Search Results (1,069)

Anthocyanins, a subclass of flavonoid pigments, impart vivid red, purple, and blue coloration to horticultural plants, playing essential roles in ornamental enhancement, stress resistance, and pollinator attraction. Recent studies have identified B-box (BBX) proteins as a critical class of transcription factors (TFs) involved in anthocyanin biosynthesis. Despite these advances, comprehensive reviews systematically addressing BBX proteins are urgently needed, especially given the complexity and diversity of their roles in regulating anthocyanin production. In this paper, we provide an in-depth overview of the fundamental structures, biological functions, and classification of BBX TFs, along with a detailed description of anthocyanin biosynthetic pathways and bioactivities. Furthermore, we emphasize the diverse molecular mechanisms through which BBX TFs regulate anthocyanin accumulation, including direct activation or repression of target genes, indirect modulation via interacting protein complexes, and co-regulation with other transcriptional regulators. Additionally, we summarize the known upstream regulatory signals and downstream target genes of BBX TFs, highlighting their significance in shaping anthocyanin biosynthesis pathways. Understanding these regulatory networks mediated by BBX proteins will not only advance fundamental horticultural science but also provide valuable insights for enhancing the aesthetic quality, nutritional benefits, and stress adaptability of horticultural crops. Full article

Developing innovative, low-cost halochromic materials for diagnosing microbial contamination in wounds and burns can effectively facilitate tissue regeneration. Here, we combine the pH-sensing capability of highly colorful red cabbage anthocyanins (RCAs) with their healing potential within a unique cellulose polymer film that mimics the skin matrix. Biological activities of RCA extract in bacterial cellulose (BC) showed no cytotoxicity and skin-sensitizing potential to human cells at concentrations of RCAs similar to those released from BC/RCA dressings (4.0–40.0 µg/mL). A decrease in cell viability and apoptosis was observed in human cancer cells with RCAs. The invisible eye detection of the early color change signal from RCAs in response to pH alteration by bacteria was recorded with a smartphone application. The incorporation of RCAs into BC polymer has altered the morphology of its matrix, resulting in a denser cellulose microfibril network. The complete coincidence of the vibrational modes detected in the absorption spectra of the cellulose/RCA composite with the modes in RCAs most likely indicates that RCAs retain their structure in the BC matrix. Affordable, sensitive halochromic BC/RCA hydrogels can be recommended for online monitoring of microbial contamination, making them accessible to patients. Full article

In this paper, we propose noncontact heart rate (HR), oxygen saturation (SpO2), and respiratory rate (RR) detection methods using a smartphone camera. HR frequency is detected through filtering after obtaining a remote PPG (rPPG) signal and its power spectral density (PSD) is detected using color difference signal amplification and the plane-orthogonal-to-the-skin method. Additionally, the SpO2 is detected using the HR frequency and the absorption ratio of the G and B color channels based on oxyhemoglobin absorption and reflectance theory. After this, the respiratory frequency is detected using the PSD of rPPG through respiratory frequency band filtering. For the image sequences recorded under various imaging conditions, the proposed method demonstrated superior HR detection accuracy compared to existing methods. The confidence intervals for HR and SpO2 detection were analyzed using Bland–Altman plots. Furthermore, the proposed RR detection method was also verified to be reliable. Full article

Fish coloration plays an important role in reproduction and camouflage, yet capturing color variation under field conditions remains challenging. We present a standardized, semi-automated protocol for measuring body coloration in the popular model fish threespine stickleback (Gasterosteus aculeatus). Individuals are photographed in a controlled light box within minutes of capture, and color is sampled from eight anatomically defined standard sites in human-perception-based CIELAB space. Analyses combine univariate color metrics, multivariate statistics, and the ΔE* perceptual difference index to detect subtle shifts in hue and brightness. Validation on pre-spawning fish shows the method reliably distinguishes males and females well before full breeding colors develop. Although it currently omits ultraviolet signals and fine-scale patterning, the approach scales efficiently to large sample sizes and varying lighting conditions, making it well suited for population-level surveys of camouflage dynamics, sexual dimorphism, and environmental influences on coloration in sticklebacks. Full article

