Search Results (682)

Visual Internet-of-Things (IoT) cameras and institution-controlled edge gateways increasingly collect artwork images in museums, galleries, and heritage sites. Centralizing these images can expose collection contents, exhibition layouts, and contextual information. This paper proposes FedArtSense, a privacy-preserving federated learning framework for artistic style and medium classification. FedArtSense combines discrepancy-adaptive dual-space prototype alignment, client-level differential privacy for model and prototype releases, and importance-aware shared sparsification compatible with secure aggregation. Experiments on WikiArt, ArtBench-10, and a seven-class Behance Artistic Media subset use emulated non-IID client partitions, persistent acquisition shifts, constrained uplinks, and client dropout. Under the default client-level target $(ϵ,\delta )=(6,{10}^{-5})$, FedArtSense obtains accuracies of $64.2\%$, $81.2\%$, and $75.3\%$, respectively, while reducing cumulative WikiArt uplink traffic to $11.5$ GiB. The results support FedArtSense as a privacy–utility–communication trade-off for gateway-assisted artistic image classification; retrieval, detection, aesthetic prediction, and direct battery-powered camera training are outside the evaluated scope. Full article

Image aesthetic assessment (IAA) has progressed from handcrafted visual features to deep neural models, yet fine-art evaluation remains difficult because aesthetic judgment depends on style, historical context, and formal composition. Large Vision-Language Models (LVLMs) offer strong multimodal reasoning capabilities, but their direct application to art critique can produce generic descriptions, unstable scores, and weakly interpretable judgments. We therefore propose the Aesthetic Expert Knowledge Injection (AEKI) framework, which translates formal art principles into structured, machine-executable instructions. AEKI operationalizes four dimensions—Contrast & Harmony, Rhythm & Flow, Symmetry & Balance, and Variety & Unity—and assigns style-dependent weights ${\mathbf{w}}^{*}$ across 16 artistic categories. The resulting three-stage pipeline performs style anchoring, expert-weight allocation, and structured instruction compilation before LVLM inference. We evaluate the framework on a multi-category painting collection and a balanced subset annotated by human evaluators. Comparisons with zero-shot LVLM baselines show improved alignment in both numerical scoring and critique professionalism, while ablation experiments clarify the contributions of style anchoring and dynamic weighting. These results indicate that domain knowledge can be incorporated into LVLM evaluation through a transparent rule-based layer, supporting applications in digital curation, computational aesthetics, and art education. Full article

Background/Objectives: Mandibular angle volumization with hyaluronic acid is used to redefine facial contours and improve the aesthetics of the lower third of the face. However, beyond the aesthetic outcomes, it is important to understand the impact of this intervention on the aesthetic perception of subjects undergoing the procedure. This preliminary prospective, non-randomized, uncontrolled clinical trial aimed to evaluate post-treatment aesthetic satisfaction and facial appearance perception in subjects who underwent mandibular angle volumization with hyaluronic acid. Methods: Ten adults (eight women and two men) with a mean age of 34.30 ± 11.20 years participated in the study. Subjects underwent injection of 2 mL of hyaluronic acid per hemiface, following the Medical Codes protocol. Volumetric analysis of the mandibular angle region was performed using the Vectra 3D imaging system. Aesthetic perception and facial self-image were assessed 60 days after the procedure using the Orofacial Esthetic Scale and FACE-Q questionnaires. Results: Volumetric analysis demonstrated descriptively higher values throughout the clinical follow-up on both sides, although no statistically significant differences were observed (p > 0.05). The questionnaires revealed high levels of aesthetic satisfaction and positive perception of facial appearance. On the Orofacial Esthetic Scale, a predominance of high aesthetic satisfaction was observed among subjects. Likewise, FACE-Q results demonstrated high levels of satisfaction related to facial appearance and self-image. Conclusions: Within the limitations of this preliminary secondary analysis, mandibular angle volumization with hyaluronic acid was associated with high post-treatment aesthetic satisfaction and favorable facial appearance perception at the 60-day follow-up. These findings are descriptive and warrant confirmation in larger controlled studies. Full article

