Search Results (157)

To address the limitations of the single-modal electroencephalogram (EEG), such as its single physiological dimension, weak anti-interference ability, and inability to fully reflect emotional states, this paper proposes a gated multi-head cross-attention module (GMHCA) for multimodal fusion of EEG, electrooculography (EOG),and electrodermal activity (EDA). This attention module employs three independent and parallel attention computation units to assign independent attention weights to different feature subsets across modalities. Combined with a modality complementarity metric, the gating mechanism suppresses redundant heads and enhances the information transmission of key heads. Through multi-head concatenation, cross-modal interaction results from different perspectives are fused. For the backbone network, a multi-scale convolution and bidirectional long short-term memory network (MC-BiLSTM) is designed for feature extraction, tailored to the characteristics of each modality. Experiments show that this method, which primarily fuses eight-channel EEG with peripheral physiological signals, achieves an emotion recognition accuracy of 89.45%, a 7.68% improvement over single-modal EEG. In addition, in cross-subject experiments conducted on the SEED-IV dataset, the EEG+EOG modality achieved a classification accuracy of 92.73%. All were significantly better than the baseline method. This fully demonstrates the effectiveness of the innovative GMHCA module architecture and MC-BiLSTM feature extraction network proposed in this paper for multimodal fusion methods. Through the novel attention gating mechanism, higher recognition accuracy is achieved while significantly reducing the number of EEG channels, providing new ideas and approaches based on attention mechanisms and gated fusion for multimodal emotion recognition in resource-constrained environments. Full article

Background: currently, there is a growing trend toward multifunctional cosmetics, which combine several active ingredients in a single product to enhance efficacy and user convenience. As ingredients may influence one another, it is important to study the behavior of mixing multiple compounds in complex formulations, especially regarding their interaction with the skin. Piceatannol, for instance, is a naturally occurring stilbene recognized for its in vitro potent antioxidant, anti-inflammatory, and anti-aging activities, making it a promising candidate for dermocosmetic use in suncare. But despite its beneficial biological activities, its cutaneous permeation remains poorly understood, particularly when delivered from complex formulations containing multiple ingredients. Objectives: in this sense, this study aimed to evaluate the in vitro skin diffusion profile of piceatannol from a passion fruit seed extract (P_ext) incorporated into a topical base (B_em) or an organic sunscreen emulsion (O_em), with or without a spilanthol-rich Acmella oleracea extract (J_ext) used as a natural permeation enhancer. Methods: due to ethical and variability issues with human and animal skins, the Strat-M™ synthetic membrane was chosen as a standardized model for the in vitro skin permeation assays. Piceatannol localization within membrane layers was examined by confocal Raman microscopy (CRM), while compound identification in donor and receptor compartments was performed via UHPLC-DAD. Results: piceatannol from B_em was detected up to 140 µm from the Strat-M™ surface and exceeded 180 µm in depth when J_ext and organic sunscreens were included in the formulation. Notably, formulations containing J_ext and those based on O_em promoted enhanced accumulation in both the stratum corneum and deeper skin layers, suggesting an improved delivery potential in lipid-rich vehicles. Conclusions: even though some instability issues were observed, piceatannol penetration into Strat-M™ from the proposed formulations was confirmed, and the results provide a foundation for further research on its topical delivery, supporting the rational development of formulations capable of harnessing its demonstrated biological properties. Full article

This study proposes a novel SSA-EMS framework that integrates Singular Spectrum Analysis (SSA) with Effect-Matched Spatial Filtering (EMS), combining the noise-reduction capability of SSA with the dynamic feature extraction advantages of EMS to optimize cross-subject EEG-based emotion feature extraction. Experiments were conducted using the SEED dataset under two evaluation paradigms: “cross-subject sample combination” and “subject-independent” assessment. Random Forest (RF) and SVM classifiers were employed to perform pairwise classification of three emotional states—positive, neutral, and negative. Results demonstrate that the SSA-EMS framework achieves RF classification accuracies exceeding 98% across the full frequency band, significantly outperforming single frequency bands. Notably, in the subject-independent evaluation, model accuracy remains above 96%, confirming the algorithm’s strong cross-subject generalization capability. Experimental results validate that the SSA-EMS framework effectively captures dynamic neural differences associated with emotions. Nevertheless, limitations in binary classification and the potential for multimodal extension remain important directions for future research. Full article

