Abstract
Purpose - This paper aims to generate knowledge of the impact of different virtual reality (VR) set-ups in tourism promotion regarding destination image, place attachment and behavioural intention.Design/methodology/approach - The paper presents a comparative study of the impact of different visualisation technologies (video, immersive VR and multisensory immersive VR) to promote tourism destinations. The study's dependent variables are destination image, place attachment and behaviour intention.Findings - Results show that VR content impacts these variables. Multisensory immersive VR is the preferred content type for destination promotion. It is also evidenced that female participants scored each variable higher than male participants. Males reported higher scores on the video set-up for destination image and place attachment. Behavioural intention reported higher values in the video when compared to immersive VR in both sexes.Practical implications - This paper concludes that there is a preference towards multisensory set-ups, which suggests that incorporating audiovisual and sensory elements can significantly enhance the effectiveness of VR experiences in attracting and engaging potential tourists.Originality/value - The paper contributes to the scarce body of knowledge regarding the impact of different VR factors on tourism promotion, including the multisensory VR component.

Abstract
This article delves into the role of the quantum Fisher information matrix (FIM) in enhancing the performance of parameterized quantum circuit (PQC)-based reinforcement learning agents. While previous studies have highlighted the effectiveness of PQC-based policies preconditioned with the quantum FIM in contextual bandits, its impact in broader reinforcement learning contexts, such as Markov decision processes, is less clear. Through a detailed analysis of L & ouml;wner inequalities between quantum and classical FIMs, this study uncovers the nuanced distinctions and implications of using each type of FIM. Our results indicate that a PQC-based agent using the quantum FIM without additional insights typically incurs a larger approximation error and does not guarantee improved performance compared to the classical FIM. Empirical evaluations in classic control benchmarks suggest even though quantum FIM preconditioning outperforms standard gradient ascent, in general, it is not superior to classical FIM preconditioning.

Abstract
More and more people are relying on the Web to find health information. Challenges faced by individuals with low health literacy in the real world likely persist in the virtual realm. To assist these users, our first step is to identify them. This study aims to uncover disparities in the information-seeking behavior of users with varying levels of health literacy. We utilized data gathered from a prior user experiment. Our approach involves a classification scheme encompassing events during web search sessions, spanning the browser, search engine, and web pages. Employing this scheme, we logged interactions from video recordings in the user study and subjected the event logs to descriptive and inferential analyses. Our data analysis unveils distinctive patterns within the low health literacy group. They exhibit a higher frequency of query reformulations with entirely new terms, engage in more left clicks, utilize the browser's backward functionality more frequently, and invest more time in interactions, including increased scrolling on results pages. Conversely, the high health literacy group demonstrates a greater propensity to click on universal results, extract text from URLs more often, and make more clicks with the mouse middle button. These findings offer valuable insights for inferring users' health literacy in a non-intrusive manner. The automatic inference of health literacy can pave the way for personalized services, enhancing accessibility to information and education for individuals with low health literacy, among other benefits.

Abstract
Socioeconomic growth and population increase are driving a constant global demand for energy. Renewable energy is emerging as a leading solution to minimise the use of fossil fuels. However, renewable resources are characterised by significant intermittency and unpredictability, which impact their energy production and integration into the power grid. Forecasting models are increasingly being developed to address these challenges and have become crucial as renewable energy sources are integrated in energy systems. In this paper, a comparative analysis of forecasting methods for renewable energy production is developed, focusing on photovoltaic and wind power. A review of state-of-the-art techniques is conducted to synthesise and categorise different forecasting models, taking into account climatic variables, optimisation algorithms, pre-processing techniques, and various forecasting horizons. By integrating diverse techniques such as optimisation algorithms and pre-processing methods and carefully selecting the forecast horizon, it is possible to highlight the accuracy and stability of forecasts. Overall, the ongoing development and refinement of forecasting methods are crucial to achieve a sustainable and reliable energy future.

Abstract
The Deep Brain Stimulation of the Anterior Nucleus of the Thalamus (ANT-DBS) is an effective treatment for refractory epilepsy. In order to assess the involvement of the ANT during voluntary hand repetitive movements similar to some seizure-induced ones, we simultaneously collected videoelectroencephalogram ( vEEG) and ANT-Local Field Potential (LFPs) signals from two epilepsy patients implanted with the PerceptTM PC neurostimulator, who stayed at an Epilepsy Monitoring Unit (EMU) for a 5 day period. For this purpose, a repetitive voluntary movement execution protocol was designed and an event-related desynchronisation/synchronisation (ERD/ERS) analysis was performed. We found a power increase in alpha and theta frequency bands during movement execution for both patients. The same pattern was not found when patients were at rest. Furthermore, a similar increase of relative power was found in LFPs from other neighboring basal ganglia. This suggests that the ERS pattern may be associated to upper limb automatisms, indicating that the ANT and other basal ganglia may be involved in the execution of these repetitive movements. These findings may open a new window for the study of seizure-induced movements (semiology) as biomarkers of the beginning of seizures, which can be helpful for the future of adaptive DBS techniques for better control of epileptic seizures of these patients.

Abstract
This paper emphasizes the need to broaden organizational perspectives through Open X, which promotes sharing and collaboration over selfishness and competition, instead of that industrial intellectual protection through patents can divert resources essential for the growth of organizations. Faced with new realities, organizations need different management approaches with the potential to transform the reindustrialization resulting from deindustrialization into a Neoindustrialization 2.0. It does not mean tearing down or creating new boundaries but an open culture where organizational efforts have social relevance. In the face of economic interests, Open X can make organizational outcomes more plentiful and robust. © 2024 Published by Faculty of Engineering.