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This paper uses a combination of EDXRF and LA-ICP-MS to analyse the chemical components including major elements and REE composition of the accompanying celadon from four different periods of tomb at the Yutu Hill burial complex on the Xunyang city site for sourcing their provenance. The combination of the two analytical methods not only provides additional data and information to explore the provenance of the accompanying celadon in the burials, but also validates the data's accuracy. A comparison with the chemical composition of the products from several kiln sites producing celadon revealed that burials from the Eastern Han period (25–220 A.D) to the Tang dynasty (618–907 A.D) included celadon from the Hongzhou kiln, indicating the connection between the Xunyang city site and the Hongzhou kiln during these two periods. In addition, the REE composition of the accompanying celadon in tombs from the Six Dynasties (222–589 A.D) and the Sui dynasty (581–618 A.D) is very similar to that of Yue kiln celadon, despite their strikingly different appearance and shape. This paper deduces, based on the previous distribution of Yue kiln products in the Jiangxi region, that only the upper classes collected Yue kiln products during the initial period of their entry into Jiangxi during the Jin dynasty (266–420 A.D), but that during the later period of the Six Dynasties, the commoner classes also began to collect Yue kiln products. [ABSTRACT FROM AUTHOR]

How to migrate text-to-image models based on pre-trained diffusion models to adapt them to domain generation tasks is a common problem. In particular, the generation task for Chinese landscape paintings with unique characteristics suffers from a scarcity of fine-grained contextual details specific to such artwork. Moreover, the use of substantial amounts of non-landscape painting data during pre-training predisposes the model to be swayed by alternative visual styles, thereby leading to generated images that inadvertently lack the distinctive traits inherent to Chinese paintings. In this paper, we propose a Fine-grained Hierarchical Semantic Adapter for Chinese landscape paintings generation, namely FHS-adapter. The method orchestrates the diffusion process in a batch-wise manner, leveraging external fine-grained multi-perspective information to guide it. It gradually diminishes the influence of other style images embedded in the pre-trained diffusion model, ultimately preserving a greater number of landscape painting elements. The encoder was also replaced with the Taiyi-CLIP encoder, which is adapted for Chinese. We propose T2ICLP, a multimodal dataset containing 10,000 high-quality image-text pairs of Chinese landscape paintings. Unlike previous datasets, this dataset extracts fine-grained textual information from four perspectives, including Meta, Description, Sentiment, Poem. We compared the proposed model with the mainstream diffusion-based T2I models. Through an anonymous user study, our FHS-adapter method performs well in simulating various aspects such as brushwork, e.g.'Gou, Cun, Dian, Ran' means hooking, texturing, dotting, and dyeing, compositional space, elemental proportions, and color usage of different painting genres and artists. Our dataset is available at https://github.com/T2ICLP/t2iclp. [ABSTRACT FROM AUTHOR]

Oracle bones (Obs) are a significant carrier of the shang dynasty civilization, primarily consisting of tortoise shells and animal bones, through the study of which we can gain a deeper understanding of the political, economic, religious, and cultural aspects of the shang dynasty. The oracle bone drill chisel (Obdc) is considered an essential non-textual material. The segmentation of Obdc assists archaeologists determine the approximate age of the Obs, which possesses considerable research value. However, the breakage of thousands of years of underground buried Obs, the blurring of the edges of the area burned by the Obdc, the different shapes, and the inconsistent number have brought challenges to the accurate segmentation of the Obdc. In this article, we propose a group convolutional attention and pvt dual-branch network (GCA-PVT-Net) for Obdc segmentation. To our knowledge, this paper is the first to research the automatic segmentation of Obdc. It is a hybrid Convolutional neural network (CNN) and Transformer framework. The work offers the following contributions: (1) The Obdc images are labeled based on the delineation criteria of different drill chisel (DC) shapes to create the Obdc dataset. (2) A convolutional attention module (CAM) is proposed as both an encoder and decoder. The feature extraction process, which effectively integrates global and local information, ensures better modeling of long-term correlations in images while preserving details. (3) A channel feature aggregation module (CFAM) is designed to enhance the effective integration of channel features, enabling feature fusion across various branches and at different levels. (4) The edge deep supervision strategy is applied to smooth the jagged edge of the predicted images at the decoder's end. Extensive experiments on the Obdc dataset show that GCA-PVT-Net outperforms other state-of-the-art (SOTA) methods. The comparative experimental results show that the edge accuracy and segmentation accuracy of the model reach the top 1. [ABSTRACT FROM AUTHOR]

