Search Results (1,186)

This study investigates the influence of façade-design parameters on daylighting performance in hot arid climates, with a particular focus on Egypt. A total of nine façade configurations of a residential building were modeled and simulated using Autodesk Revit and Insight 360, varying three critical variables: glazing type (clear, blue, and dark), Window-to-Wall Ratio (WWR) of 15%, 50%, 75%, and indoor wall finish (light, moderate, dark) colors. These were compared to the Leadership in Energy and Environmental Design (LEED) daylighting quality thresholds. The results revealed that clear glazing paired with high WWR (75%) achieved the highest Spatial Daylight Autonomy (sDA), reaching up to 92% in living spaces. However, this also led to elevated Annual Sunlight Exposure (ASE), with peak values of 53%, exceeding the LEED discomfort threshold of 10%. Blue and dark glazing types successfully reduced ASE to as low as 0–13%, yet often resulted in underlit spaces, especially in private rooms such as bedrooms and bathrooms, with sDA values falling below 20%. A 50% WWR emerged as the optimal balance, providing consistent daylight distribution while maintaining ASE within acceptable limits (≤33%). Similarly, moderate color wall finishes delivered the most balanced lighting performance, enhancing sDA by up to 30% while controlling reflective glare. Statistical analysis using Pearson correlation revealed a strong positive relationship between sDA and ASE (r = 0.84) in highly glazed, clear glass scenarios. Sensitivity analysis further indicated that low WWR configurations of 15% were highly influenced by glazing and finishing types, leading to variability in daylight metrics reaching ±40%. The study concludes that moderate glazing (blue), medium WWR (50%), and moderate color indoor finishes provide the most robust daylighting performance across diverse room types. These findings support an evidence-based approach to façade design, promoting visual comfort, daylight quality, and sustainable building practices. Full article

This study aimed to develop a functional powder using whey and milk matrices, leveraging the protective capacity of chia–alginate hydrogels and the advantages of electrohydrodynamic spraying (EHDA), a non-thermal technique suitable for encapsulating probiotic cells under stress conditions commonly encountered in food processing. A hydrogel matrix composed of chia seed mucilage and sodium alginate was used to form a biopolymeric network that protected probiotic cells during processing. The encapsulation efficiency reached 99.0 ± 0.01%, and bacterial viability remained above 9.9 log₁₀ CFU/mL after lyophilization, demonstrating the excellent protective capacity of the hydrogel matrix. Microstructural analysis using confocal laser scanning microscopy (CLSM) revealed well-retained cell morphology and homogeneous distribution within the hydrogel matrix while, in contrast, scanning electron microscopy (SEM) showed spherical, porous microcapsules with distinct surface characteristics influenced by the encapsulation method. Encapsulates were incorporated into beverages flavored with red fruits and pear and subsequently freeze-dried. The resulting powders were analyzed for moisture, protein, lipids, carbohydrates, fiber, and color determinations. The results were statistically analyzed using ANOVA and response surface methodology, highlighting the impact of ingredient ratios on nutritional composition. Raman spectroscopy identified molecular features associated with casein, lactose, pectins, anthocyanins, and other functional compounds, confirming the contribution of both matrix and encapsulants maintaining the structural characteristics of the product. The presence of antioxidant bands supported the functional potential of the powder formulations. Chia–alginate hydrogels effectively encapsulated L. reuteri, maintaining cell viability and enabling their incorporation into freeze-dried beverage powders. This approach offers a promising strategy for the development of next-generation functional food gels with enhanced probiotic stability, nutritional properties, and potential application in health-promoting dairy systems. 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

Various parameters and observation conditions contribute to the emergence of color. This phenomenon poses a challenge in modern visual communication systems, which are continuously being enhanced through new insights gained from research into specific psychophysical effects. One such effect is the psychophysical phenomenon of simultaneous contrast. Nearly 90 years ago, Kurt Koffka described one of the earliest illusions related to simultaneous contrast. This study examined the perception of gray tone variations in the Koffka ring against different background color combinations (red, blue, green) displayed on a computer screen. The intensity of the effect was measured using lightness difference ΔL₀₀ across light-, medium-, and dark-gray tones. The results were analyzed using descriptive statistics, while statistically significant differences were determined using the Friedman ANOVA and post hoc Wilcox tests. The strongest visual effect was observed the for dark-gray tones of the Koffka ring on blue/green and red/green backgrounds, indicating that perceptual organization and spatial parameters influence the illusion’s magnitude. The findings suggest important implications for digital media design, where understanding these effects can help avoid unintended color tone distortions caused by simultaneous contrast. 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

