Search Results (461)

Neltuma flexuosa exudate gum (NFEG) is a complex polysaccharide and a promising sustainable substitute for arabic gum, boasting an exceptional 92% extraction yield. Proximate analysis reveals an arabinogalactan–protein structure (89.9% carbohydrates, 3.2% protein) essential for its superior emulsifying and stabilizing properties. Composed mainly of galactose and arabinose, its random coil morphology ensures low viscosity at high concentrations, ideal for beverages. The presence of uronic acids (11.6%) provides a strong polyelectrolytic character, enhancing solubility and surface activity. Physicochemically, it mirrors arabic gum with an intrinsic viscosity of 19.90 cm³/g and thermal stability up to 237.4 °C. Structural analysis via FTIR and XRD confirms its amorphous polysaccharide nature and high chain flexibility. Furthermore, NFEG exhibits intrinsic bioactivity, including antioxidant properties confirmed by DPPH and reducing power assays. These dual functional properties present to NFEG as a high-value industrial hydrocolloid. Full article

Foot-worn electromagnetic harvesters are driven by irregular rigid-body motion, while their response is limited by mechanical stroke, coil geometry, mounting direction, and the electrical interface. This paper presents a reproducible numerical design study of a finite-stroke magnetic quasi-zero-stiffness (QZS) moving-magnet harvester. Two public three-axis foot-IMU records are processed with stated gyroscope-bias estimation, six-axis attitude estimation, gravity removal, residual-offset correction, filtering, and angular-acceleration calculation. Three explicit axes are used in the design screen, and the selected candidate is then evaluated over a 62-direction spherical grid. Rigid-body angular-acceleration and centripetal terms are included for specified sensor-to-harvester offsets. Two normalized magnetic force laws are compared. The electrical model uses position-dependent flux linkage, explicit series connection and polarity of coil sections, winding-derived resistance, and a position-dependent electromagnetic reaction force. A fixed-seed random screen evaluates 720 geometry-constrained candidates. The highest-ranked nominal candidate is a 150 mm external foot-worn module with a 40.6 g moving mass, a 30 mm hard half-stroke, 1649 turns in two series sections, and a 25.27 mm coil outer diameter. Across 72 design-screen cases formed from 12 five-second windows, three mounting axes, and two magnetic laws, this candidate remained hard-stroke- and design-stroke-safe. Its conditional ideal load-side power had a 10th percentile of 1.38 mW and a median of 2.03 mW. In the 62-direction check, all 1488 cases remained hard-stroke-safe; two opposite directions each produced one design-stroke exceedance, with a maximum displacement of 24.15 mm. Re-ranking all 30 Stage-2 candidates under coupling and magnetic-stiffness changes retained the long geometry family, although a 30% coupling reduction changed the highest-ranked candidate from 600 to 632. Soft-stop sensitivity, equation-level consistency, and multi-case Runge–Kutta convergence are also reported. The results support finite-stroke design screening, but they do not constitute prototype, finite-element, or delivered-power validation. Full article

Rice glutelin hydrolysates (RGHs) with different degrees of hydrolysis (DH) were prepared using papain, and the structural characterization, physicochemical stability, and antioxidant activity of RGH were analyzed. Results showed that RGH primarily consisted of low molecular weight (MW) peptides (<3 kDa), with hydrophobic/aromatic amino acid content increasing with DH. Higher DH level led to reduced average particle size and zeta potential of RGH. Structurally, as DH increased, a decrease in α-helix content alongside increased β-sheet/random coil ratios was observed in RGH, indicating a transition towards a more disordered structure in RGH. Furthermore, the antioxidant activity of RGH was significantly enhanced with the increase in DH, with RGH-18 showing the highest bioactivity. RGH maintained stability and antioxidant capacity under gastrointestinal digestion as well as various environmental stresses, including varying pH and temperatures, and the presence of metal ions. Cellular experiments demonstrated that RGH-18 alleviated H₂O₂-induced oxidative damage in HepG2 cells, likely by inhibiting Keap1 and activating Nrf2 via the Keap1/Nrf2 pathway. This study supports the potential of RGH as a functional ingredient and provides insights for targeted rice peptide production. Full article

