Search Results (3,625)

Machining of medium-carbon steels, such as AISI 1050, poses a significant challenge in terms of achieving stable cutting conditions, controlled chip evacuation and high surface integrity, in particular when full-face milling is performed under elevated material removal rates. The tool surface engineering approach, particularly laser-induced micro-texturing, comprises a promising route toward modifying the tribological conditions at the tool–chip interface, thus affecting friction, heat generation, chip formation and the resultant surface finish. This study investigates the combined effects of cutting speed, axial depth of cut and tool micro-texture orientation (parallel versus orthogonal to the chip flow direction) on machining performance under wet conditions. In addition to the experimental analysis of cutting forces, chip morphology and surface roughness, this work integrates a full factorial Design of Experiments, regression modeling, and ANOVA to quantify the statistical significance of each factor and to identify dominant interactions. The regression models show strong predictive capability across all measured responses, while the ANOVA confirms the axial depth of cut and tool texture orientation as the most influential parameters. Multi-objective optimization by Pareto analysis further underlines the superiority of orthogonal micro-texturing, which consistently reduces the cutting forces and improves surface quality while promoting controlled chip segmentation. The results provide quantitative and statistically validated evidence of the enhancement of lubrication effectiveness, reduction in interface friction, and stabilization in chip formation provided by the micro-textured tools. Overall, the findings contribute to the development of data-driven machining strategies and surface-engineered cutting tools in view of improved productivity, energy efficiency and surface integrity in advanced manufacturing applications. Full article

Under sample-size-limited conditions, the recognition accuracy of imperfect corn kernels is severely degraded. To address this issue, a recognition framework that integrates a Residual Generative Spatial–Channel Synergistic Attention Generative Adversarial Network (RGSGAN) with a Multi-Scale Asymmetric Convolutional Residual Network (MACRNet) was proposed. First, residual structures and a spatial–channel synergistic attention mechanism are incorporated into the RGSGAN generator, and the Wasserstein distance with gradient penalty is integrated to produce high-quality samples and expand the dataset. On this basis, the MACRNet employs a multi-branch asymmetric convolutional residual module to perform multi-scale feature fusion, thereby substantially enhancing its ability to capture subtle textural and local structural variations in imperfect corn kernels. The experimental results demonstrated that the proposed method attains a classification accuracy of 98.813%, surpassing ResNet18, EfficientNet-v2, ConvNeXt-T, and ConvNeXt-v2 by 8.3%, 6.16%, 3.01%, and 4.09%, respectively, and outperforms the model trained on the original dataset by 5.29%. These results confirm the superior performance of the proposed approach under sample-size-limited conditions, effectively alleviating the adverse impact of data scarcity on the recognition accuracy of imperfect corn kernels. Full article

Texture is a critical quality attribute of strawberry fruit, and phytohormones play a pivotal role in fruit softening, which mainly results from cell wall metabolism, which is governed by genes and enzymes. To gain further insights into strawberry (Fragaria × ananassa, Duch. cv.  Akihime ) softening, our study investigated changes across five stages in fruits in their firmness, soluble solids content (SSC), cell microstructure, cell wall materials, activities of cell wall-modifying enzymes, gene expression, endogenous phytohormone levels, and their correlation. During strawberry ripening, firmness decreased, while SSC, intercellular space, and separation of the cell wall from the plasma membrane increased. Meanwhile, the contents of ionic pectin (ISP) and cellulose (CE), pectin methylesterase (PME) activity, FaPME expression, and the levels of zeatin (Z) and strigolactone (SL) decreased, showing a positive correlation with firmness. In contrast, the activities of pectate lyase (PL) and cellulase (Cx), the expression of FaPL and FaCx, and the contents of gibberellin A₄ (GA₄), GA₉, and abscisic acid (ABA) increased during ripening, and these were negatively correlated with firmness. These results suggest that Z and SL are associated with the maintenance of cell wall integrity and firmness, whereas increases in GA₄, GA_9, and ABA are linked to enhanced cell wall disassembly and fruit softening. Full article

