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Abstract Rivers and road systems play crucial roles in urban development and in shaping the vitality of cities. The present study focuses on the spatiotemporal development patterns of canal cities. Taking Suzhou as an example, employing various spatial measurement methods combined with multidimensional spatiotemporal data, it clearly demonstrates the urban morphological patterns and societal characteristics related to the road and river network systems at different stages of urban development. Utilizing data extracted from historical and modern maps of Suzhou and employing the YOLO (You Only Look Once) algorithm, this study establishes a spatiotemporal dataset for Suzhou's ancient city, a representative Chinese canal city. An optimized space syntax algorithm for public service facilities, utilizing Python library like Geopandas, Numpy, is proposed to analyze the river and road system's impact on historical development and urban morphology. With multiple spatial econometric models applied to maps from various periods, this research explores the following findings: (1) By controlling rivers as a variable, it quantitatively confirms that rivers were crucial components of urban systems in ancient cities, playing a significant role in urban development and activities, though gradually overlooked in modern times. (2) Public service facilities of different types demonstrate patterns of Accessibility and Integration within the river-road system across various periods. (3) Changes in the distribution of public service facilities correspond to phased shifts in the center of Suzhou’s ancient city, mutually validating the authenticity of realistic paintings, historical maps, and the methodologies used in this study. This study emphasizes a broader historical and spatiotemporal perspective, augmented by quantitative research methods. It investigates the distribution and developmental characteristics of various types of public service facilities across different periods. The research aim is to understand the impact of river and road systems on urban development, as well as the morphological and social changes in historical cities that arise from urban activities.

Abstract The increase in human activities and natural degradation often leads to tilting, collapsing, and other forms of deterioration in architectural heritage, posing significant threats to its safety. Therefore, timely detection of abnormal deformation signals in buildings is essential for the protection of architectural heritage. Spaceborne synthetic aperture radar interferometry (InSAR) can detect slight displacements over large areas. However, relying solely on annual mean velocity maps derived from InSAR may not accurately assess the stability of ancient buildings. In this study, we developed a framework that evaluates the stability of individual buildings by integrating the InSAR displacements with building footprints. Vertical and rotational deformations, along with the temporal evolution of these deformations, are combined to generate the results for building stability assessment. We used 74 TerraSAR-X images captured from August 2017 to November 2019 to evaluate the stability of Jianchuan Ancient Town, a renowned National Historical and Cultural City in China. The displacement result suggests that the majority of Jianchuan Ancient Town remains stable, with over 93% of coherent points (CTs) displaying displacement velocities ranging from −5 to 5 mm/yr. Out of the 1,891 buildings in Jianchuan Ancient Town, 1404 are considered stable, 352 are of moderate stability, and 12 are deemed unstable. This study showed the potential of InSAR applications in assessing the stability of architectural heritages, emphasizing its crucial role in heritage preservation and management.

Abstract As vital carriers of cultural heritage, rural areas are facing the threats of degradation and urbanization during rapid urbanization processes. In recent years, China has formulated and implemented a series of national policies, regulations, and heritage protection lists to safeguard and perpetuate the traditional patterns and historical features of rural heritage. However, these rural heritage listings exhibit significant macro-level distributional imbalances and generally lack consideration of regional characteristics. This study uses the Taihang Baxing (THBX) in China as a case study, initially employing historical local documents and maps as base data. It utilizes the stability in the evolution of Chinese characters to compare historical and contemporary village names, filtering out existing historical rural settlements (HRS) to construct a dataset. Further, a multi-scale geographically weighted regression (MGWR) model is applied to analysis the impacts of natural, economic, and social factors on the concentration of HRS (CHRS). The study reveals that the CHRS in the region is markedly characterized by clustering, with evident spatial heterogeneity in the impacts of various factors. Slope (SLP), total annual precipitation (TP), and potential crop yield (PCY) significantly influence the CHRS globally, while elevation (ELV), distance to ancient path (DAP) and surface runoff (DSR), gross domestic product (GDP), and road density (RD) have significant local impacts. This research offers a methodological framework for HRS data compilation and provides theoretical and methodological references for national and local levels of rural heritage protection, optimization of rural spatial patterns, prediction of rural evolution pathways, and implementation of China’s rural revitalization strategy.

Abstract Exploring the coordination and analysis of intangible cultural heritage (ICH) and tourism development is a key issue in advancing cultural heritage and conservation in Chinese society. This paper employs panel data from 30 Chinese provinces from 2013 to 2022, utilizing the coupled coordination degree model and the panel vector autoregression (PVAR) model. In terms of provinces and regions, the data investigates the development relationship between intangible cultural heritage and tourism. The results of the study are: 1. The degree of coupling coordination between the two has shown an increasing trend over the ten-year sample data period. In 2021 and 2022, COVID-19 will have a stronger negative impact on the coupling degree. 2. The eastern coastal provinces of China, as well as the municipal areas, have a higher level of coupling coordination. Inland provinces, such as those in central and western China, exhibit relatively lower levels of coordination. The PVAR model data reveals a positive correlation between the interactions generated by intangible cultural heritage. The development of intangible cultural heritage has a particular impact on tourism. Intangible cultural heritage, in turn, depends on its own development. We should strengthen the development of intangible cultural heritage in the future. The study's findings provide theoretical references for the coordinated development of intangible cultural heritage and tourism in China.

Abstract The Leshan Giant Buddha’s ushnisha (Head Bun) has suffered from loss of lime plaster, cracks, and biological damage, compromising its structural integrity and reducing the effectiveness of the drainage system in the Buddha's head. The infiltration of moisture has led to water damage within the statue, significantly accelerating its weathering. This situation urgently requires protection and reinforcement measures. Detecting deterioration in the ushnisha is a crucial step in the preservation process. In this study, we utilized two deep learning models for pixel-level semantic segmentation of the damage. Due to the small size of the cracks, a weighted loss function was applied to improve both the training speed of the model and the efficiency of crack identification. This weighting strategy proved effective for both models. The weighted K-Net model achieved a mean accuracy (mAcc) of 90.23% and a mean intersection-over-union (mIoU) of 69.55%, with a damage segmentation speed of 7 images per second, which is 1309 times faster than manual segmentation. By applying the trained deep learning models to re-examine the ushnisha, we successfully identified damage that had been overlooked during manual annotation. Using the model’s enhanced results, we conducted a comprehensive quantification of the damage across all ushnisha and identified the most severely affected areas. Additionally, we performed a model interpretability analysis to explain the decision-making process and principles of the deep learning models. This research provides significant practical value for detecting and quantifying damage in the Leshan Giant Buddha.

Abstract The preservation and advancement of cultural heritage continue to present significant challenges, arising from conflicting objectives, concepts, methodologies, and limited resources. Image perception not only serves as an observational tool for cultural heritage but also as a research method to uncover deeper meanings and implications. To explore the complex dynamics of cultural heritage and address the risks of its deterioration, this study employed virtual engine software (Unity 2019) to create digital landscapes for immersive exploration. An image perception evaluation framework was established through field surveys and behavioral synthesis experiments across five key areas, including ancient tree ecosystems and architectural sites. Our findings revealed that participants showed the greatest interest in the ancient tree ecological area, indicating a strong attachment to historical continuity and natural progression. Heart rate variability (HRV) analysis further demonstrated that participants experienced positive emotional responses, suggesting that well-designed cultural landscapes can enhance mental well-being and uplift mood. Additionally, participants expressed a strong willingness to discuss the ancient tree eco-region, with image perception playing a crucial role in motivating information sharing and driving conservation efforts. This study introduces an innovative model—Design Practice, Immersive Experience, and Image Perception Evaluation—which offers a new perspective for the preservation and enhancement of cultural heritage sites.

