Search Results (12,007)

Adobe is a sustainable yet highly porous construction material, inherently vulnerable to moisture and environmental pollution, which poses challenges for both contemporary construction and heritage conservation. This study presents multifunctional coatings that combine hydrophobic/oleophobic and photocatalytic properties to enhance adobe durability. The coatings incorporate nano-heterostructured LaFeO₃ photocatalysts into water-repellent and hydro-oleo-repellent formulations, selected to preserve the characteristic dark brown color of adobe. Microstructural analyses revealed the formation of non-uniform protective layers, particularly in hydro-oleo-repellent systems, which influenced performance. The treated surfaces exhibited significant water and oil repellency, while maintaining adequate vapor permeability. Durability tests confirmed improved resistance to water ingress, reduced capillary absorption, and enhanced erosion resistance compared to untreated adobe. Sustainability assessments highlighted the environmental and economic benefits of the proposed approach, especially when using locally sourced materials. Overall, this work proposes a scalable and multifunctional strategy that integrates protective and photocatalytic functionalities to extend the service life of both historical and modern adobe structures. Full article

The Xi’an Beilin Museum preserves a large collection of archeological photographic negatives and films dating from the 1950s to the early 1980s. These images document significant archeological discoveries, including Tang dynasty imperial tomb murals, the excavation of the terracotta warriors, and various historical grottoes and stone carvings. As unique visual records of cultural heritage, these materials provide valuable references for studying environmental deterioration processes and for guiding conservation and restoration practices. However, long-term storage under uncontrolled environmental conditions has resulted in severe degradation of the negatives, including mold contamination, emulsion layer powdering, deformation, and partial detachment. Among these deterioration phenomena, microbial growth is particularly destructive because fungal hyphae cause light scattering and image obscuration, preventing scanning and digital archiving. In this study, mold species present on the negatives were isolated and identified using morphological observation and ITS rDNA sequence analysis. Based on the characteristics of the microbial contamination, targeted removal and restoration treatments were applied to recover the original image information. Furthermore, preventive protection strategies were implemented through the development of antifungal storage materials and protective containers. The results establish an integrated conservation approach combining microbial identification, restoration treatment, risk elimination, and preventive protection, providing a scientific basis for the long-term preservation of historical photographic archives. Full article

Existing studies indicate that preventive conservation (PC) has become a key strategy in heritage risk management. For traditional villages with limited resources, community participation is necessary for the implementation of risk management. However, current research mostly focuses on case-based analyses and lacks a systematic synthesis of community participation in PC. To address this gap, this study conducts a systematic review of community participation in PC from historic rural areas and relevant heritage types. Following the PRISMA guidelines, 39 eligible studies were included in the final analysis. The findings show that effective participation depends on well-defined organizational and coordination networks. Internal organizational structures support coordinated efforts among community members, while external collaborative frameworks provide ongoing resources and support. Within this structure, capacity-building translates participatory arrangements into concrete risk-governance actions, thereby influencing how roles are assigned and adapted within the community across different risk scenarios. Based on these insights, this study presents an Organization–Capacity–Role framework that offers a way for risk governance of historical rural areas. Notably, the detailed arrangements in this framework are shaped by local institutional settings, specific risk types, and case contexts, demonstrating a strong contextual dependency. Full article