Background/Objectives: Acute lung injury (ALI) is a respiratory disorder lacking specific targeted therapy. Our preliminary screening revealed that the ethanol extract of the seeds of Podocarpus nakaii (EESPN) alleviated the symptoms of ALI in mice. The objectives of this study were to identify the active constituents in EESPN and study the mechanism involved. Methods: Column chromatography was performed to separate the chemical constituents of EESPN. The structures of the isolates were determined via spectroscopic methods. MTT assays, Western blotting, histological analysis, TUNEL assays, immunofluorescence staining, transcriptomic analysis, and quantitative real-time polymerase chain reaction (qRT–PCR) were employed to evaluate the anti-inflammatory activity and to elucidate the potential mechanism of nagilactone C (3, Nag C) in ALI treatment. Results: Twelve compounds were isolated from EESPN and structurally characterized. The structure of podolactone E (1) was confirmed via single-crystal X-ray diffraction. In vitro, Nag C showed potent anti-inflammatory activity in LPS-induced RAW 264.7 cells. Nag C liposomes significantly ameliorated LPS-induced histopathological damage to the lungs, reduced neutrophil infiltration and inflammatory cytokine levels, increased myeloperoxidase (MPO) activity, and promoted apoptosis in mice. In addition to suppressing inflammation, Nag C also significantly suppressed the phosphorylation of the NF-κB, STAT3, and STAT1 proteins. Conclusions: Nag C is an active constituent of EESPN. It may protect against LPS-induced ALI via inhibition of the STAT signaling pathway. Thus, Nag C is a promising lead compound in the development of novel STAT-targeted anti-inflammatory agents. Full article

The precise identification, classification, sorting, and rapid and accurate quality assessment of soybean seeds are extremely important in terms of the continuity of agricultural production, varietal purity, seed processing, protein extraction, and food safety. Currently, commonly used methods for the identification and quality assessment of soybean seeds include morphological analysis, chemical analysis, protein electrophoresis, liquid chromatography, spectral analysis, and image analysis. The use of image analysis and artificial intelligence is the aim of the presented research, in which a method for the automatic classification of soybean varieties, the assessment of the degree of damage, and the identification of geometric features of soybean seeds based on numerical models obtained using a 3D scanner has been proposed. Unlike traditional two-dimensional images, which only represent height and width, 3D imaging adds a third dimension, allowing for a more realistic representation of the shape of the seeds. The research was conducted on soybean seeds with a moisture content of 13%, and the seeds were stored in a room with a temperature of 20–23 °C and air humidity of 60%. Individual soybean seeds were scanned to create 3D models, allowing for the measurement of their geometric parameters, assessment of texture, evaluation of damage, and identification of characteristic varietal features. The developed 3D-CNN network model comprised an architecture consisting of an input layer, three hidden layers, and one output layer with a single neuron. The aim of the conducted research is to design a new, three-dimensional 3D-CNN architecture, the main task of which is the classification of soybean seeds. For the purposes of network analysis and testing, 22 input criteria were defined, with a hierarchy of their importance. The training, testing, and validation database of the SB3D-NET network consisted of 3D models obtained as a result of scanning individual soybean seeds, 100 for each variety. The accuracy of the training process of the proposed SB3D-NET model for the qualitative classification of 3D models of soybean seeds, based on the adopted criteria, was 95.54%, and the accuracy of its validation was 90.74%. The relative loss value during the training process of the SB3D-NET model was 18.53%, and during its validation process, it was 37.76%. The proposed SB3D-NET neural network model for all twenty-two criteria achieves values of global error (GE) of prediction and classification of seeds at the level of 0.0992. Full article

