Search Results (6,804)

In the casting and rolling production process, surface longitudinal cracks are a typical casting defect. Tracing the causes of longitudinal cracks online and controlling the key parameters leading to their formation in a timely manner can enhance the stability of casting and rolling production. To this end, the influencing factors of longitudinal cracks were analyzed, a data integration storage platform was constructed, and a tracing model was established using empirical rule analysis, statistical analysis, and intelligent analysis methods. During the initial production phase of a casting machine, longitudinal cracks occurred frequently. The tracing results using the LightGBM-SHAP method showed that the relative influence of the narrow left wide inner heat flow ratio of the mold was significant, followed by the heat flow difference on the wide symmetrical face of the mold and the superheat of the molten steel, with weights of 0.135, 0.066, and 0.048, respectively. Based on the tracing results, we implemented online emergency measures. By controlling the cooling intensity of the mold, we effectively reduced the recurrence rate of longitudinal cracks. Root cause analysis revealed that the total hardness of the mold-cooling water exceeded the standard, reaching 24 mg/L, which caused scaling on the mold copper plates and uneven cooling, leading to the frequent occurrence of longitudinal cracks. After strictly controlling the water quality, the issue of longitudinal cracks was brought under control. The online application of the tracing method for the causes of longitudinal cracks has effectively improved efficiency in resolving longitudinal crack problems. Full article

Carbon fiber-reinforced polymer (CFRP) composites are widely used in aerospace due to their excellent strength-to-weight ratio and tailorable properties. However, these properties critically depend on the CFRP curing cycle. The commonly adopted manufacturer-recommended curing cycle (MRCC), designed to accommodate the most conservative conditions, involves prolonged curing times and high energy consumption. To overcome these limitations, this study proposes an efficient and adaptable method to determine the optimal curing cycle. The effects of varying heating rates on resin dynamic and isothermal–exothermic behavior were characterized via reaction kinetics analysis using differential scanning calorimetry (DSC) and rheological measurements. The activation energy of the reaction system was substituted into the modified Sun–Gang model, and the parameters were estimated using a particle swarm optimization algorithm. Based on the curing kinetic behavior of the resin, CFRP compression molding process orthogonal experiments were conducted. A weighted scoring system incorporating strength, energy consumption, and cycle time enabled multidimensional evaluation of optimized solutions. Applying this curing cycle optimization method to a commercial epoxy resin increased efficiency by 247.22% and reduced energy consumption by 35.7% while meeting general product performance requirements. These results confirm the method’s reliability and its significance for improving production efficiency. Full article

Background/Objectives: Maxillofacial silicone prostheses’ long-term color stability remains a challenge. This study aimed to evaluate and compare the color stability of conventional and digital maxillofacial silicone elastomers mixed with nano-sized antimicrobial additives (ZnO nanoparticles and chlorhexidine salt-CHX) at various concentrations over a 10-week period. Methods: A total of nine groups (n = 10) of maxillofacial silicone elastomers were prepared. These included a control group (no additives), conventionally pigmented silicone, digitally pigmented silicone (Spectromatch system), and silicone mixed with ZnO or CHX at 1%, 3%, and 5% by weight. Specimens were fabricated in steel molds and cured at 100 °C for 1 h. Color measurements were performed at baseline and after 1, 4, 6, and 10 weeks using a Minolta Chroma Meter (CIELAB system, ΔE₀₀ formula). Data were analyzed using two-way ANOVA and Tukey HSD post hoc tests (α = 0.05). Results: Color changes (ΔE₀₀) ranged from 0.74 to 2.83 across all groups. The conventional pigmented silicone group showed the highest color difference (ΔE₀₀ = 2.83), while the lowest was observed in the ZnO 1% group (ΔE₀₀ = 0.74). Digital silicone and all antimicrobial-modified groups exhibited acceptable color stability (ΔE₀₀ < 3.1). Time significantly affected color difference, with the largest change occurring during the first four weeks (p < 0.05), followed by stabilization. Regression analysis confirmed high color stability over time for all groups except the conventional pigmented group. Conclusions: This is one of the first studies to directly compare digital and conventional pigmentation methods combined with nano-antimicrobials in maxillofacial silicones. Maxillofacial silicone elastomers mixed with up to 5% ZnO or CHX maintained acceptable color stability over 10 weeks. Digital pigmentation is similar to conventional methods. The incorporation of nano-antimicrobials offers significant microbial resistance and improved color retention. Full article

