Search Results (572)

Dual-emission molecularly imprinted membranes (dual@MIPs@mbr) were developed as a proof-of-concept platform for the selective and instrument-free detection of the cancer biomarker carbohydrate antigen 19-9 (CA 19-9). The system integrates a ratiometric fluorescence response by embedding yellow-emitting quantum dots (y-QDs), serving as target-responsive probes, and blue-emitting carbon dots (b-CDs), acting as an internal reference, within a CA 19-9-imprinted polymeric matrix. Specific rebinding of CA 19-9 to the imprinted cavities induced selective quenching of the y-QDs while preserving the b-CDs emission, yielding a visible color shift from yellow/green to blue. This behavior enabled the quantification of CA 19-9 over a linear range of 4–400 U mL⁻¹, with a limit of detection of 0.056 U mL⁻¹ in diluted serum. The membranes showed good selectivity against common serum interferents and maintained short-term photochemical stability. Although the method has not yet been validated using real clinical samples, the pronounced ratiometric response and simple visual readout demonstrate its potential as a low-cost, portable sensing approach for future point-of-care cancer biomarker analysis. Full article

Sleep is an essential physiological process, and residential lighting environments significantly impact sleep quality. To address circadian phase delays exacerbated by pre-sleep smartphone use in youth, this study developed targeted lighting interventions. Through laboratory simulations, the effects of color temperature, illuminance, and horizontal blue light ratio on multisensory responses (visual, psychological, physiological) and sleep quality were examined. A rhythmic lighting strategy for healthy environments was proposed. Key findings: (1) Lighting factors revealed a hierarchy of influence on sleep quality—color temperature had the greatest influence on sleep quality, followed by illuminance and horizontal blue light ratio. Optimal conditions include cycling color temperature, 800 lx illuminance, and 25% blue light ratio. (2) Context-specific interventions were proposed—high illuminance with low color temperature enhances comfort in healthcare/leisure spaces, while medium–high color temperature, high illuminance, and cycling blue light ratios improve efficiency in office/study environments. (3) A time-sequenced rhythmic lighting scheme aligned with daily routines was implemented. This study establishes a novel health evaluation framework for residential lighting, combining sleep quality, psychological, and physiological metrics, redefines research paradigms for light-induced health effects, and provides actionable insights for optimizing workplace lighting. Full article

As a core component of emerging quantum-dot display technology, the stability of quantum-dot materials is crucial to determining the performance of quantum-dot photoluminescent diffuser plates. This study successfully synthesized high-stability thick-shell CdZnSeS/CdZnS/ZnS core–shell structured green-alloy quantum dots suitable for photoluminescent diffuser plates, providing an innovative solution for performance breakthroughs in this field. Through orthogonal experimental design, the synthesis parameters of the CdZnSeS alloy core were precisely optimized to achieve an ideal balance in emission wavelength, full width at half maximum (FWHM), and quantum yield (QY). Furthermore, by systematically adjusting ligands and synthesis parameters, a thick-shell CdZnSeS/CdZnS/ZnS core–shell structure was constructed, significantly improving the stability of the quantum dots. Critically, the replacement of the original oleic-acid ligands with tetradecylphosphonic-acid (TDPA) ligands at high temperature doubled the stability of the quantum-dot diffuser plates. Under extreme accelerated-aging conditions such as intense blue light, high temperature, and high humidity, the T90 lifetime of the diffuser plate exceeded 1000 h, and the xy chromaticity coordinate shift was strictly controlled within 1%, fully meeting the stringent commercial requirements. This achievement not only overcomes the stability bottleneck of quantum dots in the application of photoluminescent diffuser plates but also paves the way for their large-scale commercialization, promising to promote the development of display technology toward higher color gamut and longer lifetimes. Full article