Data scarcity in paleographic image datasets poses a significant challenge to researchers and scholars in the field. Unlike modern printed texts, historical manuscripts and documents are often scarce and fragile, making them difficult to digitize and create comprehensive datasets. Recently many innovations have been arrived on single image generative models for natural images but none of them are focused on paleographic character images and other handwritten datasets. In paleographic images like stone inscription characters, maintaining exact shape and structure of character is important unlike natural images. In this paper we propose an unconditional single image generative model, CharGAN for isolated paleographic character images. In the proposed system, augmented images are generated from a single image using generative adversarial networks, while maintaining their structure. Specifically, an external augmentation inducer is used to create higher-level augmentations in the generated images. In addition, the input to the generator is replaced with dynamic sampling from a Gaussian mixture model to make changes to the low-level features. From our experimental results, we infer that these two enhancements make single-image generative models suitable not only for natural images, but also for paleographic character images and other handwritten character datasets, the AHCD dataset, and EMNIST, where the global structure is important. Both the qualitative and quantitative results show that our approach is effective and superior in single-image generative tasks, particularly in isolated character image generation. [ABSTRACT FROM AUTHOR]

The tomb of Marquis Yi of Zeng was unearthed in 1978 at Leiguudun in Suizhou City, Hubei Province, China. This is the largest wooden coffin in rock pit and vertical cave in the Warring States period in China. The large wooden coffin components provide reliable material data for the study of the feudal burial system in the pre-Qin period and have high value. In this paper, the wooden coffin excavated from the tomb of Marquis Yi of Zeng was studied. By understanding the composition of wood, studying the weight gain rate, shrinkage rate, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and compression resistance, the wood reinforced by rosin and epoxy resin was compared, and the reinforcement effect and principle of the two reinforcement methods were discussed. The study found that the wood properties of rosin reinforced group were better than those of epoxy reinforced group in the aspects of compressive strength, weight gain rate and volume shrinkage rate, and the mechanical properties of wood were significantly improved. In addition, methanol or ethanol can be used to dissolve the rosin shellac in this strengthening process, which can achieve reversible strengthening treatment. The results provide valuable examples and research ideas for the selection of different conservation techniques of large wooden cultural relics unearthed in the middle and lower reaches of the Yangtze River during the Warring States Period. [ABSTRACT FROM AUTHOR]

Kolkata, renowned as the City of Joy, boasts a rich tapestry of cultural heritage spanning centuries. Despite the significance of its architectural marvels, accessing comprehensive visual documentation of Kolkata's heritage sites remains a challenge. In online searches, limited imagery often fails to provide a detailed understanding of these historical landmarks. To address this gap, this paper introduces MonuNet, a high-performance deep-learning network specifically designed for the classification of heritage images from Kolkata. The development of MonuNet addresses the critical need for efficient and accurate identification of Kolkata's architectural marvels, which are significant tangible cultural heritages. The dataset used to train MonuNet is organized by heritage sites, each category within the dataset represents distinct sites. It includes images from 13 prominent heritage sites in Kolkata. For each of these sites, there are 50 images, making it a structured collection where each category (heritage site) is equally represented. The proposed network utilizes a unique architecture incorporating a Dense channel attention module and a Parallel-spatial channel attention module to capture intricate architectural details and spatial relationships within the images. Experimental evaluations demonstrate the superior performance of MonuNet in classifying Kolkata heritage images with an accuracy of 89%, Precision of 87.77%, and Recall of 86.61%. The successful deployment of MonuNet holds significant implications for cultural preservation, tourism enhancement, and urban planning in Kolkata, aligning with the United Nations Sustainable Development Goals (SDGs) for sustainable city development. By providing a robust tool for the automatic identification and classification of heritage images, MonuNet promises to enrich online repositories with detailed visual documentation, thereby enhancing accessibility to Kolkata's cultural heritage for researchers, tourists, and urban planners alike. [ABSTRACT FROM AUTHOR]

Traditional Chinese settlements (TCSs) embody millennia of human and cultural history, with the core culture serving as their essence. However, any damage incurred by these TCSs can result in the loss of core culture. In the era of China's digital transformation, there has recently been a significant push toward digital reforms within TCSs. Thus, this paper introduces a traditional settlement digitalization (TSD) framework with a specific focus on enhancing the preservation of TCS landscape gene through the perspective of landscape gene information chain theory. This research uses the Nanxun traditional settlement (TS), Huzhou, Zhejiang, China, the first TS listed as a World Cultural Heritage Site in China, as a case study, extracting and identifying the area landscape gene and digital visualization status. This article identifies the landscape gene information chain of the Nanxun TS and redesigns its digital visualization and application scheme under the TSD framework. This study reveals the notion of a digital landscape gene characterized by four key attributes: identical, interactive, immersive, and intelligent. The results of this study will help guide the sustainable protection, application and planning of the Nanxun TS and promote the study of other sections of landscape gene theory. This research not only contributes to the development of landscape gene information chain theory but also provides guidance for the digital transformation of other TCSs and cultural heritage sites. [ABSTRACT FROM AUTHOR]

