Journal of Cultural Heritage最新文献

Built cultural heritage is exposed to various deterioration problems caused by different types of actions. To reduce the need for major interventions, preventive conservation (PC) approaches were proposed, based on data collection, regular monitoring, inspections, and control of environmental factors. Monitoring actions able to depict the evolution of buildings’ deterioration state, have been proposed and implemented in real cases. Considering that digital images (DI) of historical facades are constantly collected by different subjects and for different purposes, they represent the widest existing data source to support PC approaches and develop predictive tools. DI of historical façades can be used to help in the early recognition of different types of deterioration processes, supporting the creation and application of predictive models based on machine learning (ML) methods. This work proposes a method for the automatic detection of biological colonisation of building facades. A convolutional neural network (CNN) has been trained and tested with images representing the microalgae and cyanobacteria growth process on historical bricks’ facades, collected during experimental activities in controlled conditions. The trained model is characterized by an accuracy of 87 % and can recognise bio-colonisation on different types of bricks. The trained model has been applied to a historical building used as a case study. The facades of the case study are constantly monitored by surveillance cameras, and DI of the facades are often collected due to the public function of the building. The study shows that by simply processing these images with the trained network it is possible to detect the first stage of bio-deterioration processes. This work is part of more extensive research for the early detection of different types of building façade damages and can be easily implemented where DI coming from surveillance cameras or other sources are available.

In recent years, machine learning (ML) has gained significant importance in the field of cultural heritage research. Its advanced data analysis techniques have become a crucial tool in many areas of heritage science. This literature review intends to discuss the applications of ML to studies on cultural heritage objects using the analytical chemistry methods. The analysis of large datasets obtained from complex measurements with the use of ML algorithms has been demonstrated to result in a deeper understanding of the studied objects. Such analyses have also been shown to provide new perspectives on many problems. The article outlines studies on varied materials such as pigments, paper, metals, and ceramics. It presents analyses that use diverse ML methods, including unsupervised and supervised techniques, utilizing both traditional algorithms and neural networks. It also provides an introduction to understanding ML, its principles and methods, with the focus on practices applicable to heritage science.

The Forbidden City exemplifies the official architecture of the Ming (C.E. 1368–1644) and Qing (C.E. 1644–1911) dynasties in China. The buildings within the Forbidden City adhere to a specific construction system and hierarchy. This study examined the organic additives in eighty-three lime mortar samples collected from the Forbidden City. These mortar samples were categorised into two main groups: garden mortar and construction mortar. The construction mortar was further subdivided into masonry, rendering, tile roof, and pointing mortars. Classical chemical analysis was performed to identify organic residues in the samples, including glutinous rice, sugar, oil, blood, and protein. Additionally, ovalbumin, casein, collagen, and peach gum were detected using enzyme-linked immunosorbent assay (ELISA). The results confirmed historical records regarding to the use of organic additives in ancient mortars. Statistical analysis revealed that the organic additives added to different types of mortars were selected according to the location and function of the mortar. This evidence supports the validity of traditional Chinese composite mortar scientifically. Ancient Chinese artisans adhered to rules aimed at practicality and functional realisation when selecting organic additives.

NIR reflectography with silicon sensors (CMOS) is commonly acquired with 780 nm band-pass filters that allow the acquisition of clear images and high shutter speeds, while maintaining a low equipment cost. In this way, however, acquisition between 1000 nm and 1150nm-where the silicon sensor is still formally infrared sensitive-is in fact overhelmed by the stronger sensitivity in the infrared spectrum portion between 780 nm and 980 nm. Coupling a 1070 nm (± 5 nm) interferencial filter to an 87C nm IR pass filter (FHWH 850 nm) acquisitions in this portion of the NIR spectrum were carried out, witnessing a outstanding increase in visibility of underdrawings and pentimenti. A practical test of the effectiveness of the filters system mounted on the Nikon D800 IRUV was made, comparing the results with those obtained by the “Osiris” InGaAs detector by Opus Instruments. The comparison was performed on the “Deposition” (oil on panel) by Antonio Semino (1485–1555) in the collection of the Accademia Ligustica of Genoa, highlighting a significant qualitative proximity between the results obtained with the interference system and those with InGaAs detector, compared to the conventional acquisition with single IR long-pass filter.

In addition, the 1070nm+87C filter system was used to increase the recognition capability of azurite pigments. This procedure widens the possibilities of first-impact diagnostics by means of low-cost and market available imaging systems based on commercial CMOS IRUV cameras..

This study endeavors to confront the challenge of adhering to international guidelines for Historic Urban Landscape (HUL) values and heritage conservation in developing nations, specifically focusing on Iran. Conventional reliance on basic buffer zone methodologies for safeguarding national monuments often leads to the oversight and subsequent deterioration of valuable structures, resulting in irreversible decay. This research introduces an innovative GIS-based zoning methodology alongside a comprehensive framework for assessing heritage values to mitigate these deficiencies. Grounded in seminal texts such as the Venice Charter (1964), Washington Charter (1987), and Vienna Memorandum (2005), this study extends the HUL approach to establish a cost-effective yet robust practical foundation. Through the Lar Old City case study, the research systematically integrates the Analytical Hierarchy Process (AHP) and Inverse Distance Weighting (IDW) within GIS to evaluate heritage values and map character areas. This approach facilitates regular assessments and promotes sustainable management of built heritage, demonstrating efficiency in resource allocation. The framework aims to bolster conservation efforts by embedding HUL values and advocating for sustainable urban development consistent with contemporary planning principles. The findings underscore this approach's practical significance and applicability, offering a comprehensive framework to bridge gaps in heritage conservation practices and safeguard cultural heritage for future generations.