Dissemination and conservation of cultural heritage have been challenged by continued accessibility in museums, where traditional information delivery systems are at times ineffective in terms if interaction with visitors. The current paper investigates RumiArt IA, a mobile application, to identify cultural objects in real-time, remaining fully in the scope of this line of research without relying on internet connectivity. The system, which is developed based on the Rumiñahui Museum and Cultural Center, Ecuador, uses transfer learning in the MobileNetV2 architecture with INT8 post-training quantization to identify 21 cultural artifacts spread across six thematic rooms. The experiment involved building a dataset of 36,000 images under diverse lighting conditions, viewing angles, and distances; furthermore, artificial transformations were explicitly crafted to simulate real museum conditions such as glass reflections and non-frontal capture angles. Quantization was used to reduce each model to 775 KB as compared with the 2.4 MB, with accuracy loss not reaching more than 0.5 percent (DKL < 0.05). Assessment of 9450 validation images yielded a general accuracy of 92.2%, with an inference time of 63 ms on current devices with a high throughput and 215 ms on mid-range hardware from 2020. Practical validation involving 50 visitors of the museum showed a success rate of 93.7%, with average user satisfaction at 8.5/10 and 87%, indicating they would recommend the application. An in-depth error study of the most difficult room (88.3% accuracy) indicated that 47% of the errors were due to the angles of the camera, which blocked out distinguishing features, and 22% were caused by display case reflections and the shadows of the visitors. These results indicate that end-to-end machine learning can provide consistent cultural heritage recognition in resource-constrained settings but its efficiency is susceptible to physical capture factors that cannot be resolved by data augmentation. Offline mode and low memory footprint (less than 90 MB when loaded on six models) of the system are especially relevant to application in situations where there is no guarantee of cloud connectivity. Full article

In order to investigate the effects of bentonite and glass fiber on the macroscopic mechanical properties and microscopic mechanisms of cement soil in dry environments, a series of laboratory tests were conducted in this study, including drying tests under controlled environments (30 °C, 50% humidity), unconfined compressive strength (UCS) tests, digital image processing technology, and scanning electron microscopy (SEM) analyses. The moisture evaporation law, surface crack development process, UCS variation, and microstructure evolution of cement soil with different mix proportions (bentonite content: 0–9%; glass fiber content: 0–0.5%) were systematically analyzed. The results show that bentonite can significantly enhance the water retention capacity of cement soil, reduce the water evaporation rate, and increase the unconfined compressive strength by filling internal pores to densify the microstructure. Glass fibers form a three-dimensional network structure in the matrix, exerting a bridging effect to inhibit crack initiation and propagation, and optimize the mechanical properties. The unconfined compressive strength increases significantly with an increase in bentonite content (3–9%), and the optimal fiber content for strength improvement is determined as 0.3%. The synergistic effect of bentonite and fibers optimizes the interfacial bonding force between fibers and the matrix, which remarkably improves the anti-cracking performance of cement soil. Specifically, when the bentonite content is 6–9% and the fiber content is 0.3–0.5%, the cement soil maintains complete integrity after drying, with no obvious cracks on the surface. SEM analysis reveals that the addition of bentonite and fibers inhibits the expansion and connection of internal voids, avoiding the cycle of “void enlargement–stress concentration–crack propagation”. This study provides a scientific basis for the engineering application of cement soil in a dry environment. Full article

Stone heritage deteriorates through physical, chemical, and biological processes driven by water, climate, and microbial colonization. Multifunctional polymeric coatings combining hydrophobic and antimicrobial moieties have emerged as a promising conservation strategy, yet a substantial gap remains between laboratory innovation and real-world performance. This review critically examines advances from 2021 to 2026, covering wetting theory, antimicrobial mechanisms, and material architectures, including molecularly integrated systems, Sol–Gel hybrids, nanocomposites, and layered systems. Long-term studies on the Aurelian Walls in Rome and stone in Reims show that biocidal efficacy typically declines within one to two years despite the chemical persistence of the coatings. In parallel, hydrophobic performance often deteriorates over time due to UV exposure, particulate deposition, and surface chemical changes, leading to increased wettability and reduced protective efficiency. Substrate porosity governs durability and visual compatibility (ΔE* < 5 threshold), while treatments can reshape microbial communities, favoring stress-tolerant meristematic fungi. Regulatory pressure on fluorinated compounds drives the development of more sustainable alternatives. Emerging directions include stimuli-responsive systems, self-healing materials, slippery interfaces, and precision polymer architectures. However, future progress will depend on tailoring formulations to major lithotypes, improving compatibility with porous substrates, and validating performance through standardized accelerated aging and multi-year field trials. Bridging laboratory design with environmental exposure data and conservation practice will be essential for achieving durable and culturally acceptable protection strategies. Full article

