Search Results (65)

This study proposes a methodology for developing nature-inspired color palettes for timeless residential interiors based on classical principles of beauty and chromatic harmony. The research employed a literature review of color theory, a survey, and a research-through-design approach. To investigate residential color preferences, a survey was conducted among older adults and undergraduate architecture students using examples of living room interiors representing different color palettes. Based on the survey findings, the color palette positively evaluated by both participant groups was identified. The results indicated a preference for a balanced palette characterized by muted tones, subtle tonal transitions, and harmonious chromatic relationships. Building on these findings, an original design methodology was developed, drawing on the observed color interactions and compositional patterns of the natural environment. The proposed methodology was subsequently applied within an AI-assisted design workflow to generate and evaluate residential interior concepts through a text-to-image process. In addition, two approaches to residential color design were compared: a traditional approach based on color theory and color-wheel harmonies, and a nature-inspired approach informed by the questionnaire findings and supported by the proposed AI-assisted design workflow. The study demonstrates how nature-inspired color relationships, classical color harmony principles, and AI-assisted visualization can be integrated into a structured methodology supporting the design of coherent and timeless residential interiors. Full article

Soy protein, apple fiber, and corn starch are widely used functional ingredients, yet their combined effects on food matrix properties remain poorly characterized. A D-optimal mixture design (16 runs) was used to evaluate how these three components, individually and in binary and ternary combinations, determine the proximate composition, CIELab color parameters, and techno-functional properties (water and oil absorption and solubility, pH, apparent density, emulsifying and foaming capacity, least gelation concentration, and foam stability over 120 min) of model blends. Response surface models were statistically significant for 19 of the 21 responses evaluated (R² = 0.70–1.00, p ≤ 0.05); water and oil absorption capacity did not reach significance (R² = 0.66–0.72, p > 0.05). Formulation was the main driver of the system’s behavior. Starch increased moisture, carbohydrate content, and lightness; protein determined ash, protein content, and water solubility; and fiber dominated crude fiber, lipid content, and red–yellow chromaticity, producing the greatest total color difference relative to pure starch. Unlike composition and color, which followed largely additive, single-ingredient-driven trends, interfacial functionality was governed by strong binary interactions: a synergistic protein–fiber interaction dominated emulsifying capacity (positive) and foaming capacity (strongly negative, almost completely suppressing foam formation even at protein levels comparable to the pure-protein vertex), while a synergistic protein–starch interaction enhanced foam stability. Water and oil absorption capacities varied within narrow, statistically non-significant ranges, indicating structural rather than compositional control. These findings show that mixture design and response surface methodology can quantitatively predict and tune the physicochemical, color, and functional performance of protein–fiber–starch blends, providing a practical framework for designing plant-based functional ingredients with targeted nutritional and technological profiles. Full article

The valorization of food industry by-products is a promising strategy for developing natural additives to increase food quality. This study examined the efficiency of tomato processing industry waste (TPIW), which is a significant agro-industrial by-product, in enhancing the oxidative stability of three common edible vegetable seed oils (i.e., sunflower, soybean, and corn oils) under accelerated storage conditions. A custom response surface methodology (RSM) approach was employed to design and optimize the experiments, also using butylated hydroxytoluene (BHT), a potent synthetic antioxidant (i.e., oil type, TPIW and/or BHT enrichment). Oils were incubated under controlled conditions at 60 °C for 28 d (Schall oven test), wherein both darkness and light exposure were employed. Untreated (control), TPIW-enriched, and BHT-fortified (positive control) oils were examined in this study. The oxidative stability and shelf-life of oils was thoroughly evaluated using standard oxidative indices for both primary and secondary oxidation by-products, antioxidant capacity (DPPH radical scavenging activity), total carotenoid content, chromatic coordinates (CIE 1976 L*a*b*), and Fourier-Transform Infrared spectroscopy to monitor structural changes. The results revealed that enrichment with TPIW significantly (p < 0.05) reduced both primary and secondary oxidation products compared to untreated oils, approaching the protective efficiency of BHT in some assays. Specifically, it was observed that the combination of soybean oil enriched with both BHT and TPIW was the most preferable to enhance oxidation stability. Results from FT-IR supported these findings; slower formation of oxidative derivatives was revealed. Light exposure did not show a significant impact on the oxidation process regardless of the oil sample when compared to the temperature parameter. The results of this study confirm that TPIW could assist shelf-life prolongation of edible vegetable oils and promote a circular economy strategy by valorizing food by-products as a viable alternative to synthetic antioxidants. Full article