Architecture is arguably the human activity most directly invested in giving form to material objects and spaces. Across cultures and historical periods, architectural practice has been inseparable from the deliberate shaping of matter into useful and meaningful configurations. Over the past two decades, however, form has appeared to lose its centrality within architectural discourse. Social, environmental, and technological agendas increasingly displace formal inquiry, reframing form as secondary, insufficient, or ethically suspect—a condition further intensified by the proliferation of AI-generated images. This article reviews the development of form in Western architectural culture by retracing three enduring lineages of formal logic—normative, generative, and aesthetic—rooted respectively in Platonic idealism, Aristotelian materialism, and Kantian aesthetics. While this genealogical framework offers conceptual clarity, it also reveals persistent tensions concerning the origin, agency, and value of form. Recent hybrid practices challenge the sufficiency of any single lineage, pointing instead toward a relational understanding of form as a mediating protocol between social values, material realities, and perceptual experience. The article advances a field-based model in which architecture operates within a dynamic space defined by these three poles, proposing form as an active and indispensable instrument of architectural thought and practice. Full article

This article offers a thematic classification of traditions attributed to the Companions (ṣaḥāba), the Successors (tābiʿūn), and early Islamic scholars and rulers concerning ring engravings, situating these inscriptions within the framework of aniconism in early Islamic culture. It should be stressed at the outset that the evidence examined here consists of later hadith compilations and ṭabaqāt (biographical) works rather than dated artefacts; the study therefore analyses how the Companions, Successors, and early authorities were remembered and portrayed within a textual tradition committed to writing in subsequent generations, not the objective material history of the earliest Muslim community. The study argues that such engravings were not merely expressions of individual preference, but rather constituted a cultural practice shaped by the aesthetic constraints generated by hadith literature’s cautious stance toward figural representation, a practice that became a shared, collective idiom. The inscriptions are examined under four thematic headings: religious expressions, reminders of death and the transience of worldly life, inscriptions conveying identity and moral counsel, and figural symbols. The expressions and symbols found on rings are then subjected to a sociological reading drawing on the concepts of collective memory, symbolic capital, and productive constraint, within the paradigm of material religion. The findings indicate that figural motifs were at least partially present in the early period, and that written inscriptions subsequently came to occupy a dominant position. This transformation demonstrates that the aniconism in hadith did not merely suppress visual imagery, but functioned as the generative force behind a distinctive symbolic idiom centered on the letter and the word. Furthermore, drawing on Birgit Meyer’s notion of sensational forms, it argues that the ring bound the sacred to sensory experience through legally regulated matter: the prophetic preference for silver over gold, copper, and iron; the Abyssinian stone; the turning of the bezel toward the palm; and the pressure of the seal into clay. Aniconism thus operated not only as a rule about images but as a regime governing the material, tactile, and even olfactory life of a wearable object. While scholarship on Islamic aniconism has focused primarily on monumental art, architecture, and manuscript illustration, this study redirects attention to ring inscriptions as an underexplored domain of material culture, showing that ring inscriptions, though largely overlooked, are informative witnesses to Islamic culture and theology at the most intimate scale of everyday devotional and political life. Full article

Bio-inspired architectural design increasingly relies on generative artificial intelligence to expand early-stage concept exploration, yet current workflows often suffer from vague requirement definition, subjective proposal selection, and weak connections between user expectations, visual generation, and design evaluation. This study proposes a closed-loop human–AI decision-support framework for biomimetic architectural concept generation. The framework first uses Kansei-oriented requirement analysis and the KANO model to identify and classify stakeholder expectations concerning morphology, structural rationality, environmental integration, cultural narrative, visual novelty, interactivity, and sustainability. On the basis of 282 valid questionnaire responses, the most influential requirement categories are further translated into an Analytic Hierarchy Process (AHP) hierarchy, where expert judgement from a five-member specialist panel is used to derive criterion and sub-criterion weights. These weights are then converted into structured prompts—via a formally specified weight-to-language conversion strategy—to guide a diffusion-based image-generation system toward more targeted biomimetic concepts. Finally, TOPSIS is applied to rank generated design alternatives according to the same weighted criteria, thereby creating a traceable link from requirement discovery to generation and decision-making. Case studies involving eagle-, manta ray-, and cheetah-inspired architectural concepts indicate that the framework improves the explicitness of design objectives, supports more consistent comparison among alternatives, and reduces reliance on purely intuitive aesthetic judgement. An ablation comparison confirms that each stage of the framework contributes incrementally to the quality of final outcomes. This study proposes an integrated workflow that combines requirements modeling, multi-criteria evaluation, and AI-assisted visual design. Full article