Historic timber structures face substantial fire loads and complex fire risks. Subsequent renovations and utilization may influence their fire safety performance. Therefore, accurately predicting indoor fire development in historic buildings and assessing their fire safety performance is crucial. Numerical fire simulation is currently at the forefront of analyzing and assessing fire risks in historic buildings. However, there is a shortage of globally accessible historic building fire data. This paper proposes a method to determine fire scenarios, peak heat release rates, and development curves of indoor fires in wooden historic buildings through a fire load investigation. Using the Guangzhou ancestral hall as an example, PyroSim fire dynamics simulation software is employed to calculate fire development and assess the available safe evacuation time. The simulation results are subsequently input into the Pathfinder evacuation simulation software to ascertain the required safe evacuation time for indoor occupants. A comparative assessment is conducted to evaluate the fire safety performance before and after the renovation of historic buildings. The research findings indicate that installing closed glass curtain walls in the courtyards of ancestral hall buildings in Guangzhou accelerates the infiltration of smoke during fires, leading to rapid fire spread and long-distance ignition, significantly reducing the time available for safe evacuation. Therefore, when renovating and utilizing the ancestral hall buildings in Guangzhou, the installation of ventilation and smoke extraction systems should be prioritized to slow down fire development. Additionally, controlling the number of indoor occupants is an effective management measure to mitigate fire damage in historic buildings. [ABSTRACT FROM AUTHOR]

The renovation of traditional architecture contributes to the inheritance of cultural heritage and promotes the development of social civilization. However, executing renovation plans that simultaneously align with the demands of residents, heritage conservation personnel, and architectural experts poses a significant challenge. In this paper, we introduce an Artificial Intelligence (AI) agent, Architectural GPT (ArchGPT), designed for comprehensively and accurately understanding needs and tackling architectural renovation tasks, accelerating and assisting the renovation process. To address users' requirements, ArchGPT utilizes the reasoning capabilities of large language models (LLMs) for task planning. Operating under the use of tools, task-specific models, and professional architectural guidelines, it resolves issues within the architectural domain through sensible planning, combination, and invocation. Ultimately, ArchGPT achieves satisfactory results in terms of response and overall satisfaction rates for customized tasks related to the conservation and restoration of traditional architecture. [ABSTRACT FROM AUTHOR]

Incomplete handwritten Dongba character often appears in heritage documents and its recognition is significant for heritage and philology. However, all previous methods always suppose that a complete Dongba character is used as input, and thus fail to achieve satisfactory performance when applied to incomplete Dongba character recognition. In this paper, an end-to-end network (DB2RNet) is proposed for incomplete handwritten Dongba character image recognition by multiscale feature restoration. Specifically, we first develop datasets that contain different levels of incomplete Dongba characters. A restoration module is proposed to restore the input incomplete Dongba character, and then a recognition module is employed to recognize Dongba character. By introducing an inter-module residual connection between the restoration module and recognition module, the DB2RNet can strengthen feature information transmission and boost the recognition performance. In addition, novel multiscale feature blocks are introduced, which can provide more effective texture and contextual information transmission for Dongba character image restoration, and thus yielding better restoration effects and better recognition results. Extensive experiments are conducted on Dongba character, Chinese character and Oracle character datasets and validate the effectiveness, superiority and robustness of our methods. Experiments results demonstrate that our proposed DB2RNet achieves competitive Dongba character restoration and recognition performance and outperforms the current state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Architectural heritage health assessment is the basis of scientific repair and maintenance. However, existing methods do not adequately take into account the fuzziness, randomness and uncertainties unique to architectural heritage assessment. In this paper, a new evaluation model of VM-NCM is constructed by combining variable weight theory and normal cloud model theory. The model enables the combination of qualitative ratings and quantitative calculation, deals with the fuzziness in the assessment process, and resolves the randomness and reflects the uncertainty to a certain extent. Based on constructing the index system combining qualitative and quantitative indexes, the structural index values are acquired by the synergistic coupling of the fine laser point cloud model and finite element structural analysis model. The acquisition of surface index values is completed by the hyperspectral intelligent detection technology of surface materials and diseases. These reduce the generation of ambiguous information in the index detection process. An evaluation study is conducted using the Yingxian wooden pagoda in China as an example. The results show that this method takes into account the fuzziness and randomness in the evaluation process, and obtains more scientific and reliable evaluation results, which provides a research paradigm for assessing the architectural heritage health status. [ABSTRACT FROM AUTHOR]

The study of clan paintings reveals a shift in perspective from art aesthetics to cultural connotations to cultural identity, yet literature seldom discusses the relationship between art and kinship culture. Taking the murals of ancestral hall architecture in Guangzhou as an example, this paper utilizes text mining to identify factors influencing its decorative art. It reveals the traditional rites' artistic expression through dimensions of characters' demeanor and the transmission of content values, offering a fresh perspective for heritage value research. Findings: (1) themes and implications are mostly oriented towards positive value transmission, transitioning from idealistic layman life to the realism of lower-class existence, emphasizing humanization; (2) the extroverted portrayal of characters contrasts with the dignified, restrained etiquette of traditional rites, with some characters' portrayal and facial expressions exuding approachability; (3) murals conveying positive emotions are mostly related to longevity, auspiciousness, fortune, and heroic deeds, while those conveying negative emotions mainly involve elderly male figures, reflecting a content bias related to characters; (4) historical allusion murals with complex content reduce the emotional resonance and arousal efficiency of the viewer; (5) incomplete mural content increases negative emotions in perceivers, highlighting the impact of mural preservation on emotional resonance. To delve into the formation of clan painting art, it is essential not only to interpret the diversity of its patterns but also to demonstrate the representation of its social attributes in decorative art. The formation of clan painting decorative art exhibits kinship cultural attributes, epitomizing the essence of traditional ceremonial thought. [ABSTRACT FROM AUTHOR]