Thresholds are not simply separations between spaces; they are relational conditions through which interior spatial experience and subjectivity are formed. How thresholds are constituted through interiority, and how they produce different experiential regimes, remain less examined. Drawing on phenomenological and post-phenomenological perspectives, this article repositions the domestic threshold through the animated interiors of Encanto (2021) and Coraline (2009). These films offer two comparable cases in which similar spatial devices produce markedly different experiences. A scene-based comparative coding analysis, conducted with MAXQDA, traces five interior parameters: boundary elements, material articulation, chromatic strategies, kinetic spatial behaviors, and object relations. These parameters give rise to two distinct threshold regimes. In Encanto, a supportive regime cultivates belonging, recognition, and spatial integration; in Coraline, a deceptive and manipulative regime produces disorientation, alienation, and the uncanny. The threshold is therefore understood both as an atmospheric and multisensory experience, as phenomenology emphasizes, and as a mediating spatial arrangement that positions the subject within specific relational networks. By proposing the concept of the threshold regime, the study offers a theoretical and methodological framework for understanding domestic interiority as a dynamic, multilayered, and relational spatial formation. Full article

The growing demand for aesthetic and functional outcomes in periodontal and implant procedures has increased the use of connective tissue grafts harvested from the palate. Objective monitoring of the donor site remains challenging because healing involves progressive three-dimensional morphological changes and visible chromatic variations of the mucosal surface. This pilot feasibility study proposes an optical sensing and computer-vision workflow based on longitudinal intraoral scanner acquisitions to quantify palatal wound healing after soft-tissue harvesting. A TRIOS 3 intraoral scanner was used as a non-invasive sensing device to acquire textured three-dimensional datasets of the palatal donor area at baseline, immediately after surgery, and during follow-up at 1 and 2 weeks and at 1 and 3 months. The scanner output, consisting of surface geometry and color information, was processed as multimodal 3D data. The workflow included mesh preprocessing, reference-based registration of serial scans, robust alignment using geometric, normal, and chromatic cues, region-of-interest identification, and signed volumetric difference computation. Sensor-related uncertainty was addressed through an additional in vivo repeatability assessment on healthy volunteers and by comparison with previously published accuracy and precision data for the TRIOS scanner series. The resulting volumetric maps and healing curves enabled objective quantification of local tissue loss, swelling, and progressive recovery over time. Chromatic information from the textured scans was also considered as an additional sensing descriptor of mucosal healing. By integrating intraoral optical sensing, three-dimensional surface reconstruction, multimodal mesh registration, and quantitative volumetric analysis, the proposed approach provides a preliminary non-invasive framework for monitoring palatal donor-site healing. Six patients undergoing palatal soft-tissue harvesting were monitored using a TRIOS 3 intraoral scanner at baseline, immediately after surgery, and during follow-up at 1 and 2 weeks and at 1 and 3 months. Although all clinically evaluated patients exhibited complete clinical re-epithelialization by 3 months, quantitative 3D analysis revealed a persistent residual volumetric deficit, indicating that visual healing does not necessarily correspond to complete soft-tissue volume restoration. This sensor-based methodology may support clinical follow-up, improve the objectivity of soft-tissue assessment, and contribute to the development of digital biomarkers for oral wound healing. Full article

Ulluco (Ullucus tuberosus), the second most economically important Andean tuber after potato, has been cultivated for over 5500 years. Despite its resistance to frost, drought, and high altitudes, as well as its biochemically complex profile, ulluco remains underrepresented in the scientific literature and absent from international markets. This comparative review synthesises the evidence available up to November 2025 regarding its biology, nutritional profile, phytochemistry, and food industry applications relative to four other Andean tubers: oca (Oxalis tuberosa), mashua (Tropaeolum tuberosum), native potato (Solanum tuberosum L.), and yacon (Smallanthus sonchifolius). The main comparative findings are as follows: First, ulluco is the only Andean tuber that biosynthesises betalains instead of anthocyanins, producing up to 32 distinct compounds that are stable across a pH range of 3–7, a chromatic stability advantage over anthocyanin-based pigments from mashua, oca, and native potato, which suggests its potential as a source for the development of clean-label natural colourants. Second, among the five species evaluated, ulluco protein content across different morphotypes ranges from 5.60 to 15.7 g/100 g dry weight, ranking within the upper range of values reported for mashua and oca, and comparable to or higher than the upper ranges reported for native potato and yacon. This variability reflects the genotypic and ecogeographical diversity of the evaluated accessions and is not a methodological inconsistency, with 20% of varieties exceeding 10 g/100 g and providing six essential amino acids, supporting genetic improvement programmes aimed at nutritional security. Third, ulluco starch exhibits a low gelatinisation temperature (56–60 °C), a high amylose content (24–36%), and pseudoplastic behaviour, properties comparable or superior to potato starch for specific applications, with technical viability validated at a laboratory scale in applications including biodegradable films, food 3D printing inks, and dehydrated snacks. Unlike yacon, which accumulates fructooligosaccharides and lacks starch, ulluco aligns with oca, mashua, and potato as a starch-accumulating species. Critical gaps identified include the absence of clinical evidence on betalain bioavailability, the lack of a complete nuclear genome assembly, and the non-existence of standardised processing methods for industrial scaling. A coordinated agenda that integrates clean seed programmes, pilot-scale validation, and genomic breeding is essential for the bioeconomy of the 21st century to transform ulluco into a high-value ingredient. Full article