Impressionist artworks, marked by distinctive brushstrokes and light effects, pose challenges for holistic deep learning models. Existing classification methods often lack interpretability and mathematical rigor. To address this, we propose an explainable AI framework for Impressionist painting classification based on feature disentanglement. The framework uses Fourier transform to decompose images into magnitude and phase spectra and then applies frequency filtering to separate high-frequency components (brushstroke textures, edges) from mid-to-low frequencies (global composition, color transitions). A state space model captures long-range dependencies within frequency representations. Disentangled features are fused with the original image features via a dual-branch injection mechanism. Experiments show that a lightweight model with 10M parameters, using this injection strategy, outperforms conventional baselines with 25M parameters. Moreover, the approach provides interpretability by explicitly linking classification decisions to brushstroke organization, frequency energy distribution, and semantic composition. This work offers a unified, computationally efficient, and mathematically rigorous solution for feature disentanglement in artistic image analysis, laying a theoretical foundation for explainable computational aesthetics and human–AI collaborative appreciation. Full article

Cultural ecosystem services (CES) are widely measured but rarely attributed to the specific landscape elements that generate them. We coupled element-level image recognition with service-level text analysis across 20,447 reviews and 18,997 photographs from three social media platforms covering 15 national-, provincial-, and municipal-level forest parks in Guangzhou, China (2020–2024). A 2660-term dictionary quantified nine CES; a fine-tuned deep learning classifier identified 28 landscape elements; multiple correspondence analysis described the element-service structure and ridge regression tested associations within four case parks. Natural elements aligned with ecological, aesthetic, and inspirational services and built elements with cultural, social, and wellness services, but two results qualify that division. First, individual elements were associated with different services in opposite directions: seasonal forest with higher aesthetic appreciation but lower recreation, water features with higher aesthetic value but lower inspiration. Second, the mapping differed across the four case parks rather than holding constant; in the municipal case park, only built facilities positively predicted social interaction. These four parks are illustrative exemplars rather than representative samples of their tiers. Dynamic biological elements (birds 0.43%, insects 0.12%, fish 0.08%) ranked lowest of all 28 elements. These are descriptive associations awaiting mechanistic explanation; on that reading, planning for CES would be better organized around intended services than element inventories, calibrated to the individual park. Full article

Background. In recent years, the use of ultrasound in the diagnosis of cellulite has grown substantially, making reproducible and validated ultrasound-based grading systems for stage III cellulite increasingly necessary to support their accurate application in both clinical practice and research. The Intagliata Echo-Cellulite (IEC) staging system identifies three morphological sub-types using high-frequency ultrasound. Objective. The study aims to evaluate the inter-rater reliability and test–retest reliability of the IEC staging system. Methods. This prospective, image-based reliability study included 150 women with stage III cellulite at a single center. Standardized ultrasound images acquired by an expert were independently rated by two non-expert raters in two sessions four weeks apart and compared with the expert’s ratings; the expert is also the developer of the IEC system. Results. For the primary outcome, IEC stage, both raters achieved almost perfect inter-rater agreement with the gold standard (Rater 1: κ = 0.926, 93.3%; Rater 2: κ = 0.985, 98.7%) and almost perfect test–retest consistency (Rater 1: κ = 0.840; Rater 2: κ = 0.817). Agreement on secondary ultrasound-based variables was more heterogeneous and consistently lower than for the composite IEC stage. Limitations. The image-based design provides an upper bound reliability estimate; additionally, the gold standard rater is the developer of the IEC system, which constrains the independence of the reference standard. Conclusions. Even when applied by untrained raters, the IEC staging system shows high inter-rater reliability and test–retest consistency. These findings further independent validation as a standardized grading tool in cellulite research and precision aesthetic medicine. Full article

Social media has become an important tool for understanding visitor experiences in museums and cultural heritage sites. This literature review identifies, organizes, and thematically synthesizes existing studies on museum visitor experience based on social media data. It examines 41 studies retrieved from Scopus and Web of Science and published between 2017 and 2026. Furthermore, the review examines the selected studies across six dimensions: social media platforms, types of user-generated data, the role of digital interactions, the museums and cultural heritage sites studied, the analytical methodologies applied, and the main findings on visitor experience. The findings indicate that TripAdvisor is the most frequently used platform for collecting textual reviews and star ratings, whereas Instagram and Flickr are mainly used for visual and spatial data. Most studies rely on computational methods, often combined with quantitative techniques, while qualitative approaches are used less frequently. The identified methods include content analysis, statistical analysis, sentiment analysis, topic modeling, machine learning, image analysis, and spatial analysis. Across the reviewed studies, visitor experience is examined as a multidimensional phenomenon encompassing emotions, service quality, authenticity, historical connection, aesthetics, education, and social participation. Finally, the review identifies recurring themes across the dimensions and synthesizes them into broader research streams. These are brought together in an integrative synthesis framework that organizes existing research, highlights research gaps, and outlines directions for future studies. Full article

