at shorter incubation periods. In addition, antioxidant activity was evaluated using DPPH radical scavenging and ferrous ion chelation assays, which both revealed a marked improvement in radical scavenging ability and metal ion binding capacity in oxidized chitosan. These findings confirm that TEMPO-mediated oxidation effectively enhances the physicochemical and bioactive properties of chitosan, highlighting its potential for biomedical and environmental applications. Full article

The exponential increase in electronic waste (e-waste) from end-of-life electrical and electronic equipment presents a growing environmental challenge. E-waste contains high concentrations of rare earth elements (REEs), which are classified as critical raw materials (CRMs). Their removal and recovery from contaminated systems not only mitigate pollution but also support resource sustainability within a circular economy framework. The present study proposed the use of hazelnut shells as a biosorbent to reduce water contamination and recover REEs. The sorption capabilities of this lignocellulosic material were assessed and optimized using the response surface methodology (RSM) combined with a Box–Behnken Design (three factors, three levels). Factors such as pH (4 to 8), salinity (0 to 30), and biosorbent dose (0.25 to 0.75 g/L) were evaluated in a complex mixture containing 9 REEs (Y, La, Ce, Pr, Nd, Eu, Gd, Tb and Dy; equimolar concentration of 1 µmol/L). Salinity was found to be the factor with greater significance for REEs sorption efficiency, followed by water pH and biosorbent dose. At a pH of 7, salinity of 0, biosorbent dose of 0.75 g/L, and a contact time of 48 h, optimal conditions were observed, achieving removals of 100% for Gd and Eu and between 81 and 99% for other REEs. Optimized conditions were also predicted to maximize the REEs concentration in the biosorbent, which allowed us to obtain values (total REEs content of 2.69 mg/g) higher than those in some ores. These results underscore the high potential of this agricultural waste with no relevant commercial value to improve water quality while providing an alternative source of elements of interest for reuse (circular economy). Full article

Cable force distribution in cable-stayed bridges critically impacts structural safety and efficiency, yet traditional optimization methods struggle with unconventional designs due to nonlinear mechanics and computational inefficiency. This study proposes a hybrid approach combining Response Surface Methodology (RSM) and Multi-Objective Particle Swarm Optimization (MOPSO) to overcome these challenges. RSM constructs surrogate models for strain energy and mid-span displacement, reducing reliance on finite element analysis, while MOPSO optimizes Pareto solution sets for rapid cable force adjustment. Validated through an engineering case, the method reduces the main girder’s max bending moment by 8.7%, mid-span displacement by 31.2%, and strain energy by 7.1%, improving stiffness and mitigating stress concentrations. The response surface model demonstrates prediction errors of 0.35% for strain energy and 5.1% for maximum vertical mid-span deflection. By synergizing explicit modeling with intelligent algorithms, this methodology effectively resolves the longstanding efficiency–accuracy trade-off in cable force optimization for cable-stayed bridges. It achieves over 80% reduction in computational costs while enhancing critical structural performance metrics. Engineers are thereby equipped with a rapid and reliable optimization framework for geometrically complex cable-stayed bridges, delivering significant improvements in structural safety and construction feasibility. Ultimately, this approach establishes both theoretical substantiation and practical engineering benchmarks for designing non-conventional cable-stayed bridge configurations. Full article

In this study, alkali-activated coal gangue-slag material (AACGS) was prepared using coal gangue and slag as precursors, and its feasibility as conductive mortar substrate material was preliminarily investigated. Firstly, this study employed Response Surface Methodology (RSM) to develop statistical models correlating the alkali equivalent, water-to-binder ratio, and slag content with the compressive strength, flexural strength, and resistivity of AACGS, aiming to identify the optimal mix proportions. Secondly, based on the optimal ratio identified above and using carbon fibers (CF) as the conductive phase, an alkali-activated conductive mortar (CF-AACGS) was prepared, and its compressive strength, flexural strength, and resistivity were tested. Lastly, XRD and SEM-EDS were conducted to characterize the mineral composition and microstructure of CF-AACGS. The results indicate that when the alkali equivalent, water-to-binder ratio, and slag content are 13.34%, 0.54, and 57.52%, respectively, the AACGS achieves compressive strength, flexural strength, and resistivity of 72.5 MPa, 7.0 MPa, and 62.41 Ω·m at 28 days. Under the action of the alkali activator, coal gangue and slag undergo hydration reactions, forming a denser N, C-(A)-S-H gel. This effectively improves the interface transition zone between the CF and AACGS, endowing the CF-AACGS with superior mechanical properties. Furthermore, the AACGS matrix enhances the conductive contact point density by optimizing CF dispersion, which significantly reduces the resistivity of the CF-AACGS. Full article

Two solvents, n-hexane and ethyl acetate, were employed to extract oil from Asphodelus tenuifolius Cav. seeds using the Soxhlet extraction technique. The process was optimized using Central Composite Design (CCD) and Response Surface Methodology (RSM). ANOVA and a second-order polynomial equation were applied to evaluate the effects of key operational factors, including extraction time (20–60 min) and solvent-to-solid ratio (0.2–0.6 g/mL), on oil yield. The physicochemical properties, fatty acid composition, and functional groups of the extracted oil were analyzed. While both solvents influenced oil yield and quality, the fatty acid composition remained consistent, with unsaturated fatty acids, particularly linoleic acid, identified as the main components. Under optimized conditions, the highest oil yields were 22% with n-hexane and 19.91% with ethyl acetate. FTIR spectroscopy confirmed the presence of ester groups, suggesting potential applications in biodiesel production. These findings offer valuable insights for producing oils rich in unsaturated fatty acids for food, cosmetic and renewable energy industries. These findings pave the way for further advancements in industrial applications by promoting the sustainable use of plant-derived oils. Full article