Search Results (26,860)

This study examines the physical and mechanical properties of pedunculate oak (Quercus robur L.) wood samples taken from historical trabaccolo ship Carmen during restoration. The research is based on a methodological approach typical of conservation–restoration practice, in which only a limited number of samples can be taken to preserve the authenticity and integrity of the original material. Two groups of samples were analyzed visually: preserved (bright) wood and wood showing cross-sectional discoloration (dark). Physical properties (color, moisture content, density, porosity and swelling) and mechanical properties (compressive strength, bending strength and modulus of elasticity) were determined according to relevant ISO standards and chemical changes in the wood structure (FT-IR). FT-IR analysis revealed progressive degradation of hemicelluloses and oxidative modification of lignin, which was particularly significant in dark wood samples. The results of tests of physical properties indicate that dark samples exhibit higher moisture content (13%), lower density (about 7%) and greater porosity compared to preserved samples (bright wood). The compressive strength of the bright specimens was 38.3% higher than that of the dark specimens, suggesting reduced mechanical performance of the altered wood. The bending strength and modulus of elasticity of the preserved samples (bright wood) corresponded to literature data for recent oak wood. Full article

Light field displays offer promising autostereoscopic 3D visualization with continuous parallax, full-color reproduction, and natural depth cues. In practice, ray-tracing simulation is often employed to evaluate the effective viewing zone of light field systems. However, the actual viewing zone in conventional light field systems is significantly smaller than the simulated value, severely limited by narrow viewing angles due to crosstalk from adjacent elemental images. This study proposes an isolated microlens array (i-MLA) architecture incorporating a custom directional mesh (DM)—a 3D-printed light-blocking barrier grid with tapered pitch—to physically isolate each lenslet and completely suppress crosstalk. Combined with optimized extended coding pitch for a target viewing distance, ray-tracing simulations and experiments on a 13.3-inch 4K display with a 7 mm and 5.4 mm pitch MLA demonstrate dramatic improvement. The conventional light field system provides only a 3.4° margin, which is below the minimum angular separation required for binocular viewing, whereas the i-MLA system achieves a 7.4° margin—twice that of the conventional system. Compared with conventional systems, the i-MLA architecture does not increase overall volume; it simply replaces the glass gap with a single, simple optical element to achieve a wider viewing angle while preserving the compact form factor. Full article

A comparative chemical analysis was conducted between P. aibuhitensis of orange and green body colors, evaluating their proximate composition, fatty acid profile, amino acid profile, astaxanthin content, lipidomic profile, and other biochemical parameters. Samples were categorized by body color into two groups, each with ten biological replicates. The samples were collected from the same local polychaete farm. The results revealed that the green phenotype had significantly higher moisture content but lower crude protein, crude lipid, and ash content compared to the orange phenotype. The orange polychaete was characterized by significantly higher concentrations of 16:0 and saturated fatty acids (SFAs), whereas the green one exhibited higher contents of n-6 polyunsaturated fatty acids (n-6 PUFAs) and a higher PUFA/SFA ratio. Regarding free amino acids, the orange polychaete had significantly higher threonine content, while the green ones had significantly higher levels of valine, isoleucine, leucine, phenylalanine, glutamate, alanine, histidine and proline. Additionally, the astaxanthin content was significantly higher in the orange phenotype. The bile acid level was significantly higher in the green phenotype compared to the orange one, but no significant differences were observed in other biochemical parameters such as total protein, total cholesterol, and triglyceride content. The lipidomic analysis revealed that glycerophospholipids were the most abundant lipid class in both phenotypes, followed by glycerolipids and sphingolipids. A total of 65 differentially abundant lipid molecules were identified between the two groups. Compared to the orange polychaete, the green one had higher levels of 59 lipids (predominantly ceramides) and lower levels of six lipids, including three triglycerides, one monogalactosyldiacylglycerol, and two phosphatidylserines. In general, the orange P. aibuhitensis showed a favorable nutritional profile for aquafeed and human nutrition, whereas the green ones had potential for targeted health applications owing to its specific lipid composition. However, direct validating experiments are required. Full article