Abstract Historical maps provide insights into the morphology, cultural, and political shifts of ancient societies. Pingjiang Map is one of the earliest comprehensive ancient Chinese maps, depicting the heritage water city of Suzhou. This study takes it as the subject to examine the temporal and spatial reconstructions of Suzhou city after its devastation in the Song-Jin wars during the twelfth–thirteenth centuries. It uses historical geographical information system (H-GIS) and historical building information management (H-BIM) to simulate Suzhou city in the Southern Song dynasty (1127–1279) and the city’s subsequent modernization to the present. By comparing and contrasting Pingjiang Map, the Song dynasty Suzhou, and the current city in the configuration of clusters such as urban wall, canal, street, government and citadel, temple, and residential ward, we establish evolutionary links between Pingjiang Map and the city, providing insights to the mechanism underlying urban transformation. Through H-BIM, we conducted a temporal and spatial analysis of the twelfth–thirteenth centuries’ citadel of Suzhou, simulating the construction sequence of palatial artefacts. Our research argues that Pingjiang Map stele forged an imperial vision, serving both for documentation and planning. It encoded building information for the central government to manage post-war reconstruction. The research establishes the workflow of ‘SQS’—spatialization, quantitative analysis, and simulation—to investigate the evolution of imperial cities and their cartography.

Abstract Façade elements, such as windows, doors, balconies, sculptures, and totems, in architectural heritage images with incomplete structures should be automatically reconstructed for applications in 3D analysis, 3D modeling, virtual tourism, city planning, and the protection and reconstruction of architectural heritage. This study segments façade elements of architectural heritage semantically using YOLOv9. A parameterized expression for the semantic façade model is designed. In addition, the façade layer graph (FLG) and element layer graph (ELG) algorithms are developed based on topological, geometric, and structural constraints to automatically reconstruct the semantic façade model for architectural heritages. The results showed that the average precision (AP) and mean intersection over union (MIoU) achieved using YOLOv9 + FLG-ELG are 86.91% and 85.63%, respectively, on the dataset concerning façade elements of architectural heritages. The AP values obtained from the proposed method are 98.5% on the ECP2011 dataset and 95.3% on the Graz2012 dataset. The YOLOv9 + FLG-ELG method automatically reconstructs regular, irregular, and complex façade layouts with high accuracy and robustness.

Abstract Historic districts play an important role in urban planning and protection. While previous research on soundscapes has focused on acoustic comfort or preferences in these districts, the aspect of authenticity has been somewhat overlooked. Therefore, this study proposes a methodology for constructing soundscapes that enhance the authenticity of such districts. Using the grounded theory approach, we identified four key components for enhancing authenticity via soundscapes: the aim of soundscape design, physical and cultural characteristics of soundscapes, the effects of soundscapes, and the influence of spatial characteristics on soundscapes. A theoretical framework was developed to illustrate the enhancement of authenticity in historic districts via soundscapes. To verify the applicability and advancement of the proposed framework, it was compared with methodologies and steps obtained from previous soundscape research in historic districts. This study underscores the significance of soundscape design in creating authenticity in historic districts, thereby contributing to the development of soundscape design in historic districts and offering sustainable solutions for the protection and renewal of urban cultural heritage.

Abstract Ecological assets (EA) are fundamental to the supply of ecological products (EP). They underpin the provision of ecological functions by ecosystems, their existence, and health. However, a comprehensive assessment of EA and the supply of EP remains lacking. This study employs the Systematic Literature Review (SLR) method and identifies 215 relevant articles from the Scopus database. The study: (1) Analyzes selected literature by publication years, research themes, geographical distribution, affiliations, and stages. (2) Summarizes key advances and significant achievements in domestic and international research. (3) Formulates six critical scientific questions and provides recommendations based on the current status and characteristics of EA and the supply of EP in Karst World Heritage (WH) Sites. This study furnishes research insights for practitioners and policymakers in the field, contributing to the sustainable development of ecosystems in Karst WH Sites.

Abstract The catalytic hairpin assembly (CHA)-based miRNA detection methods have garnered significant attention due to their simplicity and acceptable amplification efficiency. However, these methods necessitate improved sensitivity. In this work, we present a colorimetric and ultrasensitive approach for the detection of cancer-related miRNAs which is initiated by CHA-mediated nicking endonuclease-assisted signals recycling. The target initiates the CHA process to expose the functional section in the P2 probe. This section can activate cascaded recycling cycles to produce numerous linker sequences by Nt.AlwI endonuclease-assisted cleavage of two hairpin signal probes. The 3,3’,5,5’-tetramethylbenzidine sulfate (TMB)/H2O2-based color reaction is induced by the fixation of the cDNA-HRP on the surface of magnetic beads, which is mediated by the linker sequence. The proposed method demonstrates a sensitivity that is either comparable to or superior to that of previous colorimetric miRNA detection methods, as a result of this design. Furthermore, the method demonstrated a promising potential for clinical applications and a high selectivity to target miRNA. Consequently, it provides a colorimetric assay that is both ultrasensitive and dependable for the visual detection of miRNA, which has the potential to revolutionize the early diagnosis of cancer.

Abstract The accurate and dynamic monitoring of osteosarcoma, one of the most prevalent cancers, has a substantial impact on the quality of life of numerous individuals. This study proposes a sample, sensitive, and portable approach to miRNA detection that integrates a catalytic hairpin assembly (CHA) circuit with self-priming mediated chain extension. This method employs CHA as a protein enzyme-free isothermal amplification technique to amplify miRNA signals and induce self-priming through a specially designed hairpin probe. The pyrophosphate sensing probe (pp probe) was employed, which enables dual high-efficiency and stable colorimetric signaling, in contrast to traditional colorimetric modes. This novel system for the colorimetric detection of target miRNA is operated with high sensitivity (LOD of 3.5 fM) and selectivity, with the entire detection procedure requiring approximately 60 min. Additionally, this system could detect miRNA from constructed serum samples with high stability and recovery. This system is unique, extremely simple, and rapid, and it is designed to detect osteosarcoma-related miRNA through a highly sensitive color change. It is likely to be useful in applications that necessitate point-of-care detection of osteosarcoma.

Abstract Exploring a non-destructive and rapid evaluation method for precious ancient ceramic relics is of significant importance. Currently, there are countless monochrome porcelain fragments awaiting measurement and categorization. Various instruments such as XRF, XRD, SEM, OM, and thermoluminescence dating have been extensively utilized by numerous researchers to study ancient ceramics. However, these techniques pose challenges in reliably identifying monochrome porcelain fragments from the same kiln with similar appearance, content, and microstructure due to their limitations. To address this issue, this study presents an acoustic measurement system that utilizes audible frequencies to non-destructively evaluate monochrome porcelain fragments. The proposed method enables the extraction of parameters related to time domain analysis (e.g., group delay), frequency domain analysis (e.g., resonance), and sound loss characteristics of these fragments. This non-destructive and efficient technology for detecting acoustic characteristics of monochrome porcelain fragments presented in this work clarifies the fundamental principles governing the interaction between sound waves and ancient ceramic fragments while providing a completely non-destructive and highly efficient method for classifying and restoring valuable solid cultural heritages like stone, jade, bronze etc. Moreover, this approach can also be applied for non-destructive testing of elastic modulus in advanced ceramic devices including detecting small cracks, deterioration effects due to aging as well as other defects.

