Search Results (746)

Popcorn maize (Zea mays everta) exhibits complex morphologies that challenge structural analysis. This study assessed the fidelity of the three-dimensional (3D) reconstruction and printing of four popcorn morphologies, unilateral, bilateral, multilateral, and mushroom, by integrating structured-light 3D scanning and (DIA), which can support the construction of food replicas. Morphometric parameters (projected area, perimeter, Feret diameter, circularity, and roundness) and fractal descriptors (fractal dimension, lacunarity, and entropy) were quantified as the relative ratios of printed/real parameters (P/R) to compare real flakes with their 3D-printed counterparts. Results revealed the lowest mean errors for Feret diameter (6%) and projected area (10%), while deviations in circularity and roundness were more pronounced in mushroom flakes. With respect to the actual mean values of the morphological parameters, real flakes showed slightly larger perimeter values (86 mm for real and 82 mm for printed objects) and a higher fractal dimension (1.36 for real and 1.33 for printed), indicating greater texture irregularity, whereas the projected area remained highly comparable (225 mm² in real/229 mm² in printed). These parameters reinforced that the overall morphological fidelity remained high (P/R = 0.9–1.0), despite localized deviations in circularity and fractal descriptors. Less complex morphologies (unilateral and bilateral) demonstrated higher structural fidelity (P/R = 0.95), whereas multilateral and mushroom types showed greater variability due to surface irregularity. Fractal dimension and lacunarity effectively described textural complexity, highlighting the role of flake geometry and moisture in determining expansion patterns and printing accuracy. Principal Component Analysis confirmed that circularity and fractal indicators are critical descriptors for distinguishing morphological fidelity. Overall, the findings demonstrated that 3D scanning and printing provided reliable physical replicas of irregular food structures as popcorn flakes supporting their application in food engineering. Full article

The drying of nanofluid films on a surface can form various patterns and plays an important role in painting, surface patterning, and nano-fabrication processes. In this paper, a two-dimensional Kinetic Monte Carlo (KMC) model is developed based on the two-dimensional Ising model to investigate the drying patterns of nanofluids in an open domain. In the KMC model, the effective chemical potential is approximated by a linear function, in contrast to the constant value used in previous studies. This ensures that the dewetting front in the open domain consistently recedes from the edges toward the center. Simulation results show that nanoparticles, initially uniformly distributed, can assemble into branched structures that remain on the substrate after complete evaporation of the nanofluid. Furthermore, the structures observed in our study differ from the fractal cavities investigated in previous studies conducted in closed domains. A parametric study reveals that both the particle diffusion rate and the chemical potential distribution significantly influence the resulting patterns. Full article

Exoskeleton-assisted bodyweight support training (BWST) has demonstrated enhanced neurorehabilitation outcomes in which joint motion prediction serves as the critical foundation for adaptive human–machine interactive control. However, joint angle prediction under dynamic unloading conditions remains unexplored. This study introduces an adaptive wavelet-denoising fusion (AWDF) model to predict lower-limb joint angles during BWST. Utilizing a custom human-tracking bodyweight support system, time series data of surface electromyography (sEMG), and inertial measurement unit (IMU) from ten adults were collected across graded bodyweight support levels (BWSLs) ranging from 0% to 40%. Systematic comparative experiments evaluated joint angle prediction performance among five models: the sEMG-based model, kinematic fusion model, wavelet-enhanced fusion model, late fusion model, and the proposed AWDF model, tested across prediction time horizons of 30–150 ms and BWSL gradients. Experimental results demonstrate that increasing BWSLs prolonged gait cycle duration and modified muscle activation patterns, with a concomitant decrease in the fractal dimension of sEMG signals. Extended prediction time degraded joint angle estimation accuracy, with 90 ms identified as the optimal tradeoff between system latency and prediction advancement. Crucially, this study reveals an enhancement in prediction performance with increased BWSLs. The proposed AWDF model demonstrated robust cross-condition adaptability for hip and knee angle prediction, achieving average root mean square errors (RMSE) of 1.468° and 2.626°, Pearson correlation coefficients (CC) of 0.983 and 0.973, and adjusted R² values of 0.992 and 0.986, respectively. This work establishes the first computational framework for BWSL-adaptive joint prediction, advancing human–machine interaction in exoskeleton-assisted neurorehabilitation. Full article

