Heritage Science最新文献

The use of digital technologies in archaeological research has become considerably more widespread in recent years. While the earliest records of the use of electronic data in archaeology date from the 1950 and 1960s, the field has kept growing with the increasing interest in digital tools such as digital photography, three-dimensional imaging, GIS, virtual and artificial reality applications, CAD and facial reconstruction. Such digitization practices are used frequently for documenting, record keeping, and preserving and representing the data recovered from archaeological contexts, and are linked to other fields, such as cultural heritage studies and museology. Facial reconstruction is used to recreate the faces of individual from the past using their skeletal remains. It has been practiced for different reasons in the fields of forensics, anthropology, and archaeology. This study focuses on the facial reconstruction of a skull unearthed from Juliopolis. The reason for choosing this skull in this study is that it is the first and only known deformed skull dated to the Roman period in Anatolia. For the facial reconstruction application, authors created a 3D modelling of the skull by photogrammetry. Then, the missing parts of the skull are completed using the virtual donor library. The results are presented in different forms, as grayscale, in colour with eyes closed or open. Also, the type of deformation is demonstrated in the skull. This study adopts a digital process and is more strongly linked to data interpolation related to the external surface of the face. The prominent advantage of the methodology is being strongly supported by information obtained from computed tomography (CT) scans of living individuals, leaving a little room for the artistic issue in relation to the basic aspect resulting from the interpolation of data. The benefit of facial reconstruction is especially important since it is a way of preserving and presenting archaeological and anthropological data.

Understanding the cultural characteristics and evolution of traditional dwellings in the context of ethnic integration is of great significance for protecting the diversity of residential cultural heritage of ethnic minorities. This article compares the ethnic differences in the internal spatial configuration of vernacular dwellings in Xiangxi region, China, a typical multi-ethnic area where “line-shaped” dwellings are prevalent among the Miao, Dong, Yao, Tujia, and Han groups. This study found that the spatial sequence, ritual axis, importance of fireplace, spatial hierarchy, and privacy of bedrooms of each ethnic group's dwellings present a trend towards Han’s dwelling culture in the order of "Western Miao, Southern Dong, Northern Dong, Yao, Eastern Miao, Tujia". Based on the analysis of the lifestyles, ethnic customs, and historical development processes of ethnic minorities, this study identifies that the main reasons for the formation of the aforementioned sequence lie in the differences in the historical diffusion patterns and paths of Han culture in Xiangxi. This article analyses the ethnicity of minority residential culture in Xiangxi and its spatial configuration formation process, revealing the relationship between the spatial effect of Han cultural diffusion pattern and the spatial difference pattern of each ethnic group's vernacular dwelling space configuration, and expanding the connotation of "cultural genotypes" in multi-ethnic areas.

Traditional Chinese landscape painting is prone to low-resolution image issues during the digital protection process. To reconstruct high-quality images from low-resolution landscape paintings, we propose a novel Chinese landscape painting generation diffusion probabilistic model (CLDiff), which is similar to the Langevin dynamic process, and realizes the transformation of the Gaussian distribution into the empirical data distribution through multiple iterative refinement steps. The proposed CLDiff can provide ink texture clear super-resolution predictions by gradually transforming the pure Gaussian noise into a super-resolution landscape painting condition on a low-resolution input through a parameterized Markov Chain. Moreover, by introducing an attention module with an energy function into the U-Net architecture, we turn the denoising diffusion probabilistic model into a powerful generator. Experimental results show that CLDiff achieves better visual results and highly competitive performance in traditional Chinese Landscape painting super-resolution tasks.

Scratches are a common continuous structural type of damage in archival films. Scratch pixel level segmentation algorithms still use general image segmentation, and with poor the detection. Based on the characteristics of scratches, a scratch model based on a Gaussian probability density function is proposed, a local adaptive one-dimensional Gaussian weighted segmentation algorithm is designed, and an invalid region filtering mechanism is described. Based on experimental results, the local one-dimensional Gaussian weighted segmentation algorithm proposed in this paper can preserve the integrity and continuity of scratches, and effectively suppresses edge defects; the invalid region filtering mechanism can effectively reduce the false detection of scratches. Adding a scratch trajectory can effectively reduce the chances of missing the detection of scratches, and the stability of the traditional algorithm using Kalman filters to predict the scratch trajectory is poor. According to the similarity of multiple scratch trajectories, a calculation method of trajectories based on U-net is described. Experimental results show that this method can calculate the scratch trajectory stably and effectively.