One of the persistent challenges in multispectral image analysis is the interference caused by dense cloud cover and its resulting shadows, which can significantly obscure surface features. This becomes especially problematic when attempting to monitor surface changes over time using satellite imagery, such as from Landsat-8. In this study, rather than simply masking visual obstructions, we aimed to investigate the role and influence of clouds within the spectral data itself. To achieve this, we employed Independent Component Analysis (ICA), a statistical method capable of decomposing mixed signals into independent source components. By applying ICA to selected Landsat-8 bands and analyzing each component individually, we assessed the extent to which cloud signatures are entangled with surface data. This process revealed that clouds contribute to multiple ICA components simultaneously, indicating their broad spectral influence. With this influence on multiple wavebands, we managed to configure a set of components that could perfectly delineate the extent and location of clouds. Moreover, because Landsat-8 lacks cloud-penetrating wavebands, such as those in the microwave range (e.g., SAR), the surface information beneath dense cloud cover is not captured at all, making it physically impossible for ICA to recover what is not sensed in the first place. Despite these limitations, ICA proved effective in isolating and delineating cloud structures, allowing us to selectively suppress them in reconstructed images. Additionally, the technique successfully highlighted features such as water bodies, vegetation, and color-based land cover differences. These findings suggest that while ICA is a powerful tool for signal separation and cloud-related artifact suppression, its performance is ultimately constrained by the spectral and spatial properties of the input data. Future improvements could be realized by integrating data from complementary sensors—especially those operating in cloud-penetrating wavelengths—or by using higher spectral resolution imagery with narrower bands. Full article

To address the challenges of unstable vibration signals, indistinct fault features, and difficulties in feature extraction during rolling bearing operation, this paper presents a novel fault diagnosis method based on the fusion of PSR-CRP and DenseNet. The Phase Space Reconstruction (PSR) method transforms one-dimensional bearing vibration data into a three-dimensional space. Euclidean distances between phase points are calculated and mapped into a Color Recurrence Plot (CRP) to represent the bearings’ operational state. This approach effectively reduces feature extraction ambiguity compared to RP, GAF, and MTF methods. Fault features are extracted and classified using DenseNet’s densely connected topology. Compared with CNN and ViT models, DenseNet improves diagnostic accuracy by reusing limited features across multiple dimensions. The training set accuracy was 99.82% and 99.90%, while the test set accuracy is 97.03% and 95.08% for the CWRU and JNU datasets under five-fold cross-validation; F1 scores were 0.9739 and 0.9537, respectively. This method achieves highly accurate diagnosis under conditions of non-smooth signals and inconspicuous fault characteristics and is applicable to fault diagnosis scenarios for precision components in aerospace, military systems, robotics, and related fields. Full article

Deep learning-based super-resolution (SR) frameworks are widely used in remote sensing applications. However, existing SR models still face limitations, particularly in recovering contours, fine features, and textures, as well as in effectively integrating channel information. To address these challenges, this study introduces a novel residual model named OARN (Optimized Attention Residual Network) specifically designed to enhance the visual quality of low-resolution images. The network operates on the Y channel of the YCbCr color space and integrates LKA (Large Kernel Attention) and OCM (Optimized Convolutional Module) blocks. These components can restore large-scale spatial relationships and refine textures and contours, improving feature reconstruction without significantly increasing computational complexity. The performance of OARN was evaluated using satellite images from WorldView-2, GaoFen-2, and Microsoft Virtual Earth. Evaluation was conducted using objective quality metrics, such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Edge Preservation Index (EPI), and Perceptual Image Patch Similarity (LPIPS), demonstrating superior results compared to state-of-the-art methods in both objective measurements and subjective visual perception. Moreover, OARN achieves this performance while maintaining computational efficiency, offering a balanced trade-off between processing time and reconstruction quality. Full article

Underwater image enhancement (UIE) technology plays a vital role in marine resource exploration, environmental monitoring, and underwater archaeology. However, due to the absorption and scattering of light in underwater environments, images often suffer from blurred details, color distortion, and low contrast, which seriously affect the usability of underwater images. To address the above limitations, a lightweight transformer-based model (LITM) is proposed for improving underwater degraded images. Firstly, our proposed method utilizes a lightweight RGB transformer enhancer (LRTE) that uses efficient channel attention blocks to capture local detail features in the RGB domain. Subsequently, a lightweight HSV transformer encoder (LHTE) is utilized to extract global brightness, color, and saturation from the hue–saturation–value (HSV) domain. Finally, we propose a multi-modal integration block (MMIB) to effectively fuse enhanced information from the RGB and HSV pathways, as well as the input image. Our proposed LITM method significantly outperforms state-of-the-art methods, achieving a peak signal-to-noise ratio (PSNR) of 26.70 and a structural similarity index (SSIM) of 0.9405 on the LSUI dataset. Furthermore, the designed method also exhibits good generality and adaptability on unpaired datasets. Full article