Background: Cancer poses a significant health risk to humans, with prostate cancer (PCa) being the second most common and deadly form among men, following lung cancer. Each year, it affects over a million individuals and presents substantial diagnostic challenges due to variations in tissue appearance and imaging quality. In recent decades, various techniques utilizing Magnetic Resonance Imaging (MRI) have been developed for identifying and classifying PCa. Accurate classification in MRI typically requires the integration of complementary feature types, such as deep semantic representations from Convolutional Neural Networks (CNNs) and handcrafted descriptors like Histogram of Oriented Gradients (HOG). Therefore, a more robust and discriminative feature integration strategy is crucial for enhancing computer-aided diagnosis performance. Objectives: This study aims to develop a multi-stage hybrid learning model that combines deep and handcrafted features, investigates various feature reduction and classification techniques, and improves diagnostic accuracy for prostate cancer using magnetic resonance imaging. Methods: The proposed framework integrates deep features extracted from convolutional architectures with handcrafted texture descriptors to capture both semantic and structural information. Multiple dimensionality reduction methods, including singular value decomposition (SVD), were evaluated to optimize the fused feature space. Several machine learning (ML) classifiers were benchmarked to identify the most effective diagnostic configuration. The overall framework was validated using k-fold cross-validation to ensure reliability and minimize evaluation bias. Results: Experimental results on the Transverse Plane Prostate (TPP) dataset for binary classification tasks showed that the hybrid model significantly outperformed individual deep or handcrafted approaches, achieving superior accuracy of 99.74%, specificity of 99.87%, precision of 99.87%, sensitivity of 99.61%, and F1-score of 99.74%. Conclusions: By combining complementary feature extraction, dimensionality reduction, and optimized classification, the proposed model offers a reliable and generalizable solution for prostate cancer diagnosis and demonstrates strong potential for integration into intelligent clinical decision-support systems. Full article

Low-resolution (LR) imagery poses significant challenges to object detection systems, particularly in autonomous and resource-constrained environments where bandwidth and sensor quality are limited. To address this issue, this paper presents an integrated framework that enhances object detection performance by incorporating a Super-Resolution (SR) preprocessing stage prior to detection. Specifically, a Dense Residual Connected Transformer (DRCT) is employed to reconstruct high-resolution (HR) images from LR inputs, effectively restoring fine-grained structural and textural information essential for accurate detection. The reconstructed HR images are subsequently processed by a YOLOv11 detector without requiring architectural modifications. Experimental evaluations demonstrate consistent improvements across multiple scaling factors, with an average increase of 13.4% in Mean Average Precision (mAP)@50 at ×2 upscaling and 9.7% at ×4 compared with direct LR detection. These results validate the effectiveness of the proposed SR-based preprocessing approach in mitigating the adverse effects of image degradation. The proposed method provides an improved yet computationally challenging solution for object detection. Full article

This study compared the muscle quality of largemouth bass (Micropterus salmoides) reared in a simplified indoor factory-scale recirculating aquaculture system (F-RAS) with those reared in a traditional pond (TP). Juveniles from the same cohort (with a mean initial body mass of approximately 16 g) were stocked into the two systems and reared for ten months. The F-RAS is a high-density indoor system utilising octagonal concrete tanks with an effective water volume of 100 m³ and a stocking density of 130 fish m⁻³. The TP is a low-density system, where fish are reared in earthen ponds with a total area of 4000 m² at a density of 1.7 fish m⁻³. At the end of the experiment, 20 fish per group were randomly sampled for morphological analysis, while subsets of 6 fish per group were used for texture analysis, 3 fish per group for water-holding capacity, 3 fish per group for proximate composition, and 9 fish per group (pooled into 3 biological replicates) for amino acid, fatty acid and volatile compound analyses. The results showed that the F-RAS group exhibited superior texture, with significantly higher chewiness, springiness and muscle fibre density. Nutritionally, the F-RAS group had significantly greater crude protein, EPA, DHA and total n-3 fatty acid contents. Although glutamate and leucine levels were lower in the F-RAS group, cysteine and histidine levels were higher. Analysis of volatile compounds indicated improved flavour in the F-RAS group, with a marked reduction in off-flavour compounds such as 1-octen-3-ol and hexanal. Overall, largemouth bass produced in F-RAS showed better muscle quality than those from the TP in terms of texture, nutritional value and flavour. This study provides a reference for future research on the regulation of muscle quality in largemouth bass using a simplified F-RAS. Full article