Contaminated seeds pose a major risk in hydroponic systems, as a single contaminated seed can compromise the entire setup. Effective decontamination strategies are essential to control seed-borne pathogens. Pecan shells, a byproduct comprising nearly 50% of the nut’s weight, have demonstrated antimicrobial properties against key pathogens. This study evaluated pecan shell extract (PSE) as a treatment to inactivate Listeria monocytogenes, Escherichia coli O157:H7, and Pseudomonas spp. on lettuce seeds and its effect on germination. Lettuce seeds were inoculated with L. monocytogenes strains (101 M, V7, LCDC, and Scott A) and treated with PSE (1:10 w/v) either by coating in sodium alginate or priming for 6 h (4 °C or room temperature). Hydropriming was used as a control. Additional trials with E. coli and Pseudomonas spp. tested PSE at 1:10, 1:20, and 1:30 w/v ratios. Priming at refrigeration significantly reduced Listeria levels. E. coli priming treatments showed significant reductions at 1:20 and 1:30 w/v. For Pseudomonas, priming at 1:20 showed the highest reduction. PSE priming also enhanced germination (88.3%), outperforming other treatments. These findings suggest PSE is a sustainable and effective seed treatment to reduce microbial contamination and enhance seed germination in hydroponic systems. Full article

Efficient and consistent DNA extraction is crucial for genotyping but often hindered by the limitations of traditional manual processes, which are labour-intensive, error-prone, and costly. We introduce a semi-automated, robotic-assisted DNA extraction (RoboCTAB) tailored for large-scale plant genotyping, leveraging advanced yet affordable liquid-handling robotic systems. The protocol/workflow integrates a CTAB extraction protocol specifically adapted for a robotic liquid-handling system, making it compatible with high-throughput genotyping techniques such as SNP genotyping and sequencing. Various plant parts (leaves, roots, manual seed chip) were explored as the source material for DNA extractions, with the aim of identifying the tissue best suited for collection on a large scale. Young roots (radicle) proved the easiest to harvest at scale, while the harvest of leaves and seed chips were more laborious and error-prone. DNA yield and quality from both leaves and roots (but not seed chips) were similar and sufficient for downstream analysis. Interestingly, root tissue could still be extracted from imbibed seeds, even if the seeds failed to germinate, thus proving useful for DNA extraction. Cost analysis indicates significant savings in labour costs, highlighting the approach’s suitability for large-scale projects. Quality assessments demonstrate that the robotic process yields high-quality DNA, maintaining integrity for downstream applications. This semi-automated DNA extraction system represents a scalable, reliable solution for large-scale genotyping that is accessible to many users who cannot implement highly sophisticated and costly systems as are known to exist in large multinational seed companies. RoboCTAB, a low-cost, optimized method for high-throughput DNA extraction, minimizes the risk of cross-contamination. RoboCTAB is capable of processing up to four 96-well plates (384 samples) simultaneously in a single run, improving cost-efficiency and providing seamless integration with laboratory workflows, potentially setting new standards for efficiency and quality in DNA processing and sequencing at scale. Full article

We report the development of a procedure for ultrasound-assisted microscale extraction of metabolites from the flowers of Saint John’s wort (Hypericum perforatum L.), designed for comparative metabolite analysis of plants from genetic resource collections and natural and segregating populations. The procedure involves high-throughput methanol extraction of metabolites from ground-frozen flowers at a selected stage of flower development, which is carried out in a standard 2 mL Eppendorf tube. A total of 18 compounds, including chlorogenic acid, catechins, glycosylated flavonoids, hypericins, and hyperforin, were identified based on LC/DAD/QTOF analysis, of which 16 could be detected in the UV-Vis spectrum. Two alternative versions of the procedure were evaluated: the “single-flower” procedure, including repeated collection and analysis of single flowers from the tested plant, and the “bulk-flower” procedure, employing the collection of a bulk flower sample from the tested plant and analysis of a portion of the ground sample. The results showed excellent technical reproducibility of the “single-flower” procedure when used with the suggested combination of the peak areas for the proto- and stable forms of pseudohypericin and hypericin. Application of the developed “single-flower” procedure for comparison of the plants derived from seed progeny of the apomictic line Hp93 revealed significantly lower metabolite variation among the apomictic progeny plants compared to the variation observed among plants belonging to different genotypes. Full article

