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This paper aims to assess the efficiency of emulsified essential oils in glycerol as eco-friendly antimicrobial and plasticized agents added to the biopolymer of gelatin for lining historical oil paintings on canvases.

Cedar oil, cinnamon oil and their mixtures were emulsified in glycerol and incorporated into gelatin adhesive as green biocides and plasticizers. Physical, biological, chemical and mechanical tests were conducted on experimental mock-ups to assess the gelatin-based adhesive formulations for the reinforcement of canvas supports. Scanning electron microscope, colorimetric measurements, antimicrobial activity test, attenuated total reflection-Fourier transform infrared spectroscopy, tensile strength and elongation tests were carried out on the mock-ups before and after the artificial aging.

The formulations of gelatin-based adhesive with cinnamon and cinnamon-cedar mixture emulsified in glycerol proved their efficiency on the antimicrobial activity test, chemically delaying the decomposition of gelatin and accordingly providing compatible mechanical properties. Gelatin-based adhesive with emulsified cinnamon oil showed a slight yellowing that was quite improved with the mixture of the cinnamon-cedar-based adhesive formulation.

This study promotes a green approach to lining historical oil paintings by developing green formulations from bio-based origins that minimize the shrinkage and microbial infection of gelatin for lining paintings.

The nickel-based alloys Inconel 625 and Inconel 718 stand out due to their high strength and corrosion resistance in important industries like aerospace, aviation and automotive. Even though they are widely used, current techniques of producing materials that are difficult to cut pose several problems from a financial, ecological and even health perspective. To handle these problems and acquire improved mechanical and structural qualities, laser powder bed fusion (LPBF) has been widely used as one of the most essential additive manufacturing techniques. The purpose of this article is to focus on the state of the art on LPBF parts of Inconel 625 and Inconel 718 for microstructure, mechanical behavior and postprocessing.

The mechanical behavior of LPBF-fabricated Inconel is described, including hardness, surface morphology and wear, as well as the influence of fabrication orientation on surface quality, biocompatibility and resultant mechanical properties, particularly tensile strength, fatigue performance and tribological behaviors.

The postprocessing techniques such as thermal treatments, polishing techniques for surface enhancement, mechanical and laser-induced peening and physical operations are summarized.

The highlighted topic presents the critical aspects of the advantages and challenges of the LPBF parts produced by Inconel 718 and 625, which can be a guideline for manufacturers and academia in practical applications.

This study aims to investigate the performance analysis, science mapping and future direction of artificial intelligence (AI) technology, applications, tools and software used to preserve, curate and predict the historical value of cultural heritage.

This study uses the bibliometric research method and utilizes the Scopus database to gather data. The keywords used are “artificial intelligence” and “cultural heritage,” resulting in 718 data sets spanning from 2001 to 2023. The data is restricted to the years 2001−2023, is in English language and encompasses all types of documents, including conference papers, articles, book chapters, lecture notes, reviews and editorials.

The performance analysis of research on the use of AI to aid in the preservation of cultural heritage has been ongoing since 2001, and research in this area continues to grow. The countries contributing to this research include Italy, China, Greece, Spain and the UK, with Italy being the most prolific in terms of authored works. The research primarily falls under the disciplines of computer science, mathematics, engineering, social sciences and arts and humanities, respectively. Document types mainly consist of articles and proceedings. In the science mapping process, five clusters have been identified. These clusters are labeled according to the contributions of AI tools, software, apps and technology to cultural heritage preservation. The clusters include “conservation assessment,” “exhibition and visualization,” “software solutions,” “virtual exhibition” and “metadata and database.” The future direction of research lies in extended reality, which integrates virtual reality (VR), augmented reality (AR) and mixed reality (MR); virtual restoration and preservation; 3D printing; as well as the utilization of robotics, drones and the Internet of Things (IoT) for mapping, conserving and monitoring historical sites and cultural heritage sites.

The cultural heritage institution can use this result as a source to develop AI-based strategic planning for curating, preservation, preventing and presenting cultural heritages. Researchers and academicians will get insight and deeper understanding on the research trend and use the interdisciplinary of AI and cultural heritage for expanding collaboration.

This study will help to reveal the trend and evolution of AI and cultural heritage. The finding also will fill the knowledge gap on the research on AI and cultural heritage.

Some similar bibliometric studies have been conducted; however, there are still limited studies on contribution of AI to preserve cultural heritage in wider view. The value of this study is the cluster in which AI is used to preserve, curate, present and assess cultural heritages.