Abstract This study investigated the changes in foundries and production techniques of modern and contemporary Korean artistic bronze constructions from the 1910s to the 2000s. To determine the characteristics of foundries and changes in alloy composition based on era, interviews with key sculptors and foundry technicians, analysis of archival materials related to casting, and nondestructive X-ray fluorescence analysis of 92 bronze sculptures by Manlin Choi, were conducted. This study found that foundries for artistic bronze underwent technical and organizational changes from the 1910s to the 2000s. Modern casting techniques and foreign technologies have been introduced since the late 1960s that have resulted in various production methods. The portable X-ray fluorescence analysis of Manlin Choi’s 92 bronze sculptures revealed distinct differences in alloy composition depending on the foundry, findings that have also been supported by records (contracts, receipts, payment confirmations). This study systematically organizes the changes in foundries and production techniques of modern and contemporary Korean artistic bronze, identifying correlations between alloy composition and foundries, and is expected to provide important data for the future conservation and scientific authentication of artistic bronze.

Abstract As an important military defense project in Chinese history, the Ming Dynasty Great Wall and its associated military settlements played a crucial role in maintaining border security. A systematic analysis of how military settlements allocated resources based on external threats and geo-strategic needs is essential to understanding their settlements defense systems. However, this aspect has been relatively under-explored in existing research. Therefore, a resource allocation assessment model for Great Wall military settlements during the Cold Weapon era is established to facilitate a more scientific analysis and quantitative assessment of Military Defense Capabilities(MDC) and Military Requirements(MR). This study employs a combined Analytical Hierarchy Process (AHP) and Principal Component Analysis (PCA) approach to determine the weight of each indicator for both military defense capability and military requirement. Spatial clustering using K-means is conducted to visualize the distribution of these strengths and weaknesses. An Ordinary Least Squares (OLS) regression model links military requirements with defense capabilities, assessing the relationship between settlement locations and historical battle sites. Residual analysis is utilized to identify areas of resource over-allocation or under-allocation. The study reveals that the regional differences in military defense capabilities and requirements within the Zhenbao Town area during the Ming Dynasty correspond closely with the locations of frequent conflicts. This finding suggests that the distribution of defensive capabilities were strengthened in areas with challenging terrain, while the effectiveness and allocation of defense capabilities were determined by logistical support and transportation conditions. This study enhances our understanding of historical military strategies from a historical geography perspective and offers innovative insights for analyzing Great Wall settlement, moving beyond mere sensory intuition and historical experience.

Abstract Ancient Chinese classics embody and transmit the intellectual heritage of China across generations. These texts, rich in enduring ideas, narratives, and insights, have been passed down through a lengthy historical process. While digital modeling of cultural heritage has advanced, research that integrates both the unique characteristics of these classics and their transmission processes remains limited. This study introduces ClaOnto, an ontology specifically designed for ancient Chinese classics. It captures the various versions of these texts and their interrelations, contents, related individuals, locations, periods, and languages. It also emphasizes the processes and evaluations involved in their transmission. This contributes to a more nuanced understanding and increased awareness of preserving ancient classics. ClaOnto comprises three modules: Basic Information, Transmission Information, and Evaluation Information. Its development involved adapting and enhancing existing mature ontologies, as well as designing new concepts and relationships to articulate the knowledge and intangible values transmitted through these classics across generations. Additionally, by employing methods such as data mining, text analysis, and data visualization, this study outlines a workflow for implementing this ontology-based knowledge graph, demonstrated using the Tao Te Ching as a case study. The methodological enhancement enriches the analysis of how the intangible value in classics manifests through transmission.

Abstract Historic gardens contain a greater number and variety of ancient trees, which are older, have unique forms, and larger volumes. These trees hold significant value in both natural ecosystems and cultural heritage. However, current research on the carbon sequestration value of ancient and non-ancient trees in historical gardens is relatively lacking. Based on the unique morphology and carbon storage estimation needs of ancient trees in historic gardens, this paper proposes a morphology-based point cloud single-tree segmentation method. This method can precisely extract the morphological structures of various tree species and accurately estimate their carbon storage. From the perspective of carbon sequestration, it evaluates the correlation between the structural characteristics and carbon storage of trees in historic gardens, as well as the potential changes in their carbon storage capacity.Using the Jing Yi Park’s Jian Xin Pavilions in Fragrant Hills Park as a case study, this method was applied to extract structural indicators of 116 ancient and non-ancient trees. The total carbon storage was found to be 19,171.13 kg, with an average carbon storage of 165.27 kg per tree. Among these, ancient trees accounted for 13,178.32 kg, or 68.74% of the total carbon storage. The study revealed that the correlation between tree age and carbon storage varied by species, and there were significant positive correlations between carbon storage and tree height, DBH, and canopy volume. Notably, there was a significant linear growth trend between DBH, canopy volume, and carbon storage. By 2030, the total carbon storage is projected to increase to 21,924.96 kg, with an annual average increase of 393.40 kg, representing a growth rate of 14.4%.The results indicate that studying the correlation between structural characteristics and carbon storage of aged trees in historical gardens can shed light on the important role of trees in sustainable carbon sequestration. The precise extraction of tree information through 3D digital technology and the prediction of carbon storage potential not only offer new perspectives for the conservation of cultural heritage in historical gardens, urban microclimate planning and design, and spatial management of carbon sinks and emissions but also have significant value for promoting the scientific management and protection of urban green spaces.

Abstract Exploring the spatial pattern and its influencing mechanism of cultural heritage is of great significance for the systematic protection, inheritance and utilization of cultural heritage. In this study, the national-level cultural heritage of China as the research object, and the spatial patterns of the cultural heritage (CH), tangible cultural heritage (TCH) and intangible cultural heritage (ICH) are analyzed are summarized using the multiple geospatial analysis method, and their spatial distribution differences. Then, the optimal parameter geodetector model was further used to analyze the influencing and interaction effect of natural environment (NE) factors, socioeconomic and cultural environment (SCE) factors on the spatial distribution of CH, TCH and ICH, and the interaction mechanism was deeply discussed. The results show that high-density region of CH are mainly located in the southeastern Heihe-Tengchong Line of China, while low-density region are mostly located in the northwestern Heihe-Tengchong Line. In terms of local spatial differences, the spatial distribution of material cultural heritage is different in different river basins, different terrains and different climates. The spatial distribution of ICH mainly shows significant differences in terrain and climate, and does not show significant differences in river basins. In terms of influencing factors, sociocultural environment, education level, historical settlement environment, road traffic, climate, economy, population and terrain factors all have a significant impact on the spatial distribution of CH and TCH. Sociocultural environment, education level, historical settlement environment, road traffic, climate, economy and population have a significant impact on the spatial distribution of ICH, while topographic factors and water system factors have no significant impact on the spatial distribution of ICH. Compared with ICH, TCH is more likely to be directly affected by topographic conditions (altitude, relief of terrain) and hydrological conditions (production and living water sources and flood risk) during its formation stage. At the same time, topographic and hydrological conditions can also indirectly affect the spatial distribution of TCH by directly affecting human agricultural activities, economic activities and cultural activities.

