Abstract

Abstract
In this paper, we analyze the progress of tourism towards sustainability and innovation through a systematic literature review summarizing the last five years of research strictly focused on innovation and sustainability applied to tourism. This research comprises a range of theories, practices, methods, and results pursuing innovation and sustainability across different levels, stages, and drivers, and in many tourism contexts. Wide, in-depth, and structured analysis, evaluation, and examination (using the PRISMA and VOSviewer tools) of a final sample of 50 scholarly papers from 27 journals, published between 2017 and the first quarter of 2021, were undertaken. Current publications emphasize qualitative, quantitative, and mixed research methods, as well as statistical and econometric methods, such as descriptive statistics, factor analysis, and structural equation modeling. This study categorizes the four major topics identified, sustainability, innovation, sustainable development, and sustainable tourism, which comprised the contextual dimensions and relevant stages of the subject areas examined. This systematic literature review highlights advances and the significantly increasing overall number of papers over recent years. Currently, sustainability is in a more advanced state compared to innovation. The outcomes highlight that the indicators of sustainability and innovation still need further analysis within the tourism context. However, more concrete process indicators are needed for continuous improvement of the front-end of innovation and sustainable tourism. The results help in better understanding the sustainability and innovation process as applied to tourism. In particular, this study explores further direct linkages between sustainability and innovation and tourism, discussing and providing new future directions aligned with the closing remarks as well as a strategic agenda for future action post-COVID-19.

Abstract

Abstract
Industrial robots are a technology which is highly present in industry and can perform several tasks, namely machining activities. Different than CNC machines, which work with G-code and have available several software applications to generate the machine code, there is a lack of software for robotic arms, in addition to each application depending on its own language and software. This work studied a way to use different robotic arms for 3D part machining processes, to perform 3D objects reconstruction obtained through a low-cost 3D scanner. Dealing with the 3D reconstruction by integrating 3D acquisition and robotic milling with software available on the market, this paper presents a system that acquires and reconstructs a 3D object, in order to seek greater flexibility with lower initial investments and checking the applicability of robot arm in these tasks. For this, a 3D object is scanned and imported to a CAD/CAM software, to generate the machining toolpath, and a software application is used to convert the G-code into robot code. Several experiments were performed, using an ABB IRB 2600 robot arm, and the results of the machining process allowed to validate the G-code conversion and milling process using robotic arms, according to the proposed methodology.

Abstract
Occupational stress is a complex process affecting health and performance. Air Traffic Control is a complex and demanding profession. The current study demonstrates the concept of using a biomonitoring wearable platform (BWP), that combines self-report measures with biomarkers, to track stress among Air Traffic Controllers. A wearable ECG device was used to gather continuously medical-grade ECG data along with a mobile app for daily stress perception, symptoms and events annotation. A total of 256 hours of data from 32 routine work shifts and 5 days-off, from 5 ATCs was recorded with 35 tagged events using Heart Rate Variability metrics- AVNN, RMSSD, pNN50 and LF/HF were computed from ECG data and analyzed during a) shifts vs days off; b) events vs non-events and c) before and after working pauses. ATCs showed low levels of chronic stress using self-reports. Results showed that stress symptomatology slightly increase from the beginning to the end of the shift (Md=1 to Md=2; p<0.05). Statistical significant physiological changes were found between shifts and days off for AVNN and LF/HF (p<0.05), showing higher physiological activation during shifts. A significant reduction of physiological arousal was verified after working pauses, particularly for AVNN and LF/IIF (p<0.001). Self-reported data also suggests the same trend (p<0.005). Findings reinforced the discriminatory power of AVNN and LF/HF for short-term stress classification using HRV measurements. Results suggest that the rotating working system, with pause/resting periods included, effective acted as a recovery period.

Abstract
Virtual Reality (VR) has been showing potential in new and diverse areas, notably in education. However, there is a lack of studies in the Foreign Language Teaching and Learning field, particularly in listening comprehension. Therefore, this study investigated the effects of avatar animations and lip synchronization, and user interaction; features deemed relevant in this broader area. A sociodemographic, a quick CEFR-Common European Framework of Reference for Languages-15-minute English test, and questionnaire were used to evaluate the participants' Presence, Quality of Experience, Cybersickness and Knowledge Retention. Results show that, overall, the use of avatars with realistic animations and movements, and featuring lip synchronization have a positive influence on the users' sense of presence, knowledge retention and a more enjoyable overall quality of experience. The same can be said for the use of object interaction and navigation in the cultural representative environment, which had an overall positive impact.