To meet the demand for controlled production of low-molecular-weight (M_w < 10 kDa) dextran with potential pharmaceutical applications, this study developed an efficient enzymatic preparation process using PC-Edex, a dextranase derived from Penicillium cyclopium CICC-4022. The effects of enzyme concentration, substrate concentration, temperature, and pH on the degradation of high-molecular-weight dextran were systematically investigated, and the optimal process conditions were established. A staged empirical control strategy based on the Malhotra model was developed to investigate and predict the behavior of dextran molecular weight changes during enzymatic hydrolysis. Under the optimized conditions, dextran with an M_w below 10 kDa was produced within 60 min, with the mass fraction of fragments smaller than 10 kDa reaching 94.56 ± 0.32% and the degradation rate exceeding 98.96 ± 0.15%. The resulting product exhibited a narrow molecular weight distribution (M_w/M_n = 1.528 ± 0.03) and adopted a compact random-coil conformation in aqueous solution. Multi-scale characterization results indicated that enzymatic degradation altered only the molecular weight of dextran, while the backbone structure, amorphous nature, and thermal stability were preserved. These findings present a robust and reproducible laboratory-scale process, which provides a reference for the industrial production of low-molecular-weight dextran for pharmaceutical purposes. Full article

Accurate prediction of the heat transfer coefficient is essential for improving the coiling temperature control in hot strip rolling, especially under frequent rolling condition changes. Conventional layer-based self-learning methods may lead to boundary discontinuities, insufficient sample support for new gauges, and limited information sharing among similar operating conditions. To address these limitations, this paper proposes a random-forest (RF) and K-nearest-neighbor (KNN)-assisted local Gaussian process regression framework for the heat transfer coefficient in hot strip rolling. In the proposed method, RF is first used to select key variables and guide similar-case retrieval. KNN is then employed to retrieve the historical strips most similar to the current strip and to construct a local sample space. Instead of directly using conventional distance-weighted averaging, Gaussian process regression (GPR) is established on the retrieved local samples to model the nonlinear relationship between the process variables and the heat transfer correction coefficient. The proposed method outperforms conventional KNN-based weighting methods in terms of all the evaluation metrics for both first coils and in-lot coils at different speeds. Industrial validation shows that the measured coiling temperature is controlled within ±20 °C over more than 96.5% of the coil length. The results demonstrate that the proposed framework improves the adaptability and online compensation capability of the controlled cooling temperature models. Full article

Ferulic acid (FA) is a phenolic acid mainly present in wheat bran. It has beneficial health effects, but may affect gluten network formation and the processing quality of wheat-based products. This study investigated the interaction mechanisms between FA and glutenin/gliadin in dough and simulated dough systems. The results show that FA’s effects on both proteins were dose and system dependent. In dough, low-dose FA (≤0.3 g) promoted structural loosening of glutenin, as suggested by β-sheet conversion to β-turns/random coil structures, increased t-g-t disulfide and free thiols, and reduced particle size, whereas high doses promoted reaggregation via microenvironment reshaping, hydrophobic enhancement, cross-linking, and subunit rearrangement. For gliadin, low-dose FA may have altered local charge and hydrogen-bonding environments, while high-dose FA increased the hydrogen-bonding proportion by 45.71% and g-g-g conformation by 60.85%, suggesting enhanced molecular aggregation. In simulated dough, FA promoted stronger structural loosening of glutenin but favored gliadin aggregation, indicating that starch, lipids, water distribution, and other dough components may redirect FA–protein interactions. Molecular docking, as a complementary approach, predicted the preferential binding of FA to gliadin, LMW-GS and HMW-GS at different sites. These findings provide a theoretical basis for regulating phenolic acid–gluten interactions in whole-wheat and functional wheat-based products. Full article