Abstract Interpreting the degradation characteristics of waterlogged archaeological wood (WAW) is crucial for the conservation of wooden cultural heritage. Generally, multidisciplinary diagnostic methods, including physical, micromorphological, and chemical approaches, are employed to evaluate the preservation state of WAW. However, primarily focused on the sample level, this methodology limits the understanding of the variability in degradation from a detailed perspective. In this paper, we adopted the in-situ microscale attenuated total reflectance Fourier transform infrared (ATR-FTIR) method to investigate the degradation variability in waterlogged archaeological Masson pine (Pinus massoniana) wood excavated from the ancient Chinese shipwreck Nanhai No. 1. Specifically, spectra of earlywood (EW), latewood (LW), and compression wood (CW) were extracted and combined with chemometrics to achieve rapid classification of their degradation levels. The micromorphological features of wood cell walls in conjunction with the ratios of lignin (A1509) and carbohydrate (A1370) peak areas were used to estimate the degradation levels. Unlike recent wood, moderate degradation in CW and severe degradation in EW and LW were classified in archaeological samples. The degradation levels were effectively determined through principal component analysis (PCA) and sparse partial least squares discriminant analysis (sPLSDA). The results suggest that chemometric analysis is a promising method to discern the variable degradation levels of archaeological wood at the tissue level. The methodologies developed in this study provide detailed insights into the degradation characteristics in WAW and improve the accuracy of evaluating the preservation state.

Abstract Micro-computed tomography (CT) of ancient Chinese glass dragonfly eye beads has enabled detailed exploration of their internal structures, contributing to our understanding of their manufacture. Segmentation of these CT images is essential but challenging due to variation in grayscale values and the presence of bubbles. This study introduces a U-Net-based model called EBV-SegNet, which enables efficient and accurate segmentation and visualization of these beads. We developed, trained, and tested the model using a dataset comprising four typical Shampula dragonfly eye beads, and the results demonstrated high-precision segmentation and precise delineation of the beads’ complex structures. These segmented data were further analyzed using the Visualization Toolkit for advanced volume rendering and reconstruction. Our application of EBV-SegNet to Shampula beads suggests the likelihood of two distinct manufacturing techniques, underscoring the potential of the model for enhancing the analysis of cultural artifacts using three-dimensional visualization and deep learning.

Abstract The architectural heritages of the Peking-Mukden Railway has witnessed the industrialization of China. When it no longer serves its original function, finding a new way for reuse becomes a trend. It requires feedback from reused cases to guide decision-making. This article aims to propose an approach to post-occupancy evaluation of architectural heritages in the Peking-Mukden Railway and apply it to real cases for analysis. The evaluation indicator system used here consists of a hierarchical structure, evaluation indicators, and interpretation indicators. Cosine similarity, entropy weight method, and precedence chart method are utilized to determine final weights. The GRA-TOPSIS method is utilized to identify reuse cases that require additional optimization. The conclusions are as follows: 1. The cosine similarity can be introduced to neutralize individual preferences. The entropy weight method can be used to neutralize subjective factors. 2. Based on the analysis of the sensitivity levels, indicators that need to be improved first can be identified. Priority should be given to spatial accessibility and cultural transmission when making adjustments with limited resources. 3. The GRA-TOPSIS evaluation method can be used to rank and find reuse cases that need further optimization.

Abstract Spindle whorls are a kind of spinning tools of crucially important in prehistoric period. Haidai region is one of the main historical and cultural areas of prehistoric China, and had a relatively developed textile handicraft production, where a large number of spindle whorls were unearthed, including many decorated ones. In order to make clear the uses of the decorated spindle whorls and the meanings of the patterns on them, the data of prehistoric decorated spindle whorls unearthed in archaeological sites of the period from Beixin Culture to Yueshi Culture in Haidai region of China were collected and analyzed, and the morphological data (dimension and shapes) of them were compared with that of undecorated ones. The patterns on the decorated spindle whorls were analyzed and classified, and the characteristics of the patterns in different cultural periods were studied, and based on this, the purpose of making decorated spindle whorls and the function and meanings of the patterns were discussed. The results showed that the range of morphological data of the decorated spindle whorls in Haidai region is consistent with that of undecorated ones belonging to the same period and unearthed in the same site, while compared with undecorated spindle whorls, decorated ones are more affected by regional culture and thus show different features from the ones unearthed in other archaeological sites belonging to the same cultural period. It is concluded that the most basic function of the decorated spindle whorls should be as practical tools for normal spinning production, and the patterns on them should have multiple meanings such as practical, decorative, distinctive and symbolic. The study of decorated spindle whorls can help us understand the prehistoric regional culture in Haidai region.

Abstract The rockeries of classical Chinese gardens are masterpieces of classical Chinese garden art and form a key element of garden heritage. Consequently, a quantitative study of “rockery shadows” is of considerable importance to the study of “rockery forms.” In this study, we selected the representative North Rockery in Zhanyuan Garden of Nanjing and Ruiyunfeng, Guanyunfeng, and Yulinglong as the objects of the study. This study aims to explore the shadow images of rockeries using image extraction and targeted quantitative analysis methods. Macroscopically, the overall shape of rockery shadows was described using fractal dimensions; microscopically, the aspect ratio, angle, and refinement indexes of each shadow based on each observation angle of the rockery were measured using the PAT-GEOM plug-in in ImageJ software. SPSS Statistics was used for the normal distribution test of the angular distribution data. Consequently, the shadow data of the North Rockery in Zhanyuan Garden and Ruiyunfeng, Guanyunfeng, and Yulinglong, respectively, were analyzed and compared, and four rockery-shadow laws were derived. Finally, the results were applied to the design of the rockery morphological translation based on quantitative analysis of the shadows. The approach presented here will enhance landscape design, support environmental planning, and preserve cultural heritage.

Cancer is a highly prevalent noncommunicable disease with low levels of awareness among the general public, as reported in numerous studies worldwide. Given the daunting nature of cancer, poor knowledge and awareness levels of this disease with regard to its warning signs, risk factors, and the importance of cancer screening among the public may lead to unfavorable health-related outcomes, such as delayed diagnosis and treatment initiation. However, there is potential to tackle this issue with properly designed health educational interventions. Quasi-experimental studies can be implemented to raise awareness in this subject matter via a myriad of traditional and digitalized educational intervention methods. Relevant studies identified across electronic databases were categorized based on the various educational interventions employed in promoting cancer knowledge and awareness. The effectiveness of these interventional approaches was assessed based on the pre-test and post-test scores, which captured the changes in knowledge and awareness levels before and after the educational intervention. Varying outcomes were observed across the diverse methods in individuals of different age groups. Nevertheless, evidence-based cancer educational interventions often yield multifaceted positive outcomes. The aim of this article is to review the various approaches of educational interventions utilized to positively alter the knowledge and awareness on cancer among the general public.

Introduction: The future of our healthcare services highly depends on the current generation of health science students since they are the ones who will work in the healthcare setting. Ensuring their mental well-being is an utmost priority so that they can offer top-tier quality care and services to people in need. This study aimed to explore the prevalence of mental well-being and mental help-seeking attitude among undergraduate sciences students and the impact of socioeconomic status toward both variables. Materials and Methods: A cross-sectional study was conducted among students (N = 364) from six sciences schools at International Islamic University Malaysia via an online survey, which contained three main parts; socioeconomic status, mental well-being assessment using the Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and assessment of mental help-seeking attitude using the General Mental Help-Seeking Attitude Scale (MHSAS). Data were analysed using SPSS, version 29.0. Results: Only 7.1% of the students have positive mental well-being, while 44.8% scored positive mental help-seeking attitude. There were no significant differences (P > 0.05) in students’ mental well-being and any of SES components. There was a significant association between students’ year of study and mental help-seeking attitude (P = 0.029), in addition, WEMWBS and MHSAS scores showed a positive correlation (P < 0.01). Conclusion: Future studies are essential to find out the contributing factors, prevention, and intervention that can be done to help the student in need.