Accurate detection of concealed items in X-ray baggage images is critical for public safety in high-security environments such as airports and railway stations. However, small objects with low material contrast, such as plastic lighters, remain challenging to identify due to background clutter, overlapping contents, and weak edge features. In this paper, we propose a novel architecture called the Contrast-Enhanced Feature Pyramid Network (CE-FPN), designed to be integrated into the YOLO detection framework. CE-FPN introduces a contrast-guided multi-branch fusion module that enhances small-object representations by emphasizing texture boundaries and improving semantic consistency across feature levels. When incorporated into YOLO, the proposed CE-FPN significantly boosts detection accuracy on the HiXray dataset, achieving up to a +10.1% improvement in mAP@50 for the nonmetallic lighter class and an overall +1.6% gain, while maintaining low computational overhead. In addition, the model attains a mAP@50 of 84.0% under low-resolution settings and 87.1% under high-resolution settings, further demonstrating its robustness across different input qualities. These results demonstrate that CE-FPN effectively enhances YOLO’s capability in detecting small and concealed objects, making it a promising solution for real-world security inspection applications. Full article

The influence of lactic acid bacteria (LAB) strains of various species isolated from Chinese traditional sourdough on the properties of rice sourdough and the textural and flavor qualities of steamed rice bread (SRB) was investigated. Lactiplantibacillus plantarum-fermented rice sourdough had a higher total titratable acidity (13.10 mL) than the other groups. Strains Lacticaseibacillus paracasei PC1 (LPC), Lactobacillus helveticus H1 (LH), Lactobacillus crustorum C1 (LC), Lactobacillus paralimentarius PA1 (LPA), and Lactiplantibacillus plantarum P1 (LP) showed marked protein hydrolysis during rice sourdough fermentation and increased free amino acid levels in rice sourdoughs relative to the control. The Fourier Transform Infrared Spectroscopy results indicated that LAB fermentation could promote the strengthening of inter-intramolecular hydrogen bonds and cause modifications in protein structures; however, these effects varied among the different strains. The LC and LPC strains had the most significant effect on improving the specific volume and textural properties of SRBs. Gas chromatography-mass spectrometry (GC-MS) and GC-ion mobility spectrometry (IMS) identified 33 and 35 volatile compounds, respectively, in the LAB-fermented SRBs, and differentiation was observed in the volatile profiles of SRBs made using different LAB strains. The differential impacts of LAB strains during rice sourdough fermentation can assist in the selection of candidate microorganisms for the production of high-quality gluten-free rice products. Full article

The Gannan navel orange (GNO) industry is large but constrained by limited deep-processing. This study employed vacuum freeze-drying (FD) and hot-air drying (HD) methods to prepare dried GNO slices, comparing their physical properties, volatile/non-volatile compounds, antioxidant activity, and sensory quality. Compared with the HD sample (ΔE= 10.11), the color changes were more pronounced in the FD sample (ΔE= 34.39), which appeared whiter and brighter. The FD method preserved more vitamin C (9.09% loss) than the HD method (27.28% loss). In contrast, HD samples contained significantly higher levels of total flavonoids, total phenols, hesperidin, narirutin and didymin, with respective increment percentages of 13.81%, 19.27%, 17.03%, 27.56% and 33.33% compared to FD samples. Volatile analysis revealed that drying treatments led to a decrease in terpene content compared with fresh slices (fresh 48.84% vs. FD 47.81% vs. HD 47.42%), while ester content increased (fresh 13.87% vs. FD 14.59% vs. HD 14.45%). Both methods reduced key monoterpenes (e.g., β-terpineol, terpinolene, 3-carene, α-terpineol, β-thujene and α-terpinene), possibly converting them into compounds such as p-mentha-1(7),8-diene-ol and thymol. Notably, HD samples contained much higher levels of harmful compounds 5-hydroxymethylfurfural and furfural. FD samples exhibited superior antioxidant activity and were preferred in sensory evaluation for appearance, aroma, texture, and taste. The findings indicate that FD offers advantages in terms of morphological retention, vitamin C preservation, antioxidant activity, safety and sensory perception, underscoring the market potential of FD navel orange slices as a high-value, healthy food product. Full article