Small-diameter vascular grafts often fail due to thrombosis and compliance mismatch. Decellularized plant scaffolds are a biocompatible, sustainable alternative. Leatherleaf viburnum leaves provide natural architecture and mechanical integrity suitable for tissue-engineered vessels. However, the persistence of immunogenic plant biomolecules and limited degradability remain barriers to clinical use. This study tested whether mild heat treatment improves scaffold biocompatibility without compromising mechanical performance. Decellularized leatherleaf viburnum scaffolds were treated at 30–40 °C in 5% NaOH for 15–60 min and then evaluated via tensile testing, burst pressure analysis, scanning electron microscopy, histology, and in vitro assays with white blood cells and endothelial cells. Scaffold properties were compared to those of untreated controls. Heat treatment did not significantly affect scaffold thickness but decreased fiber area fraction and diameter across all anatomical layers. Scaffolds treated at 30–35 °C for ≤30 min retained >90% of tensile strength and achieved burst pressures ≥820 mmHg, exceeding physiological arterial pressures. Heat treatment reduced surface fractal dimension while increasing entropy and lacunarity, producing a smoother but more heterogeneous microarchitecture. White blood cell viability increased up to 2.5-fold and endothelial cell seeding efficiency improved with treatment duration, with 60 min producing near-confluent monolayers. Mild alkaline heat treatment therefore improved immune compatibility and endothelialization while preserving mechanical integrity, offering a simple, scalable modification to advance plant-derived scaffolds for grafting. Full article

Due to the diverse origins of shale reservoirs, the coal measure shales of the Wuxiang block, Qinshui Basin typically exhibit fractal pore structures, which significantly influence shale gas occurrence and migration. Clarifying the fractal nature of pore structures is significant for the efficient development and utilization of shale gas. In this study, mercury intrusion porosimetry and liquid nitrogen adsorption experiments were conducted to develop a method that integrates pore compressibility correction and nitrogen adsorption for pore structure characterization. On this basis, this study analyzed the fractal characteristics of coal measure shale pore structures across multiple scales. The results reveal that coal measure shale pores exhibit a three-stage fractal pattern, consisting of three regions with pore diameters >65 nm (seepage pores), 6–65 nm (transition pores), and <6 nm (micropores). Samples with fractal dimensions of seepage pores ($D_{\mathrm{a}}$) exceeding 2.9 and transition pores ($D_1$) exceeding 2.5 tend to have larger specific surface areas and more complex pore structures; this is indicated by the increased surface roughness of large-scale pores, which hinders gas seepage. Samples with lower fractal dimension of micropores ($D_2$)—in the range of 2.2–2.8—exhibit higher micropore development, larger specific surface area, and simpler pore structures, as demonstrated by a greater number of micropores and a more uniform pore distribution, which promotes gas adsorption. Full article

This paper investigates the channel performance through a high-gain, circularly polarized microstrip patch antenna that is developed for contemporary wireless communication systems. The proposed antenna creates two orthogonal modes for circular propagation with slightly varying resonance frequencies by using a cross line and truncations to circulate surface currents. Compactness, reduced surface wave losses, and enhanced impedance bandwidth are made possible by the coaxial probe feed, periodic electromagnetic gap (EBG) slots, and fractal patch geometry. For in-phase reflection and beam focusing, a specially designed single-layer metasurface (MTS) reflector with an 11 × 11 circular aperture array is placed 20 mm behind the antenna. A log-normal shadowing model was used to test the antenna in real-world scenarios, and the results showed a strong correlation between the model predictions and actual data. At up to 250 m, the polarization-agile, high-gain antenna demonstrated reliable performance across a variety of channel conditions, enabling accurate characterization of the Channel Quality Indicator (CQI), Signal-to-Noise Ratio (SNR), and Reference Signal Received Power (RSRP). By combining cutting-edge antenna architecture with an empirical channel performance study, this research presents a compact, affordable, and fabrication-friendly solution for increased wireless coverage and efficiency. Full article