Low-light image enhancement (LLIE) is a fundamental task in computer vision, required for restoring luminance, contrast, and structural fidelity in images captured under suboptimal lighting environments. This paper introduces an optimization-driven, scene-adaptive LLIE framework, designated as $O{M}_{\mathrm{I}\mathrm{D}\mathrm{C}\mathrm{P}}^{\mathrm{G}\mathrm{C}\mathrm{G}\mathrm{L}}$, which exploits the optical duality between low-light inversion and atmospheric scattering. The proposed methodology transforms low-light inputs into quasi-haze representations through an optical inversion process, followed by structural restoration using an Improved Dark Channel Prior ($M_{\mathrm{I}\mathrm{D}\mathrm{C}\mathrm{P}}$) baseline. To refine the restored output, a Gamma Correction with Global Limits (GCGL) module is integrated as a boundary constraint to mitigate localized over-exposure and preserve chromatic consistency. A core novelty of this framework lies in the deployment of metaheuristic optimization algorithms (MOAs)—specifically the Gray Wolf Optimizer (GWO), Harris Hawks Optimization (HHO), and Marine Predators Algorithm (MPA)—to autonomously resolve optimal, image-specific parameter configurations. This search paradigm is guided by perception-driven fitness functions, namely the Patch-based Contrast Quality Index (PCQI) or the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE). Quantitative and qualitative evaluations across a comprehensive pool of 1092 benchmark images demonstrate that the proposed framework exhibits robust statistical resilience and cross-dataset generalization compared to four state-of-the-art deep learning methods. While data-driven deep learning architectures retain localized superiority under the extreme degradation boundaries of the DARK FACE dataset, the proposed physics-inspired optimization framework achieves the leading overall cross-dataset aggregate ranking ($\overline{R}=2.467$) across diverse evaluation environments due to its per-image dynamic solution space mapping. Full article

This research represents an advancement in smartphone-based image acquisition methodology, building upon a previous study to estimate the essential oil content of bergamot fruits in situ using a deep learning approach. To overcome an operational constraint due to a bulky portable dark box to standardise illumination, this study proposes a more versatile solution: a mobile application based on a colour card reference. By replacing physical shielding with digital compensation, the app functions as a local colourimetric sensor, enabling real-time correction of images acquired directly in the orchard, regardless of environmental variables such as direct sunlight or shadows. Workflow relies on an automated calibration procedure. Upon image acquisition, the application utilises ArUco Markers to autonomously detect and extract both the colour card and the fruit surface. The core of the innovation lies in the colour calibration algorithm based on RGB histogram matching logic, which calculates the precise chromatic transformation required to align the field data with the reference card data (acquired under controlled conditions). These calculated parameters are then dynamically mapped onto the fruit’s image. The final output is a normalised high-fidelity image, ready for the calculation of chromatic indices, such as the citrus colour index, or for seamless integration into predictive models. The results show that the application is a valid tool for colour calibration, thanks to the good agreement with the values obtained using the inspection chamber. The latter can therefore be replaced by the app, which allows reliable results to be obtained even when used on its own. Full article