This paper presents a cascaded imaging method that combines low-light enhancement and visible–long-wavelength infrared (VIS-LWIR) image fusion to mitigate image degradation in dark environments. The framework incorporates a Low-Light Enhancer Network (LLENet) for improving visible image illumination and a heterogeneous information fusion subnetwork (IXNet) for integrating features from enhanced VIS and LWIR images. Using a joint training strategy with a customized loss function, the approach effectively preserves salient targets and texture details. Experimental results on the LLVIP, M³FD, TNO, and MSRS datasets demonstrate that the method produces high-quality fused images with superior performance evaluated by quantitative metrics. It also exhibits excellent generalization ability, maintains a compact model size with low computational complexity, and significantly enhances performance in high-level visual tasks like object detection, particularly in challenging low-light scenarios. Full article

Background: Dysphagia negatively impacts quality of life and requires diets with specifically modified textures. The IDDSI (International Dysphagia Diet Standardization Initiative) scale provides standardized criteria to ensure food safety. This research aims to explore and validate the IDDSI scale adapted to the consumption of foods developed with 3D printing in patients with dysphagia. Methodology: Different dishes were designed and validated using 3D printing and were evaluated by both healthcare professionals and people with dysphagia. In the second phase, participants analyzed their texture using the IDDSI scale. A mixed methodological approach was applied, combining quantitative data (from validated scales) and qualitative data (obtained through interviews and focus groups), ensuring methodological triangulation. Methods: In the first phase of the study, different dishes were cooked and designed using 3D printing technology and were previously evaluated by both healthcare professionals and people with dysphagia. In the second phase, all the dishes validated in the first phase were analyzed and classified according to their texture using the IDDSI. Results: A total of 24 dishes, backed by 204 validations, were determined to be suitable for people with dysphagia and compatible with 3D printing. According to the IDDSI analysis, 36% of these dishes were classified as level 3 (soft texture) and 64% as level 4 (thick purée), levels internationally recognized as safe and suitable for people with dysphagia and suitable for 3D printing. The application of the IDDSI scale eliminated ambiguities in the description of textures, facilitating clear communication between healthcare professionals, caregivers, people with dysphagia, and companies that produce 3D-printed foods, as well as the standardization of 3D food printing processes related to textures. The application of the IDDSI scale eliminated ambiguities in the description of textures, facilitating clear communication between healthcare professionals, caregivers, people with dysphagia, and companies producing 3D-printed food products. This enabled the standardization of 3D food printing processes and the definition of their textures. At the same time, 3D printing proved to be a viable and effective tool for customizing meals that are safe, appropriate, and sensorially appealing. Conclusions: The feasibility of combining the IDDSI scale with 3D printing to develop diets tailored to the needs of people with dysphagia is confirmed. This integrative approach represents an innovation in the field of nutrition for people with swallowing problems, especially in contexts with limited scientific evidence, combining the validation of modified textures with 3D printing technology. There are effective tools for producing safe, suitable and sensorially appealing meals. Full article

This study investigated the effects of various concentrations of coriander seed powder (CSP) (0.1%, 0.3%, and 0.5%) on the fermentation performance, whey precipitation rate, texture, rheological properties, microstructure, and sensory characteristics of spoonable yoghurt stored at 4 °C for 21 days. The aim was to evaluate the impact of CSP on spoonable yoghurt quality and its health-promoting properties. The results revealed that the addition of CSP led to a significant decrease in pH and an increase in titratable acidity. Furthermore, the whey precipitation rate in the CSP-enriched yogurt sample was clearly lower than that of the control group (p < 0.05). The syneresis of the yogurt sample with 0.3% CSP decreased by 21.14 on the 21st day, compared to the control group (49.64%) (p < 0.05). This was accompanied by a reduction in apparent viscosity and an increase in the viscoelastic modulus. Meanwhile, the texture of the yogurt sample remains more stable, with the best sensory acceptance in the yogurt sample containing 0.3% CSP. As the concentration of coriander seed powder level increased, antioxidant activity, digestibility, and small molecule phenolic level of the yogurt samples obviously improved (p < 0.05). Yogurt with 0.3% CSP still showed significantly enhanced antioxidant capacity during the 21-day storage period. The DPPH-radical scavenging rate increased by 5.22% compared to the control group (p < 0.05). Similarly, the ABTS+ clearance activity increased by 12.52% (47.06% compared to 34.54% in the control group, p < 0.05). In the 0.3% CSP yogurt group, the total phenolic content reached 5.33 mg GAE/100 g, an increase of 1.85 compared to the control sample (3.48 mg GAE/100 g) (p < 0.05). The in vitro protein digestibility of the yogurt samples containing 0.3% CSP clearly increased by 12.65% (p < 0.05). In summary, the yogurt sample supplemented with 0.3% CSP demonstrated optimal sensory quality characteristics. Coriander seed powder may be used as a beneficial ingredient containing rich active substances to enhance the quality of spoonable yoghurt products. Full article