(1) Background: The impact of different drying methods on the functional properties and microstructure of milk powders was analyzed in this study. (2) Methods: Whole milk, skim milk, and buttermilk powders were obtained by freeze drying, spray drying, and roller drying. (3) Results: The examined powders differed in chemical composition, and these differences were attributed mainly to their fat content. The functional properties of the studied powders were determined mainly by the drying method and were less influenced by their composition. Loose and tapped bulk density was highest in roller-dried powders and lowest in freeze-dried powders. The flowability of milk powders was determined by calculating the Carr index and the Hausner ratio, and the results were used to classify the analyzed powders into the following groups: poorly flowing and cohesive (spray-dried samples), passable (roller-dried samples), and fair (freeze-dried samples). The volume of insoluble particles was highest in roller-dried powders and much lower in spray-dried powders, whereas freeze-dried powders were 99.8–99.9% soluble in water. Whole milk powder was characterized by low wettability (>180 s) regardless of the drying method. Powder morphology was influenced mainly by the drying method. (4) Conclusions: The fractal analysis demonstrated that spray-dried powders had the smallest fractal dimensions, which implies that their surface was least complex (most uniform). Regardless of the drying method, fractal dimensions were highest in whole milk powder, which could suggest that fat affects the microstructure of powders. The color parameters of milk powders were determined mainly by the drying method and were less influenced by the type of raw material used in powder production. Full article

The complex and dynamic nature of the marine environment poses significant challenges for sea surface target detection. Traditional methods relying on single-domain features suffer from performance degradation under varying conditions. To address this limitation, a multi-domain polarization-aware feature fusion network capable of controlling the false alarm rate (MP-FFN) for robust sea surface target detection is proposed in this paper. The proposed method first extracts discriminative radar echo features from time, frequency, fractal, and polarization domains. Subsequently, autoencoder-based intra-domain network is employed to reduce feature dimensionality while minimizing information loss. These compressed features are then fused through a multi-layer perceptron (MLP)-based inter-domain network, enabling comprehensive cross-domain correlation learning. Moreover, a controllable false alarm rate is achieved through a customized loss function. Extensive experiments on the IPIX radar dataset demonstrate that the proposed method outperforms traditional feature-based detection methods, exhibiting superior robustness and detection accuracy in diverse marine environments. Full article

This study presents a compact, wideband fractal antenna fabricated using silver nanoparticles (AgNPs) and screen-printing technology. The antenna consists of a decagonal monopole patch and a mesh ground plane, both printed on a transparent polyethylene terephthalate (PET) substrate. The proposed antenna has a compact size of 18 × 16 × 0.55 mm³, achieved by stacking two PET layers joined using double-sided tape. The antenna covers both C- and X-bands, with measured optical transmittance of 68.1% and radiation efficiency of 72%. The simulated −10 dB bandwidth (without bending) spans 4–10.8 GHz and 11.2–12.5 GHz, while the measured −10 dB bandwidth is 3.8–11.2 GHz without bending, 3–11.4 GHz at 30° bending, and 3–11.2 GHz at 45° bending, confirming that there was stable performance under flexure. The conductive patterns were formed using silver nanoparticle paste with a sheet resistance of 0.2 Ω/sq, followed by annealing in a vacuum oven at 140 °C for 20 min. The proposed antenna was tested under 30° and 45° bending, and the measured S₁₁ remained stable, confirming flexibility. The use of a flexible, optically transparent PET substrate enables installation on curved or see-through surfaces. Combining compact size, wideband performance, cost-effective fabrication, and optical transparency, the antenna demonstrates strong potential for application in X-band radar, C-band satellite communications, and S-band Wi-Fi. Full article