Eleonore Koch is a German artist known for her paintings featuring arrangements of colors and ordinary objects. She spent a significant part of her life in Brazil, where she had the opportunity to interact with and learn from Alfredo Volpi, a colorist artist who introduced her to the tempera technique and the use of natural and mineral pigments, replacing oil-based industrial ones. A collection of powdered pigments she used during her lifetime was studied by spectroscopic analysis, forming an initial basis of knowledgement about Koch's pigments. In this paper, one painting from the Museum of Contemporary Art of the University of Sao Paulo (MAC-USP) collection was analyzed by spectroscopic (ED-XRF, Raman and FTIR) and imaging techniques. The painting palette was compared with some powdered pigments from the artist's collection. The pigments identified in the artwork are Chrome Oxide Green, Titanium White, Phthalocyanine Blue, Ivory or Bone Black and a yellowish/brown pigment rich in hematite. The findings indicate that most of the pigments found in Koch's artwork were also part of her personal collection.

In this research, calcium hydroxide nanoparticles, as a carbonate consolidation method, have been evaluated on carbonated fossil bone samples from decontextualized Cheirogaster richardi specimens’ fragments.

The main objective was to assess whether the treatment improved fossil bone surface cohesion and mechanical strength by creating a consolidated carbonate matrix in fossil substrate. Treatment penetration capacity and chemical compatibility without causing observable alterations in substrate porosity and external appearance were considered as significant questions to be assessed. Samples were analysed both before and after treatment using scanning electron microscopy, spectrophotometry, weight measurement control, water absorption assessment, conductivity and pH measurement, Vickers microindentation and tape testing. During analysis and evaluation, changes in fossil bone after treatment compared to its original condition have been taken into account.

Results point out that hardness and cohesion increased significantly after treatment, bonding together disaggregated particles via a calcium carbonate micrometric layer, with almost negligible changes in surface topography and colour. In addition, calcium hydroxide nanoparticles penetration depth was remarkable. Conductivity, pH and weight hardly changed and porosity reduction was observed without complete pore blockage. To sum up, the treatment was effective and suitable for carbonate fossil bones having a highly compatibility with carbonate fossil bones substrates.

Cleaning a painting is a process that requires knowledge of its materiality, integrity, and solvent systems. Aqueous solvent systems are a sustainable alternative, but their use must consider the potential harm that can arise in the process- such as swelling and leaching of layers underlying the dirt. Modern oil paintings made from the twentieth century onwards may be sensitive to aqueous solvents and suffer such damage. In this work, the cleaning of a white monochromatic oil painting by artist Gilda Azevedo was carried out with a microemulsified system of water in white-spirit using Tween 80 and ethanol as surfactant and cosurfactant, respectively. The microemulsified system and emulsions are the result of a ternary pseudodiagram where water, white-spirit, and surfactant/cosurfactant are carefully rationed. The emulsions obtained were characterized by measurements of conductivity and Dynamic Light Scattering. The artwork was examined by infrared absorption spectroscopy and X-ray fluorescence spectroscopy. Cleaning tests were firstly performed with emulsions and microemulsion and the removal of pigments was qualitatively analyzed by X-ray fluorescence spectroscopy. It was observed that the microemulsified system was an efficient cleaner while causing less removal of pigments compared to emulsified systems and, thus, chosen for cleaning. This cleaning efficiency was attributed to the use of water-white-spirit mixes capable of interacting with hydrophobic and hydrophilic substances in dirt. The lower pigment removal was ascribed to the dynamic percolation system and the nanometric size of the microemulsions.

Library collections are mostly made of porous cellulose-based materials such as papers and textiles. Submicron particles, representing up to 90% of particulate matter (PM) mass in libraries and archives, deposit on book surfaces and can also penetrate into small openings, including inter-fibre spaces. These particles can cause degradation of archival documents and therefore it is necessary to clean them. An alternative method of cleaning using the CO₂ snow jet was tested and compared with six traditional mechanical dry cleaning techniques. Different types of papers and textiles (bookbinding cloths) commonly used in library collections were treated with the jet using a newly developed automatic system. Measurements included the assessment of particle removal efficiency and possible degradation of the cellulose materials. The method was verified using real archival documents. Results revealed that the jet was effective in removing submicron particles, including those embedded in the fibrous surface. The CO₂ snow jet did not alter the surface properties of uncoated papers and textiles, whereas the degradation of coated samples was probably caused by surface temperature decrease after the CO₂ snow application. In contrast, the mechanical dry cleaning methods were almost ineffective for the submicron PM. Moreover, the mechanical techniques alter the surface by leaving visible crumbs of the cleaning material, releasing fibers, and changing of fibers structure. The results indicate that CO₂ snow jet cleaning using the automatic system is a suitable method for common types of papers and textiles with uncoated surfaces.