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In recent years, cultural tourism has increasingly embraced museum visits. Museums serve as both cultural heritage guardians and integral parts of tourist destinations, significantly impacting visitor satisfaction and experience. Moreover, online museum reviews have become a crucial indicator of museum service quality, visitor experience, and public feedback in the digital age. An analysis of online reviews on major tourism websites and social media platforms can assist museums in developing appropriate management strategies. This study employed the structural topic model (STM) to analyze online museum reviews, identifying three primary attributes of museums and visitors\' personal experiences, as well as 19 sub-attributes. The study confirmed that core offerings have a positive impact on visitor experience and satisfaction, while peripheral services and overall ambiance are also positively related to visitor experience and satisfaction. Furthermore, the results of structural equation modeling demonstrated that visitors\' personal experiences have a positive impact on satisfaction. The results of structural equation modeling analysis support all seven hypothesized relationships. These findings will assist museum managers in developing effective management strategies and future plans.

This study aims to develop a digital retrieval system for art museums to solve the problems of inaccurate information and low retrieval efficiency in the digital management of cultural heritage. By introducing an improved Genetic Algorithm (GA), digital management and access efficiency are enhanced, to bring substantial optimization and innovation to the digital management of cultural heritage. Based on the collection of art museums, this study first integrates the collection\'s images, texts, and metadata with multi-source intelligent information to achieve a more accurate and comprehensive description of digital content. Second, a GA is introduced, and a GA 2 Convolutional Neural Network (GA2CNN) optimization model combining domain knowledge is proposed. Moreover, the convergence speed of traditional GA is improved to adapt to the characteristics of cultural heritage data. Lastly, the Convolutional Neural Network (CNN), GA, and GA2CNN are compared to verify the proposed system\'s superiority. The results show that in all models, the sample output results\' actual value is 2.62, which represents the real data observation results. For sample number 5, compared with the actual value of 2.62, the predicted values of the GA2CNN and GA models are 2.6177 and 2.6313, and their errors are 0.0023 and 0.0113. The CNN model\'s predicted value is 2.6237, with an error of 0.0037. It can be found that the network fitting accuracy after optimization of the GA2CNN model is high, and the predicted value is very close to the actual value. The digital retrieval system integrated with the GA2CNN model has a good performance in enhancing retrieval efficiency and accuracy. This study provides technical support for the digital organization and display of cultural heritage and offers valuable references for innovative exploration of museum information management in the digital era.

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Interview with Chris Stringer, who studies human origins at the Natural History Museum of London.

In the last decade, extensive fungal growth has developed in Danish museums parallel to climate change, challenging occupational health and heritage preservation. The growth was unexpected as the museums strived to control relative humidity below 60 %, and it should exceed 75 % to risk growth. A Danish case study found xerophilic Aspergillus species able to grow at low relative humidity in a museum repository. This cross-sectional study aimed to examine whether xerophilic growth from Aspergillus section Restricti has become a novel contaminant nationally distributed in Danish museum repositories striving to control relative humidity according to international environmental recommendations for heritage collections. The study examined The National Museum of Denmark and eight large State Recognized museums distributed throughout Denmark. It was based on 600 swab and tape-lift samples and 60 MAS100-Eco and filter air samples analyzed for fungi with cultivation and morphological identification, Big-Dye-Sanger sequencing, CaM-Nanopore and ITS-Illumina amplicon sequencing. The study showed growth from seven xerophilic Aspergillus species: A. conicus, A. domesticus, A. glabripes, A. halophilicus, A. magnivesiculatus, A. penicilloides, A. vitricola, of which three are new to Denmark, and 13 xerotolerant Aspergillus species. There was no growth from other fungal species. The multiple detection approach provided a broad characterization; however, there was variance in the detected species depending on the analysis approach. Cultivation and Big-Dye Sanger sequencing showed the highest Aspergillus diversity, detecting 17 species; CaM-Nanopore amplicon sequencing detected 12 species; and ITS-illumina amplicon sequencing detected two species but the highest overall diversity. Cultivation, followed by Big-Dye Sanger and CaM-amplicon sequencing, proved the highest compliance. The study concluded that xerophilic Aspergillus growth is nationally distributed and suggests species from Aspergillus section Restricti as a novel contaminant in climate-controlled museum repositories. To safeguard occupational health and heritage preservation research in sustainable solutions, avoiding xerophilic growth in museum collections is most important.