Aesthetic perception of rural streetscapes reflects individuals’ cognitive responses to their surroundings and is central to understanding how landscape preferences are formed. Existing studies using Scenic Beauty Estimation (SBE) are constrained by incomplete indicator systems and overreliance on linear approaches. This study proposes an interpretable machine learning framework that integrates multi-source data to examine the nonlinear influences of streetscape features on SBE. Using Sanguan Village, a water-networked settlement in Jiangsu, we developed a 24-indicator system spanning color, spatial, natural, artificial, and cultural dimensions. Based on 523 panoramic images and aesthetic ratings from 1175 respondents, we compared OLS, DT, MLP, SVR, RF, and XGBoost models. The best-performing XGBoost, combined with SHAP analysis, revealed threshold effects and interaction patterns among variables. Green visibility, architectural aesthetics, building visibility, sky visibility, environmental coordination, and water are the top six feature variables most strongly associated with rural streetscape aesthetic perception, and each exhibits threshold effects. The saturation threshold for green visibility is 0.153, and architectural aesthetics can only make a positive contribution when its score exceeds 3.815. The appropriate range for building visibility is below 0.452, while the optimal value for sky visibility is approximately 0.194. We also explored the context-dependence of these threshold effects across urban and rural settings. This study proposes streetscape optimization strategies focusing on screening key factors, controlling their thresholds, and coordinating the allocation of streetscape features. The interpretable analytical framework for rural scenic beauty established in this research can facilitate evidence-based landscape optimization and provide scientific support for sustainable rural development and tourism in this case. Full article

Product concept images combine symmetry, closure, balance, and repeated components. Existing shape analysis and computational aesthetic methods can quantify these properties; however, when evidence is reduced to global descriptors or aggregate scores, image-layer provenance and sensitivity to rasterization or heuristic settings may be obscured. This paper presents a traceable image-processing pipeline based on scenario framing, alternative specification, geometry-informed computation, evidence synthesis, and design embodiment (SAGE-D), evaluated on four controlled smart-speaker alternatives using separate body, light-band, and aperture masks. Seven dimensionless descriptors measure silhouette reflection, centroid balance, light-band closure, aperture regularity and gradient, component-scale retention, and contour compactness. Resolution resampling, one-pixel morphology, parameter perturbation, and synthetic controls assess sensitivity. At $512\times 512$ pixels, A, B, and R showed exact bilateral silhouette consistency; B and R showed complete light-band occupancy; and C and R showed strong downward aperture-radius gradients. Conventional same-mask measures gave concordant geometric readings, while leave-one-gate-out analysis showed that screening depended mainly on predefined closed-ring and linear-gradient requirements. Only R passed all six case gates. SAGE-D is used here as an auditable organization of layer-specific measurements and bounded screening rules, not as a superior descriptor set. The conclusions are limited to the supplied two-dimensional (2D) representations and do not establish population-level generalizability, preference, or engineering performance. Full article

Contextual meaning can influence art evaluation even when viewers encounter images within a structured visual stimulus family. This exploratory questionnaire-version study examined whether value-oriented textual descriptions were associated with aesthetic ratings of AI-generated variants of classical paintings in three Chinese-language questionnaire versions emphasising cultural value, artistic value, or social value. The available dataset contained 61 participants, each rating 40 images on a 1–10 aesthetic scale, yielding 2440 complete observations. A post hoc three-rater manipulation check of 30 image–description pairs found that all evaluated pairs satisfied the applied validation criterion; inter-rater reliability across item–dimension judgments was high at ICC(2,k) = 0.936. The primary analysis used a linear mixed-effects model with crossed random intercepts for participant and stimulus identity, and a fuller by-stimulus random-slope model was estimated as a diagnostic response to review. Relative to social-value descriptions, artistic-value descriptions were associated with higher ratings in the random-intercept model, where b = 1.74, SE = 0.57, z = 3.03, p = 0.002, 95% CI [0.62, 2.87], and this contrast also persisted in the diagnostic by-stimulus random-slope model, although that model converged with a non-positive-definite Hessian. Cultural-value descriptions were intermediate and should not be interpreted as showing a stable general advantage over social-value descriptions. The results therefore provide qualified evidence for an artistic-versus-social framing association, not a confirmed causal effect of all value-cue conditions. Interpretation remains bounded by the modest sample, undocumented allocation procedure, rapid-completion records, incomplete prompt metadata, and post hoc validation of a representative rather than exhaustive stimulus set. Full article