Echeveria spp. (Mexican hens and chicks) are among the most popular genera of succulents sold because they are compact and form attractive, symmetrical rosettes with brightly colored, fleshy, broad, iridescent leaves, as well as large, showy inflorescences. However, they are slow-growing, and flower induction protocols are not widely available. Therefore, the objectives of this study were (1) to determine if photoperiod and the photosynthetic daily light integral (DLI) can be manipulated to promote rapid growth and leaf expansion without excessive extension growth of several cultivars of Echeveria and (2) to establish the critical photoperiod for flower induction. Cuttings of E. spp. and hybrids ‘Apus’, ‘Canadian’, ‘Elegans Blue’, ‘Jade Point’, and ‘Topsy Turvy’ were received from a commercial breeder and grown in a greenhouse at 20 °C for 5 weeks. Photoperiods were created using a truncated 9 h short day (SD) or a SD extended to 10, 11, 13, 15, 16 h or a 4 h night-interruption (NI), using light-emitting diode (LED) lamps providing a total photon flux density of ≈2 μmol·m⁻²·s⁻¹ of red (R) + white (W) + far-red (FR) radiation. DLIs of 4.8 and 12.8 mol·m⁻²·d⁻¹ were maintained with and without shade cloth and supplemental lighting. Photoperiod and DLI interacted to influence the final height of E. ‘Canadian’, ‘Elegans Blue’, and ‘Jade Point’; plants were tallest under photoperiods > 13 h and low DLI. Similar trends were observed for growth index and average plant diameter. No clear trend was observed for leaf unfolding or leaf length across DLI or photoperiod treatments. Flower initiation of E. ‘Apus’ and ‘Jade Point’ was highest under a DLI of 12.8 mol·m⁻²·d⁻¹. Additionally, E. ‘Jade Point’ only developed inflorescences under day lengths ≤ 11 h, indicating an obligate SD response. Our results suggest that growers should maintain DLIs > 10 mol·m⁻²·d⁻¹ and SD conditions to promote flower initiation of the Echeveria cultivars tested. Such conditions would prevent excessive stem elongation and encourage flowering, increasing crop quality and marketability. Full article

Bougainvillea (Bougainvillea glabra) is a perennial woody species belonging to the Nyctaginaceae family, native to South America. It is widely recognized for its brightly colored bracts and strong adaptability, and is widely cultivated as a major ornamental plant in tropical and subtropical regions. However, QTL mapping studies on morphological traits remain limited in the genus Bougainvillea, and the genetic basis underlying its key ornamental traits is still largely unclear. In this study, an F₁ segregating population was constructed using the cultivars ‘Mrs Eva White’ and ‘Formosa’ as parents, and was used for high-density genetic map construction and quantitative trait locus analysis. Fourteen leaf and thorn-related traits were investigated, with coefficients of variation ranging from 8.16% to 64.54%. Based on specific-locus amplified fragment sequencing (SLAF-seq), a total of 1,133,206 SLAF markers were developed, among which 479,488 were polymorphic. Using the inclusive composite interval mapping (ICIM) algorithm in the GACD 1.2 software, a high-density genetic linkage map was constructed for B. glabra, consisting of 17 linkage groups and 3256 markers. The genetic map spanned 1797.64 cM, with an average marker interval of 0.55 cM. A total of 22 QTLs were detected for the measured leaf and thorn traits, including 16 major QTLs with a PVE ≥ 8%. Collectively, this study identified stable genetic loci for important morphological traits and provides a valuable theoretical foundation for marker-assisted selection and genetic improvement of ornamental traits in Bougainvillea. Full article

This paper addresses the problem of automated segmentation of plant green biomass in field crop images aimed at improving the accuracy of crop and weed identification. To construct a training dataset for neural network models, an automatic annotation algorithm is proposed, enabling the generation of polygonal object masks without human intervention. The method is based on adaptive analysis of color characteristics of plant fragments with iterative narrowing of the hue range in the HSV color space, combined with an integral quality metric that accounts for the dynamics of contour area and shape. The proposed method achieved an IoU of 93.22% and a DSC of 96.30%, demonstrating a high level of agreement between automatic and manual annotations. The generated masks are used to train segmentation models of the YOLO11-seg family. Models of different scales (n, s, m, l, x) were trained and evaluated using standard metrics, including Intersection over Union (IoU), mAP@0.5, mAP@0.5–0.95, F1-score, and Precision–Recall (PR) curves. Experimental results demonstrate that models trained on automatically generated annotations achieve stable segmentation performance of plant green biomass. The best results were obtained with the YOLO11m-seg model, achieving an F1-score of 0. 772. The results confirm the effectiveness of the proposed approach and demonstrate acceptable segmentation quality, supported by both quantitative metrics and visual analysis. The developed automatic annotation algorithm can be used to expand training datasets in computer vision tasks for agricultural applications. Full article

Gluten-free cakes formulated solely with rice flour frequently exhibit limited volume, weak internal structures, and rapid quality deterioration. This study investigated the effects of replacing rice flour with 0, 3, 6, 9, and 12% goji berry powder (GBP) in gluten-free cupcakes. Physical properties, texture profile, crumb porosity, crust and crumb color, flour pasting behavior, and antioxidant properties were evaluated. Moderate GBP addition improved cupcake quality, with the 6% treatment showing the greatest height (45.17 mm) and specific volume (3.64 cm³/g), the lowest hardness (327.50 g), the highest springiness (9.25 mm), and the largest average pore area (0.42 mm²). In contrast, higher substitution levels (9–12%) increased moisture and reduced baking loss but caused a decline in specific volume and a marked increase in hardness. GBP progressively darkened the product, especially the crumb, while significantly enhancing total phenolic content and DPPH radical-scavenging activity from 55.46 to 67.36 mg gallic acid equivalents (GAE)/100 g and from 4.85 to 15.08 mg ascorbic acid equivalents (AAE)/100 g, respectively. Monotonic decreases in peak, trough, final, and setback viscosities were observed, indicating reduced starch swelling and retrogradation tendencies as the GBP level increased. GBP at 6% showed the most balanced overall performance, while 12% maximized the antioxidant response at the expense of structural quality. Full article