Against the backdrop of expanding digital dissemination and experiential transformation in cultural heritage, visitors’ visual attention and symbolic choices increasingly shape heritage cognition and value transmission. Taking the Yellow Crane Tower as a case study, this research constructs a cultural symbol recognition dataset based on visitor-shared social media images and develops an enhanced ResNet-50 model for multi-label analysis. By integrating attention mechanisms and regularisation strategies, the model improves its capacity to capture complex cultural imagery, achieving a macro F1 score of 72.70% and a micro F1 score of 81.05% on the test set, indicating strong generalisation performance. The results reveal a significant imbalance in visual preferences: landmark symbols centred on the main architectural structure dominate at 32.95%, whereas culturally informative elements such as signage, cultural products, and interpretive facilities each account for less than 5%. Tag co-occurrence analysis further identifies three image production patterns: commemorative presentation, contextual documentation, and detail-oriented cultural photography reflecting different levels of heritage perception. Rather than directly proposing prescriptive strategies, the findings provide an empirical basis for informing future interventions aimed at shifting from landmark-focused viewing to deeper cultural perception. In this way, the study contributes to heritage display optimisation and research on visitor visual behaviour. Full article

Brownfield-transformed urban parks, particularly those derived from industrial heritage, play a critical role in both cultural preservation and public-space provision. However, existing studies often rely on linear models and general urban contexts, limiting their ability to capture nonlinear, interaction-driven perception and translate analytical results into design-oriented insights. To address this gap, this study develops an interpretable data-driven framework integrating NLP (natural language processing) with explainable machine learning. Using social media reviews from Shougang Park in Beijing, built environmental elements are identified and structured into four dimensions—Accessibility, Safety, Comfort, and Enjoyment. An XGBoost model combined with SHAP analysis is employed to examine variable importance, nonlinear relationships, and interaction effects. The results reveal that visitor satisfaction is governed by heterogeneous and nonlinear relationships rather than independent additive effects. Several variables exhibit threshold-like, diminishing, and inverted-U-shaped patterns, indicating sensitivity to intensity ranges. More importantly, spatial perception emerges from the nonlinear coupling of multiple elements, forming four representative interaction types: compensatory, inverted-U-shaped, context-dependent, and threshold-like relationships. Key interactions are concentrated around industrial landscape, leisure activities, and supporting facilities. Building on these findings, the study translates interactions into design-oriented strategies, emphasizing synergistic configuration, functional balance, moderated development intensity, and context- sensitive programming. By linking interpretable machine learning with spatial design, this research advances an interaction-oriented paradigm and provides a transferable framework for satisfaction-informed evaluation and optimization of brownfields. Full article

Understanding the spatiotemporal formation mechanisms of built cultural heritage is essential to interpreting regional cultural landscapes and informing differentiated conservation strategies. Using Fujian Province, China, as a representative mountain–sea transitional region, this study constructs a province-scale, multi-category, and dynamically oriented analytical framework to investigate the temporal evolution, spatial structure, and driving mechanisms of immovable cultural relics. Based on a georeferenced dataset of 940 immovable cultural relics, textual historical records were standardized into continuous temporal variables and integrated with GIS-based kernel density estimation, spatial autocorrelation analysis, distance-to-coast modeling, and category co-occurrence analysis. The results reveal a pronounced temporal concentration in the Ming–Qing and modern periods, with a primary formation peak during the Qing Dynasty and a secondary peak in the early 20th century driven by modern heritage. Spatially, relics exhibit significant positive spatial autocorrelation (Global Moran’s I = 0.375, p < 0.001) and form a structured dual-core pattern, consisting of a persistent coastal heritage belt and a distinct inland modern core centered in western Fujian. More than 75% of relics are located within 110 km of the coastline, confirming strong maritime orientation, while regression analysis reveals that this inland shift is primarily driven by the Modern Era rather than representing a continuous long-term trend. Category-level correlation analysis further demonstrates a clear spatial decoupling between traditional heritage and modern sites, indicating fundamentally different locational logics. Synthesizing these findings, this study proposes a dual-core driven model under a mountain–sea geographical framework, in which a path-dependent, economically reinforced coastal core coexists with a historically contingent, politically driven inland core. The results advance quantitative understanding of how multiple cultural logics, operating across different temporal scales, jointly shape complex regional heritage systems and provide a transferable framework for heritage analysis and spatially differentiated conservation planning. Full article