Straw row grouping is vital in conservation tillage for precision seeding, and accurate centerline extraction of the seedling bands enhances agricultural spraying efficiency. However, the traditional single-threshold Otsu segmentation struggles with adaptability and accuracy under complex field conditions. To overcome these issues, this study proposes an adaptive multi-threshold Otsu algorithm optimized by a Simulated Annealing-Enhanced Differential Evolution–Whale Optimization Algorithm (SADE-WOA). The method avoids premature convergence and improves population diversity by embedding the crossover mechanism of Differential Evolution (DE) into the Whale Optimization Algorithm (WOA) and introducing a vector disturbance strategy. It adaptively selects thresholds based on straw-covered image features. Combined with least-squares fitting, it suppresses noise and improves centerline continuity. The experimental results show that SADE-WOA accurately separates soil regions while preserving straw texture, achieving higher between-class variance and significantly faster convergence than the other tested algorithms. It runs at just one-tenth of the time of the Grey Wolf Optimizer and one-ninth of that of DE and requires only one-sixth to one-seventh of the time needed by DE-GWO. During centerline fitting, the mean yaw angle error (MEA) ranged from 0.34° to 0.67°, remaining well within the 5° tolerance required for agricultural navigation. The root-mean-square error (RMSE) fell between 0.37° and 0.73°, while the mean relative error (MRE) stayed below 0.2%, effectively reducing the influence of noise and improving both accuracy and robustness. Full article

This study investigated the effects of acid etching with grape seed extract (GSE)-modified etchants, varying phosphoric acid (PA) concentrations, on endogenous collagenolytic activity of etched dentin, adhesive–dentin (A/D) interfacial formation, and bond strength over time. Three PA concentrations (5%, 10%, and 20%) were combined with 2% GSE (5PA/GSE, 10PA/GSE, and 20PA/GSE) and compared to a control (CT) group using 32% PA gel (3M Universal Scotchbond etchant). Seventy-four caries-free human third molars were sectioned to expose dentin surfaces, which were etched and analyzed. In situ zymography with confocal laser microscopy was used to assess endogenous collagenolytic activity in etched dentin specimens. For A/D interfacial morphology and bond strength, etched dentin was bonded with Adper Single Bond Plus adhesive (3M ESPE) and composite buildup. The interfacial morphology of A/D specimens was evaluated using either Goldner’s trichrome staining under light microscopy after microtomy sectioning or scanning electron microscopy. A/D specimens were stored in either TESCA buffer or collagenase solution and tested immediately (IM) or at multiple time points over one year using the microtensile bond strength (μTBS) test. Data were analyzed by one- or three-way ANOVA followed by Games–Howell or Tukey’s tests (α = 0.05). GSE-modified etchants significantly reduced endogenous collagenolytic activity (p < 0.05). Although GSE-modified etchants resulted in thinner A/D interfaces, the bond strength remained unaffected (p > 0.05). Bond strength stability was prolonged up to one year with 5PA/GSE and 10PA/GSE (p < 0.001), while CT or 20PA/GSE showed significant degradation by 17 weeks (p < 0.01). Storage in the more aggressive collagenase solution did not further reduce the bond strength compared to TESCA buffer (p = 0.966). Acid etching with GSE-modified etchants effectively inhibits endogenous MMP-mediated collagenolytic activity. At 5% and 10% PA, this approach enhances the stability of the A/D bond strength, offering a promising modification for dentin bonding protocols. Full article

