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Face detection is an important task in the field of computer vision and is widely applied in various applications. However, in open and complex scenes with dense faces, occlusions, and image degradation, small face detection still faces significant challenges due to the extremely small target scale, difficult localization, and severe background interference. To address these issues, this paper proposes a small face detector for open complex scenes, SFE-DETR, which aims to simultaneously improve detection accuracy and computational efficiency. The backbone network of the model adopts an inverted residual shift convolution and dilated reparameterization structure, which enhances shallow features and enables deep feature self-adaptation, thereby better preserving small-scale information and reducing the number of parameters. Additionally, a multi-head multi-scale self-attention mechanism is introduced to fuse multi-scale convolutional features with channel-wise weighting, capturing fine-grained facial features while suppressing background noise. Moreover, a redesigned SFE-FPN introduces high-resolution layers and incorporates a novel feature fusion module consisting of local, large-scale, and global branches, efficiently aggregating multi-level features and significantly improving small face detection performance. Experimental results on two challenging small face detection datasets show that SFE-DETR reduces parameters by 28.1% compared to the original RT-DETR-R18 model, achieving a mAP50 of 94.7% and AP-s of 42.1% on the SCUT-HEAD dataset, and a mAP50 of 86.3% on the WIDER FACE (Hard) subset. These results demonstrate that SFE-DETR achieves optimal detection performance among models of the same scale while maintaining efficiency.

• Fruit ripening is governed by a complex regulatory network. Reversible histone methylation and demethylation regulate chromatin structure and gene expression. However, little is known about the involvement of histone demethylases in regulating fruit ripening. • Here, we found that the tomato (Solanum lycopersicum) SlJMJ6 encodes a histone lysine demethylase that specifically demethylates H3K27 methylation. Overexpression of SlJMJ6 accelerates tomato fruit ripening, which is associated with the upregulated expression of a large number of ripening-related genes. • Integrated analysis of RNA-seq and chromatin immunoprecipitation followed by sequencing identified 32 genes directly targeted by SlJMJ6 and transcriptionally upregulated with decreased H3K27m3 in SlJMJ6-overexpressed fruit. Numerous SlJMJ6-regulated genes are involved in transcription regulation, ethylene biosynthesis, cell wall degradation and hormone signaling. Eleven ripening-related genes including RIPENING INHIBITOR (RIN), 1-aminocyclopropane 1-carboxylate synthase-4 (ACS4), 1-aminocyclopropane-1-carboxylate oxidase 1 (ACO1), pectate lyase (PL) and beta-galactosidase 4 (TBG4), and a DNA demethylase DML2, were confirmed to be regulated directly by SlJMJ6 through removing H3K27me3. • Our results demonstrate that SlJMJ6 is a ripening-prompting H3K27me3 demethylase that activates the expression of the ripening-related genes by modulating H3K27me3, thereby facilitating tomato fruit ripening. Our work also reveals a novel link between histone demethylation and DNA demethylation in regulating fruit ripening. To our knowledge, this is the first report of the involvement of a histone lysine demethylase in the regulation of fruit ripening.

Background Banana anthracnose, caused by Colletotrichum musae , is one of the most severe postharvest diseases in banana. Melatonin is widely known for its role in enhancing plant stress tolerance. However, little is known about the control of melatonin on anthracnose in postharvest banana fruit. Results In this study, exogenous melatonin treatment could significantly reduce the incidence of anthracnose in ripe yellow banana fruit and delay fruit senescence. However, melatonin treatment did not affect the growth of Colletotrichum musae in vitro. Transcriptomic analysis of banana peel showed that 339 genes were up-regulated and 241 were down-regulated in the peel after melatonin treatment, compared with the control. Based on GO terms and KEGG pathway, these up-regulated genes were mainly categorized into signal transduction, cell wall formation, secondary metabolism, volatile compounds synthesis and response to stress, which might be related to the anti-anthracnose of banana fruit induced by melatonin treatment. This view was also supported by the increase of volatile compounds, cell wall components and IAA content in the melatonin-treated fruit peel via the metabolomic analysis. After melatonin treatment, auxin, ethylene and mitogen-activated protein kinase (MAPK) signaling pathways were enhanced, which might be involved in the enhanced fruit resistance by regulating physiological characteristics, disease-resistant proteins and metabolites. Conclusions Our results provide a better understanding of the molecular processes in melatonin treatment delaying banana fruit senescence and anthracnose incidence.

