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The Museum as a Mindful Space: Reducing Visitors’ Stress and Anxiety Levels Through the ASBA Protocol

by Annalisa Banzi, Pier Luigi Sacco, Maria Elide Vanutelli and Claudio Lucchiari

Behav. Sci. 2026, 16(1), 116; https://doi.org/10.3390/bs16010116 - 14 Jan 2026

Cited by 1 | Viewed by 2267

Active involvement in creative activities, known as creative health, has been shown to enhance wellbeing, with museums serving as unique spaces for health promotion; however, visitors often require guidance to derive significant benefits from these institutions. This study, part of the larger ASBA (Anxiety, Stress, Brain-friendly museum Approach) project, evaluates the first phase of an intervention specifically focused on a Mindfulness protocol adapted to museum contexts. It has employed a single-group pre–post design with 79 healthy adults recruited from the non-clinical population. Participants were involved in a 15 min standardized mindfulness practice adapted from Mindfulness-Based Stress Reduction (MBSR) in either an art or science museum. State anxiety (SAI) and mood (VAS) were assessed at baseline and post-intervention, alongside personality traits (BFI-10) and interest measures to identify individual moderators of treatment response. The practice appeared to reduce state anxiety significantly in both settings, with large effect sizes. Specific moderators emerged: openness to experience predicted anxiety reduction in the art museum, whereas science interest predicted outcomes in the science setting. These findings suggest that brief, standardized mindfulness protocols implemented through the ASBA framework can provide promising immediate benefits for visitor wellbeing across diverse museum environments. Full article

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13 pages, 1231 KB

Open AccessArticle

Aspect Sentiment Triplet Extraction Based on Deep Relationship Enhancement Networks

by Jun Peng and Baohua Su

Appl. Sci. 2024, 14(5), 2221; https://doi.org/10.3390/app14052221 - 6 Mar 2024

Cited by 8 | Viewed by 3837

Abstract

The task of aspect-based sentiment analysis (ASBA) is to identify all the sentiment analyses expressed by specific aspect words in the text. How to identify specific objects (i.e., aspect words), describe the modifiers of the specific objects (i.e., opinion words), and judge the sentiment analysis expressed by opinion words (sentimental classification) in one step has become a focus of research in ASBA. ASTE (Aspect Sentiment Triplet Extraction) based on DREN (Deep Relationship Enhancement Networks) has been proposed in this paper. It aims to extract the aspect words and opinion words in the review text in one-step. They can judge the sentiment analysis expressed by the opinion words. Therefore, the study defines ten kinds of word relations; then, the study uses the parts of the speech feature, syntactic feature, relative position feature and tree distance relative feature to enhance the word representation relationship, which enriches the table of information in the relational matrix. Secondly, based on the word representation of BERT and GCN, the structural information of the texts are extracted; then, further extraction of higher-level word semantic information and word relationship information through SWDA (Sliding Window Dilated Attention) occurs, as SWDA can capture the multi-granularity relationship in words. Finally, the experimental results show that the proposed method is effective. Full article

(This article belongs to the Special Issue AI Empowered Sentiment Analysis)

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13 pages, 2209 KB

Open AccessArticle

Water Diffusion Modulates the CEST Effect on Tb(III)-Mesoporous Silica Probes

by Fabio Carniato, Giuseppe Ferrauto, Mónica Muñoz-Úbeda and Lorenzo Tei

Magnetochemistry 2020, 6(3), 38; https://doi.org/10.3390/magnetochemistry6030038 - 1 Sep 2020

Cited by 4 | Viewed by 3148

Abstract

The anchoring of lanthanide(III) chelates on the surface of mesoporous silica nanoparticles (MSNs) allowed their investigation as magnetic resonance imaging (MRI) and chemical exchange saturation transfer (CEST) contrast agents. Since their efficiency is strongly related to the interaction occurring between Ln-chelates and “bulk” water, an estimation of the water diffusion inside MSNs channels is very relevant. Herein, a method based on the exploitation of the CEST properties of TbDO3A-MSNs was applied to evaluate the effect of water diffusion inside MSN channels. Two MSNs, namely MCM-41 and SBA-15, with different pores size distributions were functionalized with TbDO3A-like chelates and polyethylene glycol (PEG) molecules and characterized by HR-TEM microscopy, IR spectroscopy, N₂ physisorption, and thermogravimetric analysis (TGA). The different distribution of Tb-complexes in the two systems, mainly on the external surface in case of MCM-41 or inside the internal pores for SBA-15, resulted in variable CEST efficiency. Since water molecules diffuse slowly inside silica channels, the CEST effect of the LnDO3A-SBA-15 system was found to be one order of magnitude lower than in the case of TbDO3A-MCM-41. The latter system reaches an excellent sensitivity of ca. 55 ± 5 μM, which is useful for future theranostic or imaging applications. Full article

(This article belongs to the Special Issue Paramagnetic MRI Contrast Agents Based on the Use of Lanthanides and Transition Metals Complexes: From Small Molecules to Supramolecular Systems)

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