It is important to develop a tetracycline (TC) detection method with a simple synthesis method, high sensitivity, and fast detection speed. Herein, a novel sensor was designed using europium-doped boron nitride (BN-Eu) for evaluation on tetracycline (TC). BN-Eu was synthesized by a simple one-step hydrothermal method. Based on the dual-emission fluorescence signal characteristics of BN-Eu, the content of tetracycline was detected by ratio fluorescence sensing. When the TC concentration increased, the fluorescence emission of BN at 449 nm remained nearly constant, the characteristic emission peak of Eu³⁺ at 618 nm was enhanced due to the antenna effect(AE). The ratiometric fluorescence detection of TC in the range of 0.010–1.0 μmol L⁻¹ was achieved with a detection limit of 4.0 nmol L⁻¹. In addition, the detection system underwent a color shift from blue to red under an irradiation of 365 nm as the TC concentration increased. Based on this, TC visual detection was achieved. The colorimetric signal versus the concentration of TC in the range from 0 to 50 μmol L⁻¹ had a good linear relationship with a detection limit of 1.4 μmol L⁻¹. The probe showed good detection performance through the determination of tetracycline content in tetracycline ointment. The prepared BN-Eu probe has fast response, good sensitivity to TC, and has good potential in detecting tetracycline content in complex samples. Full article

Accurate prediction of the latent period and disease progression in tomato fungal infections is critical for enabling timely interventions and effective disease management. Unlike existing AI-based approaches that primarily classify diseases after symptom emergence, this study innovates by predicting infection stages from the asymptomatic (latent) phase through complete symptom development, integrating biologically grounded feature extraction with explainable artificial intelligence (XAI). This study presents a novel, XAI framework capable of day-wise prediction of infection stages, including the latent period, for four major fungal pathogens in tomatoes: Alternaria alternata, Alternaria solani, Botrytis cinerea, and Fusarium oxysporum. A high-resolution (Red-Green-Blue) RGB image dataset was collected under controlled inoculation conditions, capturing daily changes in infected and healthy tomato leaves over six days post-infection. The pipeline included image preprocessing, lesion segmentation, and extraction of biologically meaningful features (texture, color, and shape) reflecting underlying physiological changes in the plant. Feature relevance across infection stages was dynamically assessed using the Relief algorithm, providing interpretability by linking visual changes to disease biology. Machine learning classifiers, Support Vector Machine (SVM) and Random Forest (RF), were optimized using Particle Swarm Optimization (PSO), achieving significant improvements in infection day prediction accuracy across all four pathogens. For example, RF accuracy increased from 76.14% to 94.17% for A. alternata (with 97.96% sensitivity and 99.48% specificity on day 6 post-inoculation) and from 80.01% to 97.08% for B. cinerea. Critically, the model accurately identified the latent period for each pathogen, detecting microscopic texture changes on day 1 post-inoculation when no visible symptoms were present. By bridging the gap between AI and plant pathology, this framework enables early diagnosis of fungal diseases with explainable outputs. The approach offers a scalable, non-destructive, and biologically grounded tool for integrated disease management, with potential applications across diverse crops in precision agriculture. Full article

To develop a full-color laser virtual reality head-mounted display (VR-HMD), a white laser light source, obtained by overlapping red–green–blue (RGB) lasers, is necessary. Although many studies on VR-HMD incorporating RGB lasers have been performed, there have been no studies on the removal of interferences such as electric field synthesis generated among the laser beams irradiated at a sample, namely “polarization crosstalk removal”. Therefore, the developing methods for electric field control are crucial. In this study, an attempt has been made to build a function that avoids crosstalk among the RGB beams after the irradiation of samples by separating them in time using the “time-shift” technique. If this function is realized, negative influences such as electric field synthesis can be eliminated. Consequently, the fabrication of the polarization-adjustable VR-HMD is expected in the future. Full article

In this study, a sliding microfluidic biosensor integrating RPA-SDA cascaded amplification was developed for the rapid, visual detection of Shigella. A novel RPA primer targeting the specific ipaH gene was designed to include a 5′-end G-quadruplex (G4) sequence and the complementary sequence of an Nt.BstNBI endonuclease recognition site. The RPA product templates a subsequent SDA reaction, generating abundant G4 structures that form peroxidase-mimicking DNAzymes with hemin, catalyzing a TMB reaction that produces a distinct blue color for visual readout (on-chip detection at OD₃₇₀, distinct from conventional tube assays at OD₄₅₀). The core on-chip detection process was completed within 13 min (10 min for SDA and 3 min for color development), achieving a limit of detection of 3.5 × 10⁻⁴ ng/μL for Shigella genomic DNA. This timing explicitly excludes the preceding, off-chip steps of nucleic acid extraction and RPA amplification. Validation using spiked lettuce samples confirmed the platform’s high specificity and sensitivity. This work establishes a proof-of-concept for a portable screening tool, highlighting its potential for on-site food safety applications. However, further validation in diverse food matrices and under real-world field conditions is required to fully establish its practical utility. Full article