Background and Objectives: Dentofacial deformities require a multidisciplinary surgical–orthodontic protocol (SOP) in which orthodontic preparation, orthognathic surgery, postoperative finishing, and retention are closely coordinated to achieve stable functional and aesthetic outcomes. The increasing adoption of clear aligners, digital workflows, and artificial intelligence (AI) has profoundly modified this therapeutic pathway. This communication examines the role of clear-aligner therapy and AI throughout the contemporary surgical–orthodontic protocol, with particular emphasis on their integration into clinical practice. Discussion: From the surgical perspective, clear aligners provide treatment outcomes comparable to those achieved with conventional fixed appliances while offering greater predictability of treatment duration through digital treatment planning. However, their use requires careful management of specific clinical aspects, including surgical timing, intraoperative anchorage, postoperative dentoalveolar stabilisation, transverse dimension management, and retention, all of which demand close collaboration between the orthodontist and the maxillofacial surgeon. The communication also summarises current AI applications in orthodontics and orthognathic surgery, including automated cephalometric analysis, image segmentation, treatment-decision support, virtual patient construction, clear-aligner setup, soft-tissue prediction, refinement-risk assessment, and remote monitoring. Although AI has significantly improved the efficiency, reproducibility, and standardisation of diagnosis and treatment planning, current evidence supports its use as a clinician-supervised decision-support technology rather than as an autonomous system capable of managing the entire orthodontic–surgical pathway. Conclusions: The integration of clear aligners, digital planning, and AI represents an important step toward a more personalised and efficient workflow, while continued clinical validation and multidisciplinary expertise remain essential for achieving predictable long-term outcomes. Full article

Background: Breast implant illness (BII) is a constellation of non-specific systemic and local symptoms—including fatigue, joint pain, cognitive dysfunction, and autoimmune-like manifestations—attributed to silicone breast implants. Although BII remains a controversial clinical entity, accumulating evidence suggests symptom improvement following implant removal; however, causal mechanisms and optimal surgical strategies remain uncertain. Objective: The objective was to evaluate the prevalence of BII symptoms and the effect of explantation with en bloc total capsulectomy on symptom resolution in affected women. Methods: A prospective case series of 50 women who underwent explantation with total capsulectomy between 2023 and 2025 was conducted (Level IV evidence). The BII Questionnaire of the American Society for Aesthetic Plastic Surgery (ASAPS) was administered to assess preoperative and one-year postoperative symptom burden. Perioperative data—including implant characteristics, capsular findings, and imaging results—were analyzed. Symptom changes were assessed using descriptive statistics and nonparametric tests. Results: The mean age at explantation was 43 years, with a mean age at implantation of 31 years. Implants were predominantly placed in the retropectoral plane (80%). Intraoperative rupture was identified in 34 patients (68%). At one-year follow-up, a statistically significant reduction in symptom burden was observed, with an 81.7% decrease in mean symptom frequency (preoperative mean: 10.79 vs. postoperative: 1.97; p < 0.001). The most pronounced improvements were noted in chronic fatigue, cognitive impairment, and delayed wound healing. No surgical complications were recorded, and aesthetic outcomes were satisfactory among patients who underwent single-stage mastopexy. Conclusions: Explantation with en bloc total capsulectomy is associated with substantial symptom improvement in women presenting with BII. Although the precise pathophysiology of BII remains elusive, these findings support a patient-centered approach incorporating thorough preoperative evaluation and shared decision-making. Future research should prioritize the development of standardized diagnostic criteria, biomarker validation, and patient subgroup stratification to optimize clinical management and further advance the understanding of BII. Limitations: The absence of a control group precludes causal inference. Objective clinical and immunological assessments were not performed. Patient-reported symptoms were not corroborated by formal clinical evaluation. Most patients were self-referred, introducing referral and expectation bias. The sample size was small. Full article