Fresh fruits have good flavor and high nutritional value, but in the postharvest stage they will age and decay rapidly, so we need to find green postharvest fruit preservatives. And natural organic acids are promising natural fruit preservatives due to their safety and effectiveness. The present work reviews recent applications of natural organic acids in postharvest fruit quality management and discussed its potential biochemical mechanisms. This work indicates that numerous natural organic acids are effective postharvest fruit preservatives, such as oxalic acid, salicylic acid, citric acid, ascorbic acid, phenolic acid and terpenic acid. Natural organic acid treatments can improve postharvest fruit quality, as reflected by delaying senescence, alleviating chilling injury, controlling disease, and inhibiting browning. And natural organic acid can have multiple benefits on postharvest fruit. Natural organic acids also play a variety of roles in postharvest fruit disease control. In addition, chemical modification and cotreatment of natural organic acids can be performed to improve the efficiency of postharvest fruit preservation applications. The work provides an important reference for postharvest fruit quality management and the development of natural OAs fruit preservatives.

Density functional theory (DFT) calculations at the M06-2X-D3/6-311++G(2df,2pd) level elucidate the mechanism and selectivity origins in the NHC-catalyzed divergent synthesis of spirocyclopentane oxindoles from isatin-derived enals and N-sulfonyl ketimines. The Michael addition constitutes the regio- and stereoselectivity-determining step, where Parr function analysis demonstrates that nucleophile/electrophile electrophilicity governs regioselectivity, while distortion/interaction and non-covalent interaction analyses reveal stereoselectivity is controlled by distortion and weak interactions. K3PO4 facilitates Breslow intermediate formation and proton transfer toward the β-lactam-fused spirocyclopentane oxindole, whereas N,N-diisopropylethylamine (DIPEA) promotes these processes for the spirocyclopentane oxindole bearing an enaminone moiety. Catalyst roles are also further delineated.

Forest fires pose a significant threat to human life and property. The early detection of smoke and flames can significantly reduce the damage caused by forest fires to human society. This article presents an SFGI-YOLO model based on YOLO11n, which demonstrates outstanding advantages in detecting forest fires and smoke, particularly in the context of early fire monitoring. The main principles of the algorithm include the following: first, a small-object detection head P2 is added to better extract shallow feature information; a Feature Enhancement Module (FEM) is utilized to increase feature richness, expand the receptive field, and enhance detection capabilities for small objects across multiple scales; the lightweight GhostConv is employed to significantly reduce computational costs and decrease the number of parameters; and Inception DWConv is combined with a C3k2 module to utilize multiple parallel branches, thereby enlarging the receptive field. The improved algorithm achieved a mean Average Precision (mAP50) of 95.4% on a custom forest fire dataset, surpassing the YOLO11n model by 1.8%. This model offers more accurate detection of forest fires, reducing both missed detections and false positives and thereby meeting the high precision and real-time detection requirements in forest fire monitoring.

To address the challenges of poor model generalization and suboptimal recognition accuracy stemming from limited and imbalanced sample sizes in tomato leaf disease identification, this study proposes a novel recognition strategy. This approach synergistically combines an enhanced image augmentation method based on generative adversarial networks with a lightweight deep learning model. Initially, an Atrous Spatial Pyramid Pooling (ASPP) module is integrated into the CycleGAN framework. This integration enhances the generator’s capacity to model multi-scale pathological lesion features, thereby significantly improving the diversity and realism of synthesized images. Subsequently, the Convolutional Block Attention Module (CBAM), incorporating both channel and spatial attention mechanisms, is embedded into the MobileNetV4 architecture. This enhancement boosts the model’s ability to focus on critical disease regions. Experimental results demonstrate that the proposed ASPP-CycleGAN significantly outperforms the original CycleGAN across multiple disease image generation tasks. Furthermore, the developed CBAM-MobileNetV4 model achieves a remarkable average recognition accuracy exceeding 97% for common tomato diseases, including early blight, late blight, and mosaic disease, representing a 1.86% improvement over the baseline MobileNetV4. The findings indicate that the proposed method offers exceptional data augmentation capabilities and classification performance under small-sample learning conditions, providing an effective technical foundation for the intelligent identification and control of tomato leaf diseases.