Single image super-resolution is the inverse problem of reconstructing a high-resolution image from its low-resolution counterpart. Although recent Transformer-based architectures leverage global context integration to improve reconstruction quality, they often overlook frequency-specific characteristics, resulting in the loss of high-frequency information. To address this limitation, we propose the Dual Frequency Adaptive Network (DFAN). DFAN first decomposes the input into low- and high-frequency components via Stationary Wavelet Transform. In the low-frequency branch, Swin Transformer layers restore global structures and color consistency. In contrast, the high-frequency branch features a dedicated module that combines Directional Convolution with Residual Dense Blocks, precisely reinforcing edges and textures. A frequency fusion module then adaptively merges these complementary features using depthwise and pointwise convolutions, achieving a balanced reconstruction. During training, we introduce a frequency-aware multi-term loss alongside the standard pixel-wise loss to explicitly encourage high-frequency preservation. Extensive experiments on the Set5, Set14, BSD100, Urban100, and Manga109 benchmarks show that DFAN achieves up to +0.64 dBpeak signal-to-noise ratio, +0.01 structural similarity index measure, and −0.01learned perceptual image patch similarity over the strongest frequency-domain baselines, while also delivering visibly sharper textures and cleaner edges. By unifying spatial and frequency-domain advantages, DFAN effectively mitigates high-frequency degradation and enhances SISR performance. Full article

B-box (BBX) transcription factors are critical regulators of light-mediated anthocyanin biosynthesis, influencing peel coloration in plants. To explore their role in red mango cultivars, we identified 32 BBX genes (MiBBX1–MiBBX32) in the mango (Mangifera indica L.) genome using a genome-wide analysis. Phylogenetic and structural analyses classified these genes into five subfamilies based on conserved domains. A collinearity analysis revealed segmental duplication as the primary mechanism of MiBBX gene family expansion, with purifying selection shaping their evolution. A promoter analysis identified numerous light- and hormone-responsive cis-elements, indicating regulatory roles in the light and hormonal signaling pathways. Expression profiling in the ‘Sensation’ cultivar revealed organ-specific patterns, with several MiBBX genes showing higher expression in the peel than in the flesh. Many of these genes also consistently exhibited elevated expression in the peel of red-skinned cultivars (‘Sensation’ and ‘Guifei’) compared to yellow and green cultivars, suggesting their role in red peel pigmentation. Furthermore, postharvest light treatment of ‘Hongmang No. 6’ fruit significantly upregulated multiple MiBBX genes, suggesting their involvement in light-induced anthocyanin accumulation in red mango peel. These findings provide valuable insights into the molecular mechanisms governing light-regulated peel coloration in mango and establish a foundation for functional studies of MiBBX genes in fruit pigmentation. Full article

Anthocyanins are important phenolic compounds in grape skins, affecting the color, oxidation resistance, and aging ability of red wine. In recent years, global warming has had a negative effect on anthocyanin biosynthesis in grape berries. Ethylene serves as a crucial phytohormone regulating the development and ripening processes of fruit; however, the specific molecular mechanism and the regulatory network between ethylene signaling and the anthocyanin biosynthesis pathway remain incompletely understood. In this study, 400 mg/L ethephon (ETH) solution was sprayed onto the surface of grape berries at the lag phase (EL-34), and the changes in anthocyanin-related genes and metabolites were explored through transcriptomic and metabolomic analysis. The results showed that ETH treatment increased Brix and pH in mature berries. In total, 35 individual anthocyanins were detected, in which 21 individual anthocyanins were enhanced by ETH treatment. However, the anthocyanin profile was not affected by exogenous ethylene. Transcriptomics analysis showed that there were a total of 825 and 1399 differentially expressed genes (DEGs) 12 h and 24 h after treatment. Moreover, key structural genes in the anthocyanin synthesis pathway were strongly induced, including VvPAL, VvCHS, VvF3H, VvF3′5′H, VvDFR and VvUFGT. At the maturity stage (EL-38), the expression levels of these genes were still higher in EHT-treated berries than in the control. ETH treatment also influenced the expression of genes related to hormone biosynthesis and signal transduction. The ethylene biosynthesis gene (VvACO), ethylene receptor genes (VvETR2, VvERS1 and VvEIN4), ABA biosynthesis gene (VvNCED2), and ABA receptor gene (VvPYL4) were up-regulated by ETH treatment, while the auxin biosynthesis gene (VvTAA3) and seven genes of the auxin-responsive protein were inhibited by exogenous ethylene. Meanwhile, ETH treatment promoted the expression of the sugar transporter gene (VvEDL16) and two sucrose synthase genes (VvSUS2 and VvSUS6). In EHT-treated berries, 19 MYB and 23 ERF genes were expressed differently compared with the control (p < 0.05). This study provides the theoretical foundation and technical support for the regulation of anthocyanin synthesis in non-climacteric fruit. Full article