Chinese Haipai New Year paintings are an important part of the country’s intangible cultural heritage, and their digital preservation holds great significance. This paper proposes PSE-Net (Pyramid Scale Expansion Network), a deep learning-based segmentation method specifically designed to handle the complex textures and intricate compositions of these artworks. By constructing a dedicated large-scale dataset, we trained PSE-Net to achieve high-precision segmentation by incorporating attention mechanisms and multi-scale feature fusion to better capture detailed features. Experimental results demonstrate that the proposed method outperforms existing approaches (such as ResNet) in terms of segmentation performance, yielding superior results in edge preservation. This work establishes the first automated tool for the pixel-level analysis of Haipai New Year paintings, thereby facilitating museum digitization, art history research, and education. Furthermore, it offers new insights for the image processing and digital preservation of other traditional artworks. Full article

The Babylonian numeral system, developed more than four thousand years ago, is one of the earliest known positional number systems, employing a sexagesimal (base-60) structure and a limited set of wedge-shaped symbols. Despite their visual simplicity, Babylonian numerals exhibit substantial structural and positional complexity, particularly when multiple symbols are combined to represent larger numerical values. This complexity presents significant challenges for modern computational recognition, especially in handwritten and degraded archaeological contexts. Most existing research has focused on the recognition of isolated Babylonian numeral symbols, which does not adequately reflect real inscriptions where numerals typically appear as composite sequences. To address this limitation, this paper proposes a hybrid deep learning framework capable of identifying, interpreting, and computing the decimal values of multi-symbol handwritten Babylonian numerals. Building on prior work in single-symbol recognition, we construct a synthetic yet realistic dataset of composite numeral images by combining handwritten glyphs into sequences of two to four symbols while incorporating natural variations in spacing, alignment, and handwriting style. The proposed framework integrates a Convolutional Neural Network (CNN) for visual feature extraction with optional structural feature fusion, followed by a Support Vector Machine (SVM) classifier for reliable multi-class discrimination. A rule-based positional decoder is then applied to convert recognized symbol sequences into their corresponding decimal values using Babylonian base-60 logic. By combining visual recognition with positional numerical reasoning, the proposed system enables end-to-end interpretation of handwritten Babylonian numeral sequences. To the best of our knowledge, this work represents one of the first approaches to jointly classify, decode, and compute numerical values from multi-symbol handwritten Babylonian numerals, contributing to digital epigraphy, archaeological text analysis, and cultural heritage preservation. Full article

3D Concrete Printing (3DCP) is increasingly explored as a digital fabrication technology offering design freedom, automation, and material efficiency. Nevertheless, its application in reinforced and long-life structures remains limited by insufficient understanding and poor comparability of durability performance, as previous reviews have not systematically linked methodologies to transport-related results. This study presents a systematic and critical review of carbonation and chloride ingress in 3DCP cementitious materials, conducted in accordance with the PRISMA methodology. Following a structured database search and two-stage screening process, the selected studies are subjected to qualitative analysis. Experimental methodologies, specimen typologies, exposure conditions, and attack directions are compiled and qualitatively compared. The review highlights pronounced methodological heterogeneity and frequent under-reporting of key parameters, particularly attack direction, sealing conditions, CO₂ concentration, and indicator methods, limiting cross-study comparison. Despite these limitations, consistent qualitative trends are identified. Printed specimens generally exhibit inferior durability performance than cast specimens, while cold joints are associated with increased penetration depth and result dispersion. Directional effects are non-negligible, although they are systematically addressed in only a limited number of studies. Overall, the findings emphasise the critical role of process-induced features and the need for harmonised testing methods to enable reliable durability assessment. Full article