The recent multi-analytical study carried out on the Van Eyck's Ghent Altarpiece showed the simultaneous presence of several kinds of metal carboxylates in oil-rich glaze layers. This outcome raised the question whether these carboxylates had already formed during the preparation of the oil binder by the artists. In the case of early-stage formation, they may have had an impact on the drying rate of the resulting oil, as well as on its handling properties. This hypothesis was investigated using a model system of in-house-prepared linseed oil containing incremental concentrations (2–5–10 wt.%) of relevant metal carboxylates (i.e. Ca-, Zn-, Cu-, and Pb oleates and stearates). This paper describes the influence of these type of molecules on the drying rate of linseed oil and, to an extent, on its viscosity. The drying time of the linseed oil, to which one or more metal carboxylates were added, was measured with a drying recorder while the viscosity was assessed with a rheometer. When introduced together, some of these metal carboxylates act in synergy to shorten the drying time with respect to the situation when the same metal carboxylates were added separately to linseed oil. Mixtures of Ca- and Zn-oleates proved to have a larger effect than other binary combinations. Addition of two metal oleates (combination of Ca/Zn/Cu/Pb) reduced the drying time even more. On the other hand, specific combinations of three metal stearates and/or oleates also demonstrated a significant synergistic effect towards increasing the viscosity of the binder. Especially combinations of Ca/Zn/Cu and Ca/Zn/Pb stearates and oleates gave rise to the highest level of linseed oil viscosity increase, when compared to the situation in which the same metal carboxylates were added separately. [ABSTRACT FROM AUTHOR]

In the globalization trend, China's cultural heritage is in danger of gradually disappearing. The protection and inheritance of these precious cultural resources has become a critical task. This paper focuses on the Miao batik culture in Guizhou Province, China, and explores the application of knowledge graphs, natural language processing, and deep learning techniques in the promotion and protection of batik culture. We propose a dual-channel mechanism that integrates semantic and visual information, aiming to connect batik pattern features with cultural connotations. First, we use natural language processing techniques to automatically extract batik-related entities and relationships from the literature, and construct and visualize a structured batik pattern knowledge graph. Based on this knowledge graph, users can textually search and understand the images, meanings, taboos, and other cultural information of specific patterns. Second, for the batik pattern classification, we propose an improved ResNet34 model. By embedding average pooling and convolutional operations into the residual blocks and introducing long-range residual connections, the classification performance is enhanced. By inputting pattern images into this model, their categories can be accurately identified, and then the underlying cultural connotations can be understood. Experimental results show that our model outperforms other mainstream models in evaluation metrics such as accuracy, precision, recall, and F1-score, achieving 94.46%, 94.47%, 93.62%, and 93.8%, respectively. This research provides new ideas for the digital protection of batik culture and demonstrates the great potential of artificial intelligence technology in cultural heritage protection. [ABSTRACT FROM AUTHOR]

Along the western coastal plain of the Red Sea, the discovery of lithic tools proved that the occurrence of archaeological remains belonged to the Stone Age era. Unfortunately, until recently, most of the Stone Age site plans in the western Red Sea periphery have been unknown because of change in climate in addition to covering these sites with a large layer of sand. Recently, remote sensing (RS) data have proven to be effective at identifying buried archaeological sites using radar satellite imagery due to their ability to penetrate the land surface. This paper aims to identify and reconstruct several potential Stone Age sites using radar satellite images in the Tokar region, North-Eastern Sudan, on the western plain of the Red Sea. Radar (Sentinel-1 SAR GRD: C-band) data were processed utilizing the advantages of the Google Earth Engine platform and Snap software. The results of this research showed that some potential settlements belonging to the Stone Age era (expectedly dating back to the end of the Pleistocene and/or the initial phase of the Holocene) have subcircular shapes with some interior subcircles. These results shed new light on the potential construction technique, size, and function of the settlement in the Stone Age era and can provide some initial insights into the ancient lifestyle in this region. Additionally, this study can aid in future archaeological surveys and excavation missions in this region. [ABSTRACT FROM AUTHOR]

