Search Results (633)

Eggshell thickness is a critical indicator for evaluating egg breakage resistance and hatchability, yet traditional measurement methods remain destructive and inefficient. To address this, this study proposes a robust prediction approach by integrating Gradient Boosting Decision Tree (GBDT) feature optimization with an improved CatBoost algorithm. First, a joint strategy of Standard Normal Variate (SNV) and Multiplicative Scatter Correction (MSC) was employed to eliminate spectral scattering noise and enhance organic matrix fingerprint information. Subsequently, GBDT was introduced for nonlinear feature evaluation to adaptively screen the top 50 wavelengths, effectively mitigating the “curse of dimensionality” and multicollinearity in full-spectrum data. A CatBoost regression model was then constructed using an Ordered Boosting mechanism, supported by a dual anti-overfitting strategy that merged 10-fold nested cross-validation with Bootstrap resampling. Experimental results demonstrate that this method significantly outperforms traditional algorithms in both prediction accuracy and generalization. The coefficients of determination (R²) for the calibration and prediction sets reached 0.930 and 0.918, respectively, with a root mean square error of prediction (RMSEP) of 0.008 mm. Residual analysis confirms that prediction errors follow a zero-mean Gaussian distribution, indicating that systematic bias was effectively eliminated. This research provides a reliable theoretical foundation and technical support for the intelligent grading of poultry egg quality. Full article

Industrial organisations increasingly rely on machine learning (ML) to improve quality, maintenance, and planning in Industry 4.0/5.0 ecosystems. However, turning experimental models into reliable services on the production floor remains complex due to the heterogeneity of operational technologies (OTs) and information technologies (ITs), including implementation constraints, latency in edge-fog-cloud scenarios, governance requirements, and continuous performance degradation caused by data drift. Although Machine Learning Operations (MLOps) provides lifecycle practices for deployment, monitoring, and retraining, the evidence is fragmented across tool-centric descriptions, case-specific pipelines, and conceptual architectures, offering limited guidance on which industrial constraints should inform architectural decisions and how to evaluate solutions. This work addresses that gap through a PRISMA-guided systematic review of 49 studies on industrial MLOps (with the search and screening primarily targeting Industry 4.0/IIoT operationalisation contexts, as reflected in the search strategy and corpus) and an evidence-based synthesis of principles, challenges, lifecycle practices, and enabling technologies. From this synthesis, industrial requirements are derived that encompass OT/IT integration, edge-fog-cloud orchestration, security and traceability, and observability-based lifecycle control. On this basis, a reference architecture is proposed that maps these requirements to functional layers, data and control flows, and verifiable responsibilities. To support reproducibility and practical inspectability, the article also presents an open-source architectural instantiation aligned with the proposed decomposition. Finally, the evaluation is illustrated through a predictive maintenance use case (tool breakage) in a single CNC machining cell, where the objective is to demonstrate end-to-end feasibility under realistic operational constraints rather than cross-scenario superiority or broad industrial generalisability. Full article

Eddy-current inspection of anisotropic composites, such as aeronautical CFRP, demands models that ensure mathematical rigor, tensorial consistency, and clear energetic interpretation. This work presents a novel unified variational framework with a multiplicative tensor perturbation for the time-harmonic eddy-current problem in anisotropic media with defective regions. The formulation is posed in the natural spaces $H(\mathrm{curl};\Omega )\times H^1\left({\Omega }_c\right)$, and the well-posedness is established via the Lax–Milgram theorem under physically consistent assumptions on permeability and conductivity. The sesquilinear form admits a Hermitian decomposition that separates dissipative and reactive contributions, revealing the energetic structure of the weak formulation. Defects are modeled through multiplicative modifications of the baseline anisotropic conductivity tensor. This congruence-based approach preserves symmetry and positive definiteness, ensuring non-negative Joule losses and structural stability, allowing a modular representation of subsurface delamination, fiber breakage, conductive inclusions, and distributed porosity within a single tensorial framework. A central result of the present formulation is the reconstruction of the complex power functional from the evaluation of the weak form at the solution, showing that the active dissipated power and the magnetic reactive power arise directly from the same integral terms. Through the complex Poynting theorem, the quadratic form is linked to the internal complex power, establishing a direct connection between the variational formulation and measurable quantities such as probe impedance variations. Simulations of realistic layered CFRP configurations, including single- and multi-defect scenarios, confirm that, compared with additive perturbations, the multiplicative model provides enhanced energetic contrast, particularly in strongly anisotropic and interacting defect conditions. Agreement with experimental measurements, supported by a quantitative comparison of dissipated power variations obtained from controlled EC experiments, corroborates the physical relevance and robustness of the proposed complex power functional. Full article