Background: Coronavirus disease 2019 (COVID-19) was first reported in December 2019 in Wuhan, People’s Republic of China, and caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), As the virus took hold in the world, health experts paced efforts to solve the unknown nature of this threat. Methodology: We studied the clinical characteristics, laboratory biomarkers of healthcare workers in the single center, analytical cross-sectional study conducted in tertiary care hospital of the UAE. Sample size of 600 HCWs were screened for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (rRT-PCR) assay using Seegene Allplex and Andis FAST SARS-CoV-2 RT-qPCR detection kits for a period of 6 months. Findings: All the health care workers (HCWs) were vaccinated for the SARS-CoV-2. Out of these, 240 HCWs were reported to be positive. rRT-PCR with a Ct value of 38. The laboratory investigations of the positive cases were collected and analysed further. A comparison of the laboratory tests was made between (I) COVID severe (Ct < 25) and nonsevere (Ct > 25) groups and (II) frontline workers and non-frontline workers. Besides finding short-term and sudden relief, investigators directed their efforts to provide a long-term solution for an ensuing pandemic that influenced all areas of life in unprecedented ways. Conclusion: Awareness among healthcare workers and further long-term studies focusing on their mental health the overall wellness and especially the psychological burden on doctors have received heightened awareness in media and research publications. This information can assist in developing surveillance and infection and control policies and preparedness for future COVID epidemics in similar scenarios in the future.

Background: The effectiveness of reducing healthcare-associated infections (HCAIs) depends on increasing healthcare providers’ awareness, skills, and adherence to standard practices. Mhealth applications provide an innovative approach to enhancing access to information and resources while reducing time and expenses. Objective: The study aimed to develop and evaluate a mhealth application for healthcare providers that offers quick access to updated recommendations, evidence-based guidelines, and protocols for managing patients with HCAIs. Method: The study included the development of the app, followed by a pilot test of its usability among physicians and nursing staff by using the Mobile Application Usability Questionnaire (MAUQ). Results: The mhealth application, named HCAI Shield, was developed with four main menus. The menu includes HCAI’s care bundle: hand hygiene, personal protective equipment, and standard precautions. The information has been gathered following standards established by both national and international organizations. Twenty-one participants took part in the evaluation, and the mean score for the application’s usability was 5.28 ± 0.38. The areas of “ease of use,” “interface and satisfaction” received high mean scores. Conculsion: The HCAI Shield app provides convenient access to evidence-based guidelines and standards for HCAI management. Further evaluation is recommended.

Background: Induction of labor (IOL) initiates labor artificially, aiming to prevent potential risks for both mother and fetus. However, data on IOL outcomes for parous women in the developing countries are scarce. Objectives: This study evaluates maternal and neonatal outcomes in parous women undergoing IOL at a Sudanese hospital. Methods: A descriptive cross-sectional study included 75 parous women undergoing IOL at Haj-Alsafi Teaching Hospital. Demographic data, reasons for IOL, and maternal and neonatal outcomes were recorded. Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS) software, version 26, with P values < 0.05 considered statistically significant. Results: Of 600 women, 75 (12.5%) underwent IOL over 6 months. Main indications were hypertensive disorders (21.3%) and postterm pregnancy (17.3%). Successful vaginal delivery (88%) predominated, with 12% requiring instrumental delivery. Maternal complications included postpartum hemorrhage (8%) and ruptured uterus (1.3%), while 69.7% had no complications. The neonatal survival rate was 91%, with 30.7% admitted to the Neonatal Intensive Care Unit (NICU) for further care. Among the NICU admissions, the mortality rate was 17.4%, all were preterm neonates. Conclusion: IOL is associated with successful VD in 88% and low rate of complications among the parous women; however, greater efforts are needed to prevent serious outcomes among the neonates.

Abstract This paper collects research information and registered data regarding the relationship between climate change and heritage, aiming to present a comprehensive state of studies and research on the subject. This relationship between these two cores is basically the main subject of this research, as well as the discovery of the areas with little information. Nowadays, there is a remarkable increase in the concern of the damage of cultural heritage and the research of methods and means of protection and of interpretation of its value. In the meanwhile, climate change is the other pillar of this paper, with evident damage, eminent jeopardy and accumulative downgrade of heritage assets. The aforementioned facts create a threatening background for the safeguarding of cultural and natural heritage and the transmission to the next generations. In general, stakeholders should focus on the mitigation of the human causes of climate change and the necessary adaptation to the climatic conditions for heritage protection. Through the collection of data, this paper presents the region of Mediterranean, as it has a strategic geographic location and the climatic conditions have already shown notable deviations. The presented information relates to the indices and measurements of the effects of climate change and the overall assessment of the risks of heritage, the irreversible impairment, the most common cultural aspects of the studies and the urgent need of protection. The scope of these data is the design of the appropriate management plan, taking into account the unique identity of each piece of heritage and its environment. To sum up, the kinds of heritage incorporated into the environment structuring a completed landscape with immediate exposure to the conditions, seem to lack the essential research for their preservation. For this reason, the adequate management of cultural and natural heritage in jeopardy, such as the cases in the Mediterranean region, require multidisciplinary assessment for heritage management.

Abstract Due to long-term exposure to outdoor environments, stone artifacts exhibit complex and varying degrees of disease that need to be conserved urgently in order to perpetuate their historical, artistic and scientific values. Owing to the varying degrees of damage inflicted upon cultural relics, discrepancies exist in intervention strategies and conservation materials employed. Hence, it is considerably crucial to conduct a scientific and precise assessment of the preservation status of cultural relics at an early stage for the advancement of cultural relic conservation efforts. In this research, three masonry components of the Hailongtun Fortress site were selected as study objects. A secondary fuzzy comprehensive evaluation system was established through selecting a total of 12 indicators from four aspects, namely, surface change, rock mass structure, physical properties and matrix weathering. The weight of each indicator was determined by using an improved AHP-EWM weight coupling model. The membership degree was calculated by selecting a modified ridge function. The asymmetric nearness method was employed in the final decision-making process so as to correct the error caused by the principle of maximum membership degree. The research shows that the results of the improved evaluation method are in line with the real damage degree of each masonry component, which provides a scientific and quantitative basis for determining the priority of the conservation of masonry components in the Hailongtun Fortress Site. This method is also a reference for carrying out the disease assessment and conservation of other types of cultural relics.

Abstract Canvas paintings are layered structures composed of canvas support sized with animal glue, a preparatory layer of the ground, and paint and varnish layers on the top. Preventing or limiting humidity-induced stresses in these structures requires an understanding of the relevant processes and risks. A three-dimensional model of a canvas painting was used to analyse stresses and crack development in the two-layer structure comprised of a glue-sized canvas on a wooden stretcher with a layer of stiff chalk-glue ground representing a pictorial layer in historic canvas paintings. The model was subjected to a large relative humidity fall which induced shrinkage of the glue-sized canvas. The modelling revealed that when a stretcher with flexible wooden bars is considered, high tensile stresses arise in the ground layer at the corners of the painting, and cracks are formed in these areas in the direction perpendicular to the painting’s diagonal. Ratios of critical distances between cracks to the ground layer thickness for which stresses in the midpoints between the cracks dropped to below the level inducing fracture in the material were estimated for various magnitudes of the relative humidity drop and thicknesses of the ground layer. Increasing ground layer thickness limits the hygric response of the sized canvas and makes the paintings less vulnerable to humidity variations. The ratio of stress along the diagonal calculated for painting with one crack to the solution without cracks was described by the double Lorentz function. A simple procedure of calculating stress variations along the diagonal—using the function—on a sequential addition of cracks was developed. Cracks in central parts of canvas painting were found to be induced by permanent cumulative drying shrinkage of the oil-based paints and grounds due to the evolution of the molecular composition of the oil binder. The outcome of the modelling indicated that the risk of cracking of the pictorial layers in canvas paintings due to drops in ambient relative humidity was small.