Background/Objectives: Keratoconus (KC) is a bilateral asymmetric corneal ectasia characterized by progressive corneal thinning, irregular astigmatism, and impaired visual acuity. The National Eye Institute (NEI) developed the Visual Function Questionnaire (VFQ-25) to assess the impact of visual impairment on quality of life. This study aimed to evaluate the effect of penetrating keratoplasty (PKP) on quality of life and visual acuity in KC patients one year postoperatively. Methods: A retrospective study was conducted between January 2018 and December 2022 at the Ophthalmology Department of Saint Barbara Hospital, Trauma Center, Sosnowiec, Poland. A total of 71 patients (86 eyes) diagnosed with KC underwent PKP. The VFQ-25 questionnaire and visual acuity measurements were assessed preoperatively and one year postoperatively. Results: The study cohort included 71 patients (20 females, 28.17%; 51 males, 71.83%). Preoperative visual acuity ranged from less than 0.05 on the Snellen chart to 0.5. Postoperatively, visual acuity improved to a range of 0.1–1.0. A visual acuity of 1.0 was achieved in 21 eyes (24.42%; 5 females, 24%; 16 males, 76%), with a statistically significant improvement (p < 0.01). The mean VFQ-25 composite score increased from 57.96 (±17.58) preoperatively to 81.42 (±14.66) postoperatively (p < 0.001). Domains with the lowest preoperative scores were “role difficulties,” “general vision,” and “mental health,” while “color vision” scored highest. Conclusions: PKP significantly enhances both objective visual acuity and subjective quality of life in KC patients, as reflected in VFQ-25 questionnaire outcomes. Full article

Image binarization algorithms reduce the original color space to only two values, black and white. They are an important preprocessing step in many computer vision applications. Image binarization is typically performed using a threshold value by classifying the pixels into two categories: lower and higher than the threshold. Global thresholding uses a single threshold value for the entire image, whereas local thresholding uses different values for the different pixels. Although slower and more complex than global thresholding, local thresholding can better classify pixels in noisy areas of an image by considering not only the pixel’s value, but also its surrounding neighborhood. This study introduces a local thresholding method that uses the results of several local thresholding algorithms and other image statistics to train a decision tree ensemble. Through cross-validation, we demonstrate that the model is robust and performs well on new data. We compare the results with state-of-the-art solutions and reveal significant improvements in the average F-measure for all DIBCO datasets, obtaining an F-measure of 95.8%, whereas the previous high score was 93.1%. The proposed solution significantly outperformed the previous state-of-the-art algorithms on the DIBCO 2019 dataset, obtaining an F-measure of 95.8%, whereas the previous high score was 73.8%. Full article

This study aimed to determine the effects of LED applications and application periods on seedling development. To this end, four different LED applications (blue 100%, red 100%, green 100%, and full-spectrum 100% (control)) were applied to different star flower varieties (Figaro Violet shades—flower color: purple, Figaro Orange shades—flower color: orange, Figaro White shades—flower color: white, and Figaro Red shades—flower color: red) for 15 and 30 days. These applications were repeated over two years (two vegetation periods). The results revealed that the red-flowered and white-flowered varieties exhibited higher values in terms of root length, root number, stem diameter, 2nd and 4th leaf petiole length, 2nd and 4th leaf width, and leaf number under full-spectrum and red LED applications. We also observed that red LED application for 30 days is suitable for seedling height development in the Figaro Orange shades variety. Conversely, the results showed that the effects of LED application durations on root length and stem diameter did not show a statistically significant difference, while the 15-day application yielded the best results for root number. In the Figaro Red shades and Figaro White shades varieties, the use of red LED applications for 30 days yielded results similar to those of full-spectrum applications, indicating that both applications can be used for seedling cultivation. Full article

The demand for sustainable animal production is increasing. Microalgae such as Chlorella and Spirulina show promise as sustainable and functional ingredients in animal (poultry) feed. However, little is known about consumer perceptions regarding the use of algae in broiler diets and potential effects of algae on chicken meat. Residents of Flanders (Belgium) were surveyed to evaluate consumer knowledge, attitudes and willingness to buy chicken meat produced with algae-supplemented feed. Demographic data were collected, and both descriptive and inferential statistics were applied to assess influencing factors (n = 275 respondents who purchase chicken meat). While most respondents (69.6%) had tasted macroalgae (seaweed), only 11.4% and 24.6% indicated having tasted Chlorella and Spirulina before, respectively. Health, taste and safety were the most important drivers for consuming algae. Meat quality was the most important factor when purchasing chicken meat, while organic production was least valued. Regarding algae-fed chicken, 72.5% expressed willingness to purchase meat labeled as such, and 83.7% would buy algae-fed chicken regardless of its color. Sustainability beliefs significantly influenced willingness to accept a yellower meat color (β = 0.42 to 0.66, p < 0.001). Educational level and age also played a role, with higher-educated consumers showing greater acceptance. The influence of age was also related to the price of the meat, with consumers over 30 expressing a greater willingness to pay more than young people (under 30). Despite limited general knowledge about microalgae, the consumers surveyed are open to the idea of algae-fed chicken meat, particularly when it is framed as more sustainable. Clear ingredient labeling and consumer education may further support market acceptance. Full article