The mismatch between the rapid expansion of breeding scale and outdated techniques has hindered the development of the sea cucumber (A. japonicus) industry. Our previous work revealed that ecological seedling breeding can produce red-colored A. japonicus, a phenotype not observed in traditional artificial breeding, where individuals are typically green. To investigate the molecular and genetic basis of this novel red coloration, we compared the growth conditions of red sea cucumbers and green sea cucumbers, as well as the differences in the pigment composition, gene expression and metabolites of their body walls. Red individuals showed higher body length and weight, and elevated levels of astaxanthin, lutein, canthaxanthin, and β-carotene in the body wall. Transcriptomic and metabolomic analyses identified differentially expressed genes and metabolites associated with pigmentation. In particular, FMO2 and WDR18, involved in the cytochrome P450 drug metabolism pathway, were significantly upregulated in red individuals and are known to play roles in pigment biosynthesis and light signal perception. Key metabolites such as astaxanthin and fucoxanthin were implicated in body color formation. Moreover, genes in the arachidonic acid metabolism pathway were highly expressed, suggesting that dietary factors may contribute to pigment synthesis and accumulation. These findings provide novel insights into the mechanisms underlying body color variation in A. japonicus and offer potential for improved breeding strategies. Full article

This study investigates how lighting conditions influence emotional and neural responses in a standardized, simulated museum environment. A multimodal evaluation framework combining subjective and objective measures was used. Thirty-two international students assessed their viewing experiences using 14 semantic differential descriptors, while real-time EEG signals were recorded via the EMOTIV EPOC X device. Spectral energy analyses of the α, β, and θ frequency bands were conducted, and a θα energy ratio combined with γ coefficients was used to model attention and comfort levels. The results indicated that high illuminance (300 lx) and high correlated color temperature (4000 K) significantly enhanced both attention and comfort. Art majors showed higher attention levels than engineering majors during short-term viewing. Among four regression models, the backpropagation (BP) neural network achieved the highest predictive accuracy (R² = 88.65%). These findings provide empirical support for designing culturally inclusive museum lighting and offer neuroscience-informed strategies for promoting the global dissemination of traditional Chinese culture, further supported by retrospective interview insights. Full article

Using the rolling-shutter mechanism to enhance the signal sampling frequency of Optical Camera Communication (OCC) is a low-cost solution, but its periodic sampling interruptions may cause signal loss, and existing solutions often compromise communication rate and distance. To address this, this paper proposes NoGap-RS, a no-gap sampling method, theoretically addressing the signal loss issue at longer distances from a perspective of CMOS exposure timing. Experiments show that NoGap-OOK, a OCC system based on NoGap-RS and On-Off key modulation, can achieve a communication rate of 6.41 Kbps at a distance of 3 m, with a BER of ${10}^{-5}$ under indoor artificial light. This paper further proposes TickRS, a time slot division method, innovatively addressing the overlap that occurs during consecutive-row exposures to further enhance communication rate. Experiments show that TickRS-CSK, a OCC system based on TickRS and Color-Shift Key, can achieve a communication rate of 20.09 Kbps at a distance of 3.6 m, with a BER of ${10}^{-2}$ under indoor natural light. Full article

When a CMOS (Complementary Metal–Oxide–Semiconductor) imaging system operates at a high frame rate or a high line rate, the exposure time of the imaging system is limited, and the acquired image data will be dark, with a low signal-to-noise ratio and unsatisfactory sharpness. Therefore, in order to improve the visibility and signal-to-noise ratio of remote sensing images based on CMOS imaging systems, this paper proposes a low-light remote sensing image enhancement method and a corresponding ZYNQ (Zynq-7000 All Programmable SoC) design scheme called the BGIR (Bilateral-Guided Image Restoration) algorithm, which uses an improved multi-scale Retinex algorithm in the HSV (hue–saturation–value) color space. First, the RGB image is used to separate the original image’s H, S, and V components. Then, the V component is processed using the improved algorithm based on bilateral filtering. The image is then adjusted using the gamma correction algorithm to make preliminary adjustments to the brightness and contrast of the whole image, and the S component is processed using segmented linear enhancement to obtain the base layer. The algorithm is also deployed to ZYNQ using ARM + FPGA software synergy, reasonably allocating each algorithm module and accelerating the algorithm by using a lookup table and constructing a pipeline. The experimental results show that the proposed method improves processing speed by nearly 30 times while maintaining the recovery effect, which has the advantages of fast processing speed, miniaturization, embeddability, and portability. Following the end-to-end deployment, the processing speeds for resolutions of 640 × 480 and 1280 × 720 are shown to reach 80 fps and 30 fps, respectively, thereby satisfying the performance requirements of the imaging system. Full article