Timely understanding of the preservation status of archaeological human bones is the foundation for conducting scientific archaeological work. This paper applies Micro-CT technology to analyze the microscopic preservation status of ancient human femora unearthed from the Rui State site in Liangdai Village, Hancheng, Shaanxi, the Chejiasi Cemetery in Baoji, and the Ouerping Cemetery in Xizhou Village, Yushe, Shanxi, and obtained imaging results and cortical bone porosity (Ct.Po), bone volume fraction (BV/TV), and bone density (BMD) parameters for 9 samples. The results show that the poorly preserved fragile group has lower Ct.Po, BV/TV, and BMD, and macroscopically presents fragile and porous features; while the well-preserved dense group has relatively higher Ct.Po, BV/TV, and BMD, and macroscopically appears solid and dense. This study employs Micro-CT technology to analyze the micro-preservation status of human bones from historical periods, confirming the effectiveness of this technology in revealing the microstructure of ancient human bones, and providing a reference for establishing a human bone preservation status evaluation system. [ABSTRACT FROM AUTHOR]

The preservation of cultural heritage, including ancient photographic materials, is of paramount importance in the field of conservation science. In this context, the microbial diversity of 'Skull and Crossbones', a 1983 photograph by Robert Mapplethorpe printed on silver gelatine, was assessed. We employed both culture-dependent and culture-independent methods to characterize microbial communities inhabiting this artwork. Vibrational Raman micro spectroscopy and FT-IR spectroscopy were utilized to assess the chemical degradation condition and characterize the chemical components of the silver gelatin print. The combination of molecular sequencing methods (Sanger and HTS approach) and non-invasive vibrational spectroscopy yielded valuable insights into the microbial communities thriving on photographic material and the chemical degradation of the print. Isolated fungal strains were added to the Fungal Collection at the University of Naples Federico II, and their deteriorative potential was investigated by adding substrates, commonly used in canvas photographs to the culture media. These results establish a link between microbial communities colonizing ancient photographic materials, paper decomposition, and the enzymatic patterns of the retrieved microorganisms. This information is invaluable for understanding and addressing biodeterioration progression on valuable works of art, such as historical photographs, which remain understudied. [ABSTRACT FROM AUTHOR]

Image restoration is a prominent field of research in computer vision. Restoring broken paintings, especially ancient Chinese artworks, is a significant challenge for current restoration models. The difficulty lies in realistically reinstating the intricate and delicate textures inherent in the original pieces. This process requires preserving the unique style and artistic characteristics of the ancient Chinese paintings. To enhance the effectiveness of restoring and preserving traditional Chinese paintings, this paper presents a framework called Sketch-Guided Restoration Generative Adversarial Network, termd SGRGAN. The framework employs sketch images as structural priors, providing essential information for the restoration process. Additionally, a novel Focal block is proposed to enhance the fusion and interaction of textural and structural elements. It is noteworthy that a BiSCCFormer block, incorporating a Bi-level routing attention mechanism, is devised to comprehensively grasp the structural and semantic details of the image, including its contours and layout. Extensive experiments and ablation studies on MaskCLP and Mural datasets demonstrate the superiority of the proposed method over previous state-of-the-art methods. Specifically, the model demonstrates outstanding visual fidelity, particularly in the restoration of landscape paintings. This further underscores its efficacy and universality in the realm of cultural heritage preservation and restoration. [ABSTRACT FROM AUTHOR]

Damage and fracture of archaeological potteries not only jeopardize the long-term preservation but also hinder their exhibition. To repair these pottery sherds effectively, this study introduces a novel inorganic phosphate-based adhesive and evaluates its effectiveness through a series of experiments. To determine the optimal base adhesive, the paper investigates the influence of varying weight ratios of the H2O–H3PO4 system and the Al(OH)3–H3PO4 system on properties including tensile lap-shear strength, microstructure, high-temperature resistance and phase composition. However, the original black color of the traditional CuO–phosphate adhesive limits its application. The innovation of this study lies in the addition of nano-TiO2 to the adhesive, which not only improves the bonding strength but also adjusts the color of the adhesive. This study has defined the optimal formulation (i.e., base adhesive = m[Al(OH)3]:m[H3PO4] = 7:100, filler = 10wt% nano-TiO2), and the final product shows no residual acid in adhesives. Additionally, the fracture surfaces are successfully bonded with a high strength of 3.56 MPa. Various ageing tests including dry-thermal ageing, hygrothermal ageing and UV irradiation ageing are conducted to assess the ageing resistance of the inorganic phosphate-based adhesive. The results indicate strong tolerance of adhesive to high temperature and high humidity environment. Preliminary applications in archaeological pottery restoration suggest that the inorganic phosphate-based adhesive offers considerable promise for repairing shattered pottery. [ABSTRACT FROM AUTHOR]

Chinese Painting and Calligraphy (ChP&C) holds significant cultural value, representing integral aspects of both Chinese culture and global art. A considerable amount of ChP&C works are dispersed worldwide. With the emergence of digital humanities, a vast collection of cultural artifacts data is now available online. However, the online databases of these artifacts remain decentralized and diverse, posing significant challenges to their effective organization and utilization. Addressing this, our paper focuses on the Wu Men School of Painting and proposes a framework for constructing a multimodal knowledge graph for the ChP&C domain. We construct the domain ontology by analyzing the ChP&C knowledge schema. Then, we acquire knowledge from diverse data sources, including textual and visual information. To enhance data collection around collecting historical context and subject matter, we propose methods for seal extraction and subject extraction specific to ChP&C. We validate the effectiveness of these methods on the constructed dataset. Finally, we construct the Wu Men Multimodal Knowledge Graph (WuMKG) and implement applications such as cross-modal retrieval, knowledge-based question-answering and visualization. [ABSTRACT FROM AUTHOR]