The targeting of environmentally conscious German car drivers through product aesthetics can foster the acceptance of sustainable cars. No guidelines are currently available to designers to create product personality based on environmentally friendly design cues (EFDCs). The aim of this paper was to explore EFDCs for car interiors through bio-based materials. To address this topic, Study 1 examined a collection of bio-based material samples and samples featuring specific colors and reactions to light to determine their potential for the creation of an environmentally friendly product personality. Study 2 built on the implications of the former to examine the contribution of blue as a color and glowing attribute on the development of EFDCs. Wood veneer, cork, and cotton fabric were perceived as sustainable, natural, and renewable by most of the subjects. Brown and white leather was also perceived as sustainable. Moreover, the perception of the naturalness of materials in direct contact with blue light was reduced. Visual texture features for EFDC design are visible fibers or a wooden look. Haptic features include soft, warm, and rough surfaces, while glare, shimmer, a shiny surface, and smoothness should be avoided. The color brown should be considered, while blue, green, and yellow should be avoided. Full article

Road-marking operations generate alkaline wash water with intense color and soluble cationic additives. A new biomass adsorption material (LML) was developed to address dye pollution in road-marking wash water effectively. Enzymatically hydrolyzed lignin was used as the raw material for the first time. L-lysine was modified to the structure of the lignin benzene ring using a simple one-step synthesis method, which endowed lignin with a large number of active carboxyl and amino functional groups to improve its adsorption capacity. The adsorption performance of LML for methylene blue in water was also investigated. The experimental results show that the LML has a high dye removal rate under alkaline conditions. The fitted adsorption model shows that the saturated adsorption capacity of LML for methylene blue (MB) is 129.4 mg g⁻¹ and malachite green (MG) is 244.9 mg g⁻¹, which is in line with the Langmuir isotherm adsorption model. The adsorption process is endothermic, which means that the adsorption capacity increases with increasing temperature. Kinetic studies showed that the adsorption process reached equilibrium within 120 min following a pseudo-second-order kinetic model. The cycle experiment shows that the removal efficiency of the adsorbent for dyes can still reach 90% after five cycles, indicating a good practical application value for the polishing of road-marking wash water. Full article

This study develops and validates a weft knitted Mini-Jacquard in Peruvian Pima cotton as a print-free coloration strategy by integrating CAD-based pattern simulation with prototype manufacturing. A three-color design (red, blue, white) was programmed on a flat knitting machine using a 10 × 14 rapport. Color-wise yarn consumption was computed directly from the digital pattern, and the physical sample was characterized through combustion testing and optical micrographs. The prototype exhibited a yarn count of ~20/1 Ne, S-twist (~11.18 TPI), and 100% cellulosic composition. The blue yarn showed the highest consumption (≈73.81%), followed by white (≈19.65%) and red (≈6.55%), consistent with the digital rapport’s color distribution. The CAD stage ensured pattern fidelity and supported raw-material planning; the knitted sample showed a soft hand, dimensional stability, and sharp motif definition upon visual assessment. A sustainability and comparative analysis with chemical printing was conducted, revealing that the Mini-Jacquard achieved the highest design accuracy and tactile comfort, outperforming screen printing and heat transfer in geometric fidelity, chromatic homogeneity, and texture. The Mini-Jacquard optimized operational times (320 min/m²) compared to transfer printing (332 min/m²) and screen printing (740 min/m²), reducing process stages and complexity. Although Jacquard production involves higher energy costs ($34.8) and material expenses ($11.6), it provides greater structural value and durability, positioning it for high-end applications. Moreover, the Mini-Jacquard could reduce water consumption by approximately 90% and thermal energy use by 70%, eliminating chemical residues and extending fabric lifespan, thus offering high sustainability and circular potential. A transparent scenario-based analysis indicates substantial reductions in water and thermal-energy use when omitting printing/fixation/washing stages, along with the elimination of printing-stage effluents. Overall, design-integrated coloration via Mini-Jacquard is technically feasible and potentially eco-efficient for Pima-cotton value chains, with applications in apparel, accessories, and functional textiles. Full article