Façades play a decisive role in shaping the visual and symbolic character of historic urban environments. Recent European funding schemes promoting energy-efficient retrofitting have accelerated interventions on building envelopes. Although aligned with decarbonization objectives, these processes are generating significant chromatic and material transformations that risk eroding the visual coherence and cultural sustainability of consolidated urban areas. In the historic Ensanches of San Sebastián, the replacement of traditional envelope systems with new cladding solutions is leading to the loss of the architectural style of some facades and altering their materials, textures, and colors. A progressive “contagion effect” has been identified, whereby dissonant chromatic schemes—often associated with the proliferation of so-called “zebra blocks”, residential buildings with façades clad in alternating black and white stripes that have proliferated in recent urban developments—are replicated across adjacent buildings, gradually weakening spatial continuity and the genius loci of the neighborhood. In response to this phenomenon, this research develops a systematic methodology to analyze, quantify, and anticipate chromatic transformation in consolidated urban fabrics. The study combines historical morphological analysis, classification of architectural periods, and chromatic mapping of recent façade interventions. Based on this framework, a CARI, Chromatic Alteration Risk Index is proposed to evaluate the potential impact of façade alterations on urban chromatic coherence. Drawing on an epidemiological framework, the methodology enables the identification of critical transformation clusters, the assessment of contagion dynamics, and the definition of regulatory thresholds for color and material interventions. By integrating perceptual criteria, urban morphology, and spatial distribution patterns, the study moves beyond descriptive diagnosis and offers a transferable tool for municipal planning. The proposed approach supports the proactive regulation of façade rehabilitation processes, balancing energy efficiency objectives with the preservation of collective memory, material identity, and urban sensory quality. This study proposes a quantitative model of “urban chromatic contagion” to assess how façade color interventions propagate within a neighborhood. We define the Chromatic Integration Percentage (CIP) and the Chromatic Alteration Risk Index (CARI) of the analyzed area. Results indicate that poorly regulated façades show higher chromatic dissonance (low CIP) and act as contagion hotspots, while a clear risk gradient emerges: highly protected buildings present lower risk, whereas mixed typologies and recent rehabilitations concentrate higher CARI values. The model supports preventive urban color management by identifying areas at risk before visible alteration. Full article

The growing demand for clean-label products has intensified the search for natural and sustainable alternatives to synthetic colorants. Anthocyanins stand out as promising pigments due to their coloring capacity and bioactive properties. This study evaluated the efficiency of natural deep eutectic solvents (NADES) in extracting anthocyanins from agro-industrial by-products—molasses grass, black corn cobs, and grape skins—and their application in food and cosmetic matrices. A simplex-centroid mixture design with Response Surface Methodology was used to optimize solvent composition based on sorbitol, citric acid, and glycine. NADES showed high extraction efficiency, especially for black corn cobs, reaching 54.20 mg/100 g under optimized conditions. Although conventional extraction performed better for grape skins, NADES demonstrated competitive efficiency and superior environmental performance (AGREE index 0.73 vs. 0.58). The extracts were successfully incorporated into yogurt and moisturizing gel formulations. Yogurts maintained stable physicochemical properties and color, while gels showed good homogeneity and chromatic stability. These findings support the use of NADES as green solvents for recovering natural colorants from agro-industrial residues, with potential applications in sustainable food and cosmetic products. Full article

This study presents a multi-analytical investigation of two Baroque gilded terracotta sculptures—Hercules and the Nemean Lion (Hercules A) and Hercules and the Lernaean Hydra (Hercules B)—attributed to Lorenzo Vaccaro (1655–1706) and preserved at the Museo Civico Gaetano Filangieri in Naples. This research aimed to reconstruct the original manufacturing technique, characterize materials introduced by successive restoration interventions, and identify active degradation mechanisms. A systematic diagnostic approach integrating UV fluorescence imaging, digital optical microscopy, portable energy-dispersive X-ray fluorescence spectroscopy (EDXRF), Raman spectroscopy, Fourier-transform infrared spectroscopy in attenuated total reflectance mode (FTIR-ATR), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), and spectrocolorimetry was applied. The original gilding system—comprising a ferruginous silico-aluminous terracotta substrate, a calcium sulfate ground, a lead-white imprimitura, an iron-rich bole, and a thin gold leaf—is consistent with documented Baroque mission gilding practices in Southern Italy. Analytical evidence further documented extensive non-original interventions, including copper-based artificial patination, bronze powder (porporina) integration, poly (vinyl acetate) adhesives, and acrylic protective coatings. Raman spectroscopy identified the in situ conversion of intentionally applied tenorite (CuO) to malachite (Cu₂CO₃(OH)₂) as an active degradation pathway. Spectrocolorimetric measurements quantified chromatic alterations of up to ΔE = 52 attributable to accumulated surface deposits. The proposed integrated methodology constitutes a replicable diagnostic framework for investigating gilded terracotta artefacts in museum collections. Full article