Flotation circuits typically incorporate grinding stages, yet mathematical models for these processes often operate on different principles, leading to misalignment in circuit design. Building on a previously established grinding model for flotation performance, this research introduces significant advances to develop a more comprehensive and industrially relevant framework. The primary innovation is the integration of mechanical entrainment and gangue recovery into the kinetic model, distinguishing between species captured by true flotation and those carried to the surface despite being non-hydrophobic. We developed a robust set of grinding-mill equations based on first-order kinetics to describe the mass-fraction transformation of both true-flotation and entrainment species. To ensure practical applicability, a systematic experimental and modeling methodology for parameter adjustment is introduced, providing a clear sequence for identifying breakage rate constants and flotation kinetic parameters. The proposed strategy was validated using two distinct case studies: an expanded analysis of a copper sulfide ore (ore A) and a new case involving significant gangue entrainment (ore B). The results demonstrate that the model accurately predicts species kinetics, providing a high-fidelity, cost-effective tool to optimize mineral recovery and prevent economic losses from overgrinding in industrial processing plants. Full article

Hair loss affects over half of adults by age 70 and represents a major determinant of overall hair health, imposing significant psychosocial burden across genders. Nutritional factors play a critical role in follicle biology, yet targeted strategies remain underexplored. This comprehensive review examines five key hair-constituent macromolecules—type I collagen, elastin, keratin, ceramides, and melanin—and their physiological and clinical impacts on hair structure, density, shining, and growth. We conducted a structured literature search in PubMed and Google Scholar through January 2025, selecting in vitro studies, animal experiments, and human clinical trials that evaluated each macromolecule’s effects on follicular function and hair fiber integrity. Type I collagen enhances dermal papilla cell proliferation, upregulates Wnt/β-catenin and growth factors, and improves hair thickness and breakage resistance in randomized controlled trials. Keratin hydrolysates replenish cortical protein, reinforce disulfide cross-links, and reduce telogen shedding, with clinical studies demonstrating 30–50% decreases in hair loss and gains in tensile strength. Oral ceramide formulations restore the cuticular lipid barrier, shift follicles toward anagen, and increase hair density in double-blind trials. Although direct clinical data on melanin supplementation are lacking, ex vivo and animal models confirm its role as a UV-protective pigment, preserving keratin integrity and color fastness. Together, these macromolecules constitute a coherent framework for hair health, and clinical studies increasingly provide evidence that their combined or parallel application can meaningfully enhance hair density, strength, shine, and resilience. Full article

Real-time monitoring of wire bow is critical for ensuring wafer quality and preventing wire breakage in diamond multi-wire sawing (MWS). However, the deployment physical sensors in industrial MWS environments is hindered by severe sludge contamination, limited installation space, and high maintenance costs. To address these challenges, this paper proposes a novel data-driven soft sensor framework utilizing machine learning methods to predict wire bow based on readily accessible process data. A feature engineering pipeline, combining variance thresholding and correlation analysis, is established to identify key process variables. Subsequently, six representative ML algorithms are systematically evaluated, with eXtreme Gradient Boosting (XGBoost) optimized via two-stage hyperparameter optimization emerging as the superior model. Experimental results from an industrial MWS machine demonstrate that the proposed model achieves a coefficient of determination ($R^2$) of 0.992 and a mean absolute error (MAE) of 0.116 mm. Furthermore, the prediction is also extended to spatially distributed positions (head, middle, and tail) of the wire web. Finally, SHAP (SHapley Additive exPlanations) is utilized to elucidate the mechanical dependencies. This work provides a reliable and low-cost solution for wire bow monitoring during the MWS process. Full article