Diocletian’s palace with its cellars represents one of the most important cultural heritage sites of the ancient Roman civilisation on the present-day Croatian territory. The cellar complex has been rediscovered only recently and has been preserved remarkably well due to its centuries-long concealment beneath mediaeval urban matrices. An archaeoacoustic analysis was performed on a selected single-nave hall as a small part of this complex. A model of the hall was developed in room acoustics simulation software and calibrated based on the results of field measurements. Acoustic suitability of the hall for speech-based events and music performances was then evaluated according to contemporary objective criteria, and the findings were compared with the results of similar studies performed on other heritage sites. The hall was found to be very well suited for speech in terms of intelligibility and mid-frequency reverberation, thus showing potential for revitalisation, with excessive low-frequency reverberation in the hall and reduced audibility in the farthest part of the audience as potential issues. With a feasible audience size, the hall is not reverberant enough for music performances but provides high clarity. In terms of sound strength, the hall is suitable for solo performers or small ensembles. Excessive perceptive broadening of the sound source is expected due to strong early lateral energy. In terms of traditional Dalmatian a cappella singing, the acoustics of the hall are likely to support and enhance such performances. Full article

Social Virtual Reality (VR) is emerging as a powerful medium for remote social interaction and collaboration, enabling multiple users to share experiences together while apart. Likewise, recent advances in multimedia technologies have proposed strategically combining diverse content formats and introducing interaction techniques for recreating virtual environments and engaging with them, respectively. This study pioneers the joint exploration of Social VR enhanced with holographic communication, multimodal content integration, and advanced interaction methods to deliver realistic and interactive group visits to reconstructed cultural heritage sites, specifically an existing restaurant–museum. The reconstructed space is further augmented with Points of Interest (PoIs), which can be freely visited and dynamically activated to provide rich contextual and historical information about the venue. The proposed technology and scenario have been evaluated objectively and subjectively. Results from objective tests offer relevant insights into the technical requirements, performance metrics (including bandwidth usage and latency), and overall system stability. Results from subjective tests with 22 participant pairs reveal high levels of user satisfaction, particularly in terms of immersion, presence, togetherness, and interaction quality regardless of whether participants acted as Guides (interacting with the VR environment) or Followers (observing and following the Guide’s actions). Beyond demonstrating feasibility, the findings from this study prove, for the first time, how strategically combining multi-user holoportation with multimodal content and role-based interactions can enable guided, collaborative cultural or touristic visits that preserve social presence while supporting rich exploration and contextual learning. Full article

Traditional villages embody regional culture and local knowledge, yet culture–tourism integration often suffers from a mismatch between resource value and effective transformation. To address this problem, this study proposes a two-dimensional “benefit–obstacle” diagnostic and strategy-matching framework and tests its case-based applicability in Dayuwan Village. First, a cultural landscape gene (CLG) atlas was constructed for the village based on a geo-information coding scheme, covering both tangible and intangible CLGs. Second, a four-dimensional evaluation system was operationalized through five expert judgments and 106 valid on-site questionnaires collected from tourists (n = 67) and residents (n = 39). Criterion weights were determined using an AHP–entropy combination approach, and the comprehensive benefit closeness coefficient was calculated via TOPSIS. Third, an obstacle degree identification model was employed to pinpoint key constraints and derive composite obstacle degrees. Results within the Dayuwan case show that the TOPSIS closeness coefficients of the 17 genes ranged from 0.653 to 0.782 (mean = 0.714), with 4, 6, and 7 genes classified as excellent, good, and medium, respectively; composite obstacle degrees ranged from 0.0228 to 0.1975. In Dayuwan Village, higher obstacle degrees clustered mainly in intangible CLGs, whereas Ming–Qing architecture and frequently practiced folk-cultural genes showed comparatively lower obstacle degrees. The transformation process is constrained by four mechanisms—landscape character protection, economic transformation, social identity, and market demand—with economic transformation constraints being the most prominent. Based on the benefit–obstacle matrix, 17 CLGs were classified into five activation scenarios and matched with corresponding revitalization strategies. This framework links benefit ranking, obstacle diagnosis, and strategy matching, and provides a case-based diagnostic reference for the conservation and culture–tourism integration of villages with comparable heritage conditions, subject to local recalibration of indicators, weights, and thresholds. Full article