The anti-slip performance of road surfaces directly affects traffic safety, yet existing evaluation methods based on texture features often suffer from limited interpretability and low accuracy. To overcome these limitations, a portable 3D laser surface analyzer was used to acquire road texture data, while a dynamic friction coefficient tester provided friction measurements. A multi-view fractal dimension index was developed to comprehensively describe the complexity of texture across spatial, cross-sectional, and depth dimensions. Combined with road surface temperature, this index was integrated into an XGBoost-based prediction model to evaluate friction at driving speeds of 10 km/h and 70 km/h. Comparative analysis with linear regression, decision tree, support vector machine, random forest, and backpropagation (BP) neural network models confirmed the superior predictive performance of the proposed approach. The model achieved backpropagation (R²) values of 0.80 and 0.82, with root mean square errors (RMSEs) of 0.05 and 0.04, respectively. Feature importance analysis indicated that fractal characteristics from multiple texture perspectives, together with temperature, significantly influence anti-slip performance. The results demonstrate the feasibility of using non-contact texture-based methods to replace traditional contact-based friction testing. Compared with traditional statistical indices and alternative machine learning algorithms, the proposed model achieved improvements in R² (up to 0.82) and reduced RMSE (as low as 0.04). This study provides a robust indicator system and predictive model to advance road surface safety assessment technologies. Full article

This study investigates the tribological behavior and wear mechanisms of Q235 steel components subjected to abrasive interaction with rice, a critical challenge in agricultural machinery performance and longevity. We employed a comprehensive multi-scale framework, integrating bench-top tribological testing, advanced Discrete Element Method (DEM) coupled with a wear model (DEM-Wear), and detailed surface characterization. Bench tests revealed a composite wear mechanism for the rice–steel tribo-pair, transitioning from mechanical polishing under mild conditions to significant soft abrasive micro-cutting driven by the silica particles inherent in rice during high-load, high-velocity interactions. This elucidated fundamental friction and wear phenomena at the micro-level. A novel, calibrated DEM-Wear model was developed and validated, accurately predicting macroscopic wear “hot spots” on full-scale combine harvester header platforms with excellent geometric similarity to real-world wear profiles. This provides a robust predictive tool for component lifespan and performance optimization. Furthermore, fractal analysis was successfully applied to quantitatively characterize worn surfaces, establishing fractal dimension (Ds) as a sensitive metric for wear severity, increasing from ~2.17 on unworn surfaces to ~2.3156 in severely worn regions, directly correlating with the dominant wear mechanisms. This study offers a valuable computational approach for understanding and mitigating wear in tribosystems involving complex particulate matter, contributing to improved machinery reliability and reduced operational costs. Full article

This study investigates the fracture behavior of recycled aggregate concrete by integrating fractal theory and empirical modeling to quantify how recycled coarse aggregates (RCAs) and recycled fine aggregates (RFAs) influence crack complexity and maximum crack width under varying content and loads. The results reveal distinct scale-dependent behaviors between RCA and RFA. For RCA, moderate dosages enhance fractal complexity (a measure of surface roughness) by promoting micro-crack proliferation, while excessive RCA reduces complexity due to matrix homogenization. In contrast, RFA significantly increases both fractal complexity and crack width under equivalent loads, reflecting its susceptibility to micro-scale interfacial transition zone (ITZ) degradation. Non-linear thresholds are identified: RCA’s fractal complexity plateaus at high loads as cracks coalesce into fewer dominant paths, while RFA’s crack width growth decelerates at extreme dosages due to balancing effects like particle packing. Empirical models link aggregate dosage and load to fractal dimension and crack width with high predictive accuracy (R² > 0.85), capturing interaction effects such as RCA’s load-induced complexity reduction and RFA’s load-driven crack width amplification. Secondary analyses further demonstrate that fractal dimension correlates with crack width through non-linear relationships, emphasizing the coupled nature of micro- and macro-scale damage. These findings challenge conventional design assumptions by differentiating the impacts of RCA (macro-crack coalescence) and RFA (micro-crack proliferation), providing actionable thresholds for optimizing mix designs. The study also advances sustainable material design by offering a scientific basis for updating standards to accommodate higher recycled aggregate percentages, supporting circular economy goals through reduced carbon emissions and waste diversion, and laying the groundwork for resilient, low-carbon infrastructure. Full article