In order to improve the utilization efficiency of corn seeds and meet the demand of single-seed seeding technology in agriculture, this study was conducted to explore the effect of freezing damage detection on the endosperm and embryo sides of single corn seeds, based on hyperspectral imaging combined with a feature fusion algorithm and a machine learning method. First, hyperspectral image data of the endosperm and embryo sides of three freezing damage categories of corn seeds were collected, and the average spectra of the endosperm part and embryo part were obtained by threshold segmentation. Then, the spectral data were preprocessed (none, SNV, and 5-3 smoothing), and the feature wavelengths were extracted using the feature wavelength extraction algorithm (SPA and 2DCOS). The modeling accuracy results based on the hyperspectral data of the endosperm and embryo sides at the full waveband and feature wavelength (including feature wavelength fusion) were compared and analyzed. In the endosperm side’s freezing damage identification, the SNV+SVM model obtained the highest accuracies of 92.9% and 90.0% with the training set and testing set, based on the full-waveband data. The SNV+SPA-2DCOS+SVM model, based on the feature wavelengths, obtained the highest accuracies of 92.9% and 91.2% with the training set and testing set, respectively. In terms of the embryo side’s freezing damage identification, the results on the embryo side were better than those on the endosperm side. The 5-3 smoothing+LDA model, based on the full-waveband data, achieved the highest accuracy results of 97.7% and 95.9% with the training and testing sets. In the meantime, the none+SPA-2DCOS+LDA model, based on the feature wavelengths, achieved the same highest accuracy results with the training and testing sets. When the fusion algorithm consisting of SPA and 2D-COS was used, the model’s performance on the endosperm side was better than that of the full-waveband analysis with only 19 feature wavelengths, while the recognition effect on embryo side could be achieved with only 15 feature wavelengths. These results provide a theoretical basis for constructing a multi-spectral detection system for the rapid and nondestructive identification of frozen corn seeds. Full article

In this study, a new edible gel of Perilla essential oil (PE)/grape seed extract (GSE)–chitosan/gelatin was prepared, and it was applied to the preservation of silver carp. By establishing a fuzzy mathematical model, using a single-factor experiment and Box–Behnken response surface optimization combined with matlab analysis, the optimum preparation conditions of composite gel films were determined: the addition of PE (p < 0.01) was 6.91 μL/mL, the addition of GSE (p < 0.05) was 0.45 mg/mL, and the addition of gelatin (p > 0.05) was 1.63%. Under these conditions, the composite gel films exhibited an excellent water vapor barrier and mechanical properties. Using Fourier-transform infrared spectroscopy (FTIR) analysis, it was found that the addition of PE enhanced or weakened the absorption peaks, indicating the molecular interaction between PE and the substrate. Scanning electron microscopy (SEM) observed that the surfaces of the composite gel films with added PE were smooth, but there were a few pores in the cross-section. X-ray diffraction (XRD) analysis showed that PE had good compatibility with other components. The fresh-keeping experiment showed that the composite gel films could significantly prolong the fresh-keeping period of grass carp. After 10 days of storage at 4 °C, compared with the blank group (without plastic wrap) and the control group (with composite gel film, no PE added), the experimental group (with composite gel films, PE added) showed better fresh-keeping effect in terms of sensory score, moisture content, pH value, TBARS value, and TVB-N value (p < 0.05). Correlation analysis further confirmed the positive effects of composite gel films on water content, pH value, TVB-N, and other quality indexes of silver carp, indicating that the composite gel films will have broad application prospects in the food preservation field. This study provides an innovative basis and theoretical basis for the development and application of natural polysaccharide/protein composite edible film, which is helpful to promote the development of green food-packaging materials. Full article