Soft manipulators have garnered significant research attention in recent years due to their flexibility and adaptability. However, the inherent flexibility of these manipulators imposes limitations on their load-bearing capacity and stability. To address this, this study compares various variable stiffness technologies and proposes a novel design concept: leveraging the phase-change characteristics of low-melting-point alloys (LMPAs) with distinct melting points to fulfill the variable stiffness requirements of soft manipulators. The pneumatic structure of the manipulator is fabricated via 3D-printed molds and silicone casting. The manipulator integrates a pneumatic working chamber, variable stiffness chambers, heating devices, sensors, and a central channel, achieving multi-stage variable stiffness through controlled heating of the LMPAs. A steady-state temperature field distribution model is established based on the integral form of Fourier’s law, complemented by finite element analysis (FEA). Subsequently, the operational temperatures at which the variable stiffness mechanism activates, and the bending performance are experimentally validated. Finally, stiffness characterization and kinematic performance experiments are conducted to evaluate the manipulator’s variable stiffness capabilities and flexibility. This design enables the manipulator to switch among low, medium, and high stiffness levels, balancing flexibility and stability, and provides a new paradigm for the design of soft manipulators. Full article

This study investigates the sustainable production of NdFeB permanent magnets using powder extrusion molding (PEM) with in situ magnetic alignment, utilizing recycled powder from an end-of-life (Eol) wind turbine magnet obtained via hydrogen processing of magnetic scrap (HPMS). Finite Element Method (FEM) simulations were conducted to design and optimize alignment tool geometries and magnetic field parameters. A key challenge in the PEM process is achieving effective particle alignment while the continuous strand moves through the magnetic field during extrusion. To address this, extrusion experiments were performed using three different alignment tool geometries and varying magnetic field strengths to determine the optimal configuration for particle alignment. The experimental results demonstrate a high degree of alignment (B_r/J_s = 0.95), exceeding the values obtained with PEM without an external magnetic field (0.78). The study confirms that optimizing the alignment tool geometry and applying sufficiently strong magnetic fields during extrusion enable the production of anisotropic NdFeB permanent magnets without post-machining, providing a scalable route for permanent magnet recycling and manufacturing. Moreover, PEM with in situ magnetic particle alignment allows for the continuous fabrication of near-net-shape strands with customizable cross-sections, making it a scalable approach for permanent magnet recycling and industrial manufacturing. Full article

One of the most important features of Metschnikowia pulcherrima is its strong antimicrobial activity against phytopathogens, which makes it a suitable candidate for use in biocontrol during crop cultivation. However, the mechanisms of its antimicrobial activity are not currently well understood. In this study, we used metabolomic methods to investigate the possible mechanisms of antimicrobial activity by M. pulcherrima against phytopathogenic fungi. First, we tested the antimicrobial activity of five selected isolates against eleven phytopathogenic molds. Based on the results, selected yeast–pathogen co-cultures were cultivated on liquid and solid media. The supernatants from the liquid co-cultures were analyzed using the UHPLC-QToF-UHRMS and MS/MS methods. Co-culture growth on solid agar media was examined using the LARAPPI/CI MSI method. The yeast exhibited strong antagonism toward the mold phytopathogens. The LARAPPI/CI MSI method revealed the presence of various compounds with potential antifungal activity. The complex UHPLC-QToF-UHRMS analysis confirmed that the metabolic response of M. pulcherrima depends on specific yeast–pathogen interactions. Full article

Mixed-flow assembly lines are widely employed in industrial manufacturing to handle diverse production tasks. For mixed flow assembly lines that involve mold changes and greater processing difficulties, there are currently two approaches: batch production and production according to order sequence. The first approach struggles to meet the processing constraints of workpieces with higher production difficulty, while the second approach requires the development of suitable scheduling schemes to balance mold changes and continuous processing. Therefore, under the second approach, developing an excellent scheduling scheme is a challenging problem. This study addresses the mixed-flow assembly shop scheduling problem, considering continuous processing and mold-changing constraints, by developing a multi-objective optimization model to minimize additional production time and customer waiting time. As this NP-hard problem poses significant challenges in solution space exploration, the conventional NSGA-II algorithm suffers from limited local search capability. To address this, we propose an enhanced NSGA-II algorithm (RLVNS-NSGA-II) integrating deep reinforcement learning. Our approach combines multiple neighborhood search operators with deep reinforcement learning, which dynamically utilizes population diversity and objective function data to guide and strengthen local search. Simulation experiments confirm that the proposed algorithm surpasses existing methods in local search performance. Compared to VNS-NSGA-II and SVNS-NSGA-II, the RLVNS-NSGA-II algorithm achieved hypervolume improvements ranging from 19.72% to 42.88% and 12.63% to 31.19%, respectively. 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