Abstract Recognizing online handwriting Yi text is crucial for recording and preserving Yi literature. However, the scarcity of online handwriting Yi text datasets has limited relevant research, impeding the process of Yi informatization. In this work, we use synthetic data to train models, and an Online Handwriting Yi Text Recognition Network (YTRN) is proposed, which extracts robust character features to address the gap between synthetic and real data. YTRN adeptly learns the spatial structure features from path signature feature maps and captures trajectory features from the pen-tip trajectories. Subsequently, an innovative adaptive feature fusion module integrates these two sets of features to yield more comprehensive and robust character representations. Experiments on our newly collected Yi-OLHWDB2.0 dataset demonstrate that our method outperforms previous approaches, achieving an impressive 95.67% accuracy. This highlights the model’s effectiveness in extracting comprehensive and robust features from path signature maps and pen-tip trajectories, significantly enhancing recognition accuracy and generalization.

Abstract The objective of this study was to identify the manufacturer of Hanji, Korean handmade paper widely used in conservation science. To achieve this, machine learning models utilizing attenuated total reflectance–infrared spectroscopy (ATR–IR) were developed to assess the robustness and effectiveness of the computed models. Principal component analysis (PCA), partial least squares–discriminant analysis (PLS–DA), decision tree (DT), and k-NN models were constructed using IR spectral data, with the spectral region between 1800 and 1500 cm⁻1 identified as the critical input variable through Variable Importance in Projection (VIP) scores. The transformation of the obtained spectra into second derivative spectra proved beneficial in this key spectral region, leading to significant improvements in model performance. Additionally, the application of DBSCAN for outlier detection was effective in refining the dataset, further enhancing the performance of the models. Specifically, the k-NN model, when applied to the selected variables and preprocessed with the second derivative transformation, achieved an F1 score of 0.92. These findings underscore the importance of focusing on the 1800–1500 cm⁻1 spectral range and applying outlier detection techniques, such as DBSCAN, to enhance the robustness and accuracy of the Hanji classification models by eliminating the influence of atypical data points.

Abstract Digital technology has become crucial for the protection of cultural relics, enabling their acquisition, preservation, exhibition, and dissemination in a non-contact manner.At present, the three-dimensional(3D) visualization technology of cultural relics focuses on the research of non-true 3D visualization, which cannot provide continuous viewing angle and takes a long time to render. This paper focuses on the acquisition and reproduction of digital information related to cultural relics, and proposes to achieve the true 3D display of cultural relics from a continuous perspective based on integrated imaging(InIm). Building up on traditional InIm, an Element image array (EIA) generation algorithm based on local depth template matching is designed by using spatial geometry relation. Experimental results show that the algorithm not only enables naked-eye 3D visualization of cultural relics, but also the generation speed is more than twice that of the compared 3D display data source generation algorithm.

Abstract As a typical intangible cultural heritage, Toponymic Cultural Heritage (TCH) is rich in geographic information and semantic and physical connotations. In the context of the heritage conservation era, it is highly important to study the spatiotemporal distribution characteristics of toponymic cultural heritage and explore its historical and geographic influencing factors on the sustainable conservation and development of toponymic cultural heritage. However, most existing studies focus on the toponym cultural landscape, and less attention has been given to TCH. Therefore, on the basis of the data of 357 provincial TCH items in Jiangsu Province, this study investigated the spatiotemporal distribution characteristics and historical–geographical influencing factors of the TCH by using geospatial analysis methods, such as the average nearest neighbor, tyson polygon, kernel density estimation, standard deviational ellipse, and superposition coupling analysis, and proposed several strategies for adaptive reuse of TCH. The results show that (1) the TCHs of Jiangsu Province have a spatial distribution characteristic of "sparse in the north, scattered in the middle and dense in the south" and form a high-density agglomeration around the southern part of Jiangsu Province. In the distribution of cultural districts, the Jinling cultural district, the Wu cultural district, and the Huaiyang cultural district have the largest number of TCHs. (2) From the Pre-Qin period to the Ming and Qing Dynasties, TCHs, such as Nanjing, Yangzhou, Zhenjiang, Changzhou, and Suzhou, tended to merge in the southern part of Jiangsu. (3) In terms of type, the roads, streets and alleys of TCHs are the richest, and all types of TCHs are spatially clustered in the southern part of Jiangsu Province, which has a high level of urbanization, industrialization, and a superior geographic environment. (4) TCHs have spatial tendencies toward low altitudes and hydrophilicity, and relatively favorable natural geographical conditions provide a high-quality environment for TCHs in southern Jiangsu Province. Influenced by historical, humanistic, and geographical factors, TCH is unevenly developed spatially. As a historical population concentration area, an important political, economic, and cultural core area, and a center of gravity for cultural development, more TCH resources have survived in the southern part of Jiangsu Province. This study provides a new perspective for interpreting and recognizing TCH as a special intangible cultural heritage and can provide a reference for the sustainable conservation and development of TCH.

Abstract Many tomb murals have punctate losses, cracks, and craquelure due to underground subsidence and changes in their physical support. Visual non-destructive detection techniques enable rapid assessment of how much tomb murals are affected by cracking, providing suggestions for their conservation. However, tomb murals are typically created by sketching outlines and then colored. Detailed sketches can easily interfere with crack detection work, requiring the use of deep learning network to better learn crack features and improve detection accuracy. At the same time the limited data of tomb mural presents a challenge to build a deep learning network. To address these issues, this paper introduces a novel dual-attention detection network (DADNet) for crack segmentation of tomb murals. In this work, a customized dataset is first constructed by collecting mural images from the Tang Dynasty tombs. Then the ConvNeXt framework serves as the basis for feature extraction, enhancing the process. Lastly, a dual-attention module utilizing neighborhood attention and biaxial attention is employed to accurately identify the crack regions. Neighborhood attention performs a local self-attention operation around the pixel point, addressing the limitations of self-attention. This approach significantly reduces computational demands as the image size increases. Biaxial attention performs attention calculations in the horizontal and vertical directions. This compensates for the limitation of neighborhood attention in capturing global dependencies. Our DADNet outperformed the competing methods, achieving the highest recorded scores of 78.95% for MIoU and 61.05% for the Jaccard index.

Abstract This work aims to provide an innovative solution to enhance the accessibility of images by an innovative image to text to speech system. It is applied to Hindu and Christian divine images. The method is applicable, among others, to enhance cultural understanding of these images by the visually impaired. The proposed system utilizes advanced object detection techniques like YOLO V5 and caption generation techniques like ensemble models. The system accurately identifies significant objects in images of Deities. These objects are then translated into descriptive and culturally relevant text through a Google text-to-speech synthesis module. The incorporation of text generation techniques from images introduces a new perspective to the proposed work. The aim is to provide a more comprehensive understanding of the visual content and allow visually impaired individuals to connect with the spiritual elements of deities through the immersive experience of auditory perception through a multimodal approach to make them feel inclusive in the community. This work is also applicable to preserve Cultural Heritage, Tourism and integrating with Virtual Reality (VR) and Augmented Reality (AR). Images of the artistic cultural legacy are hardly available in annotated databases, particularly those featuring idols. So we gathered, transcribed, and created a new database of Religious Idols in order to satisfy this requirement. In this paper, we experimented how to handle an issue of religious idol recognition using deep neural networks. In order to achieve this outcome, the network is first pre-trained on various deep learning models, and the best one which outperforms others is chosen. The proposed model achieves an accuracy of 96.75% for idol detection, and an approximate 97.06% accuracy for text generation according to the BLEU score.