With the advancement of modern agricultural technology, precision seeding has emerged as a critical approach to enhancing the crop yield and quality. Consequently, a garlic seeder insertion mechanism was developed to improve the accuracy and efficiency of garlic seeding. The single-seed extraction mechanism and the adjustment mechanism for the garlic clove direction were designed based on the appearance dimensions of garlic cloves, enabling precise single-seed selection and orientation. A kinematic model of the insertion planting process was established, with key parameters meticulously described and analyzed, providing theoretical support for determining optimal insertion parameters. A timing sequential control method was adopted to accurately control the periodic motion of the insertion planting mechanism. A speed detection device was utilized to monitor the travel speed of the crawler-type chassis and a rotational speed controller was developed to accurately regulate the rotational speed of the insertion mechanism, ensuring uniform planting distances. Field trials demonstrated that when the preset planting distance was set at 150 mm and sowing operations were conducted at speeds of 0.10 m/s, 0.15 m/s, and 0.20 m/s, the average sowing spacing values were 148 mm, 149 mm, and 151 mm, respectively, the maximum sowing spacing error and root mean square (RMS) error were 30 mm and 7 mm, with an average error of less than 10 mm, and the maximum coefficient of variation was 0.046. The upright rate exceeded 85%, and the missing seeding rate was below 5%. The above results indicated that the designed garlic planting machine insertion mechanism and control method conform to the agronomic requirements for garlic sowing operations. Full article

Root-lesion nematodes (Pratylenchus spp.) reduce the yield and quality of cereal crops in Australia. Eleven of the ~90 species characterised are present in Australia, with those determined as economic pests of broadacre agriculture costing an estimated AUD 250 million annually. Two species, P. curvicauda and P. quasitereoides, recently re-described, were isolated from fields located in the grainbelt of Western Australia, but little is known about their distribution in the region surveyed in this study. To investigate this and possible co-infestations with other Pratylenchus spp., we surveyed seven commercial wheat, barley, and oat farms near Katanning, Cancanning, Kenmare, Duranillin, Darkan, and a barley seed-bulk nursery near Manjimup, all in the southwest grainbelt of Western Australia. Morphological and molecular characterisation of Pratylenchus spp. extracted from soil and plant roots indicated all fields surveyed were infested. Both P. quasitereoides and P. curvicauda were present as single or mixed populations with P. penetrans and/or P. neglectus, although they were not found in the same field. Analyses of the D2–D3 sequences of the identified nematodes indicated that the species found in Australia were distinct, particularly P. quasitereoides and P. curvicauda. This work suggests P. curvicauda is likely to be present more widely in the WA grainbelt. Expanding molecular diagnostic testing for Pratylenchus species in the region to account for both nematodes is urgently needed so effective management can be implemented. Full article

The endophytic strain Amfr20 was isolated from roots of the olive tree var. Amfissa. Based on core-genome phylogenomic analyses, it was classified as Bacillus velezensis. The isolate showed positive results in numerous plant growth promoting traits, as well as in abiotic stress tolerance and in colonization related traits in vitro. Furthermore, the strain exhibited antifungal activity in vitro through diffusible and volatile compounds. Whole genome analysis revealed that the strain possesses large and various arsenals of secondary metabolite biosynthetic gene clusters involved in the bioagent’s functional properties, including plant growth promotion, colonization, and plant defense elicitation, as well as having the genomic potential for abiotic stress mediation. Based on TLC-bioautography, the ethyl acetate extracts of secreted agar-diffusible compounds from Amfr20 through single and dual cultures were found to be bioactive independently of the fungal pathogen’s interaction. The bacterial endophyte also proved efficient in suppressing the severity of anthracnose olive rot and gray mold post-harvest diseases on olive fruits and table grape berries, respectively. Lastly, Amfr20 beneficially affected Arabidopsis thaliana growth under normal and saline conditions, while boosting the plant development of Solanum lycopersicum through seed biopriming and root irrigation methods. The results of this multilevel study indicate that the novel endophyte Amfr20 Bacillus velezensis is a promising bioagent that should be exploited in the future as an ecological biopesticide and/or biostimulant. Full article