This study was undertaken to identify foodborne bacteria and fungi from different parts of eggs depending on their storage duration, organoleptic properties, total viable count, and antibiotic resistance profile. Thirty-two samples were randomly collected from commercial layer farms in Mymensingh. Following the protocol of sample preparation, outer-surface and inner-content samples were streaked onto various selective media. Isolation and identification were carried out by observing Gram staining and biochemical properties. Molecular detection was confirmed through a PCR assay using specific primers for Salmonella spp., E. coli, Staphylococcus spp., and fungus (Simplicillium spp. and Saccharomyces spp.). To determine the antibiotic resistance profile, the disk diffusion method was followed against nine antibiotic disks. The isolation rate of E. coli, Salmonella spp., and Staphylococcus spp. was 53.13%, 40.63%, and 40.63%, respectively, in the outer eggshell and 15.63%, 25%, and 15.63%, respectively, in the inner content of the eggs. Regarding the fungus content (yeast and mold), 100% was obtained in the outer eggshell, whereas there was an absence of fungus in the inner content. It was observed that all the isolates of E. coli, Salmonella spp., and Staphylococcus spp. were highly sensitive to either Ciprofloxacin or Levofloxacin and extremely resistant to Amoxicillin or Azithromycin drug disks or both. The data also shows that storage duration had a proportional relationship with TVC and an inversely proportional relationship with organoleptic properties. This study indicates that eggs harbor multidrug-resistant foodborne bacteria, which might constitute a public health hazard if these antibiotic-resistant bacteria are transferred to humans. Full article

To investigate the effect of Botrytis cinerea infection severity on the flavor characteristics of Petit Manseng noble rot wine, this study analyzed wines produced from Petit Manseng grapes grown in the eastern foothills of Helan Mountain, Ningxia, China. The grapes were categorized into three groups based on infection status: uninfected, mildly infected, and severely infected with Botrytis cinerea. Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and an electronic nose were employed to detect and analyze the aroma components of wines under the three infection conditions. Additionally, trained sensory panelists conducted sensory evaluations of the wine aromas. The results revealed that wines made from severely infected grapes exhibited the richest and most complex aroma profiles. A total of 70 volatile compounds were identified, comprising 32 esters, 17 alcohols, 5 acids, 8 aldehydes and ketones, 4 terpenes, and 4 other compounds. Among these, esters and alcohols accounted for the highest contents. Key aroma-active compounds included isoamyl acetate, ethyl decanoate, phenethyl acetate, ethyl laurate, hexanoic acid, linalool, decanoic acid, citronellol, ethyl hexanoate, and methyl octanoate. Sensory evaluation indicated that the “floral aroma”, “pineapple/banana aroma”, “honey aroma”, and “overall aroma intensity” were most pronounced in the severely infected group. These findings provide theoretical support for the harvesting of severely Botrytis cinerea-infected Petit Manseng grapes and the production of high-quality noble rot wine in this region. Full article

True slime molds (Eumycetozoa) remain under-explored globally, particularly in water-logged forest habitats. Despite evidence suggesting a high biodiversity potential in the Knyszyn Forest of north-eastern Poland, no systematic effort had previously been undertaken there. In the present survey, plant substrates from eight swampy sub-compartments were incubated for over four months, resulting in the detection of fifteen slime mold species. Four of these taxa are newly reported for northern and north-eastern Poland, while several have been recorded only a handful of times in the global literature. These findings underscore how damp, nutrient-rich conditions foster Eumycetozoa and demonstrate the effectiveness of moist-chamber culturing in revealing rare or overlooked taxa. Current evidence shows that, although slime molds may occasionally colonize living plant or fungal tissues, their influence on crop productivity and tree vitality is negligible; they are therefore better regarded as biodiversity indicators than as pathogens or pests. By establishing a replicable framework for studying water-logged environments worldwide, this work highlights the ecological importance of swamp forests in sustaining microbial and slime mold diversity. Full article

Reducing post-harvest losses of cereal crops is a key challenge for ensuring global food security amid the limited arable land and growing population. This study investigates the effectiveness of electron beam irradiation (5 MeV, ILU-10 accelerator) as a physical decontamination method for various cereal crops cultivated in Kazakhstan. Samples were irradiated at doses ranging from 1 to 5 kGy, and microbiological indicators—including Quantity of Mesophilic Aerobic and Facultative Anaerobic Microorganisms (QMAFAnM), yeasts, and molds—were quantified according to national standards. Experimental results demonstrated an exponential decline in microbial contamination, with a >99% reduction achieved at doses of 4–5 kGy. The modeled inactivation kinetics showed strong agreement with the experimental data: R² = 0.995 for QMAFAnM and R² = 0.948 for mold, confirming the reliability of the exponential decay models. Additionally, key quality parameters—including protein content, moisture, and gluten—were evaluated post-irradiation. The results showed that protein levels remained largely stable across all doses, while slight but statistically insignificant fluctuations were observed in moisture and gluten contents. Principal component analysis and scatterplot matrix visualization confirmed clustering patterns related to radiation dose and crop type. The findings substantiate the feasibility of electron beam treatment as a scalable and safe technology for improving the microbiological quality and storage stability of cereal crops. Full article

