Abstract
VR (Virtual Reality) is a technology that has been gaining more and more traction over the years, with a market that keeps on increasing in size and great opportunities. This research aims to obtain a better grasp on how VR will impact the future of omnichannel marketing, with a focus on retail. Some businesses have already begun taking advantage of these technologies. They coordinate the integration of both physical and digital channels used to interact with customers in order to improve the customer experience. VR is one such channel, and it offers consumers a whole new way to do their shopping. As technology evolves, it is important that businesses and people stay informed in order to adapt to an ever-changing market. VR is an innovative technology that a lot of potential companies could take advantage of and even gain a competitive advantage over other businesses. Through VR people and businesses are able to access the metaverse. The metaverse is a digital world parallel to our own where customers can interact with brands and their virtual products. By interacting with a virtual version of a product, consumers will have a better grasp of the product they are interested in and make better decisions when purchasing the real one. This not only raises consumer satisfaction but could also be very useful. To fully grasp what VR is capable of, a literature review was performed to understand what VR is in fact and how the metaverse can be used. Finally, a Prisma systematic review will be presented with the research question “How VR will impact the future of omnichannel marketing?”. This was done in order to obtain unbiased data from which conclusions can be drawn. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Abstract
Industry 4.0 has brought innovative concepts and technologies that have greatly improved the development of more intelligent, flexible and reconfigurable systems. Two of these concepts, Cyber-Physical Systems (CPSs) and Digital Twins (DTs), have gained significant attention from various stakeholders, e.g., researchers, industry practitioners, and governmental organizations. Both are vital to support the digitalisation of products, machines, and systems, and they focus on the integration of physical and cyber processes, where one affects the other through feedback loops. Having this in mind, this paper aims to better understand how CPS and DT are correlated, particularly exploring their similarities and differences, their positioning within the Industry 4.0 paradigm, and their convergence to develop Industry 4.0 solutions. Some research challenges to develop Industry 4.0 solutions by integrating these concepts are also discussed.

Abstract
This article aimed to analyse state-of-the-art empirical evidence of randomized controlled trials designed to assess preventive cognitive training interventions based on virtual reality for older adults without cognitive impairment, by identifying virtual reality setups and tasks, clinical outcomes and respective measurement instruments, and positive effects on outcome parameters. A systematic electronic search was performed, and six randomized controlled trials were included in the systematic review. In terms of results, the included studies pointed to significant positive impact of virtual reality-based cognitive training interventions on global cognition, memory, attention, information processing speed, walking variability, balance, muscle strength, and falls. However, further research is required to evaluate the adequacy of the virtual reality setups and tasks, to study the impact of the interventions’ duration and intensity, to understand how to tailor the interventions to the characteristics and needs of the individuals, and to compare face-to-face to remote interventions.

Abstract
The power transformer is one of the key components of any electrical grid, and, as such, modern day industrialization activities require constant usage of the asset. This increases the possibility of failures and can potentially diminish the lifespan of a power transformer. Dissolved gas analysis (DGA) is a technique developed to quantify the existence of hydrocarbon gases in the content of the power transformer oil, which in turn can indicate the presence of faults. Since this process requires different chemical analysis for each type of gas, the overall cost of the operation increases with number of gases. Thus said, a machine learning methodology was defined to meet two simultaneous objectives, identify gas subsets, and predict the remaining gases, thus restoring them. Two subsets of equal or smaller size to those used by traditional methods (Duval's triangle, Roger's ratio, IEC table) were identified, while showing potentially superior performance. The models restored the discarded gases, and the restored set was compared with the original set in a variety of validation tasks.

Abstract

Abstract
In this paper, we consider three Relaxation Adaptive Memory Programming (RAMP) approaches for solving the Uncapacitated Facility Location Problem (UFLP), whose objective is to locate a set of facilities and allocate these facilities to all clients at minimum cost. Different levels of sophistication were implemented to measure the performance of the RAMP approach. In the simpler level, (Dual-) RAMP explores more intensively the dual side of the problem, incorporating a Lagrangean Relaxation and Subgradient Optimization with a simple Improvement Method on the primal side. In the most sophisticated level, RAMP combines a Dual-Ascent procedure on the dual side with a Scatter Search (SS) procedure on primal side, forming the Primal-Dual RAMP (PD-RAMP). The Dual-RAMP algorithm starts with (dual side) the dualization of the initial problem, and then a projection method projects the dual solutions into the primal solutions space. Next, (primal side) the projected solutions are improved through an improvement method. In the PD-RAMP algorithm, the SS procedure is incorporated in the primal side to carry out a more intensive exploration. The algorithm alternates between the dual and the primal side until a fixed number of iterations is achieved. Computational experiments on a standard testbed for the UFLP were conducted to assess the performance of all the RAMP algorithms.