Food color is a powerful determinant of consumer perception, influencing emotions, taste expectations, and hedonic responses. This study investigated how red, yellow, and blue plating colors affect emotional responses, acceptance, and taste associations. Emotional descriptors were defined through two focus groups (n = 17) and validated in a consumer study with 295 participants (63.4% female, 35.3% male). Three color-dominant samples were evaluated online using the Check-All-That-Apply (CATA), Rate-All-That-Apply (RATA), and a nine-point hedonic scale. The red sample achieved the highest acceptance (7.27), followed by blue (7.03) and yellow (6.82) (p < 0.05). Red was strongly associated with positive RATA terms such as pleasant (3.90), with pleasure (2.95), and satisfied, while blue elicited negative responses, including disgusted (72%) and no appetite (74%). Pearson correlations confirmed pleasant (r = 0.70, p < 0.001) and with pleasure (r = 0.58, p < 0.001) as key acceptance drivers, whereas disgusted (r = −0.29, p < 0.001) acted as a rejection cue. Correspondence analysis explained 68% of the variance, and Partial Least Squares Regression highlighted pleasant (VIP = 1.86) as the strongest predictor of liking. Tableware (≥4.25) and plating arrangement (≥4.31) also significantly shaped emotional perception. These results demonstrate that plating colors critically influence consumer emotions and acceptance, offering practical insights for multisensory gastronomy and food design. Overall, the study shows that plating color can be strategically leveraged in gastronomy and product development to enhance consumer emotions and acceptance, providing valuable guidance for multisensory food design. Although conducted using photographic stimuli and limited to Brazilian consumers, the study provides valuable insights into how plating color influences emotional and hedonic responses. These findings can support both academic research and professional practice, guiding chefs and food designers in developing multisensory gastronomic experiences. Full article

Current histological staining methods for intestinal tissue analysis face limitations in simultaneously visualizing multiple tissue components, often requiring multiple sequential stains that increase processing time and tissue consumption. This proof-of-concept study aimed to define and develop a pentachromatic staining method for enhanced visualization of gastrointestinal tissue architecture. We developed the Pentachroma O-H method, an original protocol using readily available histological reagents (Alcian Blue pH 2.5, Weigert’s resorcin–fuchsin, Mayer’s hematoxylin, and Van Gieson’s solution) applied in an optimized sequence. The protocol was tested on healthy human ileum tissue obtained from surgical specimens as proof of concept. Thirty serial sections were stained with Pentachroma O-H and compared to adjacent sections stained with conventional hematoxylin–eosin (H&E) to document the emerging morphological characteristics of this original stain. Pentachroma O-H achieved distinct five-color differentiation in approximately 45 min: acidic mucins appeared turquoise–blue, collagen fibers red, elastic fibers black–purple, smooth muscle and erythrocyte cytoplasm yellow, and nuclei blue–black. The method clearly delineated intestinal architecture, including mucosal goblet cells, muscularis mucosae, connective tissue vasculature (parietal smooth muscle and elastic laminae), fibers, and cellular components, as well as lymphoid tissue aggregates and infiltrates, with improved contrast compared to H&E. All tissue components were simultaneously visualized in single sections with excellent morphological preservation. This first description of Pentachroma O-H demonstrates its capability to provide comprehensive ileum tissue visualization equivalent to multiple traditional special stains in a single, efficient protocol, offering significant potential advantages for gastrointestinal pathology assessment and warranting future validation studies across diverse tissue types and pathological conditions. Full article