Coiling temperature is a pivotal process parameter for hot-rolled strip steel, which directly determines the microstructure and mechanical properties of final products. Affected by the coupling of multiple process variables, coiling temperature presents strong nonlinearity and complex time-varying characteristics. Traditional heat transfer mechanism models, Random Forest (RF), Extreme Learning Machine (ELM) and single Long Short-Term Memory (LSTM) networks fail to fully explore the deep correlation among variables. In addition, their hyperparameters are generally selected by manual trial-and-error, leading to unsatisfactory prediction accuracy and poor robustness in practical production. To address the above limitations, this paper proposes a novel prediction model named WOA-CNN-GRU-SE, where the Whale Optimization Algorithm (WOA) is adopted for parameter optimization. Firstly, Convolutional Neural Network (CNN) is utilized to extract local coupling features from various working condition parameters. Secondly, the Squeeze-and-Excitation (SE) attention mechanism is applied to adaptively recalibrate channel weights, which enhances key features closely related to temperature variation and suppresses redundant interference information. Afterwards, Gated Recurrent Unit (GRU) is employed to conduct in-depth learning of temporal features. Furthermore, WOA is used to globally optimize critical hyperparameters, including learning rate, the number of GRU hidden units and L2 regularization coefficient, so as to eliminate the drawbacks of manual parameter tuning. Comparative experiments are conducted on actual production data from a hot rolling line. The results demonstrate that the proposed model outperforms CNN-GRU, CNN-GRU-SE, LSTM, RF and ELM in prediction performance. Its hit rate reaches 92.56% within the industrial error range of ±6 °C. This model effectively realizes accurate prediction of coiling temperature under complex working conditions and possesses great application potential in industrial practice. Full article

This study used black soldier fly protein (BSFP) as a base material and added 0%, 1%, 2%, 3%, 4%, and 5% of grape seed anthocyanidins (GSAs) to prepare composite gels. Through the combined use of low-field nuclear magnetic resonance, Fourier transform infrared spectroscopy, scanning electron microscopy, and rheometry, the relationships among GSA dosage (0–3%), gel structural properties (secondary protein conformation, water status, and microscopic morphology), and rheological printability were systematically evaluated. It was found that the better GSA content fell within 1–3%, and under this condition the extrusion-type 3D printing performance of the composite gels was significantly enhanced. At a 3% addition amount, the proportion of disordered conformations decreased (random coiling decreased from 15.93% to 15.46%), the ordered structure increased (β-sheet increased from 35.25% to 35.43%), and deformation resistance was enhanced. Low-field nuclear magnetic resonance showed an increase in the proportion of non-flowing water and an increase in physical constraints. Scanning electron microscopy showed a reduction in pore size and a thickening of pore walls, forming a denser 3D network. Rheologic analysis indicated that 3% GSA reached the maximum zero-shear viscosity (η₀) and that the storage modulus (G′) and loss modulus (G″) were higher in the experimental group than those in the control group. Printing fidelity increased from 45.73% in the control group to 60.08% in the 1% group, 62.14% in the 2% group, and 71.05% in the 3% group (p < 0.05). The 3–5% groups (fidelity: 71.05–75.66%) all achieved hollow cylindrical printing without collapse and had excellent self-supporting performance. However, excessive addition (4–5%) caused excess GSA to adsorb onto the protein skeleton surface, reducing the apparent viscosity and damaging the printing performance. Based on all the indicators, the composite gel with 3% GSA achieved the best balance between printability and structural integrity. Our research offers a new idea for using flavonoid compounds to improve the 3D printing performance of insect protein gels. The prepared composite gels can be used as food printing inks and applied to personalized nutrition customization, functional food development, and sustainable protein alternative product fields. Full article