The agri-food sector faces the challenge of valorizing by-products and reducing waste. The frozen pumpkin industry generates substantial amounts of by-products rich in nutritional value, especially β-carotene. This study evaluates the nutritional and physical impact of incorporating pumpkin pulp flour (dehydrated and freeze-dried) obtained from by-products into cracker formulation. Crackers were prepared by replacing 10% and 20% of wheat flour with pumpkin flour, assessing the effects based on drying method. Physical parameters (expansion, color, and texture parameters) were measured, in the dough and in the baked products. Furthermore, β-carotene content was analyzed by HPLC-DAD, antioxidant capacity was measured with DPPH, ABTS, and ORAC, and total phenolic content was evaluated with the Folin–Ciocalteu method. Proximate composition and mineral content were also analyzed. Additionally, a preliminary sensory evaluation was conducted with 50 untrained consumer judges to assess acceptability of external appearance, texture, and taste. The inclusion of pumpkin flour significantly increased β-carotene content (up to 2.36 mg/100 g), total phenolics, and antioxidant activity of the baked crackers. Proximate analysis showed a marked improvement in fiber content and a slight reduction in energy value compared to wheat flour. Mineral analysis revealed that pumpkin flours exhibited significantly higher levels of K, Ca, Mg, and P, with improved but not always statistically significant retention in the final crackers. Freeze-dried flour retained more bioactive compounds and enhanced color. However, it also increased cracker hardness, particularly with dehydrated flour. Only the 10% freeze-dried formulation showed mechanical properties similar to those of the control. Sensory analysis indicated that all formulations were positively accepted, with the 10% freeze-dried sample showing the best balance in consumer preference across all evaluated attributes. Frozen pumpkin by-products can be effectively valorized through their incorporation into bakery products such as crackers, enhancing their nutritional and functional profile. Freeze-drying better preserves antioxidants and β-carotene, while a 10% substitution offers a balance between nutritional enrichment and technological performance and sensory acceptability. Full article

A rising demand for low-gluten beer fuels research into enzymatic solutions. This study optimized Aspergillus niger prolyl endopeptidase (AN-PEP) application timing during brewing to reduce gluten while preserving physicochemical quality. Ale-type beers were produced with AN-PEP (2% v/v) added at mashing, boiling, post-boiling, or post-fermentation, plus a control. Three mashing profiles (Mash A, B, C) were also tested. Gluten was quantified by R5 ELISA (LOQ > 270 mg/L). Color, bitterness, ABV, and foam stability were assessed. Statistical analysis involved ANOVA and Tukey’s HSD (p < 0.05). Enzyme activity and thermal inactivation were also evaluated. Initial gluten levels consistently exceeded LOQ. Significant gluten reduction occurred only post-fermentation. Mashing, boiling, and post-boiling additions effectively lowered gluten to below 20 mg/L. Post-fermentation addition resulted in significantly higher residual gluten (136.5 mg/L). Different mashing profiles (A, B, C) with early enzyme addition achieved similar low-gluten levels. AN-PEP showed optimal activity at 60–65 °C, inactivating rapidly at 100 °C. Physicochemical attributes (color, extract, bitterness, ABV) were largely unaffected. However, foam stability was significantly compromised by mashing and post-fermentation additions, while preserved with boiling and post-boiling additions. AN-PEP effectively produces low-gluten beers. Enzyme addition timing is critical: while mashing, boiling, or post-boiling additions reduce gluten to regulatory levels, only the beginning of boiling or post-boiling additions maintain desirable foam stability. These findings offer practical strategies for optimizing low-gluten beer production. Full article

Domestic wastewater discharge is the major source of pollution in Malaysia. Phytoremediation under hydroponic conditions was initiated to treat domestic wastewater and, at the same time, to resolve the space limitation issue by installing a hydroponic system in vertical space at the site. Water hyacinth (WH) was selected in this study to identify its performance of water hyacinth in removing nutrients in raw sewage under batch operation. In the batch experiment, the ratio of COD_initial/plant_initial was identified, and SPSS ANOVA analysis shows that the number of plant size factors was not statistically different in this study. Therefore, four WH, each with an initial weight of 60 ± 20 g, were recommended for this study. Throughout the 10 days of the batch experiment, the average of COD, BOD, TSS, TP, NH4, and color removal was 73%, 73%, 86%, 79%, 77%, and 54%, respectively. The WH biomass weight increased by an average of 78%. The plants have also improved the DO level from 0.24 mg/L to 4.88 mg/L. However, the pH of effluent decreased from pH 7.05 to pH 4.88 below the sewage Standard B discharge limit of pH 9–pH 5.50. Four WH plant groups were recommended for future study, as the COD removal among the other plant groups is not a statistically significant difference (p < 0.05). Furthermore, the lower plant biomass is preferable for the high pollutant removal performance due to the fact that it can reduce the maintenance and operating costs. Full article