Abstract Archaeological illustration is a graphic recording technique that delineates the shape, structure, and ornamentation of cultural artifacts using lines, serving as vital material in archaeological work and scholarly research. Aiming at the problems of low line accuracy in the results of current mainstream image generation algorithms and interference caused by severe mural damage, this paper proposes a mural archaeological illustration generation algorithm based on multi-branch feature cross fusion (U2FGAN). The algorithm optimizes skip connections in U2Net through a channel attention mechanism, constructing a multi-branch generator consisting of a line extractor and an edge detector, which separately identify line features and edge information in artifact images before fusing them to generate accurate, high-resolution illustrations. Additionally, a multi-scale conditional discriminator is incorporated to guide the generator in outputting high-quality illustrations with clear details and intact structures. Experiments conducted on the Dunhuang mural illustration datasets demonstrate that compared to mainstream counterparts, U2FGAN reduced the Mean Absolute Error (MAE) by 10.8% to 26.2%, while also showing substantial improvements in Precision (by 9.8% to 32.3%), Fβ-Score (by 5.1% to 32%), and PSNR (by 0.4 to 2.2 dB). The experimental results show that the proposed method outperforms other mainstream algorithms in archaeological illustration generation.

Abstract With the rapid advancement of digital games, serious games have emerged as a significant medium for engaging with cultural heritage. As a primary visual element in cultural heritage, color plays a crucial role in users’ digital learning. However, there is currently a scarcity of serious game designs that specifically focus on cultural heritage colors, indicating potential for improvement in the user experience. To further enhance users’ perception of color and create a more engaging and enriching digital cultural heritage experience, this study proposes a virtual reality serious game (VR SG) design method specifically tailored to cultural heritage colors. Additionally, it explores the potential of VR SG in enhancing the education, entertainment, and dissemination aspects of these colors within cultural heritage. Specifically, we explore how to integrate relevant knowledge of cultural heritage colors into the application process of VR SG and assess users’ learning performance, engagement, and interactive willingness within these VR SG. The study employs the colors of the Dunhuang cave frescoes as a case study for design practice. A total of 30 participants took part in a between-group comparison experiment, utilizing a mixed-methods approach that combined quantitative and qualitative assessments to compare the performance of a VR SG with a VR exhibition game. The results indicate that both the VR SG and the VR exhibition game effectively enhance users’ understanding and retention of knowledge, with VR SG users demonstrating higher levels of task engagement, emotional engagement, willingness to explore, and willingness to share. This study confirms the potential of VR SG to enhance the education, entertainment, and dissemination aspects of cultural heritage colors and discusses the implications of VR SG in supporting digital cultural heritage experiences.

Abstract Natural beauty evaluation is an important branch of geography and landscape studies and has profound impact on the protection and sustainable development of World Heritage sites (WHs). However, systematic literature reviews in this field are insufficient. In this study, we comprehensively analyzed 262 relevant studies in the Web of Science and CNKI databases published since 1982, systematically reviewed the research progress in the field of natural beauty evaluation, analyzed the current main research methods, theoretical frameworks, and application practices, and explored their specific implications for the World Heritage karst sites (WHKs). The following observations were made. (1) The number of publications has been increasing year by year, reaching its peak in 2019, indicating increasing research interest in this field. (2) The research content covers five aspects: theory, evaluation indicators, methods, technology, and World Heritage value. The proportion of research on technology integration (33.94%) and evaluation methods (28.05%) is the highest, accounting for 61.99% of the total, and indicating a positive inclination toward innovation and development of research methods. (3) Methodology tends toward interdisciplinary collaboration, and evaluation methods have gradually shifted from a single qualitative description to quantitative, diversified, and interdisciplinary comprehensive evaluation. The combination of traditional and emerging technologies such as SD method, SBE method, AHP method, neuroscience, and UGC data has increased, breaking through time and space constraints and expanding data sources. (4) In future studies, the assessment of natural beauty should concentrate on aesthetic preferences across diverse cultural contexts, develop a concept of global localization, and enhance evaluators' aesthetic perception through multisensory integration. Simultaneously utilizing UGC data to balance the authority of evaluation standards and the inclusiveness of evaluation systems, developing quantifiable indicators, and improving quantitative research in analogy methods; Finally, a karst landscape aesthetic evaluation model is constructed from both global and local perspectives, providing scientific reference for the formation of a unified evaluation system.

Abstract As a critical parameter, thermal conductivity directly determines the heat transfer and temperature variation within rocks, which can lead to mechanical damage and chemical corrosion. Consequently, understanding the thermal conductivity of stone heritage is vital for assessing their deterioration mechanisms and developing effective conservation strategies. This study obtained sandstone samples from the Yungang Grottoes and subjected them to freeze–thaw cycle experiments to generate weathered sandstone samples. Subsequently, the thermal conductivity of these samples was measured under both dry and water-saturated state using the transient plane source method. To analyze the relationship between air–water saturation, porosity, and thermal conductivity, a saturation influence coefficient was introduced. Thereafter, the effectiveness and applicability of 13 commonly used thermal conductivity mixing law prediction models were evaluated based on experimental data. The results suggested that the influence of water saturation on the thermal conductivity of rocks varies with porosity, and water saturation significantly enhances the thermal conductivity of weathered sandstone. Among the 13 common models, the Geometric mean model was found to be more accurate than other models, with superior performance in both dry (MAE, RMSE, MAPE are 0.148, 0.214, 5.59% respectively) and water-saturated (MAE, RMSE, MAPE are 0.244, 0.170, 8.4% respectively) state. The Albert model demonstrates a good fit in the dry state, whereas the Walsh model (with maximum effect), Ribaud model, and Huang model also exhibit good fitting efficacy in the water-saturated state. This study provides a solid foundation for better predicting the thermal conductivity of weathered stone heritage and developing effective preventive conservation strategies.

Abstract This study describes the process of digitally reconstructing the ancient Korean city of Suwon Hwaseong in 3D utilizing Historic Building Information Modeling (HBIM) resources to accurately represent its wooden architectural heritage. Previous 3D reconstructions of cultural heritage have often prioritized appearance or remained partially disassembled. However, our reconstruction method offers a comprehensive representation of the appearance and the internal structure of wooden architectural heritage, which can be suitable for restoration maintenance. To ensure accuracy in digital restoration, we collected and utilized administrative records and historical materials, including the geography, fortress walls, folk houses, and Haenggung (the temporary palace of the Joseon Dynasty)—drawing from the archive of the Korean Cultural Heritage Service’s management records and the 1796 manuscript “Uigwe: Royal Protocols of the Hwaseong Fortress” which documents the construction of the ancient city of Suwon Hwaseong. Extensive architectural records were used to generate HBIM data, which digitized historical records, documents, and drawings to accurately represent the complex layout of the wooden architectural heritage. For the folk houses that lacked design records and the fortress walls that retained their original shape, we performed a digital restoration-based façade modeling. These elements of the ancient city of Suwon Hwaseong were assembled into a 3D model using Unreal Engine (version 5.1.1) to digitally reconstruct the city and enhance its visual representation. The digital restoration content, which utilizes visual effects and precise rendering from a game engine, can be used for the restoration, repair, and maintenance of both appearance and internal structures.