To optimize the structural parameters of a peanut digging shovel and enhance its operational performance, the forces exerted on the digging shovel were examined through a graphical mechanics approach. This analysis identified the primary structural and operational parameters of the shovel’s design. A numerical simulation model for the working resistance of the shovel was established adopting EDEM (2018) discrete element analysis software and subsequently validated through comparative analysis with field experiment results. Employing the Box–Behnken response surface method, quadratic regression models were constructed with digging resistance and soil non-breakage ratio as the response variables, while forward speed, soil entry angle, and blade tilt angle were taken as the influencing factors. Optimization analysis of these parameters was conducted. The optimization results indicate that with a forward speed of 0.8 m/s, a soil entry angle of 20°, and a blade tilt angle of 40°, the working resistance of the shovel is 1667 N, and the soil non-breakage ratio is 20.56%. The error between the field test results and the predictions from the optimized model was less than 2%, illustrating the feasibility of the model and the optimization outcomes. This study offers a technical reference for future simulation-based optimization of peanut digging shovels. Full article

This study proposed a standardized oilseed rape seedling-carrying potting molding method to improve the adaptability of mechanical transplanting of potting seedlings. This method aims to address the failure in seedling pick-up and transport during the mechanized transplanting of rapeseed pot seedlings, which is caused by matrix breakage and seedling damage. This study selected cylindrical oilseed rape seedling-carrying potting as the research object and investigated the relationship between the physical characteristics of seedling-carrying potting and the proportion of the composition of the matrix soil as well as the characteristics of seedling growth after planting. The optimal parameter combination of the matrix soil was obtained using Design-Expert 8.0.6 software: dry matter ratio of 4:1, compression ratio of 0.36, and moisture content of 45%. A single-factor test was conducted using a seedling-carrying potting test bed. According to the single-factor test results, the dry matter ratios (commercial substrate: clay loam mass ratios of 2:1, 3:1, and 4:1), matrix soil compression ratios (0.35, 0.40, and 0.45), and matrix soil moisture content (35%, 40%, and 45%) were selected as the factors of influence, while the drop loss rate, shear resistance, and scattering rate were used as the indicators of evaluation. The drop loss rate of seedling-carrying potting under this parameter combination was 1.5%, the shear resistance was 7.1 N, and the scattering rate was 34.9%. Validation tests were conducted on a seedling-carrying potting test bed, and the relative errors between the actual and simulated values of the drop loss rate, shear resistance, and scattering rate were 7.1%, 7.0%, and 8.4%, respectively, verifying the accuracy of the model and the optimized parameters. Comparison tests of the growth characteristics of the optimized seedling-carrying potting, hole-tray seedling, and bare seedling in field transplanting were conducted. The results displayed that root length, root diameter, root dry matter, chlorophyll content, and seedling vigor index consistently followed the same descending order: seedling-carrying potting > hole-tray seedlings > bare seedlings. Compared to hole-tray seedlings, the corresponding growth characteristics of seedling-carrying potting were 11.7%, 10%, 21.7%, 2.8%, and 27.8% higher, respectively. Compared to bare seedlings, they were 17.1%, 12.5%, 32.2%, 10.8%, and 32.7% higher, respectively. The seedling length, seedling width, plant taper angle, and dry matter mass of stem and leaves were, in descending order, greater in hole-tray seedlings, followed by seedling-carrying potting, and then bare seedlings. In comparison, the corresponding growth characteristics of seedling-carrying potting were 8.9%, 9.8%, 2.3%, and 30.6% higher than those of bare seedlings, respectively. Full article