This study investigated the functional, pasting, and rheological properties of sprouted fava bean flour, Lactobacillus plantarum fermented red rice flour, and mixed flour. Then, the study investigated the structural properties of sprouted fava bean dough, fermented red rice dough, and mixed dough, as well as the quality and functional properties of the mixed noodles. The results showed that sprouting and fermentation treatments improved the processing properties of the flour. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and moisture distribution results of the dough showed that the mixed dough had a more stable structure. Scanning electron microscopy (SEM) and Confocal laser scanning microscopy (CLSM) of the noodles showed that the addition of sprouted fava bean flour was able to mimic the protein network structure to some extent. In addition, germination and fermentation were effective in improving the textural properties, as well as increasing the total phenolic content (1.27–2.03 mg GAE/g) and antioxidant activity, including 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging (43.54–64.84%), 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging (41.37–58.98%), Hydroxyl radical scavenging (19–48.38%), while significantly reducing the estimated glycemic index (74.64–57.60) of the mixed noodles. Full article

This study aimed to evaluate the impact of green coffee flour (GCF) addition (2–8%) and drying method (convective versus microwave-vacuum drying) on the physicochemical, textural, and bioactive properties of pasta. Both factors were found to significantly influence the assessed parameters. Green coffee had no observable effect on the microstructure of convectively dried pasta, whereas microwave-vacuum drying caused visible cracks and a heterogeneous starch-protein matrix even at a 2% supplementation level. Microwave-vacuum-dried pasta exhibited a shorter optimal cooking time and higher water absorption compared with convectively dried samples, while increasing the level of GCF prolonged cooking time and increased cooking losses. Texture analysis revealed that convectively dried pasta showed decreased elasticity and cohesiveness with increasing GCF content, whereas microwave -vacuum-dried pasta maintained a relatively uniform texture regardless of supplementation. The incorporation of GCF enhanced the antioxidant capacity of pasta, with the most pronounced effect at 2% addition, while higher levels showed reduced benefits. Similarly, fortification increased the content of phenolic acids, particularly chlorogenic acid and its isomers, with convectively dried samples exhibiting higher levels than microwave-vacuum-dried pasta. Consumer acceptance was highest for convectively dried pasta without GCF and for samples containing 2%, while pasta with higher GCF levels or microwave-vacuum-dried samples received lower scores. Full article

Effective biopreservation strategies are essential to maintain product quality and extend shelf life. However, the low storage temperature (4 °C) of low-temperature meat products limits the growth and activity of most protective cultures, highlighting the need for psychrotrophic strains. This study evaluated the impact of various bioprotective cultures on the bacterial counts, physicochemical quality, flavor profile, and sensory characteristics of the Harbin red sausage under vacuum packaging for 28 days. In comparison with the control (uninoculated) and B2 (commercial Latilactobacillus sakei B2) groups, individual and mixed (1:1) inoculations with psychrotrophic Pediococcus acidilactici L1 and Lactiplantibacillus plantarum HG1-1 significantly inhibited the growth of Acinetobacter and Staphylococcus (p < 0.05), providing the sausage with superior color and texture and delaying lipid oxidation, thereby improving the sausage’s overall acceptability on day 28. The electronic nose analyses indicated that Harbin red sausages inoculated with individual and mixed cultures of Pe. acidilactici L1 and Lac. plantarum HG1-1 exhibited less development of odor compounds during storage. Overall, both individual and mixed inoculations with Pe. acidilactici L1 and Lac. plantarum HG1-1 showed superior bioprotective effects on Harbin red sausages under vacuum packaging compared with commercial Lat. sakei B2, with the mixed inoculation treatment being the most effective. Full article