Abstract
Ensuring process quality in modern manufacturing is increasingly challenging due to the complexity of production processes and reliance on skilled operators, which can lead to suboptimal solutions and poor quality. To address these challenges, we introduce a novel, unsupervised, robust, nonparametric control chart for Phase II monitoring. This chart tracks the degradation of a quality characteristic using a condition index that captures mean and scale shifts without relying on assumptions, offering high flexibility and adaptability. Comparative studies with state-of-the-art nonparametric schemes demonstrate faster detection capabilities and competitive accuracy across various scenarios. We validate our approach through its application in the glass container production process, showcasing its effectiveness in monitoring multiple defective rates. Although tested on defective rates, the methodology is adaptable to any quantifiable quality characteristic.

Abstract
Artificial intelligence (AI) holds significant potential for enhancing quality of gastrointestinal (GI) endoscopy, but the adoption of AI in clinical practice is hampered by the lack of rigorous standardisation and development methodology ensuring generalisability. The aim of the Quality Assessment of pre-clinical AI studies in Diagnostic Endoscopy (QUAIDE) Explanation and Checklist was to develop recommendations for standardised design and reporting of preclinical AI studies in GI endoscopy. The recommendations were developed based on a formal consensus approach with an international multidisciplinary panel of 32 experts among endoscopists and computer scientists. The Delphi methodology was employed to achieve consensus on statements, with a predetermined threshold of 80% agreement. A maximum three rounds of voting were permitted. Consensus was reached on 18 key recommendations, covering 6 key domains: data acquisition and annotation (6 statements), outcome reporting (3 statements), experimental setup and algorithm architecture (4 statements) and result presentation and interpretation (5 statements). QUAIDE provides recommendations on how to properly design (1. Methods, statements 1-14), present results (2. Results, statements 15-16) and integrate and interpret the obtained results (3. Discussion, statements 17-18). The QUAIDE framework offers practical guidance for authors, readers, editors and reviewers involved in AI preclinical studies in GI endoscopy, aiming at improving design and reporting, thereby promoting research standardisation and accelerating the translation of AI innovations into clinical practice.

Abstract
Carbon dioxide (CO2) plays a crucial role in the biosphere, acting as an indicator of anthropogenic activity. Its monitoring is fundamental for controlling air and water quality, preserving the environment and optimizing industrial processes. The preparation of a bright fluorescent scaffold, named rhodol, was optimized by employing microwave heating as an alternative heating source, achieving shorter reaction times and higher yields. Structural characterization was performed by nuclear magnetic resonance (NMR) and high-resolution mass spectrometry (HRMS-ESI). Its application to produce a fluorescent optical membrane for monitoring CO2 in gas (gCO2) and in water (dCO2) was explored. Two different setups are used for this purpose, and in both, the same optical response is observed: the membrane's fluorescence intensity decreases as the CO2 concentration increases. The sensor's reliability for dCO2 is demonstrated through testing concentrations ranging from 1 ppm to 100 ppm with minimal photobleaching (0.0026 dB) over 7500 data points with an integration time of 200 ms each. The sensor performance for dCO2 evaluation exhibits an experimental error of +/- 1.81 ppm, a response time of 2 min, a limit of detection of 0.6 ppm and a Stokes-shift of 90 nm for concentrations between 1 and 100 ppm. Monitoring of gCO2 using this membrane is hindered by changes in relative humidity (RH), hence the results for concentration between 0.3 % and 100 % of gCO2 were achieved by maintaining a consistent high value of RH. Our findings highlight the effectiveness of the optimized rhodol synthesis and its application in an optical membrane for reliable monitoring of CO2 in various environmental conditions.

Abstract

Abstract
Virtual Reality (VR) has been recognised as a promising technology for enhancing the tourist experience. However, little is known about the intention of tourism business managers to adopt VR for leisure purposes. In this context, this study aims to explore this intention by interviewing managers in the sector. This process allowed us to examine their perceptions regarding the use of this technology in their business models. The results revealed that the perceived usefulness of VR is a key factor in its adoption. In addition, managers recognise the value of VR as a complement to the tourist visit, and their intention to adopt it increases when a positive return on investment is anticipated. This approach offers a unique perspective on the main factors influencing technology adoption in this context, broadens the understanding of VR applications in wine tourism, and highlights its potential to transform the visitor experience and drive growth in the sector through innovative business models.

Abstract
This study investigates spatial distribution and chemical elemental composition screening in soils in Rome (Italy) using X-ray fluorescence analysis. Fifty-nine soil samples were collected from various locations within the urban areas of the Rome municipality and were analyzed for 19 elements. Multivariate statistical techniques, including nonlinear mapping, principal component analysis, and hierarchical cluster analysis, were employed to identify clusters of similar soil samples and their spatial distribution and to try to obtain environmental quality information. The soil sample clusters result from natural geological processes and anthropogenic activities on soil contamination patterns. Spatial clustering using the k-means algorithm further identified six distinct clusters, each with specific geographical distributions and elemental characteristics. Hence, the findings underscore the importance of targeted soil assessments to ensure the sustainable use of land resources in urban areas.