This paper presents the current state of conservation of historic roof churches located in the Żuławy of Gdańsk (Poland). It also describes the architecture of these temples, the region itself and old carpentry techniques for constructing roof trusses. Interdisciplinary tests were carried out in six churches. The geometry of the load bearing structures, the moisture content and the carpentry technique were specified. The field survey also included visual inspections and non-destructive testing of timber structural elements of the roof constructions. The ground penetrating radar and ultrasonic testing methods were used to assess the structure and extent of the damage to the timber elements. The interdisciplinary research presented in this article is important in the planning of historic buildings conservation works and it might be applied to other timber structures. [ABSTRACT FROM AUTHOR]

Heritage buildings represent history and act as vessels of human civilisation. The significance of these architectural phenomena increases as society increases, which renders their preservation and ethical use increasingly crucial. Hence, preserving heritage buildings is necessary for societal benefit. The accuracy of three-dimensional (3D) point cloud models of heritage buildings is important to their digital conservation. Traditional mapping methods typically require more time and human resources. Furthermore, the outcome is subject to measurement omissions, errors, and other issues, which are contrary to the protection of the object measured. The complex elements of ancient Chinese architecture render it challenging for traditional measuring techniques to accurately capture spatial structural information. The 3D laser scanning technology is a novel technology to obtain 3D data rapidly. In this paper, the Great Achievement Palace of the Confucian Temple in Yuci District, Jinzhong City, Shanxi Province, was used as an example to examine the application of 3D laser scanning technology to acquire point cloud models of heritage buildings. Field data collection for architectural heritage using 3D laser scanning technology requires measuring station setting analysis to ensure effect accuracy while considering the elements of target location and quantity. For the 3D point cloud model of the Great Achievement Palace, error analysis and accuracy assessment were conducted on the quality elements of alignment accuracy between scanning stations, point cloud model reliability, point cloud data noise condition, and whether the point cloud data were stratified. The findings demonstrated that the improved method quickly and accurately acquired 3D point cloud model data and obtained realistic spatial data models of the heritage building. [ABSTRACT FROM AUTHOR]

In this paper, we analysed the temporal and spatial distributions of ancient archaeological sites in China as well as their influencing factors. Our aim was to reveal the developmental trajectory of Chinese civilisation and to explore the natural and cultural factors affecting human distribution, with the goal of providing insights for the conservation and development of ancient relics. We employed spatial analysis methods using ArcGIS 10.8 software, such as kernel density analysis and trend surface analysis, to analyse 1194 historical ancient sites listed in the National Cultural Relics Protection Units of China. The research findings are as follows: (1) the distribution of ancient sites demonstrates an agglomerative spatial pattern. The nearest neighbour index (R < 1) for sites from various historical periods indicates an agglomerative spatial distribution of ancient sites across historical periods, with the clustering degree being relatively poor for sites from the Wei-Jin, Northern and Southern Dynasties and in the Ming and Qing periods. The regions with a concentration of ancient sites are the middle and lower reaches of the Yangtze River and Yellow River Basins. Furthermore, there is a higher abundance of ancient sites in the southeastern region than in the northwestern region. (2) The distribution of ancient sites in different historical periods also exhibits an imbalance, with an overall decreasing trend in the number of ancient sites in China. Notably, more ancient sites were found for the prehistoric and pre-Qin periods. The temporal trend of ancient sites during historical periods follows a trajectory from northeast to northwest, northeast to southwest, etc. (3) The temporal and spatial distributions of ancient sites are influenced by multiple factors, including social development, the natural environment, geographical elements, and socioeconomic and political factors. Finally, based on an understanding of the spatiotemporal distribution pattern of ancient sites and the factors that influence this pattern, recommendations for conservation and development can be proposed and supported by modern technological methods, with the aim of offering insights for the protection and sustainable development of heritage sites. [ABSTRACT FROM AUTHOR]

Traditional Chinese villages act as the essential carriers of China's rural heritage. Such villages are considered to retain living practices of intangible heritage through know-how, artistic and folk customs, as well as a well-preserved architectural appearance. However, their conservation is at stake due to degradation, abandonment, and urbanization. Spatial cognition is one way of bringing people to the matter of what is important to conserve (attributes) and why they are important (values). This is done by analysing how people perceive and value rural heritage. Traditional methods of gathering spatial cognition data, such as laborious fieldwork or subjective qualitative analyses, often fall short of providing a holistic representation of real-world experiences. This article presents an innovative method for analysing cognitive features in traditional village spaces using an immersive virtual reality equipped with an eye-tracking system. We selected Cheng and Jitou, two traditional Chinese villages, as our case studies. In two virtual reality environments, we captured accurate 3D cognitive data, including participants' locomotion, gaze point, and sightline. The results indicate that the accessibility of village roads affects the distribution of people's locomotion, which in turn affects the distribution of people's areas of interest; the changes in the rhythm of the sightline scale reflect the rhythm of spatial changes in the villages. By broadening the understanding of spatial cognition in traditional Chinese villages related to people's values, this paper sheds light on an alternative approach to assess the cultural significance of such villages for higher conservation and sustainability. [ABSTRACT FROM AUTHOR]