There has been an increasing demand for high-resolution image sensing technologies in recent years due to their diverse and advanced optical applications. With recent advances in nanofabrication technologies, this can be achieved through the realization of high-density pixels. However, the development of high-density and miniaturized pixels introduces challenges to the conventional color filters, which generally transmit and absorb different spectral components of light. A significant portion of the incident light is inherently lost using conventional color filters. Moreover, as the pixel size is shrunk, optical losses appear to be substantial. To address these fundamental limitations, a novel nanophotonic optical router is proposed in this work. Our router utilizes a single-layer, all-dielectric metasurface as a spectral router. The metasurface is designed through an inverse design approach that exploits adjoint sensitivity analysis. A novel figure of merit is developed and incorporated in the inverse design process, enabling the metasurface design to effectively sort and route the incoming light into four targeted channels, each corresponding to a distinct spectral component—red, green, blue, and near-infrared. We demonstrate that the proposed quad-spectral metasurface router, having a compact footprint of $2 \mathsf{\mu }\mathrm{m}\times 2 \mathsf{\mu }\mathrm{m}$, achieves an average optical efficiency of approximately 39% across the broad spectral range, i.e., 400–850 nm, with each spectral channel exceeding an efficiency of 25%. This surpasses the maximum efficiency attainable by the conventional four-channel color filters. Our proposed quad-spectral metasurface router offers a wide range of applications in low-light imaging, image fusion, computational photography, and computer vision. In addition, this work highlights the applicability of an adjoint-based inverse design approach to accelerate the development of compact, efficient, and high-performance nanophotonic devices for the next generation of imaging and sensing systems. Full article

In recent years, edible flowers have gained increasing attention as unconventional foods, primarily due to their richness in bioactive compounds. Within this context, Clitoria ternatea L. (Fabaceae), commonly known as butterfly pea, stands out not only for its remarkable biological properties but also for its intense blue pigmentation. This review aims to provide a comprehensive overview of the plant’s potential in the food industry, highlighting its bioactive compounds, technological applications, and associated health benefits. Recent studies have demonstrated its antioxidant, antidiabetic, anti-obesity, hepatoprotective, and anticancer activities, as well as its use as a natural colorant, functional ingredient, active packaging component, and in nutraceutical and cosmetic formulations. Despite these promising findings, most available evidence comes from preclinical studies, with limited clinical validation to date. Therefore, further human studies are needed to confirm the efficacy and safety of the reported beneficial effects. Altogether, C. ternatea represents a promising natural resource for developing functional foods that meet the growing clean-label demand, fostering the incorporation of sustainable and natural ingredients. Full article

This study evaluated the integration of non-invasive remote sensing and colorimetry to classify the maturity stages of Coffea arabica fruits across four varieties: Caturra Amarillo, Excelencia, Milenio, and Típica. Multispectral signatures were captured using a Parrot Sequoia camera at wavelengths of 550 nm, 660 nm, 735 nm, and 790 nm, while colorimetric parameters L*, a*, and b* were measured with a high-precision colorimeter. We conducted multivariate analyses, including Principal Component Analysis (PCA) and multiple linear regression (MLR), to identify color patterns and develop predictors for fruit maturity. Spectral curve analysis revealed consistent changes related to ripening: a decrease in reflectance in the green band (550 nm), a progressive increase in the red band (660 nm), and relative stability in the RedEdge and near-infrared regions (735–790 nm). Colorimetric analysis confirmed systematic trends, indicating that the a* component (green to red) was the most reliable indicator of ripeness. Additionally, L* (lightness) decreased with maturity, and the b* component (yellowness to blue) showed varying importance depending on the variety. PCA accounted for over 98% of the variability across all varieties, demonstrating that these three parameters effectively characterize maturity. MLR models exhibited strong predictive performance, with adjusted R² values ranging between 0.789 and 0.877. Excelencia achieved the highest predictive accuracy, while Milenio demonstrated the lowest, highlighting varietal differences in pigmentation dynamics. These findings show that combining multispectral imaging, colorimetry, and statistical modeling offers a non-destructive, accessible, and cost-effective method for objectively classifying coffee maturity. Integrating this approach into computer vision or remote sensing systems could enhance harvest planning, reduce variability in specialty coffee lots, and improve competitiveness by ensuring greater consistency in cup quality. Full article