BACKGROUND: This study was motivated due to psychological exhaustion, demands, and conflict degenerating from the work environment and family responsibilities facing career female workers. These roles and expectations have posed serious dilemmas to female populations in workplaces. Leaving them untreated is risky and could lead to severe psychological disturbances. Based on these, this study investigated the effect of the occupation health model of Rational Emotive Behaviour Therapy on work-family conflict and work-deviant behavior among female workers in Tourism, Museum, Art Gallery and Exhibition Centers in Enugu State.
METHODS: A randomized control design was used. A total of 119 female workers were randomized into intervention and control groups, measured at 3 points (pretest, posttest, and follow-up test), and the data collected were analyzed using repeated measure statistics.
RESULTS: The finding showed that the intervention is significantly effective in reducing the work-family conflict and work deviance behavior among female workers in Tourism, Museum, and Art Gallery Exhibition Centers. Nonetheless, the findings show that the gender and time interaction effects did not significantly affect the work-family conflict and work deviance behavior scores of the workers. The follow-up stage improved the intervention\'s favorable impact on the reduction of work-family conflict and work-deviant behaviors.
CONCLUSIONS: This suggest that occupation health model of Rational Emotive Behaviour Therapy has significant impact in reducing and changing female workers\' perceptions of work-family conflict and work deviant behaviors.

Although adults are known to play an important role in young children\'s development, little work has focused on the enactive features of scaffolding in informal learning settings, and the embodied dynamics of intergenerational interaction. To address this gap, this paper undertakes a microinteractional analysis to examine intergenerational collaborative interaction in a science museum setting. The paper presents a fine-grained moment-by-moment analysis of video-recorded interaction of children and their adult carers around science-themed objects. Taking an enactive cognition perspective, the analysis enables access to subtle shifts in interactants\' perception, action, gesture, and movement to examine how young children engage with exhibits, and the role adult action plays in supporting young children\'s engagement with exhibits and developing ideas about science. Our findings demonstrate that intergenerational \"embodied scaffolding\" is instrumental in making \"enactive potentialities\" in the environment more accessible for children, thus deepening and enriching children\'s engagement with science. Adult action is central to revealing scientific dimensions of objects\' interaction and relationships in ways that expose novel types of perception and action opportunities in shaping science experiences and meaning making. This has implications for science education practices since it foregrounds not only \"doing\" science, through active hands-on activities, but also speaks to the interconnectedness between senses and the role of the body in thinking. Drawing on the findings, this paper also offers design implications for informal science learning environments.

The saturniid moth genus Automeris includes 145 described species. Their geographic distribution ranges from the eastern half of North America to as far south as Peru. Automeris moths are cryptically colored, with forewings that resemble dead leaves, and conspicuously colored, elaborate eyespots hidden on their hindwings. Despite their charismatic nature, the evolutionary history and relationships within Automeris and between closely related genera, remain poorly understood. In this study, we present the most comprehensive phylogeny of Automeris to date, including 80 of the 145 described species. We also incorporate two morphologically similar hemileucine genera, Pseudautomeris and Leucanella, as well as a morphologically distinct genus, Molippa. We obtained DNA data from both dry-pinned and ethanol-stored museum specimens and conducted Anchored Hybrid Enrichment (AHE) sequencing to assemble a high-quality dataset for phylogenetic analysis. The resulting phylogeny supports Automeris as a paraphyletic genus, with Leucanella and Pseudautomeris nested within, with the most recent common ancestor dating back to 21 mya. This study lays the foundation for future research on various aspects of Automeris biology, including geographical distribution patterns, potential drivers of speciation, and ecological adaptations such as antipredator defense mechanisms.

More than tools for managing physical and digital objects, museum collection management systems (CMS) serve as platforms for structuring, integrating, and making accessible the rich data embodied by natural history collections. Here we describe Arctos, a scalable community solution for managing and publishing global biological, geological, and cultural collections data for research and education. Specific goals are to: (1) Describe the core features and implementation of Arctos for a broad audience with respect to the biodiversity informatics principles that enable high quality research; (2) Highlight the unique aspects of Arctos; (3) Illustrate Arctos as a model for supporting and enhancing the Digital Extended Specimen concept; and (4) Emphasize the role of the Arctos community for improving data discovery and enabling cross-disciplinary, integrative studies within a sustainable governance model. In addition to detailing Arctos as both a community of museum professionals and a collection database platform, we discuss how Arctos achieves its richly annotated data by creating a web of knowledge with deep connections between catalog records and derived or associated data. We also highlight the value of Arctos as an educational resource. Finally, we present the financial model of fiscal sponsorship by a nonprofit organization, implemented in 2022, to ensure the long-term success and sustainability of Arctos.