The design and implementation of virtual museums have evolved over decades, broadening the scope of traditional museum exhibitions and serving as an effective complement to physical museums. However, virtual visual effects have consistently fallen short of replicating the authentic exhibition experience and cannot substitute for physical museums. In this paper, we report a dual-mode mixed visualization system combining computational photography and binocular stereo vision techniques, and introduce an innovative virtual museum for Sanxingdui bronzes. This approach enables visitors to engage with the artifacts in a multifaceted manner-allowing for navigation, interaction, auditory guidance, and the examination of textural details as if handling the artifacts directly. Further analysis of participant responses in terms of visual cognition and aesthetic appreciation across different settings demonstrates that this dual-mode mixed visualization delivers not only a spatiotemporal experience consistent with the real world but also surreal visual effects. This immersive experience allows audiences to experience Sanxingdui art intimately, offering both high-resolution visuals and cost-effectiveness. [ABSTRACT FROM AUTHOR]

The production of traditional Peking opera facial masks often relies on hand painting by experienced painters, which restricts the inheritance and development of this intangible cultural heritage. Current research mainly focuses on the digital reconstruction and storage of existing Peking opera facial masks, while high-quality facial mask generation technology is still in an infancy stage. In this paper, different deep learning frameworks are improved for learning features of Peking opera facial masks and generating new masks, which can effectively promote the creative application of Peking opera facial masks. First, using different data enhancement methods, an improved Style Generative Adversarial Network-2 (StyleGAN2) can learn implicit and explicit features of Peking opera facial masks and automatically generate new facial masks. In addition, an image translation framework for joint cross-domain communication under weak supervision is used to translate face sketches and color reference maps to an intermediate feature domain, and then synthesize new facial masks through an image generation network. The experimental results show that the generated Peking opera facial masks have good local randomness and excellent visual quality. [ABSTRACT FROM AUTHOR]

The Grand Canal is one of the most important hydraulic engineering projects in Chinese history. The city of Suzhou has abundant and concentrated cultural heritage sites in the southern section of the Grand Canal. However, due to natural hazards, anthropogenic damage, and lack of human management, the cultural heritage sites have suffered irreversible damage. Digital preservation of these sites will make it possible to maintain their aesthetic and cultural value. This paper takes cultural heritage sites along the Suzhou Canal as its research subject and establishes a cultural heritage dataset using geographical information system (GIS). The paper uses geocoding and spatial analysis methods based on GIS, including nearest neighbor analysis, kernel density analysis, center of gravity analysis, and standard deviation ellipse. The paper explores the distribution of 104 cultural heritage sites along the Suzhou Canal across six historical periods and discusses the influencing factors for evolution of the distribution. The results show that: (1) major constructions on the Grand Canal water system were started in the Pre-Sui period and completed in the Sui and Tang Dynasties; (2) the degree of clustering of the distribution has increased since the Sui and Tang Dynasties until Modern Times; (3) the high-density area has been centered around the ancient city since the Pre-Sui period, and has shown a migration trend towards the Shantang Canal since the Ming Dynasty; (4) the center of gravity first moved from northwest to southeast along the Canal and then moved northeast towards the ancient city; (5) the aggregation of the sites peaked in the Qing dynasty (1636 CE-1911 CE), and the elliptical direction of distribution has become stable since then; and (6) the types of the cultural heritage in the evolution process are affected by the joint effects of natural and human factors, namely, elevation, canals, population, water transportation, and intangible cultural heritage, among which the canal characteristics play the decisive role. This study reveals the internal evolution mechanisms of the cultural heritage in the Suzhou Canal area and presents a scientific basis for the protection and utilization of the cultural heritage in other parts of the world. [ABSTRACT FROM AUTHOR]

Located in Dunhuang, northwest China, the Mogao Grottoes are a cultural treasure of China and the world. However, after more than 2000 years of weathering and destruction, many murals faded and were damaged. This treasure of human art is in danger. Mural inpainting through deep learning can permanently preserve mural information. Therefore, a digital restoration method combining the Deformable Convolution (DCN), ECANet, ResNet and Cycle Generative Adversarial Network (CycleGAN) is proposed. We name it DC-CycleGAN. Compared with other image digital inpainting methods, the proposed DC-CycleGAN based mural image color inpainting method has better inpainting effects and higher model performance. Compared with the current repair network, the Frechet Inception Distance (FID) value and the two-image structural similarity metric (SSIM) value are increased by 52.61% and 7.08%, respectively. Image color inpainting of Dunhuang murals can not only protect and inherit Chinese culture, but also promote academic research and development in related fields. [ABSTRACT FROM AUTHOR]