Background/Objectives: The dark green leaf color trait in bunching onion (Allium fistulosum L.) is an important agronomic trait closely associated with market value; however, its genetic basis remains poorly understood. This study aimed to identify quantitative trait loci (QTLs) associated with leaf color using SPAD values as a phenotypic indicator. Methods: An ${\mathrm{F}}_2$ population derived from a cross between the dark green line YSG1go and the light green line Asagikei-KUJYO was used. A linkage map was constructed based on RNA-seq-derived SNP markers, and SPAD values were measured for QTL analysis. Results: The linkage map consisted of eight linkage groups with a total length of 2103.0 cM and 765 mapped markers. SPAD values showed significant differences between the parental lines, with high broad-sense heritability ($H^2$ = 0.76), indicating a strong genetic contribution to this trait. Multiple significant QTLs were detected on chromosomes 4 and 5, each explaining 27.4–38.1% of the phenotypic variance. The direction of allelic effects differed among QTLs, suggesting that favorable alleles are distributed between the parental lines. In addition, genes related to chloroplast protein translation were identified within the QTL regions. Conclusions: SPAD values are a suitable indicator for genetic analysis of leaf color in bunching onion, and the QTLs identified in this study provide valuable information for molecular breeding aimed at improving dark green leaf color. Full article

Background: Artificial intelligence (AI) has shown strong performance in disease-specific retinal screening tasks; however, its reliability in heterogeneous clinical diagnostic settings remains unclear. This study compared a general-purpose multimodal AI model with experienced retinal specialists in the interpretation of color fundus photographs (CFPs). Methods: In this pilot retrospective cross-sectional study, 66 CFPs were independently evaluated by a masked retinal specialist and an AI model (Google Gemini 2.5 Flash). Diagnoses were compared with those of the unblinded treating specialist. The comparison was inherently asymmetric, as the reference specialist had access to full clinical information, whereas the masked evaluators performed image-only assessment. Agreement was assessed using weighted percent agreement and Gwet’s AC2 with quadratic weights. Results: Substantial agreement was observed between the two human specialists (AC2 = 0.67). In contrast, agreement between the AI model and the reference specialist was low (AC2 = −0.58). Direct comparison between the masked specialist and the AI also showed limited reliability (AC2 = −0.38). Conclusions: In this pilot study, the evaluated AI model demonstrated limited agreement relative to a context-informed specialist reference. These findings support cautious interpretation of consumer-facing multimodal AI in open-ended retinal image assessment and warrant validation in larger, multicenter studies. Full article

This review examines how plant polyphenols enable multifunctional textiles, offering a sustainable alternative to synthetic dyes and nanomaterial-based treatments. A literature search (2001–2025) identified 105 peer-reviewed studies across eight functional areas. Abundant in agricultural and industrial byproducts, plant polyphenols act as natural colorants, bio-adhesives, and performance enhancers—providing coloration, antibacterial activity, UV protection, flame retardancy, deodorization, antioxidant capacity, superhydrophobicity, and more. Their catechol and pyrogallol groups bind strongly to natural and synthetic fibers via hydrogen bonding, π–π stacking, and metal chelation, ensuring durable, nontoxic functionality. We analyze structure–function links and scalable methods, including pad-dry-cure and metal–phenolic network (MPN) assembly, which were validated against ISO, ASTM, and AATCC standards. Polyphenol-based textiles match or exceed conventional ones in key metrics, with added benefits: full biodegradability, low ecotoxicity, and skin compatibility. Key advances include enzymatic polymerization for wash-stable color, MPN tuning for customizable functions, and using waste-derived polyphenols. However, major challenges remain: narrow color range (mostly yellow, brown, black) and poor wash/UV resistance, leading to rapid fading and loss of antibacterial/UV protection after laundering. Solving these is a top priority for future work. Overall, this review delivers a practical, science-based roadmap for high-performance, sustainable textiles that align with the Sustainable Development Goals and meet real-world needs in healthcare, sportswear, and smart wearables. Full article