Background Temperature stress is a major environmental factor affecting not only plant growth and development, but also fruit postharvest life and quality. MicroRNAs (miRNAs) are a class of non-coding small RNAs that play important roles in various biological processes. Harvested banana fruit can exhibit distinct symptoms in response to different temperature stresses, but the underlying miRNA-mediated regulatory mechanisms remained unknown. Results Here, we profiled temperature-responsive miRNAs in banana, using deep sequencing and computational and molecular analyses. In total 113 known miRNAs and 26 novel banana-specific miRNAs were identified. Of these miRNAs, 42 miRNAs were expressed differentially under cold and heat stresses. Degradome sequencing identified 60 target genes regulated by known miRNAs and half of these targets were regulated by 15 temperature-responsive miRNAs. The correlative expression patterns between several miRNAs and their target genes were further validated via qRT-PCR. Our data showed that miR535 and miR156 families may derive from a common ancestor during evolution and jointly play a role in fine-tuning SPL gene expression in banana. We also identified the miRNA-triggered phased secondary siRNAs in banana and found miR393- TIR1 / AFB phasiRNA production displaying cold stress-specific enrichment. Conclusions Our results provide a foundation for understanding the miRNA-dependent temperature stress response in banana. The characterized correlations between miRNAs and their response to temperature stress could serve as markers in the breeding programs or tools for improving temperature tolerance of banana.

Osteoarthritis (OA) is featured as cartilage loss, joint pain and loss of labor, which the inflammatory reaction may play critical roles. Ononin is an isoflavone isolating from medicinal plants and has anti-inflammatory effects. Our study investigated the anti-inflammation response of ononin on OA. Anterior cruciate ligament transection (ACLT)-induced OA operation was used to establish research model, then treated with ononin for 8 weeks. The condition of joint injury was assessed using pathological staining. The concentration of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and interleukin-6 (IL-6) in serum were measured by Elisa kit. The expression of collagen II and matrix metalloproteinase 13 (MMP-13) proteins to assess cartilage metabolism level by immunohistochemistry and Western blot. We detected the expression of proteins involved in the MAPK and NF-κB signaling pathways. Finally, we used molecular docking to assess the affinity of ononin for the target proteins ERK1/2, JNK1/2, p38 and p65. Our results confirmed that ononin ameliorated cartilage impairment through histopathological analysis by improving the morphological structures and cartilage tidal lines and decreasing Osteoarthritis Research Society International (OARSI) scores in OA rats. Moreover, ononin inhibited the secretion of above factors in OA rats. Furthermore, ononin has been shown to improve cartilage content levels in OA rats. In addition, ononin inhibited the reactivity of MAPK and NF-κB pathways in OA rats. And molecular docking indicated the ligand molecules could stably bind to the proteins of above receptors. Our results demonstrated that ononin may ameliorate cartilage damage and inflammatory response in OA rats by downgrading MAPK and NF-κB pathways, thus identifying ononin as a potential novel drug to treat OA.

Astragalus membranaceus is a valuable medicinal plant species widely distributed in Asia. Its root is the main medicinal tissue rich in methoxylated flavonoids. Origin can highly influence the chemical composition and bioactivity. To characterize the principal chemicals influenced by origin and provide more information about their antioxidant profile, the extracts of A. membranaceus roots from four origins were analysed by UHPLC-MS/MS. Thirty-four flavonoids, including thirteen methoxylated flavonoids, fifteen flavonoid glycosides and six flavonols, were identified. By principal component analysis, eighteen identified compounds were considered to be principal compounds. They could be used to differentiate A. membranaceus from Shanxi, Inner Mongolia, Heilongjiang and Gansu. The antioxidant activity was analysed by ORAC assay, DPPH radical scavenging activity assay and cell antioxidant activity assay. ‘Inner Mongolia’ extract showed the highest antioxidant activity. These results were helpful to understand how origin influenced the quality of A. membranaceus.