Background/Objectives: From a phenomenological perspective, the body is not merely a biological entity but the primary medium through which we experience and interpret the world. This study aimed to understand the lived body experience of advanced physiotherapy students at a university in Cali, Colombia, exploring how significant life events are embodied and expressed. Methods: A qualitative phenomenological design was employed. Twenty physiotherapy students participated in a body mapping exercise within a mental health elective. Participants graphically represented sensations, emotions, and memories on a body silhouette using colors and symbols. Data from the resulting body maps were analyzed using a thematic analysis approach via a data extraction matrix to identify patterns in symbolic, chromatic, and narrative elements. Results: The analysis revealed that students consistently inscribe both traumatic and positive life events onto their body maps, illustrating a narrative of resilience. Specific colors and body parts were symbolically charged: black and red in the heart, head, and shoulders represented pain and emotional burden, while blue and green in areas like the hands and stomach signified stability and achievement. External symbols (e.g., landscapes, bicycles) served as emotional anchors or representations of personal growth. Conclusions: Body mapping proves to be a powerful technique for accessing the embodied, often non-verbal, narratives of students. It underscores that the body functions as a living archive of experience. Integrating such methodologies into physiotherapy education can significantly enrich professional training by fostering sensitivity to corporality as a lived, relational, and cultural phenomenon, thereby strengthening future clinicians’ holistic and humanistic competencies. Full article

Accurate and timely diagnosis of citrus diseases is essential for reducing economic losses in global agriculture. Although deep learning models provide high diagnostic accuracy, their computational demands often hinder deployment on resource-limited edge devices. To overcome this challenge, this study proposes an optimized hybrid framework for phytopathological classification. The methodology combines handcrafted descriptors (Blue-Green-Red “BGR” color statistical moments) with hierarchical spatial abstractions derived from a pre-trained Visual Geometry Group 16-layer (VGG16) deep architecture. An initial high-dimensional feature space was created by concatenating 360 handcrafted statistical descriptors and 12,800 deep textural features. By implementing a Wrapper-Greedy Stepwise selection strategy, this original space was reduced by over 96%. The resulting Elite Model identifies 12 and 18 critical attributes across two independent, transcontinental datasets (Mexico and Pakistan, respectively), effectively capturing both subtle chromatic anomalies and complex structural lesions. Experimental benchmarking confirms that this parsimonious hybrid approach delivers robust classification accuracy ranging from 87.30% to 95.23%, significantly outperforming unimodal architectures. Ultimately, this framework provides a highly efficient, interpretable, and scalable solution for real-time disease monitoring in precision agriculture. Full article

In the context of advancing manufacturing, production systems are shifting toward human-centric and personalized production. However, accurately quantifying subjective user needs into precise product specifications remains a challenge. Taking child companion robots as an example, this paper proposed a novel product innovation design framework based on Extenics and Kansei engineering to optimize the texture design of smart products. By systematically integrating synergistic relationships among colour, material, and surface processing technology, the framework aimed to enhance the sustainable value and social sustainability of products by more precisely meeting users’ perceptual and emotional needs. The research methodology employed the semantic differential method to quantify user perception and utilized the K-means clustering algorithm to construct a chromatic colour sample library for smart products. Subsequently, by combining the multi-criteria decision-making tool grey relational analysis with statistical verification, the optimal design scheme was selected from the generated alternatives. Experimental results demonstrated that this method significantly reduced design subjectivity and ambiguity. By bridging the gap between user expectations and engineering solutions, the framework provides a systematic solution for mass customization and process optimization that promotes resource efficient and sustainable production, while also reducing the resource waste associated with traditional trial and error design processes. Full article

Historic towns often lack thorough records, complicating the study of long-term material changes in the built environment. This study develops RoofChronoNet, a machine learning workflow that extracts roof covering classes from grayscale imagery and quantifies roofscape change over time. Applied to Tirilye (Bursa, Turkey), historical aerial photographs from 1970 and 1984 are colourised using a pix2pix generative adversarial network trained on 2022 imagery. A YOLOv11m-seg model then detects roof surfaces and classifies them into three roof covering categories: red, white, and dark grey, producing diachronic roofscape maps for 1970–2022. Bounding box detection reached mask mAP@0.50 of 0.81 (2022), ≈0.71 (1984), and 0.76 (1970, single class), while class-averaged mask mAP@0.50 was lower due to pixel-level delineation complexity. Results indicate the persistence of red-tiled roof regimes within the historic core alongside a growing presence of white and dark-grey roof coverings in peripheral areas, consistent with renovation-driven material diffusion after the 1980s. Methodologically, the study contributes a reproducible framework that operationalises chromatic differentiation as a measurable variable for mapping roof covering regimes in planning history research using monochrome historical aerial imagery. RoofChronoNet supports heritage-oriented and planning history interpretations of material regime shifts in data-scarce contexts; however, colourised outputs are synthetic and probabilistic, and spatial inferences should be corroborated with archival or field-based evidence where feasible. Full article