Accurate and rapid fault diagnosis is critical for active distribution networks characterized by growing structural complexity and diverse load profiles. This paper proposes a two-stage fault diagnosis framework that synergistically combines colored Petri nets (CPN) and fuzzy colored Petri nets (FCPN). In the first stage, a CPN fault zone search model employing a breadth-first search (BFS) strategy is developed to identify suspected faulty components by processing circuit breaker operation information and grid topology. In the second stage, an FCPN diagnosis model is constructed by extending hierarchical fuzzy Petri nets through color assignment to confidence tokens. A key feature of this model is a dedicated initial confidence assessment module that dynamically evaluates the reliability of protection and circuit breaker actions by synthesizing device self-check alarms and operational timing information, thereby overcoming the limitation of empirical, static confidence assignment in existing methods. The resulting initial confidence values are then propagated through a hierarchical confidence inference module to determine the fault likelihood of each suspected component. Comparative simulations across four fault scenarios demonstrate that the proposed method achieves higher diagnostic accuracy and stronger fault tolerance than state-of-the-art approaches, correctly identifying all faulty components even under degraded alarm conditions. Full article

Wood coatings play a critical role in protecting wood substrates from environmental degradation, particularly ultraviolet (UV)-induced photodegradation. This review comprehensively examines the mechanisms of wood coating photodegradation, the factors influencing their durability, and current anti-aging strategies. Photodegradation arises from polymer chain scission, chemical structure reorganization, and photo-oxidation of lignin and cellulose, leading to coating chalking, cracking, gloss loss, and color changes, ultimately compromising wood mechanical properties and service life. Key anti-aging strategies include UV absorbers, which convert harmful UV radiation into heat; hindered amine light stabilizers (HALSs) that capture free radicals and quench excited-state molecules; barrier and shielding materials that form dense physical or nanostructured networks to block UV penetration and enhance mechanical and water resistance; and antioxidants that neutralize free radicals or decompose peroxides at the molecular level. Each approach can be employed individually or synergistically to enhance coating durability. Challenges remain in achieving long-term outdoor stability, balancing transparency and UV shielding, optimizing nanoparticle dispersion, and maintaining the activity of natural antioxidants. Future research should focus on multifunctional composite coatings integrating bio-based materials and nanotechnology, smart responsive systems, adaptive protection mechanisms, and standardized long-term evaluation protocols. These advancements will facilitate the development of high-performance, sustainable wood coatings and promote the value-added utilization of wood resources. Full article

Plaque-disclosing agents are widely used to enhance visualization of dental biofilm. However, their chromogenic components may adhere to enamel surfaces, resulting in transient extrinsic discoloration. This study evaluated the extent and short-term recovery of such discoloration and compared three removal modalities in terms of enamel color change (CIEDE2000, ΔE₀₀), surface roughness (Ra), and gloss (GU). Extracted human anterior teeth with intact buccal enamel were stained using an erythrosine-based disclosing agent and randomly allocated into three groups (n = 15): manual brushing with conventional toothpaste, rubber-cup polishing with a perlite-containing paste (1000 rpm, 5 s), or erythritol-based air-polishing (5 s; 50% power/100% water). ΔE₀₀ was measured at baseline, immediately after cleaning, and after 1 week of storage in artificial saliva. Ra and GU were recorded at baseline and post-cleaning. Data were analyzed using appropriate tests (p < 0.05). All modalities were associated with a reduction in visible discoloration without significantly affecting Ra or GU (p > 0.05). Immediate ΔE₀₀ values remained above commonly reported acceptability thresholds, indicating residual discoloration. Partial color recovery occurred after artificial saliva storage. Within the limitations of this study, the findings indicate no statistically significant differences among the tested procedures, without evidence of superiority of any single modality. Full article

Underwater multi-class object detection in nearshore waters is essential for intelligent cleaning operations and ecological monitoring. However, strong reflection and scattering interference, color attenuation, frequent occlusion, and non-rigid deformation often cause fine-grained information loss and feature misalignment in conventional detectors, leading to missed and false detections. To address these challenges, we propose an enhanced YOLOv11 framework integrating FasterNet and attention mechanisms. Specifically, we include FasterNet to replace the YOLOv11 baseline backbone to improve fine-grained feature preservation while reducing computational redundancy. Furthermore, a Deformable Underwater Attention Module (DUAM) is introduced to capture local texture variations and deformation-aware features, enhancing discrimination among heterogeneous categories. Additionally, a Submerged Occlusion-Aware Head (SOAH) is designed to recalibrate features based on occlusion visibility, improving the detection of small-scale and partially occluded objects in the high-resolution P2 layer. Performance gains mainly stem from the recalibration strategy and its synergy with multi-scale optimization objectives. Experiments on a nearshore underwater multi-class dataset (8610 images across 40 classes) show that the proposed method increases mAP from 66.9% to 82.3%, achieving a 15.4-point improvement over baseline YOLOv11, with superior robustness under complex backgrounds. Full article