It is of great significance to clarify the evolution law and control mechanism of fracture conductivity in different production stages for the efficient development of coalbed methane. However, research on fracture conductivity in coal–rock remains limited, and the existing models are inadequate for predicting fracture conductivity with a consideration of staged proppant crushing. To address this gap, long-term conductivity tests were conducted on deep coal–rock under varying closure pressures and proppant gradation ratios. Within a coupled computational fluid dynamics and discrete element method (CFD-DEM) framework, a particle substitution scheme was integrated with the energy-based breakage model (Tavares breakage model) to develop a fracture conductivity predictor that incorporates proppant crushing and captures the time-dependent kinetics of proppant breakage during fracture conductivity evaluation. The model’s predictions align well with the experimental data, with an average error of less than 5%. The results indicate that fracture conductivity evolution can be delineated into three stages according to particle-breakage characteristics, (i) proppant pack compaction, (ii) the primary crushing of coarse proppant grains, and (iii) the secondary crushing of proppant fines, and the contributions of these three stages to the total conductivity loss are approximately 60%, 30%, and 10%, respectively. At a low closure pressure, fracture conductivity varies markedly among proppant packs with different particle sizes; once the closure pressure exceeds 40 MPa, the proppant pack enters the fines-breakage stage, and the conductivity differences among various particle size blends become marginal. Furthermore, a semi-empirical prediction model incorporating a composite crushing factor (CCF) was developed based on the Kozeny–Carman relationship, enabling a rapid evaluation of fracture conductivity in deep coal–rock fractures. Overall, these results provide a practical basis for fracture conductivity prediction and hydraulic fracturing parameter optimization in coal–rock reservoirs. Full article

To address the problems of high labor intensity, high production cost, low efficiency, and unevenness in the manual seed dressing process of cut potatoes, as well as the poor quality and easy damage caused by the poor adaptability of existing seed dressing equipment, this study designs a drum-type seed dressing device for cut potatoes based on design principles of seed treatment machinery. A kinematic model of the seed dressing process was established, and the process was simulated using EDEM 2024 discrete element simulation software combined with ray tracing. Two indicators commonly used in the pharmaceutical industry were introduced to evaluate seed dressing uniformity: the inter-tablet variation coefficient (CoV_inter) and intra-tablet variation coefficient (CoV_intra). Through single-factor experiments and three-factor, five-level orthogonal rotational combination experiments, the influence of drum speed, spiral guide plate pitch, and feed rate on the seed dressing effect were explored, and the parameters were optimized. The results show that the optimal parameter combination is a drum speed of 32.84 r·min⁻¹, a spiral guide plate pitch of 682.64 mm, and a feed rate of 10.44 t·h⁻¹, at which CoV_inter was 6.33% and CoV_intra was 6.35%. Bench tests verified that the seed dressing pass rate reached 94.1% and the breakage rate was only 0.32% under this parameter combination, meeting the requirements for seed potato treatment in mechanized potato planting. These findings can facilitate the progress of potato-seed engineering and offer theoretical and technical support for the development of mechanized potato seed dressing equipment. Full article

