Abstract
Despite advancements in interaction with immersive Virtual Reality (VR) systems, using hand gestures for all interactions still imposes some challenges, especially in interactions with graphical user interfaces that are usually performed with point-and-click interfaces. Therefore, exploring the use of alternative hands-free methods for selection is essential to overcome usability problems and provide natural interaction for users. The results and insights gained from this exploration can lead to enhanced user experiences in VR applications. This study aims to contribute to the literature with the evaluation of the usability of the most commonly used hands-free methods for selection and system control tasks in immersive VR and their impact on standard and validated experience and usability metrics, namely the sense of presence, cybersickness, system usability, workload, and user satisfaction. A Fitts' selection task was performed using a within-subjects design by nine participants experienced in VR. The methods evaluated were the handheld controllers, the head gaze, eye gaze, and voice commands for pointing at the targets, and dwell time and voice commands to confirm the selections. Results show that the methods provide similar levels of sense of presence and low cybersickness while showing low workload values and high user satisfaction, matching the experience of traditional handheld controllers for non-multimodal approaches. The assisted eye gaze with dwell was the preferred hands-free method and the one with the highest values of usability. Still, developers should minimize the number of gaze movements to reduce fatigue. The evaluation also showed that using a multimodal approach for selections, especially using the voice, decreases user satisfaction and increases users' frustration.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Abstract
In this article, the use of diffuse reflectance (R-d) spectroscopy is explored to evaluate the diffusion properties of water and sucrose in skeletal muscle during optical clearing treatments. Treating muscle samples with sucrose-water solutions with different osmolarities, collimated transmittance (T-c) and R-d measurements were performed to obtain the diffusion time (t) and the diffusion coefficient (D) values that characterize the unique water and sucrose fluxes in the muscle and also the optical clearing mechanisms designated as tissue dehydration and refractive index matching. Considering the R-d measurements, the estimated t and D values for water in the muscle were 63.1s and 1.72x10(-6) cm(2)/s, while the ones estimated for sucrose were 261s and 4.86x10(-7) cm(2)/s. Comparing these values with the ones estimated from the T-c measurements, the relative differences observed for t and D were 1.6% and 2.8% in the case of water and 0.3% and 0.4% in the case of sucrose.

Abstract
Evaluating predictive models is a crucial task in predictive analytics. This process is especially challenging with time series data because observations are not independent. Several studies have analyzed how different performance estimation methods compare with each other for approximating the true loss incurred by a given forecasting model. However, these studies do not address how the estimators behave for model selection: the ability to select the best solution among a set of alternatives. This paper addresses this issue. The goal of this work is to compare a set of estimation methods for model selection in time series forecasting tasks. This objective is split into two main questions: (i) analyze how often a given estimation method selects the best possible model; and (ii) analyze what is the performance loss when the best model is not selected. Experiments were carried out using a case study that contains 3111 time series. The accuracy of the estimators for selecting the best solution is low, despite being significantly better than random selection. Moreover, the overall forecasting performance loss associated with the model selection process ranges from 0.28 to 0.58%. Yet, no considerable differences between different approaches were found. Besides, the sample size of the time series is an important factor in the relative performance of the estimators.

Abstract

Abstract
The growing use of technology and social media has resulted in the emergence of digital influencers, a new profession capable of changing the mentalities and behaviours of those who follow them. This study arises to better understand the potential impact digital influencers might have on the Portuguese population’s purchase behaviour and patterns, and for this purpose, seven hypotheses were formulated. An online questionnaire was conducted to respond to these theoretical assumptions and collected data from 175 respondents. A total of 129 valid answers were considered. It was possible to conclude that purchase intention does not necessarily translate into a purchase action. It was also concluded that the relationship between social network use and the purchase of products/services recommended by influencers is only significant for Instagram. Furthermore, individuals’ Generation is not significantly linked with purchasing a product/service recommended by influencers. Furthermore, a small percentage of respondents have also identified themselves as impulsive shoppers and perceived Instagram as their favourite social network. With the results of this study, it is also possible to state that the influencer’s opinion was classified as the last factor considered in the purchase decision process. Additionally, there is a weak negative association between purchasing a product/service recommended by influencers with sponsorship disclosure and remunerated partnership, which decreases credibility and discourages purchasing.

Abstract
The consumption of plant-based beverages has seen a substantial increase in Portugal, which reflects the consumers changing eating habits, due to their growing ethical and environmental concerns. This study takes into account a specific Portuguese brand of plant-based beverages and empirically tested, using the PLS-SEM technique, a conceptual model to analyze the impact of perceived value, brand equity and satisfaction on loyalty intentions of Portuguese plant-based beverages' consumers. Based on 216 responses to a survey questionnaire, both the perceived value and the brand equity of this plant-based beverage brand explain satisfaction and loyalty intention. Moreover, brand equity mediates the relationship between perceived value and satisfaction and loyalty intention being this indirect effect more relevant than the direct one.