This literature review presents a comprehensive review of life Cycle Assessmernt (LCA), as an emerging tool in the field of cultural heritage research and demonstrate how this tool could be useful to support the development of green heritage science into an environmentally responsible field of scientific endeavour. LCA is a standardised, structured, comprehensive, international environmental assessment tool and a rapidly evolving field of research that leverages and harmonises efforts across many sectors to inform environmentally-friendly solutions and choices. LCA has been growing in importance as an evidence-based tool in the field of heritage science, being used as a decision-support tool at micro level (typically for questions related to specific products/processes) and macro levels (e.g. strategies, scenarios, and policy options). This review explores applications of LCA (and the complementary Life Cycle Cost Assessment (LCC), and Social Life Cycle Assessment (S-LCA)) to a wide array of conservation and preservation actions. The paper also examines challenges associated with the application of these life cycle-based methods in heritage science, in order to put forward a set of recommendations to guide the domain of heritage science towards greener and more sustainable practices and impacts.

Based on a review of the principles of green chemistry, green analytical chemistry, green engineering, and nature conservation, the paper also attempts to formulate nine principles of green heritage science, taking into account the complexity of research challenges and the environmental and socio-economic sustainability.

This paper studied Late Iron Age ceramic fragments from Nditam village (Centre Region, Cameroon), the technological features and deduced the type of the raw materials used to produce them by combining different analytical techniques based on X-ray fluorescence, powder X-ray diffraction, thermogravimetry, polarized optical microscopy, spectrophotometry and hydric tests. Macroscopic observations suggest the existence of three types of ceramics according to their colour, black, greyish and red, in the two opposite surfaces, outer (or external) and inner (internal). The chemistry indicates that non-calcareous clayey material was used for ceramic production. The correlation between mineralogy, petrography and the geology of the region suggests a local production of ceramics. Moreover, the chemistry of the samples confirms the existence of the three macroscopic groups and suggests the use of local raw materials for their production. From the mineralogical point of view, quartz, feldspar and mica (biotite and muscovite) were identified in all the samples, while kaolinite and amphibole were detected in some of them. The differences in the mineralogy may indicate some variations in the firing temperature, being lower in the ceramics containing kaolinite compared to the other samples. All the samples have similar water absorption behaviour. According to the colours of the ceramics, a prevalence of oxidising firing conditions was present in the kilns. However, partial reducing and short duration firing conditions were also possible. Comparative study with the mineralogy of ethnographic ceramics from southern Cameroon shows some similarities and suggests a continuity in the use of different local clay pits in this region over time.

Palm leaf manuscripts (PLMs) are of great importance in recording Buddhist Scriptures, medicine, history, philosophy, etc. Some damages occur during the use, spread, and preservation procedure. The comprehensive investigation of Sanskrit PLMs is a prerequisite for further conservation and restoration. However, current damage identification and investigation are carried out manually. They require strong professional skills and are extraordinarily time-consuming. In this study, PLM-SegFormer is developed to provide an automated damage segmentation for Sanskrit PLMs based on the SegFormer architecture. Firstly, a digital image dataset of Sanskrit PLMs (the PLM dataset) was obtained from the Potala Palace in Tibet. Then, the hyperparameters for pre-processing, model training, prediction, and post-processing phases were fully optimized to make the SegFormer model more suitable for the PLM damage segmentation task. The optimized segmentation model reaches 70.1% mHit and 51.2% mIoU. The proposed framework automates the damage segmentation of 10,064 folios of PLMs within 12 h. The PLM-SegFormer framework will facilitate the preservation state survey and record of the Palm-leaf manuscript and be of great value to the subsequent preservation and restoration. The source code is available at https://github.com/Ryan21wy/PLM_SegFormer.