This study evaluates the efficacy of commercial clean-label additives, specifically fermentates, in inhibiting mold growth in vitro and extending the shelf life of preservative-free bread. The mold growth on selected bread was modeled using the time-to-growth approach. The pH, a_w, and moisture content of fresh bread were determined. In addition, selected fermentates were characterized physicochemically. Fermentates, defined as liquid or powdered preparations containing microorganisms, their metabolites, and culture supernatants, were tested at varying concentrations (1% to 12%) to assess their antimicrobial performance and impact on bread quality parameters, including moisture content, water activity, and pH. The results showed significant differences in fermentate efficacy, with Product A as the best mold growth inhibitor in vitro and a clear dose-dependent response. For Penicillium corylophilum, inhibition increased from 51.90% at 1% to 62.60% at 4%, while P. chrysogenum had an inhibition ranging from 32.26% to 34.49%. Product F exhibited moderate activity on both molds at 4%, inhibiting between 28.48% and 46.27%. The two molds exhibited differing sensitivities to the fermentates, with P. corylophilum consistently more susceptible to inhibition. Product A displayed a low pH (2.61) and high levels of lactic acid (1053.6 mmol/L) and acetic acid (1061.3 mmol/L). Product F presented a similar pH but lower levels of lactic and acetic acid. A time-to-growth model, validated by significant coefficients (p < 0.05) and high predictive accuracy (R² > 0.95), was employed to predict the appearance of mold on bread loaves. The model revealed that higher concentrations of fermentates A and F delayed mold growth, with fermentate A demonstrating superior efficacy. At 2% concentration, fermentate A delayed mold growth for 8 days, compared to 6 days for fermentate F. At 8% concentration, fermentate A prevented mold growth for over 25 days, significantly outperforming the control (4 days). Additionally, fermentates influenced bread quality parameters, with fermentate A improving crust moisture retention and reducing water activity at higher concentrations. These findings highlight the potential of fermentates as sustainable, consumer-friendly alternatives to synthetic preservatives, offering a viable solution to the challenge of bread spoilage while maintaining product quality. Full article

The Slime Mould Algorithm (SMA) is a widely used swarm intelligence algorithm. Encouraged by the theory of no free lunch and the inherent shortcomings of the SMA, this work proposes a new variant of the SMA, called the BWSMA, in which three improvement mechanisms are integrated. The adaptive greedy mechanism is used to accelerate the convergence of the algorithm and avoid ineffective updates. The best–worst management strategy improves the quality of the population and increases its search capability. The stagnant replacement mechanism prevents the algorithm from falling into a local optimum by replacing stalled individuals. In order to verify the effectiveness of the proposed method, this paper conducts a full range of experiments on the CEC2018 test suite and the CEC2022 test suite and compares BWSMA with three derived algorithms, eight SMA variants, and eight other improved algorithms. The experimental results are analyzed using the Wilcoxon rank-sum test, the Friedman test, and the Nemenyi test. The results indicate that the BWSMA significantly outperforms these compared algorithms. In the comparison with the SMA variants, the BWSMA obtained average rankings of 1.414, 1.138, 1.069, and 1.414. In comparison with other improved algorithms, the BWSMA obtained average rankings of 2.583 and 1.833. Finally, the applicability of the BWSMA is further validated through two structural optimization problems. In conclusion, the proposed BWSMA is a promising algorithm with excellent search accuracy and robustness. Full article

Thermal wick-debinding, commonly used in low-pressure injection molding, remains challenging due to complex interactions between binder transport, capillary forces, and thermal effects. This study presents a numerical simulation of binder removal kinetics by coupling Darcy’s law with the Phase Transport in Porous Media interface in COMSOL Multiphysics. The model was validated and subsequently used to study the influence of key debinding parameters. Contrary to the Level Set method, which predicts isolated binder clusters, the Multiphase Flow in Porous Media method proposed in this work more accurately reflects the physical behavior of the process, capturing a continuous binder extraction throughout the green part and a uniform binder distribution within the wicking medium. The model successfully predicted the experimentally observed decrease in binder saturation with increasing debinding temperature or time, with deviation limited 3–10 vol. % (attributed to a mandatory brushing operation, which may underestimate the residual binder mass). The model was then used to optimize the debinding process: for a temperature of 100 °C and an inter-part gap distance of 5 mm, the debinding time was minimized to 7 h. These findings highlight the model’s practical utility for process design, offering a valuable tool for determining optimal debinding parameters and improving productivity. Full article