Background/Objectives: DNA polymerase ε (Pol ε), encoded by POLE1, plays a pivotal role in high-fidelity DNA replication and in coordinating DNA repair. While pathogenic exonuclease-domain variants are well established in cancer, biallelic POLE1 variants remain largely unexplored in non-malignant human cells. Methods: Here, we analyzed primary fibroblasts derived from a skin biopsy of a compound-heterozygous patient carrying two POLE1 variants. Western blot analysis confirmed detectable Pol ε protein levels, indicating preserved protein expression despite the underlying variants. Results: Nevertheless, functional alterations were observed across multiple independent assays. Compared with healthy control fibroblasts, this patient-derived Pol ε fibroblast line exhibited reduced clonogenic survival following ionizing radiation. Surviving fractions were consistently lower across radiation doses from 2 to 4 Gy, with an approximately twofold reduction at 2 Gy and progressively greater differences at higher doses. The isoeffect dose corresponding to 10% survival was reduced relative to pooled control fibroblasts. In addition, chromosomal breakage was increased, supporting altered processing of radiation-induced DNA damage in this cellular model. Live-cell imaging and senescence assays revealed delayed proliferation and an increased proportion of senescent or senescence-like cells under baseline and genotoxic stress conditions, including enhanced senescence-associated β-galactosidase activity. Flow-cytometric analysis demonstrated S phase accumulation and G2/M arrest, consistent with replication stress and cell-cycle perturbation. Immunofluorescence staining revealed increased γH2AX foci, consistent with persistent DNA double strand breaks. RAD51 foci formation was not reduced; instead, increased RAD51 recruitment was observed under combined cisplatin and irradiation treatment, arguing against a primary defect in RAD51-mediated homologous recombination. POLE1-variant fibroblasts also showed impaired proliferative recovery, reduced wound closure, increased γH2AX accumulation following cisplatin exposure, suggesting heightened susceptibility to DNA crosslinking stress. Conclusions: Collectively, these findings provide the first functional characterization of a patient-derived POLE1-variant fibroblast cell line and indicate that altered Pol ε function may influence cellular responses to genotoxic stress. While based on primary fibroblasts from a single compound-heterozygous patient, validation in additional patient-derived or isogenic models will be required to determine the broader relevance of these findings. Full article

This study presents a case-specific joining method for modular, large-scale components manufactured using Selective Laser Sintering (SLS). A T-slot joint reinforced with a pultruded carbon fiber rod was developed to enable the segmental assembly of polymer fan blades that exceed the build volume of common SLS printers. Through an iterative design process, five joint variations were investigated, focusing on the optimization of slot geometry (fillet radii and wall thickness) and the integration of carbon fiber reinforcements to create a high-strength hybrid connection. The experimental findings were validated using a non-linear finite element analysis (FEA) utilizing an iteratively calibrated Young’s modulus of 710 MPa, which accounts for the 50/50 virgin-to-reused PA2200 powder ratio employed in the study. The numerical model identified that the primary sites for crack initiation were the fillet radii of the female slot, where localized equivalent plastic strains reached critical levels of up to 84% in tension and 78% in bending. The final design achieved an average tensile strength of 27.6 MPa, exceeding the design threshold of 21.9 MPa with a safety factor of 2.5. While unreinforced joints showed a 73.4% reduction in bending strength compared to solid specimens, the addition of an 8 mm carbon rod increased performance by 238.7%, restoring over 90% of the monolithic material’s strength. Numerical results confirmed that the reinforcement assumed the primary load-bearing role, effectively mitigating stresses in the polymer matrix below the ultimate tensile strength. Failure analysis clarified that the observed audible failure originated from internal fiber breakage within the rod at stresses between 900–1050 MPa. This work demonstrates that a segmental, reinforcement-based joining method can effectively overcome size constraints in polymer additive manufacturing, providing a robust and repeatable solution for rotating components subject to complex loading conditions. Full article

Grain breakage occurs in sand specimens subjected to high stress levels; however, the magnitude and characteristics of the resulting deformation remain insufficiently quantified. This study investigates particle-scale fracture behavior in a standardized quartz sand subjected to controlled mechanical loading. Rapid, unconsolidated–undrained (UU) direct shear box tests were performed under normal stresses of 700, 800, and 900 kPa to induce grain breakage. The mechanical loading procedure was applied as a controlled stress induction mechanism to promote particle fragmentation rather than to determine conventional geotechnical parameters. A uniformly prepared quartz sand containing no additional mineral phases was used to ensure material consistency. Post-test specimens were examined through systematic visual and image-based analysis. The sample obtained from the 900 kPa test, where breakage was most pronounced, was analyzed in detail to characterize quartz fracture behavior under compressive and shear stress conditions using advanced image processing techniques. A deep learning-based mineral segmentation framework was developed using a ResNet50 architecture with transfer learning. A custom dataset consisting of high-resolution mineral images and corresponding pixel-level segmentation masks was constructed. The proposed model achieved 86.21% overall accuracy, a Dice coefficient of 91.35%, and an Intersection-over-Union (IoU) score of 84.07%. Validation results demonstrated strong generalization capability, with validation accuracy, Dice score, and IoU of 87.47%, 90.07%, and 81.96%, respectively. The high-precision segmentation performance enabled a comprehensive fracture analysis of 3333 quartz mineral images obtained from specimens exposed to systematic stress conditions. Full article