Abstract In this work, four mainstream machine learning (ML) techniques are used to evaluate the bulk porosity and static elastic modulus of weathered Yungang Grottoes sandstone. Datasets are gathered from the experiments, which includes 432 groups effective experimental data including 8 inputs features. bulk porosity and static elastic modulus were considered as outputs to determine the weathering degrees of Yungang Grottoes sandstone. The 4 performance criteria were used to evaluate the ML models. Results demonstrate that the Artificial Neural Network (ANN) is the best-fitted models for estimating the bulk porosity and static elastic modulus compared to Multiple Linear Regression (MLR), Support Vector Regression (SVR), Gaussian Process Regression (GPR). The accuracy of the trained model for static elastic modulus is slightly higher than that of bulk porosity. The GPR and ANN model can accurately predict the bulk porosity and static elastic modulus in training stages. The ANN with multi-hidden layers developed is competent with high degree of precision and generalization ability for bulk porosity and static elastic modulus compared to other selected regression-based ML models (MLR, SVR, and GPR). The coefficient of determinations of ANN in the range of (0.9537–0.9641) during the testing stages is more stable and higher than that of (0.8883–0.9453) other built ML models. The prediction efficiency of pretrained ANN model was well adjusted for the actual and forecast datasets at the training and testing stages, and the error range was no more than 0.7% and 0.15 GPa at both stages of prediction for bulk porosity and static elastic modulus respectively. And the ANN based static elastic modulus prediction model’s error proportions significantly decreased and were confined to a modest range between + 10% and − 10%. The proposed surrogate models are valid for the bulk porosity ranging from 7 to 14% and the static elastic modulus ranging from 0.7 to 1.4 Gpa, which can be utilized for the accurate and fast prediction of the weathering degrees of Yungang Grottoes sandstone.

Abstract Against the backdrop of the deep integration of culture and technology, research and practice in digitization of intangible cultural heritage has continued to deepen. However, due to the lack of data and training, it is still very difficult to apply artificial intelligence to the field of cultural heritage protection. This article integrates image generation technology into the digital protection of Peking opera facial makeup, using a self-built Peking opera facial makeup dataset. Based on the StyleGAN2 network, we propose a style generative cooperative training network Co-StyleGAN2, which integrates the adaptive data augmentation (ADA) to alleviate the problem of discriminator overfitting and introduces the idea of cooperative training to stabilize the training process. We design a Peking opera facial makeup image transform conditional generation network TC-StyleGAN2 which is transferred from unconditional generation network. The weights of the unconditional pre-training model are fixed, and an adaptive filtering modulation module is added to modulate the category parameters to complete the conversion from unconditional to conditional StyleGAN2 to deal with the training difficulty of conditional GANs on limited data, which suffer from severe mode collapse. The experimental results show that the proposed training strategy is better than the comparison algorithms, and the image generation quality and diversity have been improved.

Abstract The Eastern Mausoleum of Qin State is a significant component of the Qin Dynasty's royal tombs, reflecting the social development level during the Warring States period (475 BC ~ 221 BC) in China. At the onset of our investigation, we mapped the site's boundaries utilizing Corona satellite imagery and employed the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) to identify archaeological features. Additionally, this study is the first to propose the use of thermal infrared band data from the SDGSAT-1 satellite to explore thermal archaeological traces, demonstrating their viability for archaeological site analysis. Subsequently, electromagnetic (EM) prospection was utilized to validate the presence of an ancient burial chamber passage. Landscape monitoring and analysis of the No.1 Mausoleum were performed using Corona and Google Earth images, revealing the accuracy of the Geomancy Theory of Chinese mausoleums through dynamic remote sensing of surface changes. Furthermore, our employment of space-to-ground observational modalities and resultant Digital Elevation Models (DEM) have been used to provided new insights into the application of Remote Sensing (RS) and Geomancy in archaeology, thereby emphasizing the pivotal role of site selection in heritage preservation. This research underscores the promise of synergistic space-ground observations in both exploiting the archaeological riches of cultural heritage sites and ensuring the enduring conservation of these irreplaceable patrimonial assets.

Abstract Historical figures have important significance worldwide. This paper introduces the concept of historical Geographical Information System (HGIS) using the lives of two personalities from Chinese history as case studies: Su Shi, a literary figure of the Northern Song Dynasty, and Zuo Zongtang, a military strategist from the late Qing era. By studying the geographical points marking their life activities, their migratory patterns were explored, along with the dynamics of their social networks within time and space, examining the distinctive phases and characteristics of their individual journeys. Kernel density estimation, standard deviation ellipse, location-based distance analysis, and social network graphs were employed in this work. Our findings reveal that Su Shi’s migrations were largely dictated by official appointments, ultimately rooted in imperial successions and factional strife, with his intellectual pursuits significantly influenced by the humanistic milieu. Conversely, Zuo Zongtang’s migrations were predominantly shaped by war, reflecting the challenges of the late Qing era in relation to governance, sovereignty, and diplomacy. The military encampments selected by Zuo Zongtang tended to be situated near water sources, illustrating how his migratory trajectory was influenced by natural geographic conditions. The social circles of these figures are tied to their social and political stature. Through the socio-historic context, the characteristics of these historical figures’ behavioral trajectories relate to the unfolding process of societal and historical development. These insights offer a glimpse into the life journey behind historical figures, implicitly highlighting their perseverance and resilience in adversity, thereby describing innovative approaches to inheriting and disseminating the cultural legacy.

Abstract Weiyang Palace, the royal palace of the Western Han Dynasty, is a part of the Silk Roads: the Routes Network of Chang’an-Tianshan Corridor on the World Heritage list. The south palace wall of Weiyang Palace is a well-preserved earthen heritage site within the palace, but it is undergoing continuous deterioration due to the influence of vegetation and external environmental factors. This study pioneers the integration of high-resolution three-dimensional LiDAR scanning with multi-source data analysis, including unprecedented on-site botanical surveys, to explore the subtle effects of different vegetation types on the structural integrity of the south palace wall. Through contour line analysis and facade grid analysis, we extracted the deterioration locations of typical sections of the earthen heritage sites. And we classified the overlying vegetation types on the wall using an object-oriented classification algorithm. Our findings reveal a complex interaction between vegetation and earthen structures: paper mulberry exhibits protective qualities against erosion, while Ziziphus jujuba significantly exacerbates structural vulnerabilities. The methodologies applied in this study for extracting deterioration at earthen heritage sites and integrating multi-source spatial data can serve as a technical application model for monitoring and analyzing the driving forces of earthen heritage sites along the entire Silk Road network, thereby better guiding the conservation of earthen heritage sites.

Abstract The 35 wooden coffin paintings from the Tubo period of the Tang Dynasty, housed in the collection of Qinghai Tibetan Medicine Cultural Museum, are valuable materials for studying Tubo culture. Research has shown that the wood used for coffin paintings was cypress. The adhesives contain bovine collagen and chicken ovalbumin. The pigments used include carbon black, azurite, cinnabar, orpiment, minium, and lead white. This article provides a statistical analysis of the types and areas of diseases that appear in wooden coffin paintings. Through the application of descriptive statistics, correlation coefficient analysis, principal component analysis, and cluster analysis, it was determined that deterioration phenomena such as rotten, crack, pulverization, and discoloration disease were particularly pronounced in coffin paintings. Key variables influencing the disease of wooden coffin paintings include crystal salt, drop, and pulverization. The dataset was categorized into three distinct clusters, each exhibiting significant differences. This study offers valuable insights and foundational support for the future conservation and restoration of coffin paintings.