The stamp technique with bulk-fill composites aims to enhance occlusal surface replication in Class I restorations. Limited research exists on its void formation and volumetric changes. This study measures internal and external voids as well as volumetric changes in occlusal surfaces for both the stamp and conventional bulk-fill techniques. Materials and methods: Twenty-four permanent molars were divided into two groups (n = 12 each): Group 1 (conventional bulk fill) and Group 2 (stamp technique with bulk-fill composite). Standardized Class I cavities were prepared and restored using Tetric EvoCeram^® Bulk Fill composite. Micro-CT scanning was performed before and after restoration to quantify internal and external void percentages and volumetric changes. An independent samples t-test (α = 0.05) was used to compare void percentages and volumetric changes between groups. Results: The mean internal void percentage was similar between groups (Group 1: 0.38 ± 0.22%; Group 2: 0.39 ± 0.30%; p = 0.914), indicating comparable internal adaptation. Group 2 showed a significantly higher external void percentage (17.59 ± 1.76%) compared to Group 1 (9.05 ± 1.98%; p < 0.001), attributed to the stamp technique’s precise replication of occlusal micromorphology, misinterpreted as porosity by analysis software. Fractal dimension analysis revealed that the stamp technique resulted in the formation of a more complex structure. Restoration volumes (Group 1: 34.10 ± 8.09 mm³; Group 2: 35.52 ± 4.80 mm³; p = 0.639) and volumetric changes (Group 1: 5.91 ± 2.72 mm³; Group 2: 4.64 ± 1.31 mm³; p = 0.199) showed no significant differences. in conclusion, the stamp technique produced internal void percentages comparable to the conventional bulk-fill method in Class I restorations. The significantly higher external void percentage in the stamp technique group was due to the accurate replication of occlusal micromorphology, which was detected as porosity by analysis software. No significant differences were observed in volumetric changes of the occlusal surface before and after restoration between the two techniques, supporting the clinical viability of the stamp technique for precise occlusal restorations. Full article

Three-dimensional (3D) surface-enhanced Raman scattering (SERS) substrates have demonstrated remarkable abilities of ultrasensitive and reproducible molecular detection. The combination of both electromagnetic and chemical enhancement processes, light trapping, and multiple scattering effects of 3D structures are what enhance their performance. The principles of underlying enhancements are summarized systematically, and the main types of 3D substrates—vertically aligned nanowires, dendritic and fractal nanostructures, porous frameworks and aerogels, core–shell and hollow nanospheres, and hierarchical hybrid structures—are categorized in this review. Advances in fabrication techniques, such as template-assisted growth, electrochemical and galvanic deposition, dealloying and freeze-drying, self-assembly, and hybrid integration, are critically evaluated in terms of structural tunability and scalability. Novel developments in the field of biosensing are also highlighted, including non-enzymatic glucose sensing, tumor biomarker sensing, and drug delivery. The remaining limitations, such as low reproducibility, mechanical stability, and substrate standardization, are also noted, and future directions, such as stimuli-responsive designs, multifunctional hybrid platforms, and data-driven optimization strategies of SERS technologies, are also included. Full article

This study investigates the influence of carbonation duration and sand-to-powder ratio on the compressive strength and pore structure of recycled cement paste–sand (RCP-S) mortar. Specimens incorporating four different sand contents were subjected to carbonation for 1 and 24 h. Fractal dimensions, ranging from 2.60159 to 3.86742, indicated increased pore complexity with extended carbonation exposure. Mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) were employed to characterize pore features, including volume, surface area, and diameter. A Menger sponge-based fractal model was applied to compute the fractal dimensions and investigate their relationships with microstructural parameters and mechanical performance. Results showed that prolonged carbonation markedly reduced macropores and large capillary pores, enhanced fine pore content, and improved overall pore connectivity. Fractal analysis revealed that Segments I and IV exhibited the most significant fractal characteristics. The fractal dimension demonstrated exponential correlations with pore diameter; quadratic relationships—with superior statistical performance—with porosity, surface area, and pore volume; and a power–law relationship with compressive strength. These findings highlight the potential of fractal parameters as effective indicators of pore structure complexity and mechanical performance. This study offers a quantitative basis for optimizing pore structure in recycled cementitious materials, promoting their sustainable application in construction. Full article