Calcineurin B-like (CBL) proteins are plant-specific calcium sensors critical for ion homeostasis and stress tolerance. Here, seven MdCBL genes were genome-wide identified in apple (Malus domestica). We conducted systematic bioinformatic profiling of their physicochemical features, subcellular localization, cis-regulatory elements, phylogeny, secondary structures, phosphorylation sites, and functional annotations and further verified the salt-stress regulatory function of MdCBL5 via transgenic tests. MdCBL proteins contain 210–246 amino acids, with molecular weights of 24,196.73–28,283.39 Da, pI values of 4.63–4.97 and instability indices of 37.12–49.20. Localization prediction placed these proteins in nuclei, cytosol and chloroplasts. Their promoter regions are rich in hormone-responsive (auxin, ABA, salicylic acid) and stress-responsive (cold, drought, salt) cis-elements. Phylogenetic clustering divided MdCBLs into five subgroups (A–E) with high homology to Arabidopsis CBLs. Random coils and α-helices dominate their secondary structures, and serine residues constitute most phosphorylation sites. Functional annotation supports their involvement in calcium signaling, ion transport and diverse stress adaptation. Salt stress experiments have confirmed that MdCBL5 may enhance apple salt resistance by promoting MdSOS gene expression. Meanwhile, transient transformation in apple fruit showed that MdCBL5 can effectively enhance fruit quality traits. Collectively, this study establishes a theoretical foundation for further elucidating the biological functions of the apple MdCBL5 gene and provides valuable insights for genetically improving stress resistance and fruit quality in apple via molecular breeding strategies. Full article

To address the residual lateral coil misalignment after an unmanned aerial vehicle (UAV) lands on a fixed wireless-charging platform, this study proposes a graph-attention-based knowledge distillation method for embedded self-alignment localization. Four detection-coil voltages form an induced-voltage fingerprint database organized as a multi-scale spatial graph. A graph attention network (GAT) teacher model is trained offline to learn neighborhood correlations in the voltage–position mapping, and its spatial knowledge is distilled into a lightweight Tiny-MLP student model for microcontroller unit (MCU)-based online inference. Experimental results show that the GAT teacher achieves a mean absolute error (MAE) of 0.589 cm, while the distilled Tiny-MLP reduces the MAE of the directly trained Tiny-MLP from 1.548 cm to 1.148 cm (a 25.8% reduction under a fixed seed). In 2000 closed-loop alignment trials with random initial positions, the system achieves an 85.5% success rate under a 0.5 cm threshold, indicating that the method supports low-complexity closed-loop self-alignment for UAV wireless charging. Full article

To evaluate the potential of defatted and dephenolized walnut meal as a modified functional food ingredient, this study examined how ball milling and processing time affect its structural, physicochemical, and functional properties. Walnut meal was ball-milled for 5, 10, 15, and 20 h. Ball milling increased the lightness and whiteness, reduced particle size, and broadened the particle size distribution into a characteristic three-peak pattern. Scanning electron microscopy revealed the progressive formation of flake-like surface structures. With increasing milling duration, free sulfhydryl groups, surface hydrophobicity, and solubility were increased, while dynamic surface tension decreased, leading to improved foaming capacity and foaming stability. SDS-PAGE confirmed that the primary structure remained unchanged, while Fourier transform infrared spectroscopy indicated a decrease in α-helix and β-sheet contents and an increase in random coil structures. X-ray diffraction revealed a reduction in the diffraction peak at 2θ = 8.963°, and differential scanning calorimetry showed irregular changes in the thermal stability with ball milling time. Overall, increasing ball milling time is beneficial for improving the functional properties of walnut meal, providing a preliminary theoretical reference for the potential application of walnut powder in foods with specific functional properties, such as aerated foods. Full article

Peanut protein (PP) is an abundant plant protein resource with limited gelation performance. In this study, the effects of co-precipitation with egg white protein (EWP) on the structural and gelation properties of PP were investigated. Structural analysis revealed that co-precipitation induced secondary structure rearrangement of PP, accompanied by decreased α-helix and β-sheet contents and increased random coil and β-turn contents. These changes were associated with the exposure of hydrophilic groups and the partial shielding of hydrophobic regions, contributing to the significantly improved solubility of PP-EWP co-precipitated proteins (p < 0.05). These structural changes were conducive to the formation of a denser and more continuous gel network. Compared with the PP gel, the gel prepared from PP-EWP co-precipitated protein at the PP:EWP ratio of 2:1 showed an increase in gel strength from 429.30 g to 911.94 g and in water holding capacity from 56.78% to 85.53%. This study provides a theoretical basis and practical guidance for improving the gel properties of PP through co-precipitation and developing functional peanut protein ingredients, although the relatively high cost of EWP should be considered in practical applications. Full article