Solar power generation is rapidly emerging within renewable energy due to its cost-effectiveness and ease of deployment. However, improper inspection and maintenance lead to significant damage from unnoticed solar hotspots. Even with inspections, factors like shadows, dust, and shading cause localized heat, mimicking hotspot behavior. This study emphasizes interpretability and efficiency, identifying key predictive features through feature-level and What-if Analysis. It evaluates model training and inference times to assess effectiveness in resource-limited environments, aiming to balance accuracy, generalization, and efficiency. Using Unmanned Aerial Vehicle (UAV)-acquired thermal images from five datasets, the study compares five Machine Learning (ML) models and five Deep Learning (DL) models. Explainable AI (XAI) techniques guide the analysis, with a particular focus on MPEG (Moving Picture Experts Group)-7 features for hotspot discrimination, supported by statistical validation. Medium Gaussian SVM achieved the best trade-off, with 99.3% accuracy and 18 s inference time. Feature analysis revealed blue chrominance as a strong early indicator of hotspot detection. Statistical validation across datasets confirmed the discriminative strength of MPEG-7 features. This study revisits the assumption that DL models are inherently superior, presenting an interpretable alternative for hotspot detection; highlighting the potential impact of domain mismatch. Model-level insight shows that both absolute and relative temperature variations are important in solar panel inspections. The relative decrease in “blueness” provides a crucial early indication of faults, especially in low-contrast thermal images where distinguishing normal warm areas from actual hotspot is difficult. Feature-level insight highlights how subtle changes in color composition, particularly reductions in blue components, serve as early indicators of developing anomalies. Full article

The underwater environment severely degrades image quality by absorbing and scattering light. This causes significant challenges, including non-uniform illumination, low contrast, color distortion, and blurring. These degradations compromise the performance of critical underwater applications, including water quality monitoring, object detection, and identification. To address these issues, this study proposes a detail-oriented hybrid framework for underwater image enhancement that synergizes the strengths of traditional image processing with the powerful feature extraction capabilities of unsupervised deep learning. Our framework introduces a novel multi-scale detail enhancement unit to accentuate structural information, followed by a Latent Low-Rank Representation (LatLRR)-based simplification step. This unique combination effectively suppresses common artifacts like oversharpening, spurious edges, and noise by decomposing the image into meaningful subspaces. The principal structural features are then optimally combined with a gamma-corrected luminance channel using an unsupervised MU-Fusion network, achieving a balanced optimization of both global contrast and local details. The experimental results on the challenging Test-C60 and OceanDark datasets demonstrate that our method consistently outperforms state-of-the-art fusion-based approaches, achieving average improvements of 7.5% in UIQM, 6% in IL-NIQE, and 3% in AG. Wilcoxon signed-rank tests confirm that these performance gains are statistically significant (p < 0.01). Consequently, the proposed method significantly mitigates prevalent issues such as color aberration, detail loss, and artificial haze, which are frequently encountered in existing techniques. Full article

The oxidative degradation of anthocyanins in red wine was investigated under controlled conditions using hydroxyl radicals generated in the presence of Cu (II) as a catalyst. A full factorial experimental design with 23 replicates was used to evaluate the effects of hydrogen peroxide concentration, catalyst dosage, and reaction temperature on anthocyanin degradation over a fixed time. Statistical analysis (ANOVA and multiple regression) showed that all three variables and the main interactions significantly affected anthocyanin loss, with temperature identified as the most influential factor. The combined effects were described by a first-order polynomial model. The activation energies for degradation ranged from 56.62 kJ/mol (cyanidin-3-O-glucoside) to 40.58 kJ/mol (peonidin-3-O-glucoside acetate). Increasing the temperature from 30 °C to 40 °C accelerated the degradation kinetics, almost doubled the rate constants and shortened the half-life of the pigments. At 40 °C, the half-lives ranged from 62.3 min to 154.0 min, depending on the anthocyanin structure. These results contribute to a deeper understanding of the stability of anthocyanins in red wine under oxidative stress and provide insights into the chemical behavior of derived pigments. The results are of practical importance for both oenology and viticulture and support efforts to improve the color stability of wine and extend the shelf life of grape-based products. Full article