The conservation and preservation of shadow puppet artifacts is an important task that requires accurate assessment of their preservation status. Currently, there are many shadow puppet artifacts in collections with varying degrees of deterioration, and an easy-to-use and accurate deterioration assessment method is urgently needed. To address this, this paper proposes a method to convert the color rendering characteristics of shadow puppet artifacts in two-dimensional images into digital information, which is used to create a pixel lattice in processing software Adobe Photoshop. The quantitative signal of the shadow puppet image is extracted and used to calculate the offset of the overall or local chromaticity of the shadow puppet relative to the average chromaticity, allowing for the assessment of the degree of cortical variation and risk of deterioration. A membership function is established based on the observed values of shadow puppet color in the pixel lattice, and the discrete fuzzy set and its scoring index are specified to assign corresponding weight values to the regions with different chromaticity attributes in the pixel lattice.The method of computing scores using the membership function involves ordinary mathematical operations, the overall scoring values are used to comprehensively evaluate the preservation status of the shadow puppet artifacts. This paper establishes a preliminary technical standard for the preventive conservation evaluation of shadow puppet artifacts using pixel lattice and membership function, providing an important guideline for the quantitative and standardized virtual restoration of shadow puppets. The proposed method provides a new approach to quantitatively assess the preservation status of shadow puppets, which is essential for their efficient scientific conservation. [ABSTRACT FROM AUTHOR]

Volatile organic solids, such as cyclododecane or menthol, have been employed as temporary reinforcement material during archaeological excavations. They are usually applied as melts and reinforcement is achieved once the melts solidify. Such solidification process can induce internal stress on the artifacts, which can be a big concern, especially to those very precious and fragile ones. However, information about such stress is still extremely limited at present. This paper proposes an experimental method based on resistance strain gauge technique to monitor the deformation induced by solidification of menthol melt. Bending tests are performed on very thin glass slides. The solidification process of menthol melt is well characterized by the development of mechanical strains. Then, menthol melts are applied to three kinds of simulated samples, i.e. glass, sandstone and rice paper, to investigate the mechanical response of preserved bodies upon solidification. It is found that menthol melt will generate certain amount expansion or contraction of the objects upon solidification. The stresses induced, evaluated according to obtained strains, are generally quite small, indicating that application of menthol as reinforcement material is safe in mechanics for cultural relics. [ABSTRACT FROM AUTHOR]

Due to the coating materials used, historic raincoats are vulnerable to degradation and rarely survive long periods of time. The investigated raincoat dating from 1943 is no exception—the coating is unusually stiff and flaking off in areas around folds and cracks. Study into its material composition can contribute to important knowledge of the availability of materials for waterproof clothing during the time of the German occupation of Denmark (1940–1945) when the usual materials for raincoats, cotton fabric and rubber, were in short supply. Optical microscopy and attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) identified the fabric to consist of rayon staple fibres and paper yarn, and the coating to be based on cellulose nitrate (CN) lacquer and an unknown plasticiser. Though the results are atypical for a raincoat, they are in good accordance with the raw materials available in Denmark in 1943. Analysis by matrix-assisted laser desorption-ionisation mass spectrometry (MALDI-MS), and 1H and 13C nuclear magnetic resonance spectroscopy (NMR), identified the plasticiser as poly(1,3-butylene) adipate. Powder X-ray diffraction (PXRD) moreover identified the pigment as titanium white of the anatase form. By historical discussion, this study argues that IG Farben is the likely producer of poly(1,3-butylene) adipate, even though the first known marketing of the plasticiser is from 1986 where the Swiss firm Ciba-Geigy introduced poly(1,3-butylene) adipate as a plasticiser for PVC cling films under the tradename Reoplex® 346. The results give an interesting insight into the use of substitution products during WWII and provide new information on polymer science of the time. [ABSTRACT FROM AUTHOR]

Cultural heritage is closely linked with individual historical figures, who become a key focus for cultural tourism. Confucianism laid the foundation for much of Chinese civilization, and Confucius and Mencius have been studied extensively and have been influential in many parts of the world. Zhu Xi, the founder and master of Neo-Confucianism (an important part of the Mount Wuyi world cultural heritage), has received less research attention. With the big bang of the metaverse, research on the immersive cultural heritage digital documentation and information service for historical figures has become a new perspective. This paper presents a metaverse-based digital documentation framework for historical figures. This framework addresses the digitization of multimodal data for cultural heritage and adapts to the needs of metaverse presentations. For cultural research and cultural preservation, the paper has explored a combined contactless virtual and real cultural heritage experience system. For tourists, we intend to develop an immersive and holistic cultural tourism information service before, during and after the tour. In particular, we have also developed the Zhu Xi metaverse system. This is a step forward in the construction of a metaverse of historical figures. [ABSTRACT FROM AUTHOR]