This study added two types of resistant dextrin (RD), i.e., Bailong (BL) and Luo Gaite (LGT)) to a Japonica (cv. RXY) and an early indica (cv. IP44) rice during cooking and analysed the functional and structural properties of the cooked rice. Compared with no RD addition, 3–10% RD addition induced a declinein cooking time and an incrementin gruel solid loss. Further, 3–10% RD addition increased the hardness, chewiness, and springiness of cooked rice but decreased the cohesiveness. With increases in the added RD amount, the smell, structural appearance, palatability, taste, cool rice texture, and total score of the cooked rice all increased; the peak time and pasting temperature increased, but the peak, final, breakdown, and setback viscosities all significantly decreased. The enthalpy, conclusion temperature of gelatinisation, and gelatinisation peak width and height all decreased with increasing RD amount, but the peak temperature of gelatinisation increased. The addition of 3–7% RD did not change amylopectin ageing, but 10% RD significantly increased amylopectin ageing. RD addition reduced the protein weakness degree and starch breakdown torque of rice doughbut appeared to increase the amorphous and crystalline regions of cooked rice. The addition of 10% BL or LGT induced the formation of α-helix and random coil secondary protein structures in cooked rice, with optimal cooking properties and total sensory score. Microstructure analysis further showed that low-viscous RD induced the formation of new gel-like structures. In conclusion, 3–10% RD addition in cooking rice decreases amylose recrystallisation, weakens the protein structure, and induces new gel-like structures, enhancing the hardness, chewiness, adhesiveness, springiness, and sensory score of cooked rice. This study is useful for developing functionalcooked rice. Full article

Porcine blood meal-derived hydrolysate peptides and hemin are natural antioxidants, and the formation of peptide–hemin conjugates can synergistically improve antioxidant performance. Ultrasonic (US) treatment facilitates the binding of different molecules. Therefore, in this study, the effects of ultrasonic power treatments on the antioxidant activity and binding behavior of peptide–hemin conjugates were investigated. The spatial structure of the peptide–hemin conjugates was characterized using endogenous fluorescence spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, and circular dichroism (CD) spectroscopy, respectively. The results demonstrated that the peptide–hemin binding rate reached the highest value of 91.63% at 400 W US power, with structural changes in conjugates from α-helix to random coil structures. Additionally, US treatment increased the surface hydrophobicity and reduced the enthalpy change in conjugates. The antioxidant capacity was greatly improved and peaked at 400 W US, where DPPH and ABTS radical scavenging rates exceeded 55% and 65%, respectively. This study provided a scientific basis for the high-value utilization of US treatment on porcine blood meal resources. Full article

Wireless power transfer (WPT) systems for electric vehicles require reliable foreign object detection (FOD) mechanisms both during and prior to power transfer to ensure operational safety and efficiency. The primary purpose of this study was to develop a foreign object detection system to ensure that no objects are present in the area of magnetic coupling (between primary and secondary coils) prior to initiating power transfer. Conventional FOD techniques based on impedance, visual light, or thermal monitoring provide limited spatial information and are sensitive to coil misalignment. This paper proposes a machine learning-based FOD approach using a planar Magnetic Inductance Tomography (MIT) sensor array that enables spatial electromagnetic sensing for early detection and localisation of conductive foreign objects. A dataset comprising 17,800 measurement frames was collected using a custom STM32-based data acquisition system in the absence of (prior to) power transfer. Likewise, a dataset comprising 300 sets of measurement frames was collected during power transfer, in which each frame contains 120 electromagnetic sensor readings. This capture methodology coincides with the detection requirements of live WPT systems. Four classification models, including Random Forest, Support Vector Machine, XGBoost, and Multi-Layer Perceptron, were evaluated. To enhance robustness against sensor drift and environmental variations, feature-engineering techniques incorporating statistical, temporal, frequency-domain, and derivative-based features were developed. Experimental results demonstrate high detection accuracy under both controlled and real-world conditions. The proposed approach demonstrates the feasibility of integrating machine learning-based MIT sensing into wireless EV charging infrastructure for reliable foreign object detection. Full article