Abstract
Training in VR can reduce risks and costs while allowing frequent and diversified experiential learning activities. We present a novel VR immersive authoring tool for experiential learning courses with industrial machinery. A trainer can create a course from scratch, defining all its components (structure, models, tools, and settings). The actions which trainees should perform can be specified by demonstration. After completing the course, trainees' actions will be matched against the trainer's.

Abstract
Societies face complex challenges, which require a harmonious transition to future patterns. A strategic response to reconfigure society should assure the provision of critical resources and the resilience of the socio-technical systems in the long-term. The implementation of a new dominant technology and paradigm in the transport context is a complex process: it is multidimensional, requires seamless integration of various features and entails trade-offs in the decision-making process. The authors use general morphological analysis (GMA) as a theoretical framework that supports decision making in the transition management of transport to a new powertrain technology. This example is just an illustration of a broader representation of all the possible solutions of a large-scale problem as it is the case of any multi-level process of governance, leading to the pursuit of new paradigms. The originality of the paper lies on using a GMA that addresses sustainable challenges in a transport system from a multi-level perspective. Copyright © 2021 Inderscience Enterprises Ltd.

Abstract
Application execution requests in cloud architecture and fog paradigm are generally heterogeneous and scheduling in these architectures is an optimization problem with multiple constraints. In this paper, we conducted a survey on the related works on scheduling in cloud architecture and fog paradigm, we identify their limitations, we explore some prospects for improvements and we propose a context-aware scheduling model for fog paradigm. The proposed solution uses Min-Max normalization, to solve heterogeneity and normalize the different context parameters. The priority of requests is set by applying the Multiple Linear Regression analysis technique and the scheduling is done using the Multiobjective Nonlinear Programming Optimization technique. The results obtained from simulations on iFogSim toolkit, show that our proposal performs better compared to the non-context-aware proposals.

Abstract
The interdisciplinary field of immersive learning research is scattered. Combining efforts for better exploration of this field from the different disciplines requires researchers to communicate and coordinate effectively. We call upon the community of immersive learning researchers for planting the Knowledge Tree of Immersive Learning Research, a proposal for a systematization effort for this field, combining both scholarly and practical knowledge, cultivating a robust and ever-growing knowledge base and methodological toolbox for immersive learning. This endeavor aims at promoting evidence-informed practice and guiding future research in the field. This paper contributes with the rationale for three objectives: 1) Developing common scientific terminology amidst the community of researchers; 2) Cultivating a common understanding of methodology, and 3) Advancing common use of theoretical approaches, frameworks, and models.

Abstract
One of the main decisions that a car rental company has to make regards the definition of the fleet size and mix, i.e., the capacity to meet demand. This demand is highly unpredictable and price-sensitive; thus, the definition of the prices charged influences capacity decisions. Moreover, capacity decisions are also linked to other company strategies to meet demand, such as offering upgrades or transferring empty cars between stations. Typically, these problems are tackled focusing on the maximization of profits, disregarding the environmental impacts associated with these decisions. There is a growing need for models and analytical tools that can support decisions considering the trade-off between profit and environmental impact in mobility. Therefore, this work incorporates environmental concerns into the capacity-pricing problem for car rental, proposing a bi-objective model to tackle the trade-off between profit and environmental impact. The Life Cycle Assessment method is applied not only to vehicles but also to fuel to define environmental parameters accurately. Four types of vehicles are considered: internal combustion engine vehicles, hybrids, hybrids plug-in, and electric vehicles. Solving multi-objective models is a computationally challenging problem, which requires efficient and applicable methods. These methods can support policy and business decisions in a real-world context, running different scenarios and evaluating solutions under varying conditions. Due to its efficiency in solving bi-objective models, an Epsilon-constraint method is developed and applied in diverse situations to retrieve managerial insights. The results obtained enable quantifying the feasible trade-offs, overall showing that, on average, with a decrease of 14.44% in financial results, it is possible to obtain a decrease of 63.41% in environmental impact. Additional insights are also retrieved related to the fleet, fuel, prices and demand.

Abstract
The rise of smart manufacturing environments, characterized by high quantity of data/information available, contributes to a growing interest and research towards the use of immersive technologies not only in factories but also across entire value chains. New immersive technologies and devices are being developed to improve cooperation within Collaborative Networks (CNs), especially in the human-machine hybrid networks context. The application of these technologies in such complex environments expands substantially the modes how information is delivered and used, which may exacerbate one of the oldest problems of cognitive ergonomics: information overload. Therefore, this work presents applications of immersive technologies in manufacturing into the perspective of "information work" and "immersive human-centered manufacturing systems". A framework is proposed to be developed in a FabLab to understand the worker needs and interactions. This FabLab aims to demonstrate the potential/real application of immersive technologies, towards the enhancement of the human worker cognitive capabilities.