Parboiling improves rice-milling performance and consumer acceptance; however, drying parboiled rice can be energy intensive and highly sensitive to drying conditions, making it costly for processors. High head rice yield (HRY) and whiteness index (WI) are essential for commercial value because they reduce breakage and improve visual quality. In the United States, parboiled rice is typically dried in a two-stage process using rotary drum and crossflow dryers, but the high temperature condition of rotary drums can increase energy demand and compromise rice quality. This study evaluated the drying kinetics, effective moisture diffusivity (D_eff), energy consumption, and quality for three common cultivars (CLL 18, RT 7521, and Titan) using four methods: natural air drying (NAD), two-pass hot air oven drying (OO), two-pass fluidized bed drying (FBD), and a hybrid of oven and fluidized bed method (OFBD). Moisture content (MC) was monitored during drying until 12.5% (w.b.) to understand the drying kinetics. FBD achieved the fastest drying, reducing Titan MC from 38.24% to 13.79% (w.b.) in 60 min (two passes). It also produced highest D_eff across cultivars and consumed less energy (1.6599 kWh) as compared to OFBD (1.6733 kWh) and OO (1.68 kWh). Among nine thin-layer models explored, the logarithmic model provided the best fit, and Midilli–Küçük and Verma et al. models performed better in specific cases. NAD produced a higher quality of HRY (Titan: 65.33 ± 2.07%) and WI (RT 7521: 63.99 ± 0.25) than FBD but required 7–10 days to reach the target moisture content, limiting industrial applicability. Results from this study show that drying method and rice cultivars significantly influenced parboiled rice quality, and FBD offered efficient drying without compromising parboiled rice quality. Full article

To address the lack of contact and breakage parameters in the discrete element method (DEM) simulation of potato seed cutting and sorting processes, this study took the ‘Atlantic’ potato seed as the research object and constructed a crushable potato model using EDEM. Through physical experiments, the mean average diameter, moisture content, density, Poisson’s ratio, and elastic modulus were measured. The coefficients of collision restitution, static friction, and rolling friction between the potato seed and the Q235 steel plate were determined as 0.576, 0.559, and 0.073, respectively. Using the actual repose angle of 22.89° as the response target, and combining the steepest ascent test with the Box–Behnken design, the non-cohesive contact parameters between potato seed particles were calibrated. The resulting coefficients of collision restitution, static friction, and rolling friction between particles were determined as 0.404, 0.412, and 0.0156, respectively. Finally, based on physical shear tests (maximum shear force 23.56 N), significant influencing factors were identified through Plackett–Burman screening as the bonding radius ratio r and the normal stiffness per unit area Kn. Using the steepest ascent test and the Box–Behnken response surface method, the key bonding parameters of the Bonding V2 model were calibrated as follows: r = 1.098, K_n = 8.597 × 10⁷ N·mm⁻³, tangential stiffness per unit area K_t = 3.250 × 10⁶ N·mm⁻³, critical compressive stress σ_n = 5.500 × 10⁵ Pa, and shear strength τ_t = 3.000 × 10⁴ Pa. The relative error between the simulated and actual maximum shear forces was 0.89%, which is small. The calibrated flexible model accurately represents the physical characteristics of potato seeds and provides a reliable reference for the design of mechanized potato seed cutting and sorting equipment. Full article