Changzhi Guanyin Hall, a folk temple from the Ming Dynasty, embodies the essence of the ‘unity of the three religions’ philosophy, centred around Guanyin Bodhisattva. Over 500 sculptures reside within a modest 70 m² space, encompassing representations from Confucianism, Buddhism and Taoism. Ranging from a towering 2 m to a mere 10 cm, these sculptures depict an array of characters and mythological scenes, bestowing considerable importance upon the painted sculptures of Guanyin Hall. Varying degrees of deterioration have affected these sculptures due to the passage of time and suboptimal preservation conditions, highlighting the imperative need for meticulous restoration efforts. However, the absence of comprehensive analyses pertaining to the production process of Guanyin Hall sculptures has hindered the restoration groundwork. This study focuses on fallen hanging sculptures and debris, encompassing intact sculptures, clay fragments, wooden sticks, plant fibres, wires and pigments. Employing a series of techniques, including X-ray photography, microscopic analysis, mineral analysis (MLA), laser particle size testing, ion chromatography, X-ray fluorescence spectroscopy (XRF), X-ray diffractometer (XRD) and energy dispersive spectrometer (SEM–EDS) analysis, this research characterises the constituent materials used in crafting these artifacts. Instead of a full-body skeleton, the findings reveal that the small hanging sculpture is supported by delicate wires that hold specific areas, such as the arms and the gown hems. The hanging sculptures are made from a single type of clay and are reinforced with either mulberry bast or wheat straw fibres. A Pinaceae wood stick affixes the head to the body, and the sculpture is then suspended on the wall through nails inserted into the feet. The moulded clay undergoes a sequence of carving, drying and polishing and is coated with a white ash layer before receiving intricate painting. Mineral pigments, including cinnabar, red lead, iron red, cerussite, atacamite, brochantite and azurite, adorn the surface of the sculptures, with gold foil embellishing the golden elements. The intricate artisanry and multifaceted material composition of Guanyin Hall’s painted sculptures render them unparalleled artistic treasures, not solely within Shanxi but across the entire nation. Furthermore, this study establishes a dependable foundation for conservation and restoration endeavours.

Abstract

Visual analysis and authentication of artworks are challenging tasks central to art history and criticism. This preliminary study presents a computational tool for scholars examining and authenticating a restricted class of paintings, with a specific focus on the paintings of Raffaello Sanzio da Urbino, more popularly known as Raphael. We applied transfer learning to the ResNet50 deep neural network for feature extraction and used a support vector machine (SVM) binary classifier in support of authentication. Edge detection and analysis algorithms, considered to be crucial for capturing the essence of Raphael’s artistic style, including the brushwork signatures, were also integrated and are used as an authentication tool. The machine learning approach we have developed demonstrates an accuracy of 98% in image-based classification tasks during validation using a test set of well known and authentic paintings by Raphael. Of course, a full authentication protocol relies on provenance, history, material studies, iconography, studies of a work’s condition, and more. Our work, then, contributes to just a portion of a full authentication protocol. Our findings suggest that machine learning methods, properly employed by experts aware of context, may enhance and expand traditional visual analysis for problems in art authentication.

The Beijing-Hangzhou Grand Canal carries unique social and cultural significance as a world cultural heritage, but with the acceleration of global urbanization, it has potentially severe environmental risks under continuous anthropogenic disturbances. Therefore, to protect the ecological and cultural values of the Grand Canal, it is necessary to assess the corresponding relationship of water quality to land use and the perception of ecosystem services that focus on cultural ecosystem services (CES). This study aims to analyze the water quality response to land use in the Beijing-Hangzhou Grand Canal, describe the land use types closely related to water quality, and propose corresponding management strategies for enhancing CES. This study investigated the impacts of land use structure and landscape pattern on water quality by calculating the correlation between land use structure and landscape pattern indices and water quality in buffer zones of different distances on both sides of the canal. The results show that green land dominates the land use structure and can effectively reduce water pollution in the canal. On the other hand, urban impervious surfaces showed a significant positive correlation with pollution contributing to low water quality. We accessed the impact of water quality on the perception of CES in the Beijing-Hangzhou Grand Canal and proposed optimization strategies for promoting CES. Both content analysis and thematic analysis were applied to analyze the impact of the water environment quality of the Beijing-Hangzhou Grand Canal on the perception of CES. We found that the perceptions of CES along the Beijing-Hangzhou Grand Canal are associated with the public’s opinions on its cultural heritage services and artistic inspiration services. The perceptions of CES are closely related to the quality of the water environment and riparian greenness, which affect the values of cultural heritage and conservation of the Beijing-Hangzhou Grand Canal.